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Wu Y, Maul J, Vaugeois M, Galic N. Advancing ecotoxicological studies: Utilizing new approach methodologies to enable cross-species extrapolation and reduce avian testing. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 360:124765. [PMID: 39173863 DOI: 10.1016/j.envpol.2024.124765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2024] [Revised: 08/15/2024] [Accepted: 08/16/2024] [Indexed: 08/24/2024]
Abstract
Ecological risk assessments of agrochemicals have traditionally depended on in vivo guideline tests using northern bobwhite and mallard to provide relevant endpoints for avian species. However, these studies have limitations, including animal welfare concerns, the time and cost involved, limited potential for extrapolation to more realistic exposure conditions, and the lack of mechanistic understanding. The proof-of-concept work presented a case study for thiamethoxam in three avian species, demonstrating the potential of physiologically based kinetic (PBK) modeling to enable dosimetry extrapolations that inform hazard characterization in risk assessment, and reduce the use of avian testing. The model structure for northern bobwhite and mallard contained ten compartments, while an additional ovulation model was included for chicken in the physiological state of egg-laying. The model was first parameterized and evaluated for chicken and northern bobwhite using in vitro kinetic measurements and in vivo toxicokinetic (TK) data. The chicken model was then extrapolated to mallard based on allometric scaling. The models were then used to map the TK profiles across species by simulating internal dose metrics in different avian toxicology studies. These metrics, including peak blood concentrations (Cmax) and area under the curve (AUC) for blood concentration, were determined for acute, subacute, or chronic toxicity endpoints for mallard and northern bobwhite, enabling a quantitative cross-species and cross-route comparison of dosimetry. The results suggested that the chronic toxicological response of birds exposed to thiamethoxam is highly dependent on internal exposure, while mallard appeared to be more dynamically sensitive to thiamethoxam on an acute oral exposure basis. The case study increases the confidence in using new approach methodologies (NAMs) for interpreting avian toxicity studies and facilitating in vitro-in silico-based ecological risk assessments of agrochemicals.
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Affiliation(s)
- Yaoxing Wu
- Product Safety, Syngenta Crop Protection LLC, Greensboro, NC, 27409, USA.
| | - Jonathan Maul
- Product Safety, Syngenta Crop Protection LLC, Greensboro, NC, 27409, USA
| | - Maxime Vaugeois
- Product Safety, Syngenta Crop Protection LLC, Greensboro, NC, 27409, USA
| | - Nika Galic
- Product Safety, Syngenta Crop Protection AG, 4058 Basel, Switzerland
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Lou Z, Mu C, Corpstein CD, Li T. In vivo deposition of poorly soluble drugs. Adv Drug Deliv Rev 2024; 211:115358. [PMID: 38851590 DOI: 10.1016/j.addr.2024.115358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 05/12/2024] [Accepted: 06/05/2024] [Indexed: 06/10/2024]
Abstract
Administered drug molecules, whether dissolved or solubilized, have the potential to precipitate and accumulate as solid forms in tissues and cells within the body. This phase transition can significantly impact the pharmacokinetics of treatment. It is thus crucial to gain an understanding of how drug solubility/permeability, drug formulations and routes of administration affect in vivo behaviors of drug deposition. This review examines literature reports on the drug deposition in tissues and cells of poorly water-soluble drugs, as well as underlying physical mechanisms that lead to precipitation. Our work particularly highlights drug deposition in macrophages and the subcellular fate of precipitated drugs. We also propose a tissue permeability-based classification framework to evaluate precipitation potentials of poorly soluble drugs in major organs and tissues. The impact on pharmacokinetics is further discussed and needs to be considered in developing drug delivery systems. Finally, bioimaging techniques that are used to examine aggregated states and the intracellular trafficking of absorbed drugs are summarized.
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Affiliation(s)
- Zhaohuan Lou
- School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Zhejiang, Hangzhou 310053, China; Department of Industrial and Physical Pharmacy, College of Pharmacy, Purdue University, 575 Stadium Mall Drive, West Lafayette, IN 47906, USA
| | - Chaofeng Mu
- School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Zhejiang, Hangzhou 310053, China
| | - Clairissa D Corpstein
- Department of Industrial and Physical Pharmacy, College of Pharmacy, Purdue University, 575 Stadium Mall Drive, West Lafayette, IN 47906, USA
| | - Tonglei Li
- Department of Industrial and Physical Pharmacy, College of Pharmacy, Purdue University, 575 Stadium Mall Drive, West Lafayette, IN 47906, USA.
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Ramisetty BS, Yang S, Dorlo TPC, Wang MZ. Determining tissue distribution of the oral antileishmanial agent miltefosine: a physiologically-based pharmacokinetic modeling approach. Antimicrob Agents Chemother 2024; 68:e0032824. [PMID: 38842325 PMCID: PMC11232387 DOI: 10.1128/aac.00328-24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 05/15/2024] [Indexed: 06/07/2024] Open
Abstract
Miltefosine (MTS) is the only approved oral drug for treating leishmaniasis caused by intracellular Leishmania parasites that localize in macrophages of the liver, spleen, skin, bone marrow, and lymph nodes. MTS is extensively distributed in tissues and has prolonged elimination half-lives due to its high plasma protein binding, slow metabolic clearance, and minimal urinary excretion. Thus, understanding and predicting the tissue distribution of MTS help assess therapeutic and toxicologic outcomes of MTS, especially in special populations, e.g., pediatrics. In this study, a whole-body physiologically-based pharmacokinetic (PBPK) model of MTS was built on mice and extrapolated to rats and humans. MTS plasma and tissue concentration data obtained by intravenous and oral administration to mice were fitted simultaneously to estimate model parameters. The resulting high tissue-to-plasma partition coefficient values corroborate extensive distribution in all major organs except the bone marrow. Sensitivity analysis suggests that plasma exposure is most susceptible to changes in fraction unbound in plasma. The murine oral-PBPK model was further validated by assessing overlay of simulations with plasma and tissue profiles obtained from an independent study. Subsequently, the murine PBPK model was extrapolated to rats and humans based on species-specific physiological and drug-related parameters, as well as allometrically scaled parameters. Fold errors for pharmacokinetic parameters were within acceptable range in both extrapolated models, except for a slight underprediction in the human plasma exposure. These animal and human PBPK models are expected to provide reliable estimates of MTS tissue distribution and assist dose regimen optimization in special populations.
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Affiliation(s)
| | - Sihyung Yang
- Department of Pharmaceutical Chemistry, The University of Kansas, Lawrence, Kansas, USA
| | - Thomas P. C. Dorlo
- Pharmacometrics Research Group, Department of Pharmacy, Uppsala University, Uppsala, Sweden
| | - Michael Zhuo Wang
- Department of Pharmaceutical Chemistry, The University of Kansas, Lawrence, Kansas, USA
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Wang Q, Yan Y, Li S, Yi H, Xie F. Physiologically based pharmacokinetic modelling of cefoperazone in paediatrics. Br J Clin Pharmacol 2024. [PMID: 38958222 DOI: 10.1111/bcp.16163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 04/23/2024] [Accepted: 06/12/2024] [Indexed: 07/04/2024] Open
Abstract
AIMS Cefoperazone is commonly used off-label in the treatment of bacterial meningitis and sepsis in children, and the pharmacokinetic (PK) data are limited in this vulnerable population. The goal of this study was to develop a physiologically based pharmacokinetic (PBPK) model to predict pediatric cefoperazone exposure for rational dosing recommendations. METHODS A cefoperazone PBPK model for adults was first constructed using Simcyp V22 simulator. Subsequently, the model was extended to children based on the built in age-dependent physiological parameters, while the drug characteristics remained unchanged. The verified pediatric PBPK model was then utilized to assess the rationality of the common dosing regimens for children at different age groups. RESULTS Cefoperazone PBPK model included elimination via biliary excretion, glomerular filtration, and organic anion transporter 3 (OAT3)-mediated tubular secretion. 95.2% of the observed mean concentrations and 100% of the area under the plasma drug concentration-time curve (AUC) and peak concentration (Cmax) in adults were within a twofold range of model mean predictions. Good predictive accuracy was also observed in children, including neonates. 50 mg/kg q12h cefoperazone demonstrated effective target attainment in virtual term neonates (<1 month) when the MIC was ≤1 mg/L, adhering to the stringent PK/PD target of 75% fT > MIC. 37.5 mg/kg q12h cefoperazone achieved the common 50% fT > MIC target for an MIC ≤ 0. 25 mg/L in virtual pediatric patients ranging from 1 month to 18 years of age. CONCLUSIONS A pediatric PBPK model was developed for cefoperazone, and it could serve as the basis for deriving rational dosing regimens in children.
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Affiliation(s)
- Qiushi Wang
- Division of Biopharmaceutics and Pharmacokinetics, Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, China
| | - Yunan Yan
- Division of Biopharmaceutics and Pharmacokinetics, Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, China
| | - Sanwang Li
- Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, China
- Institute of Clinical Pharmacy, Central South University, Changsha, China
| | - Hanxi Yi
- Department of Pathology, School of Basic Medical Science, Central South University, Changsha, China
| | - Feifan Xie
- Division of Biopharmaceutics and Pharmacokinetics, Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, China
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Li Y, Wang Z, Li Y, Du J, Gao X, Li Y, Lai L. A Combination of Machine Learning and PBPK Modeling Approach for Pharmacokinetics Prediction of Small Molecules in Humans. Pharm Res 2024; 41:1369-1379. [PMID: 38918309 DOI: 10.1007/s11095-024-03725-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Accepted: 06/02/2024] [Indexed: 06/27/2024]
Abstract
PURPOSE Recently, there has been rapid development in model-informed drug development, which has the potential to reduce animal experiments and accelerate drug discovery. Physiologically based pharmacokinetic (PBPK) and machine learning (ML) models are commonly used in early drug discovery to predict drug properties. However, basic PBPK models require a large number of molecule-specific inputs from in vitro experiments, which hinders the efficiency and accuracy of these models. To address this issue, this paper introduces a new computational platform that combines ML and PBPK models. The platform predicts molecule PK profiles with high accuracy and without the need for experimental data. METHODS This study developed a whole-body PBPK model and ML models of plasma protein fraction unbound ( f up ), Caco-2 cell permeability, and total plasma clearance to predict the PK of small molecules after intravenous administration. Pharmacokinetic profiles were simulated using a "bottom-up" PBPK modeling approach with ML inputs. Additionally, 40 compounds were used to evaluate the platform's accuracy. RESULTS Results showed that the ML-PBPK model predicted the area under the concentration-time curve (AUC) with 65.0 % accuracy within a 2-fold range, which was higher than using in vitro inputs with 47.5 % accuracy. CONCLUSION The ML-PBPK model platform provides high accuracy in prediction and reduces the number of experiments and time required compared to traditional PBPK approaches. The platform successfully predicts human PK parameters without in vitro and in vivo experiments and can potentially guide early drug discovery and development.
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Affiliation(s)
- Yuelin Li
- XtalPi Innovation Center, XtalPi Inc., Beijing, 100080, China
| | - Zonghu Wang
- XtalPi Innovation Center, XtalPi Inc., Beijing, 100080, China
| | - Yuru Li
- XtalPi Innovation Center, XtalPi Inc., Beijing, 100080, China
| | - Jiewen Du
- XtalPi Innovation Center, XtalPi Inc., Beijing, 100080, China
| | - Xiangrui Gao
- XtalPi Innovation Center, XtalPi Inc., Beijing, 100080, China
| | - Yuanpeng Li
- XtalPi Innovation Center, XtalPi Inc., Beijing, 100080, China
| | - Lipeng Lai
- XtalPi Innovation Center, XtalPi Inc., Beijing, 100080, China.
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6
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Shuklinova O, Neuhoff S, Polak S. How PBPK Can Help to Understand Old Drugs and Inform their Dosing in Elderly: Amantadine Case Study. Clin Pharmacol Ther 2024; 116:225-234. [PMID: 38666589 DOI: 10.1002/cpt.3276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 03/17/2024] [Indexed: 06/18/2024]
Abstract
Amantadine, despite being on the market for 55 years, has several unknown aspects of its pharmacokinetics especially related to the influence of covariates such as age, disease, or interactions linked to amantadine's renal elimination. As amantadine is used in Parkinson's disease and is considered a potential candidate in COVID treatment and other diseases, there is an unmet need for thorough understanding of its pharmacokinetic in special populations, such as the elderly. We aimed to mechanistically describe amantadine pharmacokinetics in healthy subjects and shed some light on the differences in drug behavior between healthy volunteers (18-65 years) and an elderly/geriatric population (65-98 years) using PBPK modeling and simulation. The middle-out PBPK model includes mechanistic description of drug renal elimination, specifically an organic cation transporter (OCT)2-mediated electrogenic bidirectional transport (basolateral) and multidrug and toxic compound extrusion (MATE)1-mediated efflux (apical). The model performance was verified against plasma and urine data reported after single and multiple dose administration in healthy volunteers and elderly patients from 18 independent studies. The ratios of predicted vs. observed maximal plasma concentration and area under the concentration-time curve values were within 1.25-fold. The model illustrates that renal transporter activity is expected to decrease in healthy elderly compared to healthy volunteers, which is in line with literature proteomic data for OCT2. The model was applied to assess the potential of reaching toxicity-related plasma concentrations in different age groups of geriatric subjects.
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Affiliation(s)
- Olha Shuklinova
- Doctoral School of Medical and Health Sciences, Jagiellonian University Medical College, Kraków, Poland
- Simcyp Division, Certara UK Limited, Sheffield, UK
| | | | - Sebastian Polak
- Simcyp Division, Certara UK Limited, Sheffield, UK
- Faculty of Pharmacy, Jagiellonian University Medical College, Kraków, Poland
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Lautz LS, Dorne JLCM, Punt A. Application of partition coefficient methods to predict tissue:plasma affinities in common farm animals: Influence of ionisation state. Toxicol Lett 2024; 398:140-149. [PMID: 38925423 DOI: 10.1016/j.toxlet.2024.06.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 05/17/2024] [Accepted: 06/21/2024] [Indexed: 06/28/2024]
Abstract
Tissue affinities are conventionally determined from in vivo steady-state tissue and plasma or plasma-water chemical concentration data. In silico approaches were initially developed for preclinical species but standardly applied and tested in human physiologically-based kinetic (PBK) models. Recently, generic PBK models for farm animals have been made available and require partition coefficients as input parameters. In the current investigation, data for species-specific tissue compositions have been collected, and prediction of chemical distribution in various tissues of livestock species for cattle, chicken, sheep and swine have been performed. Overall, tissue composition was very similar across the four farm animal species. However, small differences were observed in moisture, fat and protein content in the various organs within each species. Such differences could be attributed to factors such as variations in age, breed, and weight of the animals and general conditions of the animal itself. With regards to the predictions of tissue:plasma partition coefficients, 80 %, 71 %, 77 % of the model predictions were within a factor 10 using the methods of Berezhkovskiy (2004), Rodgers and Rowland (2006) and Schmitt (2008). The method of Berezhkovskiy (2004) was often providing the most reliable predictions except for swine, where the method of Schmitt (2008) performed best. In addition, investigation of the impact of chemical classes on prediction performance, all methods had very similar reliability. Notwithstanding, no clear pattern regarding specific chemicals or tissues could be detected for the values predicted outside a 10-fold change in certain chemicals or specific tissues. This manuscript concludes with the need for future research, particularly focusing on lipophilicity and species differences in protein binding.
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Affiliation(s)
- L S Lautz
- Wageningen Food Safety Research, Akkermaalsbos 2, Wageningen, WB 6708, the Netherlands.
| | - J-L C M Dorne
- European Food Safety Authority, Via Carlo Magno 1A, Parma 43126, Italy
| | - A Punt
- Wageningen Food Safety Research, Akkermaalsbos 2, Wageningen, WB 6708, the Netherlands
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Ozbey AC, Keemink J, Wagner B, Pugliano A, Krähenbühl S, Annaert P, Fowler S, Parrott N, Umehara K. Physiologically Based Pharmacokinetic Modeling to Predict the Impact of Liver Cirrhosis on Glucuronidation via UGT1A4 and UGT2B7/2B4-A Case Study with Midazolam. Drug Metab Dispos 2024; 52:614-625. [PMID: 38653501 DOI: 10.1124/dmd.123.001635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Revised: 04/17/2024] [Accepted: 04/22/2024] [Indexed: 04/25/2024] Open
Abstract
Hepatic impairment, due to liver cirrhosis, decreases the activity of cytochrome P450 enzymes (CYPs). The use of physiologically based pharmacokinetic (PBPK) modeling to predict this effect for CYP substrates has been well-established, but the effect of cirrhosis on uridine-glucuronosyltransferase (UGT) activities is less studied and few PBPK models have been reported. UGT enzymes are involved in primary N-glucuronidation of midazolam and glucuronidation of 1'-OH-midazolam following CYP3A hydroxylation. In this study, Simcyp was used to establish PBPK models for midazolam, its primary metabolites midazolam-N-glucuronide (UGT1A4) and 1'-OH midazolam (CYP3A4/3A5), and the secondary metabolite 1'-OH-midazolam-O-glucuronide (UGT2B7/2B4), allowing to simulate the impact of liver cirrhosis on the primary and secondary glucuronidation of midazolam. The model was verified in noncirrhotic subjects before extrapolation to cirrhotic patients of Child-Pugh (CP) classes A, B, and C. Our model successfully predicted the exposures of midazolam and its metabolites in noncirrhotic and cirrhotic patients, with 86% of observed plasma concentrations within 5th-95th percentiles of predictions and observed geometrical mean of area under the plasma concentration curve between 0 hours to infinity and maximal plasma concentration within 0.7- to 1.43-fold of predictions. The simulated metabolic ratio defined as the ratio of the glucuronide metabolite AUC over the parent compound AUC (AUCglucuronide/AUCparent, metabolic ratio [MR]), was calculated for midazolam-N-glucuronide to midazolam (indicative of UGT1A4 activity) and decreased by 40% (CP A), 48% (CP B), and 75% (CP C). For 1'-OH-midazolam-O-glucuronide to 1'-OH-midazolam, the MR (indicative of UGT2B7/2B4 activity) dropped by 35% (CP A), 51% (CP B), and 64% (CP C). These predicted MRs were corroborated by the observed data. This work thus increases confidence in Simcyp predictions of the effect of liver cirrhosis on the pharmacokinetics of UGT1A4 and UGT2B7/UGT2B4 substrates. SIGNIFICANCE STATEMENT: This article presents a physiologically based pharmacokinetic model for midazolam and its metabolites and verifies the accurate simulation of pharmacokinetic profiles when using the Simcyp hepatic impairment population models. Exposure changes of midazolam-N-glucuronide and 1'-OH-midazolam-O-glucuronide reflect the impact of decreases in UGT1A4 and UGT2B7/2B4 glucuronidation activity in cirrhotic patients. The approach used in this study may be extended to verify the modeling of other uridine glucuronosyltransferase enzymes affected by liver cirrhosis.
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Affiliation(s)
- Agustos C Ozbey
- Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland (A.C.O., J.K., B.W., A.P., S.F., N.P., K.U.); Drug Delivery and Disposition Laboratory, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Belgium (A.C.O., A.P., P.A.); BioNotus GCV, Niel, Belgium (P.A.); Division of Clinical Pharmacology and Toxicology, University Hospital Basel, Basel, Switzerland (S.K.); Department of Clinical Research (S.K.) and Division of Molecular and Systems Toxicology, Department of Pharmaceutical Sciences (S.K.), University of Basel, Basel, Switzerland
| | - Janneke Keemink
- Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland (A.C.O., J.K., B.W., A.P., S.F., N.P., K.U.); Drug Delivery and Disposition Laboratory, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Belgium (A.C.O., A.P., P.A.); BioNotus GCV, Niel, Belgium (P.A.); Division of Clinical Pharmacology and Toxicology, University Hospital Basel, Basel, Switzerland (S.K.); Department of Clinical Research (S.K.) and Division of Molecular and Systems Toxicology, Department of Pharmaceutical Sciences (S.K.), University of Basel, Basel, Switzerland
| | - Bjoern Wagner
- Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland (A.C.O., J.K., B.W., A.P., S.F., N.P., K.U.); Drug Delivery and Disposition Laboratory, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Belgium (A.C.O., A.P., P.A.); BioNotus GCV, Niel, Belgium (P.A.); Division of Clinical Pharmacology and Toxicology, University Hospital Basel, Basel, Switzerland (S.K.); Department of Clinical Research (S.K.) and Division of Molecular and Systems Toxicology, Department of Pharmaceutical Sciences (S.K.), University of Basel, Basel, Switzerland
| | - Alessandra Pugliano
- Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland (A.C.O., J.K., B.W., A.P., S.F., N.P., K.U.); Drug Delivery and Disposition Laboratory, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Belgium (A.C.O., A.P., P.A.); BioNotus GCV, Niel, Belgium (P.A.); Division of Clinical Pharmacology and Toxicology, University Hospital Basel, Basel, Switzerland (S.K.); Department of Clinical Research (S.K.) and Division of Molecular and Systems Toxicology, Department of Pharmaceutical Sciences (S.K.), University of Basel, Basel, Switzerland
| | - Stephan Krähenbühl
- Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland (A.C.O., J.K., B.W., A.P., S.F., N.P., K.U.); Drug Delivery and Disposition Laboratory, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Belgium (A.C.O., A.P., P.A.); BioNotus GCV, Niel, Belgium (P.A.); Division of Clinical Pharmacology and Toxicology, University Hospital Basel, Basel, Switzerland (S.K.); Department of Clinical Research (S.K.) and Division of Molecular and Systems Toxicology, Department of Pharmaceutical Sciences (S.K.), University of Basel, Basel, Switzerland
| | - Pieter Annaert
- Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland (A.C.O., J.K., B.W., A.P., S.F., N.P., K.U.); Drug Delivery and Disposition Laboratory, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Belgium (A.C.O., A.P., P.A.); BioNotus GCV, Niel, Belgium (P.A.); Division of Clinical Pharmacology and Toxicology, University Hospital Basel, Basel, Switzerland (S.K.); Department of Clinical Research (S.K.) and Division of Molecular and Systems Toxicology, Department of Pharmaceutical Sciences (S.K.), University of Basel, Basel, Switzerland
| | - Stephen Fowler
- Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland (A.C.O., J.K., B.W., A.P., S.F., N.P., K.U.); Drug Delivery and Disposition Laboratory, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Belgium (A.C.O., A.P., P.A.); BioNotus GCV, Niel, Belgium (P.A.); Division of Clinical Pharmacology and Toxicology, University Hospital Basel, Basel, Switzerland (S.K.); Department of Clinical Research (S.K.) and Division of Molecular and Systems Toxicology, Department of Pharmaceutical Sciences (S.K.), University of Basel, Basel, Switzerland
| | - Neil Parrott
- Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland (A.C.O., J.K., B.W., A.P., S.F., N.P., K.U.); Drug Delivery and Disposition Laboratory, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Belgium (A.C.O., A.P., P.A.); BioNotus GCV, Niel, Belgium (P.A.); Division of Clinical Pharmacology and Toxicology, University Hospital Basel, Basel, Switzerland (S.K.); Department of Clinical Research (S.K.) and Division of Molecular and Systems Toxicology, Department of Pharmaceutical Sciences (S.K.), University of Basel, Basel, Switzerland
| | - Kenichi Umehara
- Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland (A.C.O., J.K., B.W., A.P., S.F., N.P., K.U.); Drug Delivery and Disposition Laboratory, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Belgium (A.C.O., A.P., P.A.); BioNotus GCV, Niel, Belgium (P.A.); Division of Clinical Pharmacology and Toxicology, University Hospital Basel, Basel, Switzerland (S.K.); Department of Clinical Research (S.K.) and Division of Molecular and Systems Toxicology, Department of Pharmaceutical Sciences (S.K.), University of Basel, Basel, Switzerland
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9
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Baird A, White SA, Das R, Tatum N, Bisgaard EK. Whole body physiology model to simulate respiratory depression of fentanyl and associated naloxone reversal. COMMUNICATIONS MEDICINE 2024; 4:114. [PMID: 38866911 PMCID: PMC11169242 DOI: 10.1038/s43856-024-00536-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 05/31/2024] [Indexed: 06/14/2024] Open
Abstract
BACKGROUND Opioid use in the United States and abroad is an endemic part of society with yearly increases in overdose rates and deaths. In response, the use of the safe and effective reversal agent, naloxone, is being fielded and used by emergency medical technicians at a greater rate. There is evidence that repeated dosing of a naloxone nasal spray is becoming more common. Despite this we lack repeated dosing guidelines as a function of the amount of opiate the patient has taken. METHODS To measure repeat dosing guidelines, we construct a whole-body model of the pharmacokinetics and dynamics of an opiate, fentanyl on respiratory depression. We then construct a model of nasal deposition and administration of naloxone to investigate repeat dosing requirements for large overdose scenarios. We run a single patient through multiple goal directed resuscitation protocols and measure total naloxone administered. RESULTS Here we show that naloxone is highly effective at reversing the respiratory symptoms of the patient and recommend dosing requirements as a function of the fentanyl amount administered. We show that for increasing doses of fentanyl, naloxone requirements also increase. The rescue dose displays a nonlinear response to the initial opioid dose. This nonlinear response is largely logistic with three distinct phases: onset, rapid acceleration, and a plateau period for doses above 1.2 mg. CONCLUSIONS This paper investigates the total naloxone dose needed to properly reverse respiratory depression associated with fentanyl overdose. We show that the current guidelines for a rescue dose may be much lower than required.
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Affiliation(s)
- Austin Baird
- University of Washington Department of Surgery, Division of Healthcare Simulation Sciences, Seattle, WA, USA.
| | - Steven A White
- Applied Research Associated Southeast Division, Raleigh, NC, USA
| | - Rishi Das
- Applied Research Associated Southeast Division, Raleigh, NC, USA
| | - Nathan Tatum
- Applied Research Associated Southeast Division, Raleigh, NC, USA
| | - Erika K Bisgaard
- University of Washington Department of Surgery, Division of Trauma, Burn, and Critical Care Surgery, Seattle, WA, USA
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10
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Karakitsios E, Dokoumetzidis A. Extrapolation of lung pharmacokinetics of antitubercular drugs from preclinical species to humans using PBPK modelling. J Antimicrob Chemother 2024; 79:1362-1371. [PMID: 38598449 PMCID: PMC11144487 DOI: 10.1093/jac/dkae109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 03/21/2024] [Indexed: 04/12/2024] Open
Abstract
OBJECTIVES To develop physiologically based pharmacokinetic (PBPK) models for widely used anti-TB drugs, namely rifampicin, pyrazinamide, isoniazid, ethambutol and moxifloxacin lung pharmacokinetics (PK)-regarding both healthy and TB-infected tissue (cellular lesion and caseum)-in preclinical species and to extrapolate to humans. METHODS Empirical models were used for the plasma PK of each species, which were connected to multicompartment permeability-limited lung models within a middle-out PBPK approach with an appropriate physiological parameterization that was scalable across species. Lung's extracellular water (EW) was assumed to be the linking component between healthy and infected tissue, while passive diffusion was assumed for the drug transferring between cellular lesion and caseum. RESULTS In rabbits, optimized unbound fractions in intracellular water of rifampicin, moxifloxacin and ethambutol were 0.015, 0.056 and 0.08, respectively, while the optimized unbound fractions in EW of pyrazinamide and isoniazid in mice were 0.25 and 0.17, respectively. In humans, all mean extrapolated daily AUC and Cmax values of various lung regions were within 2-fold of the observed ones. Unbound concentrations in the caseum were lower than unbound plasma concentrations for both rifampicin and moxifloxacin. For rifampicin, unbound concentrations in cellular rim are slightly lower, while for moxifloxacin they are significantly higher than unbound plasma concentrations. CONCLUSIONS The developed PBPK approach was able to extrapolate lung PK from preclinical species to humans and to predict unbound concentrations in the various TB-infected regions, unlike empirical lung models. We found that plasma free drug PK is not always a good surrogate for TB-infected tissue unbound PK.
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Affiliation(s)
- Evangelos Karakitsios
- Department of Pharmacy, University of Athens, Panepistimiopolis Zografou, 15784 Athens, Greece
- Pharma-Informatics Unit, Athena Research Center, Artemidos 6 & Epidavrou, 15125 Marousi, Greece
- Institute for Applied Computing “Mauro Picone”, National Research Council (CNR), Via dei Taurini 19, 00185 Rome, Italy
| | - Aristides Dokoumetzidis
- Department of Pharmacy, University of Athens, Panepistimiopolis Zografou, 15784 Athens, Greece
- Pharma-Informatics Unit, Athena Research Center, Artemidos 6 & Epidavrou, 15125 Marousi, Greece
- Institute for Applied Computing “Mauro Picone”, National Research Council (CNR), Via dei Taurini 19, 00185 Rome, Italy
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11
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Coutinho AL, Cristofoletti R, Wu F, Al Shoyaib A, Dressman J, Polli JE. Relative Performance of Volume of Distribution Prediction Methods for Lipophilic Drugs with Uncertainty in LogP Value. Pharm Res 2024; 41:1121-1138. [PMID: 38720034 PMCID: PMC11196289 DOI: 10.1007/s11095-024-03703-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Accepted: 04/16/2024] [Indexed: 06/26/2024]
Abstract
PURPOSE The goal was to assess, for lipophilic drugs, the impact of logP on human volume of distribution at steady-state (VDss) predictions, including intermediate fut and Kp values, from six methods: Oie-Tozer, Rodgers-Rowland (tissue-specific Kp and only muscle Kp), GastroPlus, Korzekwa-Nagar, and TCM-New. METHOD A sensitivity analysis with focus on logP was conducted by keeping pKa and fup constant for each of four drugs, while varying logP. VDss was also calculated for the specific literature logP values. Error prediction analysis was conducted by analyzing prediction errors by source of logP values, drug, and overall values. RESULTS The Rodgers-Rowland methods were highly sensitive to logP values, followed by GastroPlus and Korzekwa-Nagar. The Oie-Tozer and TCM-New methods were only modestly sensitive to logP. Hence, the relative performance of these methods depended upon the source of logP value. As logP values increased, TCM-New and Oie-Tozer were the most accurate methods. TCM-New was the only method that was accurate regardless of logP value source. Oie-Tozer provided accurate predictions for griseofulvin, posaconazole, and isavuconazole; GastroPlus for itraconazole and isavuconazole; Korzekwa-Nagar for posaconazole; and TCM-New for griseofulvin, posaconazole, and isavuconazole. Both Rodgers-Rowland methods provided inaccurate predictions due to the overprediction of VDss. CONCLUSIONS TCM-New was the most accurate prediction of human VDss across four drugs and three logP sources, followed by Oie-Tozer. TCM-New showed to be the best method for VDss prediction of highly lipophilic drugs, suggesting BPR as a favorable surrogate for drug partitioning in the tissues, and which avoids the use of fup.
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Affiliation(s)
- Ana L Coutinho
- Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20 Penn Street, Room 623, HSF2 Building, Baltimore, MD, 21201, USA
| | - Rodrigo Cristofoletti
- Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, FL, USA
| | - Fang Wu
- Office of Generic Drugs, Food and Drug Administration, White Oak, MD, USA
| | | | - Jennifer Dressman
- Fraunhofer Institute of Translational Medicine and Pharmacology, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany
| | - James E Polli
- Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20 Penn Street, Room 623, HSF2 Building, Baltimore, MD, 21201, USA.
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12
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Reig-López J, Cuquerella-Gilabert M, Bandín-Vilar E, Merino-Sanjuán M, Mangas-Sanjuán V, García-Arieta A. Bioequivalence risk assessment of oral formulations containing racemic ibuprofen through a chiral physiologically based pharmacokinetic model of ibuprofen enantiomers. Eur J Pharm Biopharm 2024; 199:114293. [PMID: 38641229 DOI: 10.1016/j.ejpb.2024.114293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Revised: 03/26/2024] [Accepted: 04/15/2024] [Indexed: 04/21/2024]
Abstract
The characterization of the time course of ibuprofen enantiomers can be useful in the selection of the most sensitive analyte in bioequivalence studies. Physiologically based pharmacokinetic (PBPK) modelling and simulation represents the most efficient methodology to virtually assess bioequivalence outcomes. In this work, we aim to develop and verify a PBPK model for ibuprofen enantiomers administered as a racemic mixture with different immediate release dosage forms to anticipate bioequivalence outcomes based on different particle size distributions. A PBPK model incorporating stereoselectivity and non-linearity in plasma protein binding and metabolism as well as R-to-S unidirectional inversion has been developed in Simcyp®. A dataset composed of 11 Phase I clinical trials with 54 scenarios (27 per enantiomer) and 14,452 observations (7129 for R-ibuprofen and 7323 for S-ibuprofen) was used. Prediction errors for AUC0-t and Cmax for both enantiomers fell within the 0.8-1.25 range in 50/54 (93 %) and 42/54 (78 %) of scenarios, respectively. Outstanding model performance, with 10/10 (100 %) of Cmax and 9/10 (90 %) of AUC0-t within the 0.9-1.1 range, was demonstrated for oral suspensions, which strongly supported its use for bioequivalence risk assessment. The deterministic bioequivalence risk assessment has revealed R-ibuprofen as the most sensitive analyte to detect differences in particle size distribution for oral suspensions containing 400 mg of racemic ibuprofen, suggesting that achiral bioanalytical methods would increase type II error and declare non-bioequivalence for formulations that are bioequivalent for the eutomer.
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Affiliation(s)
- Javier Reig-López
- Department of Pharmacy and Pharmaceutical Technology and Parasitology, University of Valencia, Valencia, Spain; Interuniversity Research Institute for Molecular Recognition and Technological Development, University of Valencia-Polytechnic University of Valencia, Spain
| | - Marina Cuquerella-Gilabert
- Department of Pharmacy and Pharmaceutical Technology and Parasitology, University of Valencia, Valencia, Spain; Interuniversity Research Institute for Molecular Recognition and Technological Development, University of Valencia-Polytechnic University of Valencia, Spain; Simulation Department, Empresarios Agrupados Internacional S.A., Madrid, Spain
| | - Enrique Bandín-Vilar
- Pharmacy Department, University Clinical Hospital Santiago de Compostela (CHUS), Spain; Clinical Pharmacology Group, Health Research Institute of Santiago de Compostela (IDIS), Spain; Pharmacology, Pharmacy and Pharmaceutical Technology Department, Faculty of Pharmacy, University of Santiago de Compostela (USC), Spain
| | - Matilde Merino-Sanjuán
- Department of Pharmacy and Pharmaceutical Technology and Parasitology, University of Valencia, Valencia, Spain; Interuniversity Research Institute for Molecular Recognition and Technological Development, University of Valencia-Polytechnic University of Valencia, Spain
| | - Víctor Mangas-Sanjuán
- Department of Pharmacy and Pharmaceutical Technology and Parasitology, University of Valencia, Valencia, Spain; Interuniversity Research Institute for Molecular Recognition and Technological Development, University of Valencia-Polytechnic University of Valencia, Spain.
| | - Alfredo García-Arieta
- Área de Farmacocinética y Medicamentos Genéricos, División de Farmacología y Evaluación Clínica, Departamento de Medicamentos de Uso Humano, Agencia Española de Medicamentos y Productos Sanitarios, Spain
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13
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Cho CK, Kang P, Jang CG, Lee SY, Lee YJ, Bae JW, Choi CI. PBPK modeling to predict the pharmacokinetics of venlafaxine and its active metabolite in different CYP2D6 genotypes and drug-drug interactions with clarithromycin and paroxetine. Arch Pharm Res 2024; 47:481-504. [PMID: 38664354 DOI: 10.1007/s12272-024-01495-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 04/11/2024] [Indexed: 06/20/2024]
Abstract
Venlafaxine, a serotonin-norepinephrine reuptake inhibitor (SNRI), is indicated for the treatment of major depressive disorder, social anxiety disorder, generalized anxiety disorder, and panic disorder. Venlafaxine is metabolized to the active metabolite desvenlafaxine mainly by CYP2D6. Genetic polymorphism of CYP2D6 and coadministration with other medications can significantly affect the pharmacokinetics and/or pharmacodynamics of venlafaxine and its active metabolite. This study aimed to establish the PBPK models of venlafaxine and its active metabolite related to CYP2D6 genetic polymorphism and to predict drug-drug interactions (DDIs) with clarithromycin and paroxetine in different CYP2D6 genotypes. Clinical pharmacogenomic data for venlafaxine and desvenlafaxine were collected to build the PBPK model. Physicochemical and absorption, distribution, metabolism, and excretion (ADME) characteristics of respective compounds were obtained from previously reported data, predicted by the PK-Sim® software, or optimized to capture the plasma concentration-time profiles. Model evaluation was performed by comparing the predicted pharmacokinetic parameters and plasma concentration-time profiles to the observed data. Predicted plasma concentration-time profiles of venlafaxine and its active metabolite were visually similar to the observed profiles and all predicted AUC and Cmax values for respective compounds were included in the twofold error range of observed values in non-genotyped populations and different CYP2D6 genotypes. When clarithromycin or clarithromycin plus paroxetine was concomitantly administered, predicted plasma concentration-time profiles of venlafaxine properly captured the observed profiles in two different CYP2D6 genotypes and all predicted DDI ratios for AUC and Cmax were included within the acceptance range. Consequently, the present model successfully captured the pharmacokinetic alterations of venlafaxine and its active metabolite according to CYP2D6 genetic polymorphism as well as the DDIs between venlafaxine and two CYP inhibitors. The present model can be used to predict the pharmacokinetics of venlafaxine and its active metabolite considering different races, ages, coadministered drugs, and CYP2D6 activity of individuals and it can contribute to individualized pharmacotherapy of venlafaxine.
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Affiliation(s)
- Chang-Keun Cho
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Pureum Kang
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Choon-Gon Jang
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Seok-Yong Lee
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea.
| | - Yun Jeong Lee
- College of Pharmacy, Dankook University, Cheonan, 31116, Republic of Korea
| | - Jung-Woo Bae
- College of Pharmacy, Keimyung University, Daegu, 42601, Republic of Korea
| | - Chang-Ik Choi
- College of Pharmacy, Dongguk University-Seoul, Goyang, 10326, Republic of Korea.
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14
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Su BD, Li XM, Huang ZW, Wang Y, Shao J, Xu YY, Shu LX, Li YB. Development and application of the physiologically-based toxicokinetic (PBTK) model for ochratoxin A (OTA) in rats and humans. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 276:116277. [PMID: 38604061 DOI: 10.1016/j.ecoenv.2024.116277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 03/15/2024] [Accepted: 03/29/2024] [Indexed: 04/13/2024]
Abstract
Ochratoxin A (OTA) is a common fungal toxin frequently detected in food and human plasma samples. Currently, the physiologically based toxicokinetic (PBTK) model plays an active role in dose translation and can improve and enhance the risk assessment of toxins. In this study, the PBTK model of OTA in rats and humans was established based on knowledge of OTA-specific absorption, distribution, metabolism, and excretion (ADME) in order to better explain the disposition of OTA in humans and the discrepancies with other species. The models were calibrated and optimized using the available kinetic and toxicokinetic (TK) data, and independent test datasets were used for model evaluation. Subsequently, sensitivity analyses and population simulations were performed to characterize the extent to which variations in physiological and specific chemical parameters affected the model output. Finally, the constructed models were used for dose extrapolation of OTA, including the rat-to-human dose adjustment factor (DAF) and the human exposure conversion factor (ECF). The results showed that the unbound fraction (Fup) of OTA in plasma of rat and human was 0.02-0.04% and 0.13-4.21%, respectively. In vitro experiments, the maximum enzyme velocity (Vmax) and Michaelis-Menten constant (Km) of OTA in rat and human liver microsomes were 3.86 and 78.17 μg/g min-1, 0.46 and 4.108 μg/mL, respectively. The predicted results of the model were in good agreement with the observed data, and the models in rats and humans were verified. The PBTK model derived a DAF of 0.1081 between rats and humans, whereas the ECF was 2.03. The established PBTK model can be used to estimate short- or long-term OTA exposure levels in rats and humans, with the capacity for dose translation of OTA to provide the underlying data for risk assessment of OTA.
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Affiliation(s)
- Bu-Da Su
- Tianjin State Key Laboratory of Modern Chinese Medicine, School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China
| | - Xiao-Meng Li
- Tianjin State Key Laboratory of Modern Chinese Medicine, School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China
| | - Zhi-Wei Huang
- Phase Ⅰ Clinical Research Center, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Yue Wang
- Tianjin State Key Laboratory of Modern Chinese Medicine, School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China
| | - Jia Shao
- Department of Pharmacy, Tianjin First Central Hospital, Tianjin 300192, China
| | - Yan-Yan Xu
- Tianjin State Key Laboratory of Modern Chinese Medicine, School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.
| | - Le-Xin Shu
- Tianjin State Key Laboratory of Modern Chinese Medicine, School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.
| | - Yu-Bo Li
- Tianjin State Key Laboratory of Modern Chinese Medicine, School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.
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15
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Pillai N, Abos A, Teutonico D, Mavroudis PD. Machine learning framework to predict pharmacokinetic profile of small molecule drugs based on chemical structure. Clin Transl Sci 2024; 17:e13824. [PMID: 38752574 PMCID: PMC11097621 DOI: 10.1111/cts.13824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2024] [Revised: 04/09/2024] [Accepted: 04/30/2024] [Indexed: 05/19/2024] Open
Abstract
Accurate prediction of a new compound's pharmacokinetic (PK) profile is pivotal for the success of drug discovery programs. An initial assessment of PK in preclinical species and humans is typically performed through allometric scaling and mathematical modeling. These methods use parameters estimated from in vitro or in vivo experiments, which although helpful for an initial estimation, require extensive animal experiments. Furthermore, mathematical models are limited by the mechanistic underpinning of the drugs' absorption, distribution, metabolism, and elimination (ADME) which are largely unknown in the early stages of drug discovery. In this work, we propose a novel methodology in which concentration versus time profile of small molecules in rats is directly predicted by machine learning (ML) using structure-driven molecular properties as input and thus mitigating the need for animal experimentation. The proposed framework initially predicts ADME properties based on molecular structure and then uses them as input to a ML model to predict the PK profile. For the compounds tested, our results demonstrate that PK profiles can be adequately predicted using the proposed algorithm, especially for compounds with Tanimoto score greater than 0.5, the average mean absolute percentage error between predicted PK profile and observed PK profile data was found to be less than 150%. The suggested framework aims to facilitate PK predictions and thus support molecular screening and design earlier in the drug discovery process.
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Affiliation(s)
- Nikhil Pillai
- Global DMPK Modeling & Simulation, SanofiCambridgeMassachusettsUSA
| | | | - Donato Teutonico
- Translational Medicine & Early Development, SanofiVitry‐sur‐SeineFrance
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16
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Yan Y, Wang Q, Wu W, Yi H, Xie F. Evaluation of Various Approaches to Estimate Transplacental Clearance of Vancomycin for Predicting Fetal Concentrations using a Maternal-Fetal Physiologically Based Pharmacokinetic Model. Pharm Res 2024; 41:899-910. [PMID: 38684563 DOI: 10.1007/s11095-024-03705-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2024] [Accepted: 04/16/2024] [Indexed: 05/02/2024]
Abstract
BACKGROUND Evaluating drug transplacental clearance is vital for forecasting fetal drug exposure. Ex vivo human placenta perfusion experiments are the most suitable approach for this assessment. Various in silico methods are also proposed. This study aims to compare these prediction methods for drug transplacental clearance, focusing on the large molecular weight drug vancomycin (1449.3 g/mol), using maternal-fetal physiologically based pharmacokinetic (m-f PBPK) modeling. METHODS Ex vivo human placenta perfusion experiments, in silico approaches using intestinal permeability as a substitute (quantitative structure property relationship (QSPR) model and Caco-2 permeability in vitro-in vivo correlation model) and midazolam calibration model with Caco-2 scaling were assessed for determining the transplacental clearance (CLPD) of vancomycin. The m-f PBPK model was developed stepwise using Simcyp, incorporating the determined CLPD values as a crucial input parameter for transplacental kinetics. RESULTS The developed PBPK model of vancomycin for non-pregnant adults demonstrated excellent predictive performance. By incorporating the CLPD parameterization derived from ex vivo human placenta perfusion experiments, the extrapolated m-f PBPK model consistently predicted maternal and fetal concentrations of vancomycin across diverse doses and distinct gestational ages. However, when the CLPD parameter was derived from alternative prediction methods, none of the extrapolated maternal-fetal PBPK models produced fetal predictions in line with the observed data. CONCLUSION Our study showcased that combination of ex vivo human placenta perfusion experiments and m-f PBPK model has the capability to predict fetal exposure for the large molecular weight drug vancomycin, whereas other in silico approaches failed to achieve the same level of accuracy.
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Affiliation(s)
- Yunan Yan
- Division of Biopharmaceutics and Pharmacokinetics, Xiangya School of Pharmaceutical Sciences, Central South University, Tongzipo Road 172, Changsha, 410013, China
| | - Qiushi Wang
- Division of Biopharmaceutics and Pharmacokinetics, Xiangya School of Pharmaceutical Sciences, Central South University, Tongzipo Road 172, Changsha, 410013, China
| | - Wei Wu
- The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University, Changsha, China
- Department of Pharmacy, The First Hospital of Changsha, Changsha, China
| | - Hanxi Yi
- Department of Pathology, School of Basic Medical Science, Central South University, Changsha, China
| | - Feifan Xie
- Division of Biopharmaceutics and Pharmacokinetics, Xiangya School of Pharmaceutical Sciences, Central South University, Tongzipo Road 172, Changsha, 410013, China.
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17
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Burhanuddin K, Mohammed A, Badhan RKS. The Impact of Paediatric Obesity on Drug Pharmacokinetics: A Virtual Clinical Trials Case Study with Amlodipine. Pharmaceutics 2024; 16:489. [PMID: 38675150 PMCID: PMC11053426 DOI: 10.3390/pharmaceutics16040489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 03/26/2024] [Accepted: 03/28/2024] [Indexed: 04/28/2024] Open
Abstract
The incidence of paediatric obesity continues to rise worldwide and contributes to a range of diseases including cardiovascular disease. Obesity in children has been shown to impact upon the plasma concentrations of various compounds, including amlodipine. Nonetheless, information on the influence of obesity on amlodipine pharmacokinetics and the need for dose adjustment has not been studied previously. This study applied the physiologically based pharmacokinetic modelling and established a paediatric obesity population to assess the impact of obesity on amlodipine pharmacokinetics in children and explore the possible dose adjustments required to reach the same plasma concentration as non-obese paediatrics. The difference in predicted maximum concentration (Cmax) and area under the curve (AUC) were significant between children with and without obesity across the age group 2 to 18 years old when a fixed-dose regimen was used. On the contrary, a weight-based dose regimen showed no difference in Cmax between obese and non-obese from 2 to 9 years old. Thus, when a fixed-dose regimen is to be administered, a 1.25- to 1.5-fold increase in dose is required in obese children to achieve the same Cmax concentration as non-obese children, specifically for children aged 5 years and above.
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Affiliation(s)
| | | | - Raj K. S. Badhan
- School of Pharmacy, College of Health and Life Science, Aston University, Birmingham B4 7ET, UK; (K.B.); (A.M.)
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18
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Jordan S, Ryu S, Burchett W, Davis C, Jones R, Zhang S, Zueva L, Chang G, Di L. Comparison of Tumor Binding Across Tumor Types and Cell Lines to Support Free Drug Considerations for Oncology Drug Discovery. J Pharm Sci 2024; 113:826-835. [PMID: 38042346 DOI: 10.1016/j.xphs.2023.11.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 11/24/2023] [Accepted: 11/24/2023] [Indexed: 12/04/2023]
Abstract
Tumor binding is an important parameter to derive unbound tumor concentration to explore pharmacokinetics (PK) and pharmacodynamics (PD) relationships for oncology disease targets. Tumor binding was evaluated using eleven matrices, including various commonly used ex vivo human and mouse xenograft and syngeneic tumors, tumor cell lines and liver as a surrogate tissue. The results showed that tumor binding is highly correlated among the different tumors and tumor cell lines except for the mouse melanoma (B16F10) tumor type. Liver fraction unbound (fu) has a good correlation with B16F10 tumor binding. Liver also demonstrates a two-fold equivalency, on average, with binding of other tumor types when a scaling factor is applied. Predictive models were developed for tumor binding, with correlations established with LogD (acids), predicted muscle fu (neutrals) and measured plasma protein binding (bases) to estimate tumor fu when experimental data are not available. Many approaches can be applied to obtain and estimate tumor binding values. One strategy proposed is to use a surrogate tumor tissue, such as mouse xenograft ovarian cancer (OVCAR3) tumor, as a surrogate for tumor binding (except for B16F10) to provide an early assessment of unbound tumor concentrations for development of PK/PD relationships.
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Affiliation(s)
- Samantha Jordan
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, Groton, CT, United States
| | - Sangwoo Ryu
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, Groton, CT, United States
| | - Woodrow Burchett
- Global Biometrics and Data Management, Pfizer Worldwide Research and Development, Groton, CT, United States
| | - Carl Davis
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, La Jolla, CA, United States
| | - Rhys Jones
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, La Jolla, CA, United States
| | - Sam Zhang
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, Groton, CT, United States
| | - Larisa Zueva
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, Groton, CT, United States
| | - George Chang
- Translational Modeling and Simulation, Pfizer Worldwide Research and Development, Groton, CT, United States
| | - Li Di
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, Groton, CT, United States.
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Yeung CHT, Autmizguine J, Dalvi P, Denoncourt A, Ito S, Katz P, Rahman M, Theoret Y, Edginton AN. Maternal Ezetimibe Concentrations Measured in Breast Milk and Its Use in Breastfeeding Infant Exposure Predictions. Clin Pharmacokinet 2024; 63:317-332. [PMID: 38278872 DOI: 10.1007/s40262-023-01345-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/22/2023] [Indexed: 01/28/2024]
Abstract
BACKGROUND Lactating mothers taking ezetimibe, an antihyperlipidemic agent, may be hesitant to breastfeed despite the known benefit of breastfeeding to both mother and infant. Currently, no data exist on the presence or concentration of ezetimibe and its main active metabolite, ezetimibe-glucuronide (EZE-glucuronide), in human breast milk. METHODS Voluntary breast milk samples containing ezetimibe and EZE-glucuronide were attained from lactating mothers taking ezetimibe as part of their treatment. An assay was developed and validated to measure ezetimibe and EZE-glucuronide concentrations in breast milk. A workflow that utilized a developed and evaluated pediatric physiologically based pharmacokinetic (PBPK) model, the measured concentrations in milk, and weight-normalized breast milk intake volumes was applied to predict infant exposures and determine the upper area under the curve ratio (UAR). RESULTS Fifteen breast milk samples from two maternal-infant pairs were collected. The developed liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay showed an analytical range of 0.039-5.0 ng/mL and 0.39-50.0 ng/mL for ezetimibe and EZE-glucuronide, respectively. The measured concentrations in the breast milk samples were 0.17-1.02 ng/mL and 0.42-2.65 ng/mL of ezetimibe and EZE-glucuronide, respectively. The evaluated pediatric PBPK model demonstrated minimal exposure overlap in adult therapeutic dose and breastfed infant simulated area under the concentration-time curve from time zero to 24 h (AUC24). Calculated UAR across infant age groups ranged from 0.0015 to 0.0026. CONCLUSIONS PBPK model-predicted ezetimibe and EZE-glucuronide exposures and UAR suggest that breastfeeding infants would receive non-therapeutic exposures. Future work should involve a 'mother-infant pair study' to ascertain breastfed infant plasma ezetimibe and EZE-glucuronide concentrations to confirm the findings of this work.
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Affiliation(s)
- Cindy H T Yeung
- Division of Clinical Pharmacology and Toxicology, Hospital for Sick Children, Toronto, ON, Canada
| | - Julie Autmizguine
- Department of Clinical Pharmacology Unit, Centre Hospitalier Universitaire Sainte-Justine, Montreal, QC, Canada
- Department of Pharmacology and Physiology, Universite de Montreal, Montreal, QC, Canada
| | - Pooja Dalvi
- Division of Clinical Pharmacology and Toxicology, Hospital for Sick Children, Toronto, ON, Canada
| | - Audrey Denoncourt
- Department of Clinical Pharmacology Unit, Centre Hospitalier Universitaire Sainte-Justine, Montreal, QC, Canada
| | - Shinya Ito
- Division of Clinical Pharmacology and Toxicology, Hospital for Sick Children, Toronto, ON, Canada
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada
| | - Pamela Katz
- Division of Endocrinology and Metabolism, Department of Medicine, University of Manitoba, Winnipeg, MB, Canada
| | - Mehzabin Rahman
- Division of Clinical Pharmacology and Toxicology, Hospital for Sick Children, Toronto, ON, Canada
| | - Yves Theoret
- Department of Clinical Pharmacology Unit, Centre Hospitalier Universitaire Sainte-Justine, Montreal, QC, Canada
| | - Andrea N Edginton
- School of Pharmacy, University of Waterloo, 10 Victoria St S A, Kitchener, ON, N2G 1C5, Canada.
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20
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Zheng L, Zhang W, Olkkola KT, Dallmann A, Ni L, Zhao Y, Wang L, Zhang Q, Hu W. Physiologically based pharmacokinetic modeling of ritonavir-oxycodone drug interactions and its implication for dosing strategy. Eur J Pharm Sci 2024; 194:106697. [PMID: 38199444 DOI: 10.1016/j.ejps.2024.106697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 11/13/2023] [Accepted: 01/07/2024] [Indexed: 01/12/2024]
Abstract
The concomitant administration of ritonavir and oxycodone may significantly increase the plasma concentrations of oxycodone. This study was aimed to simulate DDI between ritonavir and oxycodone, a widely used opioid, and to formulate dosing protocols for oxycodone by using physiologically based pharmacokinetic (PBPK) modeling. We developed a ritonavir PBPK model incorporating induction and competitive and time-dependent inhibition of CYP3A4 and competitive inhibition of CYP2D6. The ritonavir model was evaluated with observed clinical pharmacokinetic data and validated for its CYP3A4 inhibition potency. We then used the model to simulate drug interactions between oxycodone and ritonavir under various dosing scenarios. The developed model captured the pharmacokinetic characteristics of ritonavir from clinical studies. The model also accurately predicts exposure changes of midazolam, triazolam, and oxycodone in the presence of ritonavir. According to model simulations, the steady-state maximum, minimum and average concentrations of oxycodone increased by up to 166% after co-administration with ritonavir, and the total exposure increased by approximately 120%. To achieve similar steady-state concentrations, halving the dose with an unchanged dosing interval or doubling the dosing interval with an unaltered single dose should be practical for oxycodone, whether formulated in uncoated or controlled-release tablets during long-term co-medication with ritonavir. The results revealed exposure-related risks of oxycodone-ritonavir interactions that have not been studied clinically and emphasized PBPK as a workable method to direct judicious dosage.
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Affiliation(s)
- Liang Zheng
- Department of Clinical Pharmacology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
| | - Wei Zhang
- Department of Clinical Pharmacology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Klaus T Olkkola
- Department of Anaesthesiology and Intensive Care Medicine, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
| | - André Dallmann
- Pharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer AG, Leverkusen, Germany.
| | - Liang Ni
- Clinical Pharmacokinetics Laboratory, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Yingjie Zhao
- Department of Clinical Pharmacology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Ling Wang
- Department of Clinical Pharmacy and Pharmacy Administration, West China School of Pharmacy, Sichuan University, Chengdu, China
| | - Qian Zhang
- Department of Clinical Pharmacology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
| | - Wei Hu
- Department of Clinical Pharmacology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
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21
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Shuklinova O, Wyszogrodzka-Gaweł G, Baran E, Lisowski B, Wiśniowska B, Dorożyński P, Kulinowski P, Polak S. Can 3D Printed Tablets Be Bioequivalent and How to Test It: A PBPK Model Based Virtual Bioequivalence Study for Ropinirole Modified Release Tablets. Pharmaceutics 2024; 16:259. [PMID: 38399313 PMCID: PMC10893163 DOI: 10.3390/pharmaceutics16020259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 01/27/2024] [Accepted: 01/31/2024] [Indexed: 02/25/2024] Open
Abstract
As the field of personalized dosing develops, the pharmaceutical manufacturing industry needs to offer flexibility in terms of tailoring the drug release and strength to the individual patient's needs. One of the promising tools which have such capacity is 3D printing technology. However, manufacturing small batches of drugs for each patient might lead to huge test burden, including the need to conduct bioequivalence trials of formulations to support the change of equipment or strength. In this paper we demonstrate how to use 3D printing in conjunction with virtual bioequivalence trials based on physiologically based pharmacokinetic (PBPK) modeling. For this purpose, we developed 3D printed ropinirole formulations and tested their bioequivalence with the reference product Polpix. The Simcyp simulator and previously developed ropinirole PBPK model were used for the clinical trial simulations. The Weibull-fitted dissolution profiles of test and reference formulations were used as inputs for the model. The virtual bioequivalence trials were run using parallel design. The study power of 80% was reached using 125 individuals. The study demonstrated how to use PBPK modeling in conjunction with 3D printing to test the virtual bioequivalence of newly developed formulations. This virtual experiment demonstrated the bioequivalence of one of the newly developed formulations with a reference product available on a market.
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Affiliation(s)
- Olha Shuklinova
- Doctoral School of Medical and Health Sciences, Jagiellonian University Medical College, 16 Łazarza St., 31-530 Kraków, Poland
- Simcyp Division, Certara UK Limited, Level 2-Acero, 1 Concourse Way, Sheffield S1 2BJ, UK;
| | - Gabriela Wyszogrodzka-Gaweł
- Faculty of Pharmacy, Jagiellonian University Medical College, Medyczna 9, 30-688 Krakow, Poland; (G.W.-G.); (B.L.); (B.W.); (P.D.)
| | - Ewelina Baran
- Institute of Technology, University of the National Education Commission, Podchorążych 2, 30-084 Kraków, Poland; (E.B.); (P.K.)
| | - Bartosz Lisowski
- Faculty of Pharmacy, Jagiellonian University Medical College, Medyczna 9, 30-688 Krakow, Poland; (G.W.-G.); (B.L.); (B.W.); (P.D.)
| | - Barbara Wiśniowska
- Faculty of Pharmacy, Jagiellonian University Medical College, Medyczna 9, 30-688 Krakow, Poland; (G.W.-G.); (B.L.); (B.W.); (P.D.)
| | - Przemysław Dorożyński
- Faculty of Pharmacy, Jagiellonian University Medical College, Medyczna 9, 30-688 Krakow, Poland; (G.W.-G.); (B.L.); (B.W.); (P.D.)
| | - Piotr Kulinowski
- Institute of Technology, University of the National Education Commission, Podchorążych 2, 30-084 Kraków, Poland; (E.B.); (P.K.)
| | - Sebastian Polak
- Simcyp Division, Certara UK Limited, Level 2-Acero, 1 Concourse Way, Sheffield S1 2BJ, UK;
- Faculty of Pharmacy, Jagiellonian University Medical College, Medyczna 9, 30-688 Krakow, Poland; (G.W.-G.); (B.L.); (B.W.); (P.D.)
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22
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Mehta P, Soliman A, Rodriguez-Vera L, Schmidt S, Muniz P, Rodriguez M, Forcadell M, Gonzalez-Perez E, Vozmediano V. Interspecies Brain PBPK Modeling Platform to Predict Passive Transport through the Blood-Brain Barrier and Assess Target Site Disposition. Pharmaceutics 2024; 16:226. [PMID: 38399280 PMCID: PMC10892872 DOI: 10.3390/pharmaceutics16020226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Revised: 01/30/2024] [Accepted: 02/01/2024] [Indexed: 02/25/2024] Open
Abstract
The high failure rate of central nervous system (CNS) drugs is partly associated with an insufficient understanding of target site exposure. Blood-brain barrier (BBB) permeability evaluation tools are needed to explore drugs' ability to access the CNS. An outstanding aspect of physiologically based pharmacokinetic (PBPK) models is the integration of knowledge on drug-specific and system-specific characteristics, allowing the identification of the relevant factors involved in target site distribution. We aimed to qualify a PBPK platform model to be used as a tool to predict CNS concentrations when significant transporter activity is absent and human data are sparse or unavailable. Data from the literature on the plasma and CNS of rats and humans regarding acetaminophen, oxycodone, lacosamide, ibuprofen, and levetiracetam were collected. Human BBB permeability values were extrapolated from rats using inter-species differences in BBB surface area. The percentage of predicted AUC and Cmax within the 1.25-fold criterion was 85% and 100% for rats and humans, respectively, with an overall GMFE of <1.25 in all cases. This work demonstrated the successful application of the PBPK platform for predicting human CNS concentrations of drugs passively crossing the BBB. Future applications include the selection of promising CNS drug candidates and the evaluation of new posologies for existing drugs.
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Affiliation(s)
- Parsshava Mehta
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL 32827, USA; (P.M.); (A.S.); (S.S.)
| | - Amira Soliman
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL 32827, USA; (P.M.); (A.S.); (S.S.)
- Department of Pharmacy Practice, Faculty of Pharmacy, Helwan University, Helwan 11795, Egypt
| | - Leyanis Rodriguez-Vera
- Model Informed Development, CTI Laboratories, Covington, KY 41011, USA; (L.R.-V.); (P.M.); (M.R.)
| | - Stephan Schmidt
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL 32827, USA; (P.M.); (A.S.); (S.S.)
| | - Paula Muniz
- Model Informed Development, CTI Laboratories, Covington, KY 41011, USA; (L.R.-V.); (P.M.); (M.R.)
| | - Monica Rodriguez
- Model Informed Development, CTI Laboratories, Covington, KY 41011, USA; (L.R.-V.); (P.M.); (M.R.)
| | - Marta Forcadell
- Neuraxpharm Pharmaceuticals SL, Clinical Research and Evidence-Generation Science, 08970 Barcelona, Spain; (M.F.); (E.G.-P.)
| | - Emili Gonzalez-Perez
- Neuraxpharm Pharmaceuticals SL, Clinical Research and Evidence-Generation Science, 08970 Barcelona, Spain; (M.F.); (E.G.-P.)
| | - Valvanera Vozmediano
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL 32827, USA; (P.M.); (A.S.); (S.S.)
- Model Informed Development, CTI Laboratories, Covington, KY 41011, USA; (L.R.-V.); (P.M.); (M.R.)
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23
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Führer F, Gruber A, Diedam H, Göller AH, Menz S, Schneckener S. A deep neural network: mechanistic hybrid model to predict pharmacokinetics in rat. J Comput Aided Mol Des 2024; 38:7. [PMID: 38294570 DOI: 10.1007/s10822-023-00547-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 12/21/2023] [Indexed: 02/01/2024]
Abstract
An important aspect in the development of small molecules as drugs or agrochemicals is their systemic availability after intravenous and oral administration. The prediction of the systemic availability from the chemical structure of a potential candidate is highly desirable, as it allows to focus the drug or agrochemical development on compounds with a favorable kinetic profile. However, such predictions are challenging as the availability is the result of the complex interplay between molecular properties, biology and physiology and training data is rare. In this work we improve the hybrid model developed earlier (Schneckener in J Chem Inf Model 59:4893-4905, 2019). We reduce the median fold change error for the total oral exposure from 2.85 to 2.35 and for intravenous administration from 1.95 to 1.62. This is achieved by training on a larger data set, improving the neural network architecture as well as the parametrization of mechanistic model. Further, we extend our approach to predict additional endpoints and to handle different covariates, like sex and dosage form. In contrast to a pure machine learning model, our model is able to predict new end points on which it has not been trained. We demonstrate this feature by predicting the exposure over the first 24 h, while the model has only been trained on the total exposure.
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Affiliation(s)
- Florian Führer
- Engineering & Technology, Applied Mathematics, Bayer AG, 51368, Leverkusen, Germany.
| | - Andrea Gruber
- Pharmaceuticals, R&D, Preclinical Modeling & Simulation, Bayer AG, 13353, Berlin, Germany
| | - Holger Diedam
- Crop Science, Product Supply, SC Simulation & Analysis, Bayer AG, 40789, Monheim, Germany
| | - Andreas H Göller
- Pharmaceuticals, R&D, Molecular Design, Bayer AG, 42096, Wuppertal, Germany
| | - Stephan Menz
- Pharmaceuticals, R&D, Preclinical Modeling & Simulation, Bayer AG, 13353, Berlin, Germany
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24
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Zhang S, Wang Z, Chen J, Luo X, Mai B. Multimodal Model to Predict Tissue-to-Blood Partition Coefficients of Chemicals in Mammals and Fish. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:1944-1953. [PMID: 38240238 DOI: 10.1021/acs.est.3c08016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/31/2024]
Abstract
Tissue-to-blood partition coefficients (Ptb) are key parameters for assessing toxicokinetics of xenobiotics in organisms, yet their experimental data were lacking. Experimental methods for measuring Ptb values are inefficient, underscoring the urgent need for prediction models. However, most existing models failed to fully exploit Ptb data from diverse sources, and their applicability domain (AD) was limited. The current study developed a multimodal model capable of processing and integrating textual (categorical features) and numerical information (molecular descriptors/fingerprints) to simultaneously predict Ptb values across various species, tissues, blood matrices, and measurement methods. Artificial neural network algorithms with embedding layers were used for the multimodal modeling. The corresponding unimodal models were developed for comparison. Results showed that the multimodal model outperformed unimodal models. To enhance the reliability of the model, a method considering categorical features, weighted molecular similarity density, and weighted inconsistency in molecular activities of structure-activity landscapes was used to characterize the AD. The model constrained by the AD exhibited better prediction accuracy for the validation set, with the determination coefficient, root mean-square error, and mean absolute error being 0.843, 0.276, and 0.213 log units, respectively. The multimodal model coupled with the AD characterization can serve as an efficient tool for internal exposure assessment of chemicals.
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Affiliation(s)
- Shuying Zhang
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Resources Utilization and Protection, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
| | - Zhongyu Wang
- Solid Waste and Chemicals Management Center, Ministry of Ecology and Environment of the People's Republic of China, Beijing 100029, China
| | - Jingwen Chen
- Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education), Dalian Key Laboratory on Chemicals Risk Control and Pollution Prevention Technology, School of Environmental Science and Technology, Dalian University of Technology, Dalian 116024, China
| | - Xiaojun Luo
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Resources Utilization and Protection, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
| | - Bixian Mai
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Resources Utilization and Protection, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
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25
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Zhang S, Luo X, Mai B. Multi-task machine learning models for simultaneous prediction of tissue-to-blood partition coefficients of chemicals in mammals. ENVIRONMENTAL RESEARCH 2024; 241:117603. [PMID: 37939805 DOI: 10.1016/j.envres.2023.117603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 10/25/2023] [Accepted: 11/04/2023] [Indexed: 11/10/2023]
Abstract
Tissue-to-blood partition coefficients (Ptb) are crucial for assessing the distribution of chemicals in organisms. Given the lack of experimental data and laborious nature of experimental methods, there is an urgent need to develop efficient predictive models. With the help of machine learning algorithms, i,e., random forest (RF), and artificial neural network (ANN), this study developed multi-task (MT) models that can simultaneously predict Ptb values for various mammalian tissues, including liver, muscle, brain, lung, and adipose. Single-task (ST) models using partial least squares regression, RF, and ANN algorithms for each endpoint were established for comparison. Overall, the performances of MT models were superior to those of ST models. The MT model using ANN algorithms showed the highest prediction accuracy with determination coefficients ranging from 0.704 to 0.886, root mean square errors between 0.223 and 0.410, and mean absolute errors ranging from 0.178 to 0.285 log units. Results showed that lipophilicity and polarizability of molecules significantly influence their partition behavior in organisms. Applicability domains (ADs) of the models were characterized by weighted molecular similarity density, and weighted inconsistency in molecular activities of structure-activity landscapes. When constrained by ADs, the models displayed enhanced predictive accuracy, making them valuable tools for the risk assessment and management of chemicals.
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Affiliation(s)
- Shuying Zhang
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Resources Utilization and Protection, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, 510640, China
| | - Xiaojun Luo
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Resources Utilization and Protection, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, 510640, China.
| | - Bixian Mai
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Resources Utilization and Protection, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, 510640, China
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26
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Reali F, Fochesato A, Kaddi C, Visintainer R, Watson S, Levi M, Dartois V, Azer K, Marchetti L. A minimal PBPK model to accelerate preclinical development of drugs against tuberculosis. Front Pharmacol 2024; 14:1272091. [PMID: 38239195 PMCID: PMC10794428 DOI: 10.3389/fphar.2023.1272091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 12/04/2023] [Indexed: 01/22/2024] Open
Abstract
Introduction: Understanding drug exposure at disease target sites is pivotal to profiling new drug candidates in terms of tolerability and efficacy. Such quantification is particularly tedious for anti-tuberculosis (TB) compounds as the heterogeneous pulmonary microenvironment due to the infection may alter lung permeability and affect drug disposition. Murine models have been a longstanding support in TB research so far and are here used as human surrogates to unveil the distribution of several anti-TB compounds at the site-of-action via a novel and centralized PBPK design framework. Methods: As an intermediate approach between data-driven pharmacokinetic (PK) models and whole-body physiologically based (PB) PK models, we propose a parsimonious framework for PK investigation (minimal PBPK approach) that retains key physiological processes involved in TB disease, while reducing computational costs and prior knowledge requirements. By lumping together pulmonary TB-unessential organs, our minimal PBPK model counts 9 equations compared to the 36 of published full models, accelerating the simulation more than 3-folds in Matlab 2022b. Results: The model has been successfully tested and validated against 11 anti-TB compounds-rifampicin, rifapentine, pyrazinamide, ethambutol, isoniazid, moxifloxacin, delamanid, pretomanid, bedaquiline, OPC-167832, GSK2556286 - showing robust predictability power in recapitulating PK dynamics in mice. Structural inspections on the proposed design have ensured global identifiability and listed free fraction in plasma and blood-to-plasma ratio as top sensitive parameters for PK metrics. The platform-oriented implementation allows fast comparison of the compounds in terms of exposure and target attainment. Discrepancies in plasma and lung levels for the latest BPaMZ and HPMZ regimens have been analyzed in terms of their impact on preclinical experiment design and on PK/PD indices. Conclusion: The framework we developed requires limited drug- and species-specific information to reconstruct accurate PK dynamics, delivering a unified viewpoint on anti-TB drug distribution at the site-of-action and a flexible fit-for-purpose tool to accelerate model-informed drug design pipelines and facilitate translation into the clinic.
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Affiliation(s)
- Federico Reali
- Fondazione The Microsoft Research—University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy
| | - Anna Fochesato
- Fondazione The Microsoft Research—University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy
- Department of Mathematics, University of Trento, Povo, Italy
| | - Chanchala Kaddi
- Gates Medical Research Institute, Cambridge, MD, United States
| | - Roberto Visintainer
- Fondazione The Microsoft Research—University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy
| | - Shayne Watson
- Gates Medical Research Institute, Cambridge, MD, United States
| | - Micha Levi
- Gates Medical Research Institute, Cambridge, MD, United States
| | | | - Karim Azer
- Gates Medical Research Institute, Cambridge, MD, United States
| | - Luca Marchetti
- Fondazione The Microsoft Research—University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Povo, Italy
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27
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Cho CK, Ko E, Mo JY, Kang P, Jang CG, Lee SY, Lee YJ, Bae JW, Choi CI. PBPK modeling to predict the pharmacokinetics of pantoprazole in different CYP2C19 genotypes. Arch Pharm Res 2024; 47:82-94. [PMID: 38150171 DOI: 10.1007/s12272-023-01478-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 12/18/2023] [Indexed: 12/28/2023]
Abstract
Pantoprazole is used to treat gastroesophageal reflux disease (GERD), maintain healing of erosive esophagitis (EE), and control symptoms related to Zollinger-Ellison syndrome (ZES). Pantoprazole is mainly metabolized by cytochrome P450 (CYP) 2C19, converting to 4'-demethyl pantoprazole. CYP2C19 is a genetically polymorphic enzyme, and the genetic polymorphism affects the pharmacokinetics and/or pharmacodynamics of pantoprazole. In this study, we aimed to establish the physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics of pantoprazole in populations with various CYP2C19 metabolic activities. A comprehensive investigation of previous reports and drug databases was conducted to collect the clinical pharmacogenomic data, physicochemical data, and disposition properties of pantoprazole, and the collected data were used for model establishment. The model was evaluated by comparing the predicted plasma concentration-time profiles and/or pharmacokinetic parameters (AUC and Cmax) with the clinical observation results. The predicted plasma concentration-time profiles in different CYP2C19 phenotypes properly captured the observed profiles. All fold error values for AUC and Cmax were included in the two-fold range. Consequently, the minimal PBPK model for pantoprazole related to CYP2C19 genetic polymorphism was properly established and it can predict the pharmacokinetics of pantoprazole in different CYP2C19 phenotypes. The present model can broaden the insight into the individualized pharmacotherapy for pantoprazole.
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Affiliation(s)
- Chang-Keun Cho
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Eunvin Ko
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Ju Yeon Mo
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Pureum Kang
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Choon-Gon Jang
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Seok-Yong Lee
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea.
| | - Yun Jeong Lee
- College of Pharmacy, Dankook University, Cheonan, 31116, Republic of Korea
| | - Jung-Woo Bae
- College of Pharmacy, Keimyung University, Daegu, 42601, Republic of Korea
| | - Chang-Ik Choi
- College of Pharmacy, Dongguk University-Seoul, Goyang, 10326, Republic of Korea.
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28
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Blumenfeld Z, Bera K, Castrén E, Lester HA. Antidepressants enter cells, organelles, and membranes. Neuropsychopharmacology 2024; 49:246-261. [PMID: 37783840 PMCID: PMC10700606 DOI: 10.1038/s41386-023-01725-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 08/28/2023] [Accepted: 08/28/2023] [Indexed: 10/04/2023]
Abstract
We begin by summarizing several examples of antidepressants whose therapeutic actions begin when they encounter their targets in the cytoplasm or in the lumen of an organelle. These actions contrast with the prevailing view that most neuropharmacological actions begin when drugs engage their therapeutic targets at extracellular binding sites of plasma membrane targets-ion channels, receptors, and transporters. We review the chemical, pharmacokinetic, and pharmacodynamic principles underlying the movements of drugs into subcellular compartments. We note the relationship between protonation-deprotonation events and membrane permeation of antidepressant drugs. The key properties relate to charge and hydrophobicity/lipid solubility, summarized by the parameters LogP, pKa, and LogDpH7.4. The classical metric, volume of distribution (Vd), is unusually large for some antidepressants and has both supracellular and subcellular components. A table gathers structures, LogP, PKa, LogDpH7.4, and Vd data and/or calculations for most antidepressants and antidepressant candidates. The subcellular components, which can now be measured in some cases, are dominated by membrane binding and by trapping in the lumen of acidic organelles. For common antidepressants, such as selective serotonin reuptake inhibitors (SSRIs) and serotonin/norepinephrine reuptake inhibitors (SNRIs), the target is assumed to be the eponymous reuptake transporter(s), although in fact the compartment of target engagement is unknown. We review special aspects of the pharmacokinetics of ketamine, ketamine metabolites, and other rapidly acting antidepressants (RAADs) including methoxetamine and scopolamine, psychedelics, and neurosteroids. Therefore, the reader can assess properties that markedly affect a drug's ability to enter or cross membranes-and therefore, to interact with target sites that face the cytoplasm, the lumen of organelles, or a membrane. In the current literature, mechanisms involving intracellular targets are termed "location-biased actions" or "inside-out pharmacology". Hopefully, these general terms will eventually acquire additional mechanistic details.
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Affiliation(s)
- Zack Blumenfeld
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
- Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA
| | - Kallol Bera
- Department of Neurosciences and Howard Hughes Medical Institute, University of California at San Diego, La Jolla, CA, USA
| | - Eero Castrén
- Neuroscience Center, University of Helsinki, Helsinki, Finland
| | - Henry A Lester
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
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29
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Jeong YS, Jusko WJ. A Complete Extension of Classical Hepatic Clearance Models Using Fractional Distribution Parameter f d in Physiologically Based Pharmacokinetics. J Pharm Sci 2024; 113:95-117. [PMID: 37279835 PMCID: PMC10902797 DOI: 10.1016/j.xphs.2023.05.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 05/30/2023] [Accepted: 05/30/2023] [Indexed: 06/08/2023]
Abstract
The classical organ clearance models have been proposed to relate the plasma clearance CLp to probable mechanism(s) of hepatic clearance. However, the classical models assume the intrinsic capability of drug elimination (CLu,int) that is physically segregated from the vascular blood but directly acts upon the unbound drug concentration in the blood (fubCavg), and do not handle the transit-time delay between the inlet/outlet concentrations in their closed-form clearance equations. Therefore, we propose unified model structures that can address the internal blood concentration patterns of clearance organs in a more mechanistic/physiological manner, based on the fractional distribution parameter fd operative in PBPK. The basic partial/ordinary differential equations for four classical models are revisited/modified to yield a more complete set of extended clearance models, i.e., the Rattle, Sieve, Tube, and Jar models, which are the counterparts of the dispersion, series-compartment, parallel-tube, and well-stirred models. We demonstrate the feasibility of applying the resulting extended models to isolated perfused rat liver data for 11 compounds and an example dataset for in vitro-in vivo extrapolation of the intrinsic to the systemic clearances. Based on their feasibilities to handle such real data, these models may serve as an improved basis for applying clearance models in the future.
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Affiliation(s)
- Yoo-Seong Jeong
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, State University of New York at Buffalo, Buffalo, NY, 14214, USA
| | - William J Jusko
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, State University of New York at Buffalo, Buffalo, NY, 14214, USA.
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Guo L, Zhu X, Zhang L, Xu Y. Physiologically based pharmacokinetic modeling of candesartan to predict the exposure in hepatic and renal impairment and elderly populations. Ther Adv Drug Saf 2023; 14:20420986231220222. [PMID: 38157240 PMCID: PMC10752084 DOI: 10.1177/20420986231220222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 11/27/2023] [Indexed: 01/03/2024] Open
Abstract
Background Candesartan cilexetil is a widely used angiotensin II receptor blocker with minimal adverse effects and high tolerability for the treatment of hypertension. Candesartan is administered orally as the prodrug candesartan cilexetil, which is wholly and swiftly converted to the active metabolite candesartan by carboxylesterase during absorption in the intestinal tract. In populations with renal or hepatic impairment, candesartan's pharmacokinetic (PK) behavior may be altered, necessitating dosage adjustments. Objectives This study was conducted to examine how the physiologically based PK (PBPK) model characterizes the PKs of candesartan in adult and geriatric populations and to predict the PKs of candesartan in elderly populations with renal and hepatic impairment. Design After developing PBPK models using the reported physicochemical properties of candesartan and clinical data, these models were validated using data from clinical investigations involving various dose ranges. Methods Comparing predicted and observed blood concentration data and PK parameters was used to assess the fit performance of the models. Results Doses should be reduced to approximately 94% of Chinese healthy adults for the Chinese healthy elderly population; approximately 92%, 68%, and 64% of that of the Chinese healthy adult dose in elderly populations with mild, moderate, and severe renal impairment, respectively; and approximately 72%, 71%, and 52% of that of the Chinese healthy adult dose in elderly populations with Child-Pugh-A, Child-Pugh-B, and Child-Pugh-C hepatic impairment, respectively. Conclusion The results suggest that the PBPK model of candesartan can be utilized to optimize dosage regimens for special populations.
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Affiliation(s)
- Lingfeng Guo
- The First Affiliated Hospital of Zhejiang University Shengzhou Branch, School of Medicine, Shengzhou, Zhejiang, China
| | - Xinyu Zhu
- The First Affiliated Hospital of Zhejiang University Shengzhou Branch, School of Medicine, Shengzhou, Zhejiang, China
| | - Lei Zhang
- Department of Pharmacy, The Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, Zhejiang, China
| | - Yichao Xu
- Center of Clinical Pharmacology, The Second Affiliated Hospital of Zhejiang University, School of Medicine, 88 Jiefang Road, Hangzhou, Zhejiang 310009, China
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Zhang X, Li Z. Co-PBK: a computational biomonitoring tool for assessing chronic internal exposure to chemicals and metabolites. ENVIRONMENTAL SCIENCE. PROCESSES & IMPACTS 2023; 25:2167-2180. [PMID: 37982278 DOI: 10.1039/d3em00396e] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/21/2023]
Abstract
Toxic chemicals are released into the environment through diverse human activities. An increasing number of chronic diseases are associated with ambient pollution, thus posing a threat to people. Given the high consumption of resources for human biomonitoring, this study proposed coupled physiologically-based kinetic (co-PBK) modeling matrices as a biomonitoring tool for simplifying chronic internal exposure estimates of environmental chemicals and their metabolites using naphthalene (NAP) and its metabolites (i.e., 1-OHN and 2-OHN) as simulation examples. According to the simulation of the steady-state mass among various organs/tissues via the co-PBK modeling matrices, fat had the highest potential bioaccumulation of NAP and its metabolites. With respect to body fluids, 1-OHN and 2-OHN tended to bioaccumulate more in the bile than in the urine. According to the sensitivity analysis, the calculated sensitivity factors for the first-order kinetics-based rate constants imply that due to the biotransformation process, target organs/tissues (e.g., liver and kidneys) would be continuously exposed to more NAP metabolites under chronic exposure. Meanwhile, 1-OHN may be more stably transported to the urine than 2-OHN for further human biomonitoring during long-term internal exposure. According to the case study of simulating population chronic exposure to NAP in Shenzhen, the co-PBK modeling estimated the population exposure to NAP with an intake rate of 8.77 × 10-2 mg d-1 and the aggregated urinary concentration of NAP metabolites of 2.60 μg L-1. Furthermore, the accuracy of the urinary levels between the real-world data and the values simulated by the co-PBK modeling was assessed and the root-mean-square error of c1-OHN,urine was found to be lower than that of c2-OHN,urine.
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Affiliation(s)
- Xiaoyu Zhang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong 518107, China.
| | - Zijian Li
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong 518107, China.
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Moreau M, Jamalpoor A, Hall JC, Fisher J, Hartvelt S, Hendriks G, Nong A. Animal-free assessment of developmental toxicity: Combining PBPK modeling with the ReproTracker assay. Toxicology 2023; 500:153684. [PMID: 38029956 PMCID: PMC10842933 DOI: 10.1016/j.tox.2023.153684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 11/20/2023] [Accepted: 11/22/2023] [Indexed: 12/01/2023]
Abstract
in vitro screening platforms to assess teratogenic potential of compounds are emerging rapidly. ReproTracker is a human induced pluripotent stem cells (hiPSCs)-based biomarker assay that is shown to identify the teratogenicity potential of new pharmaceuticals and chemicals reliably. In its current state, the assay is limited to identifying the potential teratogenic effects and does not immediately quantify a clinical dose relevant to the exposure of chemicals or drugs observable in mothers or fetuses. The goal of this study was to evaluate whether the ReproTracker assay can be extrapolated in vivo and quantitatively predict developmental toxicity exposure levels of two known human teratogens, thalidomide, and carbamazepine. Here, we utilized Physiologically Based Pharmacokinetic (PBPK) modeling to describe the pharmacokinetic behavior of these compounds and conducted an in vitro to in vivo extrapolation (IVIVE) approach to predict human equivalent effect doses (HEDs) that correspond with in vitro concentrations potentially associated with adverse outcomes in ReproTracker. The HEDs derived from the ReproTracker concentration predicted to cause developmental toxicity were close to the reported teratogenic human clinical doses and the HED derived from the rat or rabbit developmental toxicity study. The ReproTracker derived-HED revealed to be sensitive and protective of humans. Overall, this pilot study demonstrated the importance of integrating PBPK model in extrapolating and assessing developmental toxicity in vitro. The combination of these tools demonstrated that they could improve the safety assessment of drugs and chemicals without animal testing.
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Affiliation(s)
- Marjory Moreau
- ScitoVation, LLC, Research Triangle Park, NC 27713, USA.
| | - Amer Jamalpoor
- Toxys, Leiden Bioscience Park, Oegstgeest, the Netherlands
| | | | | | | | - Giel Hendriks
- Toxys, Leiden Bioscience Park, Oegstgeest, the Netherlands
| | - Andy Nong
- ScitoVation, LLC, Research Triangle Park, NC 27713, USA
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Li Z, Zhang X. Assessing human internal exposure to chemicals at different physical activity levels: A physiologically based kinetic (PBK) model incorporating metabolic equivalent of task (MET). ENVIRONMENT INTERNATIONAL 2023; 182:108312. [PMID: 37956621 DOI: 10.1016/j.envint.2023.108312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 10/27/2023] [Accepted: 11/06/2023] [Indexed: 11/15/2023]
Abstract
Physical activity levels have the potential to impact human internal exposure to environmental chemicals. However, the current lack of simple modeling approaches hinders the high-throughput screening of chemical exposure at different physical activity levels. To address this gap, this study proposes a straightforward model for assessing human internal exposure to chemicals. Our approach is based on the physiologically based kinetic (PBK) model and utilizes the metabolic equivalent of task (MET) to characterize internal exposure to chemicals at varying activity levels. To facilitate the application of this model, we have developed an Excel-based operation tool, allowing users to easily modify the MET value and generate simulation results for different physical activity levels. The simulation results demonstrate that as physical activity levels increase, the biotransfer factors (BTFs) of chemicals decrease, suggesting that higher physical activity levels reduce the bioaccumulation potential of chemicals. The intensified physical activity enhances the overall elimination kinetics of chemicals from the human body. However, the simulated concentrations of chemicals in the human body increase with higher physical activity levels, due to the significantly increased external exposure to chemicals, such as through inhalation. Our proposed modeling approach, along with the operational tool, enables high-throughput simulation of human chronic internal exposure to chemicals at different physical activity levels, where the findings can assist in screening chemicals for further health risk assessment. To accomplish this, the model incorporates certain assumptions and utilizes generic model input values. However, due to the intricate nature of the interaction between external and internal exposures at different physical activity levels, validating the simulation through experimental studies becomes challenging and is not performed in this study. For future studies, we recommend incorporating more MET-related physiological input variables, improving energy balance estimates, comprehending external exposure estimates, and conducting cohort studies to enhance and validate the proposed modeling approach.
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Affiliation(s)
- Zijian Li
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong 518107, China.
| | - Xiaoyu Zhang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong 518107, China
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El-Khateeb E, Chinnadurai R, Al Qassabi J, Scotcher D, Darwich AS, Kalra PA, Rostami-Hodjegan A. Using Prior Knowledge on Systems Through PBPK to Gain Further Insight into Routine Clinical Data on Trough Concentrations: The Case of Tacrolimus in Chronic Kidney Disease. Ther Drug Monit 2023; 45:743-753. [PMID: 37315152 PMCID: PMC10635338 DOI: 10.1097/ftd.0000000000001108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 03/23/2023] [Indexed: 06/16/2023]
Abstract
BACKGROUND Routine therapeutic drug monitoring (TDM) relies heavily on measuring trough drug concentrations. Trough concentrations are affected not only by drug bioavailability and clearance, but also by various patient and disease factors and the volume of distribution. This often makes interpreting differences in drug exposure from trough data challenging. This study aimed to combine the advantages of top-down analysis of therapeutic drug monitoring data with bottom-up physiologically-based pharmacokinetic (PBPK) modeling to investigate the effect of declining renal function in chronic kidney disease (CKD) on the nonrenal intrinsic metabolic clearance ( CLint ) of tacrolimus as a case example. METHODS Data on biochemistry, demographics, and kidney function, along with 1167 tacrolimus trough concentrations for 40 renal transplant patients, were collected from the Salford Royal Hospital's database. A reduced PBPK model was developed to estimate CLint for each patient. Personalized unbound fractions, blood-to-plasma ratios, and drug affinities for various tissues were used as priors to estimate the apparent volume of distribution. Kidney function based on the estimated glomerular filtration rate ( eGFR ) was assessed as a covariate for CLint using the stochastic approximation of expectation and maximization method. RESULTS At baseline, the median (interquartile range) eGFR was 45 (34.5-55.5) mL/min/1.73 m 2 . A significant but weak correlation was observed between tacrolimus CLint and eGFR (r = 0.2, P < 0.001). The CLint declined gradually (up to 36%) with CKD progression. Tacrolimus CLint did not differ significantly between stable and failing transplant patients. CONCLUSIONS Kidney function deterioration in CKD can affect nonrenal CLint for drugs that undergo extensive hepatic metabolism, such as tacrolimus, with critical implications in clinical practice. This study demonstrates the advantages of combining prior system information (via PBPK) to investigate covariate effects in sparse real-world datasets.
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Affiliation(s)
- Eman El-Khateeb
- Certara UK Limited (Simcyp Division), Sheffield, United Kingdom
- Clinical Pharmacy Department, Faculty of Pharmacy, Tanta University, Tanta, Egypt
| | - Rajkumar Chinnadurai
- Northern Care Alliance NHS Foundation Trust, Salford, United Kingdom
- Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Jokha Al Qassabi
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, United Kingdom
- University of Technology and Applied Sciences, Muscat, Oman; and
| | - Daniel Scotcher
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, United Kingdom
| | - Adam S. Darwich
- Logistics and Informatics in Health Care, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Philip A. Kalra
- Northern Care Alliance NHS Foundation Trust, Salford, United Kingdom
- Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Amin Rostami-Hodjegan
- Certara UK Limited (Simcyp Division), Sheffield, United Kingdom
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, United Kingdom
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Tan SPF, Willemin ME, Snoeys J, Shen H, Rostami-Hodjegan A, Scotcher D, Galetin A. Development of 4-Pyridoxic Acid PBPK Model to Support Biomarker-Informed Evaluation of OAT1/3 Inhibition and Effect of Chronic Kidney Disease. Clin Pharmacol Ther 2023; 114:1243-1253. [PMID: 37620246 DOI: 10.1002/cpt.3029] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 08/14/2023] [Indexed: 08/26/2023]
Abstract
Monitoring endogenous biomarkers is increasingly used to evaluate transporter-mediated drug-drug interactions (DDIs) in early drug development and may be applied to elucidate changes in transporter activity in disease. 4-pyridoxic acid (PDA) has been identified as the most sensitive plasma endogenous biomarker of renal organic anion transporters (OAT1/3). Increase in PDA baseline concentrations was observed after administration of probenecid, a strong clinical inhibitor of OAT1/3 and also in patients with chronic kidney disease (CKD). The aim of this study was to develop and verify a physiologically-based pharmacokinetic (PBPK) model of PDA, to predict the magnitude of probenecid DDI and predict the CKD-related changes in PDA baseline. The PBPK model for PDA was first developed in healthy population, building on from previous population pharmacokinetic modeling, and incorporating a mechanistic kidney model to consider OAT1/3-mediated renal secretion. Probenecid PBPK model was adapted from the Simcyp database and re-verified to capture its dose-dependent pharmacokinetics (n = 9 studies). The PBPK model successfully predicted the PDA plasma concentrations, area under the curve, and renal clearance in healthy subjects at baseline and after single/multiple probenecid doses. Prospective simulations in severe CKD predicted successfully the increase in PDA plasma concentration relative to healthy (within 2-fold of observed data) after accounting for 60% increase in fraction unbound in plasma and additional 50% decline in OAT1/3 activity beyond the decrease in glomerular filtration rate. The verified PDA PBPK model supports future robust evaluation of OAT1/3 DDI in drug development and increases our confidence in predicting exposure and renal secretion in patients with CKD.
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Affiliation(s)
- Shawn Pei Feng Tan
- Centre for Applied Pharmacokinetic Research, School of Health Sciences, University of Manchester, Manchester, UK
| | - Marie-Emilie Willemin
- Janssen Pharmaceutical Companies of Johnson & Johnson, Janssen Research & Development, Beerse, Belgium
| | - Jan Snoeys
- Janssen Pharmaceutical Companies of Johnson & Johnson, Janssen Research & Development, Beerse, Belgium
| | - Hong Shen
- Bristol Myers Squibb, Princeton, New Jersey, USA
| | - Amin Rostami-Hodjegan
- Centre for Applied Pharmacokinetic Research, School of Health Sciences, University of Manchester, Manchester, UK
- Certara UK Limited (Simcyp Division), Sheffield, UK
| | - Daniel Scotcher
- Centre for Applied Pharmacokinetic Research, School of Health Sciences, University of Manchester, Manchester, UK
| | - Aleksandra Galetin
- Centre for Applied Pharmacokinetic Research, School of Health Sciences, University of Manchester, Manchester, UK
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Madu SJ, Wang K, Chirumamilla SK, Turner DB, Steel PG, Li M. Assessing Dose-Exposure-Response Relationships of Miltefosine in Adults and Children using Physiologically-Based Pharmacokinetic Modeling Approach. Pharm Res 2023; 40:2983-3000. [PMID: 37816929 PMCID: PMC10746618 DOI: 10.1007/s11095-023-03610-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 09/18/2023] [Indexed: 10/12/2023]
Abstract
OBJECTIVES Miltefosine is the first and only oral medication to be successfully utilized as an antileishmanial agent. However, the drug is associated with differences in exposure patterns and cure rates among different population groups e.g. ethnicity and age (i.e., children v adults) in clinical trials. In this work, mechanistic population physiologically-based pharmacokinetic (PBPK) models have been developed to study the dose-exposure-response relationship of miltefosine in in silico clinical trials and evaluate the differences in population groups, particularly children and adults. METHODS The Simcyp population pharmacokinetics platform was employed to predict miltefosine exposure in plasma and peripheral blood mononuclear cells (PBMCs) in a virtual population under different dosing regimens. The cure rate of a simulation was based on the percentage of number of the individual virtual subjects with AUCd0-28 > 535 µg⋅day/mL in the virtual population. RESULTS It is shown that both adult and paediatric PBPK models of miltefosine can be developed to predict the PK data of the clinical trials accurately. There was no significant difference in the predicted dose-exposure-response of the miltefosine treatment for different simulated ethnicities under the same dose regime and the dose-selection strategies determined the clinical outcome of the miltefosine treatment. A lower cure rate of the miltefosine treatment in paediatrics was predicted because a lower exposure of miltefosine was simulated in virtual paediatric in comparison with adult virtual populations when they received the same dose of the treatment. CONCLUSIONS The mechanistic PBPK model suggested that the higher fraction of unbound miltefosine in plasma was responsible for a higher probability of failure in paediatrics because of the difference in the distribution of plasma proteins between adults and paediatrics. The developed PBPK models could be used to determine an optimal miltefosine dose regime in future clinical trials.
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Affiliation(s)
- Shadrack J Madu
- School of Pharmacy, De Montfort University, Leicester, LE1 9BH, UK
| | - Ke Wang
- School of Pharmacy, De Montfort University, Leicester, LE1 9BH, UK
| | | | - David B Turner
- Certara UK Limited, Simcyp Division, Sheffield, S1 2BJ, UK
| | - Patrick G Steel
- Department of Chemistry, Durham University, Durham, DH1 3LE, UK
| | - Mingzhong Li
- School of Pharmacy, De Montfort University, Leicester, LE1 9BH, UK.
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Gaohua L, Zhang M, Sychterz C, Chang M, Schmidt BJ. The Interplay of Permeability, Metabolism, Transporters, and Dosing in Determining the Dynamics of the Tissue/Plasma Partition Coefficient and Volume of Distribution-A Theoretical Investigation Using Permeability-Limited, Physiologically Based Pharmacokinetic Modeling. Int J Mol Sci 2023; 24:16224. [PMID: 38003416 PMCID: PMC10671645 DOI: 10.3390/ijms242216224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Revised: 10/26/2023] [Accepted: 11/08/2023] [Indexed: 11/26/2023] Open
Abstract
A permeability-limited physiologically based pharmacokinetic (PBPK) model featuring four subcompartments (corresponding to the intracellular and extracellular water of the tissue, the residual plasma, and blood cells) for each tissue has been developed in MATLAB/SimBiology and applied to various what-if scenario simulations. This model allowed us to explore the complex interplay of passive permeability, metabolism in tissue or residual blood, active uptake or efflux transporters, and different dosing routes (intravenous (IV) or oral (PO)) in determining the dynamics of the tissue/plasma partition coefficient (Kp) and volume of distribution (Vd) within a realistic pseudo-steady state. Based on the modeling exercise, the permeability, metabolism, and transporters demonstrated significant effects on the dynamics of the Kp and Vd for IV bolus administration and PO fast absorption, but these effects were not as pronounced for IV infusion or PO slow absorption. Especially for low-permeability compounds, uptake transporters were found to increase both the Kp and Vd at the pseudo-steady state (Vdss), while efflux transporters had the opposite effect of decreasing the Kp and Vdss. For IV bolus administration and PO fast absorption, increasing tissue metabolism was predicted to elevate the Kp and Vdss, which contrasted with the traditional derivation from the steady-state perfusion-limited PBPK model. Moreover, metabolism in the residual blood had more impact on the Kp and Vdss compared to metabolism in tissue. Due to its ability to offer a more realistic description of tissue dynamics, the permeability-limited PBPK model is expected to gain broader acceptance in describing clinical PK and observed Kp and Vdss, even for certain small molecules like cyclosporine, which are currently treated as perfusion-limited in commercial PBPK platforms.
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Affiliation(s)
- Lu Gaohua
- Clinical Pharmacology & Pharmacometrics, Bristol Myers Squibb, Lawrenceville, NJ 08540, USA; (M.Z.); (C.S.); (M.C.); (B.J.S.)
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van der Heijden JEM, Freriksen JJM, de Hoop-Sommen MA, Greupink R, de Wildt SN. Physiologically-Based Pharmacokinetic Modeling for Drug Dosing in Pediatric Patients: A Tutorial for a Pragmatic Approach in Clinical Care. Clin Pharmacol Ther 2023; 114:960-971. [PMID: 37553784 DOI: 10.1002/cpt.3023] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 08/02/2023] [Indexed: 08/10/2023]
Abstract
It is well-accepted that off-label drug dosing recommendations for pediatric patients should be based on the best available evidence. However, the available traditional evidence is often low. To bridge this gap, physiologically-based pharmacokinetic (PBPK) modeling is a scientifically well-founded tool that can be used to enable model-informed dosing (MID) recommendations in children in clinical practice. In this tutorial, we provide a pragmatic, PBPK-based pediatric modeling workflow. For this approach to be successfully implemented in pediatric clinical practice, a thorough understanding of the model assumptions and limitations is required. More importantly, careful evaluation of an MID approach within the context of overall benefits and the potential risks is crucial. The tutorial is aimed to help modelers, researchers, and clinicians, to effectively use PBPK simulations to support pediatric drug dosing.
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Affiliation(s)
- Joyce E M van der Heijden
- Division of Pharmacology and Toxicology, Department of Pharmacy, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jolien J M Freriksen
- Division of Pharmacology and Toxicology, Department of Pharmacy, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Marika A de Hoop-Sommen
- Division of Pharmacology and Toxicology, Department of Pharmacy, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Rick Greupink
- Division of Pharmacology and Toxicology, Department of Pharmacy, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Saskia N de Wildt
- Division of Pharmacology and Toxicology, Department of Pharmacy, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Pediatric and Neonatal Intensive Care, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands
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Chen M, Du R, Zhang T, Li C, Bao W, Xin F, Hou S, Yang Q, Chen L, Wang Q, Zhu A. The Application of a Physiologically Based Toxicokinetic Model in Health Risk Assessment. TOXICS 2023; 11:874. [PMID: 37888724 PMCID: PMC10611306 DOI: 10.3390/toxics11100874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 10/17/2023] [Accepted: 10/19/2023] [Indexed: 10/28/2023]
Abstract
Toxicokinetics plays a crucial role in the health risk assessments of xenobiotics. Classical compartmental models are limited in their ability to determine chemical concentrations in specific organs or tissues, particularly target organs or tissues, and their limited interspecific and exposure route extrapolation hinders satisfactory health risk assessment. In contrast, physiologically based toxicokinetic (PBTK) models quantitatively describe the absorption, distribution, metabolism, and excretion of chemicals across various exposure routes and doses in organisms, establishing correlations with toxic effects. Consequently, PBTK models serve as potent tools for extrapolation and provide a theoretical foundation for health risk assessment and management. This review outlines the construction and application of PBTK models in health risk assessment while analyzing their limitations and future perspectives.
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Affiliation(s)
- Mengting Chen
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, China
| | - Ruihu Du
- Department of Toxicology, School of Public Health, Peking University, Beijing 100191, China
| | - Tao Zhang
- Department of Toxicology, School of Public Health, Peking University, Beijing 100191, China
| | - Chutao Li
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, China
| | - Wenqiang Bao
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, China
| | - Fan Xin
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, China
| | - Shaozhang Hou
- Department of Pathology, School of Basic Medical Sciences, Ningxia Medical University, Yinchuan 750004, China
| | - Qiaomei Yang
- Department of Gynecology, Fujian Maternity and Child Health Hospital (Fujian Obstetrics and Gynecology Hospital), Fuzhou 350001, China
| | - Li Chen
- Department of Gynecology, Fujian Maternity and Child Health Hospital (Fujian Obstetrics and Gynecology Hospital), Fuzhou 350001, China
| | - Qi Wang
- Department of Toxicology, School of Public Health, Peking University, Beijing 100191, China
- Key Laboratory of State Administration of Traditional Chinese Medicine for Compatibility Toxicology, Beijing 100191, China
- Beijing Key Laboratory of Toxicological Research and Risk Assessment for Food Safety, Beijing 100191, China
| | - An Zhu
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, China
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Filipski KJ, Edmonds DJ, Garnsey MR, Smaltz DJ, Coffman K, Futatsugi K, Lee J, O’Neil SV, Wright A, Nason D, Gosset JR, Orozco CC, Blackler D, Fakhoury G, Gutierrez JA, Perez S, Ross T, Stock I, Tesz G, Dullea R. Design of Next-Generation DGAT2 Inhibitor PF-07202954 with Longer Predicted Half-Life. ACS Med Chem Lett 2023; 14:1427-1433. [PMID: 37849537 PMCID: PMC10577701 DOI: 10.1021/acsmedchemlett.3c00330] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 09/26/2023] [Indexed: 10/19/2023] Open
Abstract
Diacylglycerol O-acyltransferase 2 (DGAT2) inhibitors have been shown to lower liver triglyceride content and are being explored clinically as a treatment for non-alcoholic steatohepatitis (NASH). This work details efforts to find an extended-half-life DGAT2 inhibitor. A basic moiety was added to a known inhibitor template, and the basicity and lipophilicity were fine-tuned by the addition of electrophilic fluorines. A weakly basic profile was required to find an appropriate balance of potency, clearance, and permeability. This work culminated in the discovery of PF-07202954 (12), a weakly basic DGAT2 inhibitor that has advanced to clinical studies. This molecule displays a higher volume of distribution and longer half-life in preclinical species, in keeping with its physicochemical profile, and lowers liver triglyceride content in a Western-diet-fed rat model.
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Affiliation(s)
- Kevin J. Filipski
- Pfizer
Research & Development, 1 Portland Street, Cambridge, Massachusetts 02139, United States
| | - David J. Edmonds
- Pfizer
Research & Development, 1 Portland Street, Cambridge, Massachusetts 02139, United States
| | - Michelle R. Garnsey
- Pfizer
Research & Development, 1 Portland Street, Cambridge, Massachusetts 02139, United States
- Pfizer
Research & Development, 558 Eastern Point Road, Groton, Connecticut 06340, United States
| | - Daniel J. Smaltz
- Pfizer
Research & Development, 1 Portland Street, Cambridge, Massachusetts 02139, United States
- Pfizer
Research & Development, 558 Eastern Point Road, Groton, Connecticut 06340, United States
| | - Karen Coffman
- Pfizer
Research & Development, 558 Eastern Point Road, Groton, Connecticut 06340, United States
| | - Kentaro Futatsugi
- Pfizer
Research & Development, 1 Portland Street, Cambridge, Massachusetts 02139, United States
| | - Jack Lee
- Pfizer
Research & Development, 558 Eastern Point Road, Groton, Connecticut 06340, United States
| | - Steven V. O’Neil
- Pfizer
Research & Development, 558 Eastern Point Road, Groton, Connecticut 06340, United States
| | - Ann Wright
- Pfizer
Research & Development, 558 Eastern Point Road, Groton, Connecticut 06340, United States
| | - Deane Nason
- Pfizer
Research & Development, 558 Eastern Point Road, Groton, Connecticut 06340, United States
| | - James R. Gosset
- Pfizer
Research & Development, 1 Portland Street, Cambridge, Massachusetts 02139, United States
| | - Christine C. Orozco
- Pfizer
Research & Development, 558 Eastern Point Road, Groton, Connecticut 06340, United States
| | - Dan Blackler
- Pfizer
Research & Development, 1 Portland Street, Cambridge, Massachusetts 02139, United States
| | - Guila Fakhoury
- Pfizer
Research & Development, 1 Portland Street, Cambridge, Massachusetts 02139, United States
| | - Jemy A. Gutierrez
- Pfizer
Research & Development, 1 Portland Street, Cambridge, Massachusetts 02139, United States
| | - Sylvie Perez
- Pfizer
Research & Development, 1 Portland Street, Cambridge, Massachusetts 02139, United States
| | - Trenton Ross
- Pfizer
Research & Development, 1 Portland Street, Cambridge, Massachusetts 02139, United States
| | - Ingrid Stock
- Pfizer
Research & Development, 558 Eastern Point Road, Groton, Connecticut 06340, United States
| | - Gregory Tesz
- Pfizer
Research & Development, 1 Portland Street, Cambridge, Massachusetts 02139, United States
| | - Robert Dullea
- Pfizer
Research & Development, 1 Portland Street, Cambridge, Massachusetts 02139, United States
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Gall L, Jardi F, Lammens L, Piñero J, Souza TM, Rodrigues D, Jennen DGJ, de Kok TM, Coyle L, Chung S, Ferreira S, Jo H, Beattie KA, Kelly C, Duckworth CA, Pritchard DM, Pin C. A dynamic model of the intestinal epithelium integrates multiple sources of preclinical data and enables clinical translation of drug-induced toxicity. CPT Pharmacometrics Syst Pharmacol 2023; 12:1511-1528. [PMID: 37621010 PMCID: PMC10583244 DOI: 10.1002/psp4.13029] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 07/13/2023] [Accepted: 07/17/2023] [Indexed: 08/26/2023] Open
Abstract
We have built a quantitative systems toxicology modeling framework focused on the early prediction of oncotherapeutic-induced clinical intestinal adverse effects. The model describes stem and progenitor cell dynamics in the small intestinal epithelium and integrates heterogeneous epithelial-related processes, such as transcriptional profiles, citrulline kinetics, and probability of diarrhea. We fitted a mouse-specific version of the model to quantify doxorubicin and 5-fluorouracil (5-FU)-induced toxicity, which included pharmacokinetics and 5-FU metabolism and assumed that both drugs led to cell cycle arrest and apoptosis in stem cells and proliferative progenitors. The model successfully recapitulated observations in mice regarding dose-dependent disruption of proliferation which could lead to villus shortening, decrease of circulating citrulline, increased diarrhea risk, and transcriptional induction of the p53 pathway. Using a human-specific epithelial model, we translated the cytotoxic activity of doxorubicin and 5-FU quantified in mice into human intestinal injury and predicted with accuracy clinical diarrhea incidence. However, for gefitinib, a specific-molecularly targeted therapy, the mice failed to reproduce epithelial toxicity at exposures much higher than those associated with clinical diarrhea. This indicates that, regardless of the translational modeling approach, preclinical experimental settings have to be suitable to quantify drug-induced clinical toxicity with precision at the structural scale of the model. Our work demonstrates the usefulness of translational models at early stages of the drug development pipeline to predict clinical toxicity and highlights the importance of understanding cross-settings differences in toxicity when building these approaches.
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Affiliation(s)
- Louis Gall
- Clinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology and Safety Sciences, R&DAstraZenecaCambridgeUK
| | - Ferran Jardi
- Preclinical Sciences & Translational SafetyJanssen Pharmaceutica NVBeerseBelgium
| | - Lieve Lammens
- Preclinical Sciences & Translational SafetyJanssen Pharmaceutica NVBeerseBelgium
| | - Janet Piñero
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)UPFBarcelonaSpain
| | - Terezinha M. Souza
- Department of Toxicogenomics, GROW School for Oncology and Developmental BiologyMaastricht UniversityMaastrichtThe Netherlands
| | - Daniela Rodrigues
- Department of Toxicogenomics, GROW School for Oncology and Developmental BiologyMaastricht UniversityMaastrichtThe Netherlands
| | - Danyel G. J. Jennen
- Department of Toxicogenomics, GROW School for Oncology and Developmental BiologyMaastricht UniversityMaastrichtThe Netherlands
| | - Theo M. de Kok
- Department of Toxicogenomics, GROW School for Oncology and Developmental BiologyMaastricht UniversityMaastrichtThe Netherlands
| | - Luke Coyle
- Boehringer Ingelheim International GmbHRidgefieldConnecticutUSA
| | | | | | - Heeseung Jo
- Simcyp DivisionCertara UK LimitedSheffieldUK
| | - Kylie A. Beattie
- Target and Systems Safety, Non‐Clinical Safety, In Vivo/In Vitro TranslationGSKStevenageUK
| | - Colette Kelly
- Institute of Systems, Molecular and Integrative BiologyUniversity of LiverpoolLiverpoolUK
| | - Carrie A. Duckworth
- Institute of Systems, Molecular and Integrative BiologyUniversity of LiverpoolLiverpoolUK
| | - D. Mark Pritchard
- Institute of Systems, Molecular and Integrative BiologyUniversity of LiverpoolLiverpoolUK
| | - Carmen Pin
- Clinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology and Safety Sciences, R&DAstraZenecaCambridgeUK
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42
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Nakayama S, Toshimoto K, Yamazaki S, Snoeys J, Sugiyama Y. Physiologically-based pharmacokinetic modeling for investigating the effect of simeprevir on concomitant drugs and an endogenous biomarker of OATP1B. CPT Pharmacometrics Syst Pharmacol 2023; 12:1461-1472. [PMID: 37667529 PMCID: PMC10583237 DOI: 10.1002/psp4.13023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 07/11/2023] [Accepted: 07/18/2023] [Indexed: 09/06/2023] Open
Abstract
The orally available anti-hepatitis C virus (HCV) drug simeprevir exhibits nonlinear pharmacokinetics at the clinical doses due to saturation of cytochrome P450 (CYP) 3A4 metabolism and organic anion transporting peptide (OATP) 1B mediated hepatic uptake. Additionally, simeprevir increases exposures of concomitant drugs by CYP3A4 and OATP1B inhibition. The objective of this study was to develop physiologically-based pharmacokinetic (PBPK) models that could describe drug-drug interactions (DDIs) of simeprevir with concomitant drugs via CYP3A4 and OATP1B inhibition, and also to capture the effects on coproporphyrin-I (CP-I), an endogenous biomarker of OATP1B. PBPK modeling estimated unbound simeprevir inhibitory constant (Ki ) of 2.89 μM against CYP3A4 in the DDI results between simeprevir and midazolam in healthy volunteers. Then, we analyzed the DDIs between simeprevir and atorvastatin, a dual substrate of CYP3A4 and OATP1B, in healthy volunteers, and unbound Ki against OATP1B was estimated to be 0.00347 μM. Finally, we analyzed the increase in the blood level of CP-I by simeprevir to verify the Ki,OATP1B . Because CP-I was measured in subjects with HCV with various hepatic fibrosis state, Monte Carlo simulation was performed to involve the decreases in expression levels of hepatic CYP3A4 and OATP1B and their interindividual variabilities. The PBPK modeling coupled with Monte Carlo simulation using the Ki,OATP1B value obtained from atorvastatin study reasonably recovered the observed relationship between CP-I and simeprevir blood levels. In conclusion, the simeprevir PBPK model developed in this study can quantitatively describe the increase in exposures of concomitant drugs and an endogenous biomarker via inhibition of CYP3A4 and OATP1B.
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Affiliation(s)
- Shinji Nakayama
- DMPK Research Laboratories, Shoyaku, Innovative Research DivisionMitsubishi Tanabe Pharma CorporationYokohamaKanagawaJapan
| | - Kota Toshimoto
- Systems Pharmacology, Non‐Clinical Biomedical Science, Applied Research and OperationsAstellas Pharma Inc.IbarakiJapan
- Sugiyama Laboratory, RIKEN Cluster for ScienceRIKENYokohamaKanagawaJapan
| | - Shinji Yamazaki
- Drug Metabolism and PharmacokineticsJanssen Research and Development, LLCSan DiegoCaliforniaUSA
| | - Jan Snoeys
- Drug Metabolism and PharmacokineticsJanssen Research and DevelopmentBeerseBelgium
| | - Yuichi Sugiyama
- Sugiyama Laboratory, RIKEN Cluster for ScienceRIKENYokohamaKanagawaJapan
- Laboratory of Quantitative System Pharmacokinetics/PharmacodynamicsJosai International University (JIU)TokyoJapan
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43
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Zhang M, Zhang S, Yu Z, Yao X, Lei Z, Yan P, Wu N, Wang X, Hu Q, Liu D. Dose decision of HSK7653 oral immediate release tablets in specific populations clinical trials based on mechanistic physiologically-based pharmacokinetic model. Eur J Pharm Sci 2023; 189:106553. [PMID: 37532063 PMCID: PMC10485820 DOI: 10.1016/j.ejps.2023.106553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 07/25/2023] [Accepted: 07/30/2023] [Indexed: 08/04/2023]
Abstract
HSK7653, an oral dipeptidyl peptidase-4 inhibitor administered every 2 weeks, is a candidate for the treatment of type 2 diabetes mellitus. The major elimination pathway of HSK7653 in vivo is renal excretion, and hepatic metabolism and fecal excretion of unchanged compound contribute less to the systemic clearance of HSK7653. Considering the disposition characteristics and the potential indication population of HSK7653, evaluating the HSK7653 exposure in patients with renal impairment and geriatric populations is a prerequisite for bringing more benefits to the patients. Here, a PBPK model was developed based on in vitro experimental results, such as dissolution, permeability, and metabolism, and the in vivo renal clearance, to evaluate the effects of physiological factors and food on HSK7653 exposure in specific populations, including adult and elder individuals with renal impairment and geriatric populations. Simulation results showed that the AUC of HSK7653 increased by 46%, 82%, and 129% in adult patients with mild, moderate, and severe renal impairment, and by 56%, 78%, and 101% in patients aged 65-75, 75-85 and 85-95 years, respectively. The AUC increased in the range of 62%-83%, 98%-133%, and 153%-195% in elderly patients (65-95 years) with mild, moderate, and severe renal impairment, respectively. Moreover, two different absorption model development methods (dissolution profile method and the diffusion layer model method) predicted that food had no effect on the exposure of the same simulated population. Since the predicted AUC of HSK7653 at the 10 mg dose in various specific populations was still within the relatively flat results of the exposure-response analysis, the 10 mg dose of HSK7653 was first used to explore the exposure in the renal impairment population (CTR20221952).
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Affiliation(s)
- Miao Zhang
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China; Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, United States
| | - Shudong Zhang
- Beijing Institute for Drug Control, NMPA Key Laboratory for Research and Evaluation of Generic Drugs, Beijing Key Laboratory of Analysis and Evaluation on Chinese Medicine, Beijing, China
| | - Zhiheng Yu
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China; Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, China
| | - Xueting Yao
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China
| | - Zihan Lei
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China
| | - Pangke Yan
- Haisco Pharmaceutical Group Co., Ltd., Chengdu, China
| | - Nan Wu
- Haisco Pharmaceutical Group Co., Ltd., Chengdu, China
| | - Xu Wang
- Haisco Pharmaceutical Group Co., Ltd., Chengdu, China
| | - Qin Hu
- Beijing Institute for Drug Control, NMPA Key Laboratory for Research and Evaluation of Generic Drugs, Beijing Key Laboratory of Analysis and Evaluation on Chinese Medicine, Beijing, China
| | - Dongyang Liu
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China.
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44
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Wyszogrodzka-Gaweł G, Shuklinova O, Lisowski B, Wiśniowska B, Polak S. 3D printing combined with biopredictive dissolution and PBPK/PD modeling optimization and personalization of pharmacotherapy: Are we there yet? Drug Discov Today 2023; 28:103731. [PMID: 37541422 DOI: 10.1016/j.drudis.2023.103731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 07/25/2023] [Accepted: 07/28/2023] [Indexed: 08/06/2023]
Abstract
Precision medicine requires selecting the appropriate dosage regimen for a patient using the right drug, at the right time. Model-Informed Precision Dosing (MIPD) is a concept suggesting utilization of model-based prediction methods for optimizing the treatment benefit-harm balance, based on individual characteristics of the patient, disease, treatment method, and other factors. Here, we discuss a theoretical workflow comprising several elements, beginning from the physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) models, through 3D printed tablets with the model proposed dose, information range and flow, and the patient themselves. We also describe each of these elements, and the connection between them, highlighting challenges and potential obstacles.
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Affiliation(s)
- Gabriela Wyszogrodzka-Gaweł
- Department of Social Pharmacy, Faculty of Pharmacy, Jagiellonian University Medical College, Medyczna 9, 30-688 Kraków, Poland.
| | - Olha Shuklinova
- Chair of Pharmaceutical Technology and Biopharmaceutics, Faculty of Pharmacy. Jagiellonian University Medical College, Medyczna 9, 30-688 Kraków, Poland
| | - Bartek Lisowski
- Chair of Pharmaceutical Technology and Biopharmaceutics, Faculty of Pharmacy. Jagiellonian University Medical College, Medyczna 9, 30-688 Kraków, Poland.
| | - Barbara Wiśniowska
- Chair of Pharmaceutical Technology and Biopharmaceutics, Faculty of Pharmacy. Jagiellonian University Medical College, Medyczna 9, 30-688 Kraków, Poland.
| | - Sebastian Polak
- Chair of Pharmaceutical Technology and Biopharmaceutics, Faculty of Pharmacy. Jagiellonian University Medical College, Medyczna 9, 30-688 Kraków, Poland.
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45
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Ramachandran A, Gadgil CJ. A physiologically-based pharmacokinetic model for tuberculosis drug disposition at extrapulmonary sites. CPT Pharmacometrics Syst Pharmacol 2023; 12:1274-1284. [PMID: 37431175 PMCID: PMC10508491 DOI: 10.1002/psp4.13008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 05/20/2023] [Accepted: 06/20/2023] [Indexed: 07/12/2023] Open
Abstract
Tuberculosis (TB) is a leading cause of mortality attributed to an infectious agent. TB primarily targets the lungs, but in about 16% cases can affect other organs as well, giving rise to extrapulmonary TB (EPTB). However, an optimal regimen for EPTB treatment is not defined. Although the recommended treatment for most forms of EPTB is the same as pulmonary TB, the pharmacokinetics of EPTB therapy are not as well studied. To address this gap, we formulate a whole-body physiologically-based pharmacokinetic (PBPK) model for EPTB that for the first time includes the ability to simulate drug concentrations in the pleura and lymph node, the most commonly affected sites of EPTB. Using this model, we estimate the time-dependent concentrations, at potential EPTB infection sites, of the following four first-line anti-TB drugs: rifampicin, ethambutol, isoniazid, and pyrazinamide. We use reported plasma concentration kinetics data to estimate model parameters for each drug and validate our model using reported concentration data not used for model formulation or parameter estimation. Model predictions match the validation data, and reported pharmacokinetic parameters (maximum plasma concentration, time to reach maximum concentration) for the drugs. The model also predicts ethambutol, isoniazid, and pyrazinamide concentrations in the pleura that match reported experimental values from an independent study. For each drug, the predicted drug concentrations at EPTB sites are compared with their critical concentration. Simulations suggest that although rifampicin and isoniazid concentrations are greater than critical concentration values at most EPTB sites, the concentrations of ethambutol and pyrazinamide are lower than their critical concentrations at most EPTB sites.
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Affiliation(s)
- Aparna Ramachandran
- Chemical Engineering and Process Development DivisionCouncil of Scientific and Industrial Research‐National Chemical LaboratoryPuneIndia
- Academy of Scientific and Innovative Research, Council Of Scientific And Industrial Research–Human Resource Development Centre CampusGhaziabadIndia
| | - Chetan J. Gadgil
- Chemical Engineering and Process Development DivisionCouncil of Scientific and Industrial Research‐National Chemical LaboratoryPuneIndia
- Academy of Scientific and Innovative Research, Council Of Scientific And Industrial Research–Human Resource Development Centre CampusGhaziabadIndia
- Council of Scientific and Industrial Research‐Institute of Genomics and Integrative BiologyDelhiIndia
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46
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Adachi K, Utsumi M, Sato T, Nakano H, Shimizu M, Yamazaki H. Modeled Rat Hepatic and Plasma Concentrations of Chemicals after Virtual Administrations Using Two Sets of in Silico Liver-to-Plasma Partition Coefficients. Biol Pharm Bull 2023; 46:1316-1323. [PMID: 37380443 DOI: 10.1248/bpb.b23-00371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/30/2023]
Abstract
The hepatic elimination of chemical substances in pharmacokinetic models requires hepatic intrinsic clearance (CLh,int) parameters for unbound drug in the liver, and these are regulated by the liver-to-plasma partition coefficients (Kp,h). Both Poulin and Theil and Rodgers and Rowland have proposed in silico expressions for Kp,h for a variety of chemicals. In this study, two sets of in silico Kp,h values for 14 model substances were assessed using experimentally reported in vivo steady-state Kp,h data and time-dependent virtual internal exposures in the liver and plasma modeled by forward dosimetry in rats. The Kp,h values for 14 chemicals independently calculated using the primary Poulin and Theil method in this study were significantly correlated with those obtained using the updated Rodgers and Rowland method and with reported in vivo steady-state Kp,h data in rats. When pharmacokinetic parameters were derived based on individual in vivo time-dependent data for diazepam, phenytoin, and nicotine in rats, the modeled liver and plasma concentrations after intravenous administration of the selected substrates in rats using two sets of in silico Kp,h values were mostly similar to the reported time-dependent in vivo internal exposures. Similar results for modeled liver and plasma concentrations were observed with input parameters estimated by machine-learning systems for hexobarbital, fingolimod, and pentazocine, with no reference to experimental pharmacokinetic data. These results suggest that the output values from rat pharmacokinetic models based on in silico Kp,h values derived from the primary Poulin and Theil model would be applicable for estimating toxicokinetics or internal exposure to substances.
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47
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Alsmadi MM, Jaradat MM, Obaidat RM, Alnaief M, Tayyem R, Idkaidek N. The In Vitro, In Vivo, and PBPK Evaluation of a Novel Lung-Targeted Cardiac-Safe Hydroxychloroquine Inhalation Aerogel. AAPS PharmSciTech 2023; 24:172. [PMID: 37566183 DOI: 10.1208/s12249-023-02627-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 07/21/2023] [Accepted: 07/25/2023] [Indexed: 08/12/2023] Open
Abstract
Hydroxychloroquine (HCQ) was repurposed for COVID-19 treatment. Subtherapeutic HCQ lung levels and cardiac toxicity of oral HCQ were overcome by intratracheal (IT) administration of lower HCQ doses. The crosslinker-free supercritical fluid technology (SFT) produces aerogels and impregnates them with drugs in their amorphous form with efficient controlled release. Mechanistic physiologically based pharmacokinetic (PBPK) modeling can predict the lung's epithelial lining fluid (ELF) drug levels. This study aimed to develop a novel HCQ SFT formulation for IT administration to achieve maximal ELF levels and minimal cardiac toxicity. HCQ SFT formulation was prepared and evaluated for physicochemical, in vitro release, pharmacokinetics, and cardiac toxicity. Finally, the rat HCQ ELF concentrations were predicted using PBPK modeling. HCQ was amorphous after loading into the chitosan-alginate nanoporous microparticles (22.7±7.6 μm). The formulation showed a zero-order release, with only 40% released over 30 min compared to 94% for raw HCQ. The formulation had a tapped density of 0.28 g/cm3 and a loading efficiency of 35.3±1.3%. The IT administration of SFT HCQ at 1 mg/kg resulted in 23.7-fold higher bioavailability, fourfold longer MRT, and eightfold faster absorption but lower CK-MB and LDH levels than oral raw HCQ at 4 mg/kg. The PBPK model predicted 6 h of therapeutic ELF levels for IT SFT HCQ and a 100-fold higher ELF-to-heart concentration ratio than oral HCQ. Our findings support the feasibility of lung-targeted and more effective SFT HCQ IT administration for COVID-19 compared to oral HCQ with less cardiac toxicity. Graphical abstract.
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Affiliation(s)
- Mo'tasem M Alsmadi
- Department of Pharmaceutical Technology, Faculty of Pharmacy, Jordan University of Science and Technology, P.O. Box 3030, Irbid, 22110, Jordan.
- Nanotechnology Institute, Jordan University of Science and Technology, Irbid, Jordan.
| | - Mays M Jaradat
- Department of Pharmaceutical Technology, Faculty of Pharmacy, Jordan University of Science and Technology, P.O. Box 3030, Irbid, 22110, Jordan
| | - Rana M Obaidat
- Department of Pharmaceutics and Pharmaceutical Technology, Faculty of Pharmacy, The University of Jordan, Amman, Jordan
| | - Mohammad Alnaief
- Department of Pharmaceutical and Chemical Engineering, Faculty of Applied Medical Sciences, German Jordanian University, Amman, Jordan
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48
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Ganti A, Yu S, Sharpnack D, Ingalla E, De Bruyn T. Physiologically-based pharmacokinetic/pharmacodynamic modeling to predict tumor growth inhibition and the efficacious dose of selective estrogen receptor degraders in humans. Biopharm Drug Dispos 2023; 44:301-314. [PMID: 37102506 DOI: 10.1002/bdd.2358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 02/17/2023] [Accepted: 04/04/2023] [Indexed: 04/28/2023]
Abstract
GDC-9545 (giredestrant) is a highly potent, nonsteroidal, oral selective estrogen receptor antagonist and degrader that is being developed as a best-in-class drug candidate for early-stage and advanced drug-resistant breast cancer. GDC-9545 was designed to improve the poor absorption and metabolism of its predecessor GDC-0927, for which development was halted due to a high pill burden. This study aimed to develop physiologically-based pharmacokinetic/pharmacodynamic (PBPK-PD) models to characterize the relationships between oral exposure of GDC-9545 and GDC-0927 and tumor regression in HCI-013 tumor-bearing mice, and to translate these PK-PD relationships to a projected human efficacious dose by integrating clinical PK data. PBPK and Simeoni tumor growth inhibition (TGI) models were developed using the animal and human Simcyp V20 Simulator (Certara) and adequately described each compound's systemic drug concentrations and antitumor activity in the dose-ranging xenograft experiments in mice. The established PK-PD relationship was translated to a human efficacious dose by substituting mouse PK for human PK. PBPK input values for human clearance were predicted using allometry and in vitro in vivo extrapolation approaches and human volume of distribution was predicted from simple allometry or tissue composition equations. The integrated human PBPK-PD model was used to simulate TGI at clinically relevant doses. Translating the murine PBPK-PD relationship to a human efficacious dose projected a much lower efficacious dose for GDC-9545 than GDC-0927. Additional sensitivity analysis of key parameters in the PK-PD model demonstrated that the lower efficacious dose of GDC-9545 is a result of improvements in clearance and absorption. The presented PBPK-PD methodology can be applied to support lead optimization and clinical development of many drug candidates in discovery or early development programs.
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Affiliation(s)
- Anjani Ganti
- Drug Metabolism and Pharmacokinetics, Genentech, Inc., South San Francisco, California, USA
| | - Sijia Yu
- Drug Metabolism and Pharmacokinetics, Genentech, Inc., South San Francisco, California, USA
- Rutgers University, New Brunswick, New Jersey, USA
| | - Danielle Sharpnack
- Drug Metabolism and Pharmacokinetics, Genentech, Inc., South San Francisco, California, USA
| | - Ellen Ingalla
- Drug Metabolism and Pharmacokinetics, Genentech, Inc., South San Francisco, California, USA
| | - Tom De Bruyn
- Drug Metabolism and Pharmacokinetics, Genentech, Inc., South San Francisco, California, USA
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49
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Sagawa K, Lin J, Jaini R, Di L. Physiologically-Based Pharmacokinetic Modeling of PAXLOVID™ with First-Order Absorption Kinetics. Pharm Res 2023; 40:1927-1938. [PMID: 37231296 PMCID: PMC10212229 DOI: 10.1007/s11095-023-03538-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 05/15/2023] [Indexed: 05/27/2023]
Abstract
PURPOSE PAXLOVID™ is nirmatrelvir tablets co-packaged with ritonavir tablets. Ritonavir is used as a pharmacokinetics (PK) enhancer to reduce metabolism and increase exposure of nirmatrelvir. This is the first disclosure of Paxlovid physiologically-based pharmacokinetic (PBPK) model. METHODS Nirmatrelvir PBPK model with first-order absorption kinetics was developed using in vitro, preclinical, and clinical data of nirmatrelvir in the presence and absence of ritonavir. Clearance and volume of distribution were derived from nirmatrelvir PK obtained using a spray-dried dispersion (SDD) formulation where it is considered to be dosed as an oral solution, and absorption is near complete. The fraction of nirmatrelvir metabolized by CYP3A was estimated based on in vitro and clinical ritonavir drug-drug interaction (DDI) data. First-order absorption parameters were established for both SDD and tablet formulation using clinical data. Nirmatrelvir PBPK model was verified with both single and multiple dose human PK data, as well as DDI studies. Simcyp® first-order ritonavir compound file was also verified with additional clinical data. RESULTS The nirmatrelvir PBPK model described the observed PK profiles of nirmatrelvir well with predicted AUC and Cmax values within ± 20% of the observed. The ritonavir model performed well resulting in predicted values within twofold of observed. CONCLUSIONS Paxlovid PBPK model developed in this study can be applied to predict PK changes in special populations, as well as model the effect of victim and perpetrator DDI. PBPK modeling continues to play a critical role in accelerating drug discovery and development of potential treatments for devastating diseases such as COVID-19. NCT05263895, NCT05129475, NCT05032950 and NCT05064800.
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Affiliation(s)
- Kazuko Sagawa
- Pharmaceutical Science, Pfizer Worldwide Research and Development, 445 Eastern Point Road, Groton, CT, 06340, USA
| | - Jian Lin
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, 445 Eastern Point Road, Groton, CT, 06340, USA
| | - Rohit Jaini
- Pharmaceutical Science, Pfizer Worldwide Research and Development, 445 Eastern Point Road, Groton, CT, 06340, USA
- Pharmaceutical Science, Pfizer Worldwide Research and Development, 1 Portland Street, Cambridge, MA, 02139, USA
| | - Li Di
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, 445 Eastern Point Road, Groton, CT, 06340, USA.
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Salerno SN, Capparelli EV, McIlleron H, Gerhart JG, Dumond JB, Kashuba AD, Denti P, Gonzalez D. Leveraging physiologically based pharmacokinetic modeling to optimize dosing for lopinavir/ritonavir with rifampin in pediatric patients. Pharmacotherapy 2023; 43:638-649. [PMID: 35607886 PMCID: PMC9684348 DOI: 10.1002/phar.2703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 04/28/2022] [Indexed: 11/11/2022]
Abstract
STUDY OBJECTIVE Treatment of HIV and tuberculosis co-infection leads to significant mortality in pediatric patients, and treatment can be challenging due to the clinically significant drug-drug interaction (DDI) between lopinavir/ritonavir (LPV/RTV) and rifampin. Doubling LPV/RTV results in insufficient lopinavir trough concentrations in pediatric patients. The objective of this study was to leverage physiologically based pharmacokinetic (PBPK) modeling to optimize the adjusted doses of LPV/RTV in children receiving the WHO-revised doses of rifampin (15 mg/kg daily). DESIGN Adult and pediatric PBPK models for LPV/RTV with rifampin were developed, including CYP3A and P-glycoprotein inhibition and induction. SETTING (OR DATA SOURCE) Data for LPV/RTV model development and evaluation were available from the pediatric AIDS Clinical Trials Group. PATIENTS Dosing simulations were next performed to optimize dosing in children (2 months to 8 years of age). INTERVENTION Exposure following super-boosted LPV/RTV with 10 and 15 mg/kg PO daily rifampin was simulated. MEASUREMENTS AND MAIN RESULTS Simulated parameters were within twofold observations for LPV, RTV, and rifampin in adults and children ≥2 weeks old. The model predicted that, in healthy adults receiving 400/100 mg oral LPV/RTV twice daily (BID), co-treatment with 600 mg oral rifampin daily decreased the steady-state area under the concentration vs. time curve of LPV by 79%, in line with the observed change of 75%. Simulated and observed concentration profiles were comparable for LPV/RTV (230/57.5 mg/m2 ) PO BID without rifampin and 230/230 mg/m2 LPV/RTV PO BID with 10 mg/kg PO daily rifampin in pediatric patients. Sixteen mg/kg of super-boosted LPV (LPV/RTV 1:1) PO BID with 15 mg/kg PO daily rifampin achieved simulated LPV troughs >1 mg/L in ≥93% of virtual children weighing 3.0-24.9 kg, which was comparable with 10 mg/kg PO daily rifampin. CONCLUSIONS Super-boosted LPV/RTV with 15 mg/kg rifampin achieves therapeutic LPV troughs in HIV/TB-infected simulated children.
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Affiliation(s)
- Sara N. Salerno
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Edmund V. Capparelli
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Helen McIlleron
- Division of Clinical Pharmacology, Department of Medicine, University of Cape Town, Cape Town, South Africa
- Wellcome Centre for Infectious Diseases Research in Africa, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Observatory, South Africa
| | - Jacqueline G. Gerhart
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Julie B. Dumond
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Angela D.M. Kashuba
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Paolo Denti
- Division of Clinical Pharmacology, Department of Medicine, University of Cape Town, Cape Town, South Africa
| | - Daniel Gonzalez
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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