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Isoherranen N. Physiologically based pharmacokinetic modeling of small molecules: How much progress have we made? Drug Metab Dispos 2025; 53:100013. [PMID: 39884807 DOI: 10.1124/dmd.123.000960] [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: 11/01/2023] [Revised: 01/10/2024] [Accepted: 02/01/2024] [Indexed: 02/09/2024] Open
Abstract
Physiologically based pharmacokinetic (PBPK) models of small molecules have become mainstream in drug development and in academic research. The use of PBPK models is continuously expanding, with the majority of work now focusing on predictions of drug-drug interactions, drug-disease interactions, and changes in drug disposition across lifespan. Recently, publications that use PBPK modeling to predict drug disposition during pregnancy and in organ impairment have increased reflecting the advances in incorporating diverse physiologic changes into the models. Because of the expanding computational power and diversity of modeling platforms available, the complexity of PBPK models has also increased. Academic efforts have provided clear advances in better capturing human physiology in PBPK models and incorporating more complex mathematical concepts into PBPK models. Examples of such advances include the segregated gut model with a series of gut compartments allowing modeling of physiologic blood flow distribution within an organ and zonation of metabolic enzymes and series compartment liver models allowing simulations of hepatic clearance for high extraction drugs. Despite these advances in academic research, the progress in assessing model quality and defining model acceptance criteria based on the intended use of the models has not kept pace. This Minireview suggests that awareness of the need for predefined criteria for model acceptance has increased, but many manuscripts still lack description of scientific justification and/or rationale for chosen acceptance criteria. As artificial intelligence and machine learning approaches become more broadly accepted, these tools offer promise for development of comprehensive assessment for existing observed data and analysis of model performance. SIGNIFICANCE STATEMENT: Physiologically based pharmacokinetic (PBPK) modeling has become a mainstream application in academic literature and is broadly used for predictions, analysis, and evaluation of pharmacokinetic data. Significant progress has been made in developing advanced PBPK models that better capture human physiology, but oftentimes sufficient justification for the chosen model acceptance criterion and model structure is still missing. This Minireview provides a summary of the current landscape of PBPK applications used and highlights the need for advancing PBPK modeling science and training in academia.
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Affiliation(s)
- Nina Isoherranen
- Department of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, Washington.
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Palacharla VRC, Nirogi R, Kumar N, Nandakumar K. Determination of Intrinsic Clearance and Fraction Unbound in Human Liver Microsomes and In Vitro-In Vivo Extrapolation of Human Hepatic Clearance for Marketed Central Nervous System Drugs. Eur J Drug Metab Pharmacokinet 2024:10.1007/s13318-024-00931-2. [PMID: 39724218 DOI: 10.1007/s13318-024-00931-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/09/2024] [Indexed: 12/28/2024]
Abstract
OBJECTIVE The objective of this study was to determine the apparent intrinsic clearance (Clint, app) and fraction unbound in human liver microsomes (fu, mic) of 86 marketed central nervous system (CNS) drugs and to predict the in vivo hepatic blood clearance (CLh, b). METHODS Clint, app in human liver microsomes (HLM) was determined by substrate depletion, and fu, mic was determined by equilibrium dialysis. The relationship between lipophilicity (logP) and unbound intrinsic clearance (Clint, u) was explored using the Biopharmaceutical Drug Disposition Classification System (BDDCS) and Extended Clearance Classification System (ECCS). The predicted hepatic blood clearance by direct scaling, conventional method and Poulin method using well-stirred (WS) and parallel-tube (PT) models were compared with observed values. RESULTS The Clint, app in HLM ranged from < 5.8 to 477 µl/min/mg. The fu, mic in HLM ranged from 0.02 to 1.0. The scaled Clint values ranged from < 5 to 4496 ml/min/kg. The metabolic rate increased with an increase in logP (logP ≥ 2.5) of the CNS compounds. The direct scaling and Poulin methods showed comparable results based on the percentage of clearance predictions within a two-fold error. The conventional method resulted in under-predictions of Clint, in vivo or CLh, b using the WS or PT models. The Poulin method is favored over the other methods based on the statistical parameters. CONCLUSIONS Experimental Clint, app and fu, mic for 86 CNS compounds were successfully determined, and the scaled clearance was used to predict the hepatic blood clearance of 34 drugs. The success of prospective clearance predictions using HLM is expected to be high for most of the lipophilic BDDCS class 1 and class 2 and ECCS class 2 CNS compounds. The Poulin method resulted in more accurate predictions falling within a two-fold error of the observed values using the WS or PT models.
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Affiliation(s)
| | - Ramakrishna Nirogi
- Suven Life Sciences Limited, Serene Chambers, Road # 7, Hyderabad, 500034, India.
| | - Nitesh Kumar
- National Institute of Pharmaceutical Education and Research, Vaishali, Hajipur, Bihar, India
- Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India
| | - Krishnadas Nandakumar
- Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India
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Watanabe A, Akazawa T, Fujiu M. Understanding mechanisms of negative food effect for voclosporin using physiologically based pharmacokinetic modeling. Drug Metab Pharmacokinet 2024; 59:101032. [PMID: 39432969 DOI: 10.1016/j.dmpk.2024.101032] [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: 03/16/2024] [Revised: 09/04/2024] [Accepted: 09/09/2024] [Indexed: 10/23/2024]
Abstract
Negative food effect refers to a reduction in bioavailability, when a drug is taken with food. Voclosporin, a highly lipophilic cyclic peptide drug for treatment of active lupus nephritis, has shown negative food effect in clinical trials. Here, the cause of the negative food effect of voclosporin was investigated using physiologically based pharmacokinetic (PBPK) modeling to understand the mechanism responsible for oral absorption of voclosporin. Voclosporin is a substrate for P-glycoprotein and CYP3A4, and it has been evaluated for intestinal membrane permeability in human induced pluripotent stem cell-derived intestinal epithelial cells (hiPSC-IECs). The membrane permeability in hiPSC-IECs is integrated into the PBPK model for simulating permeability accurately. The PBPK model simulated the systemic PK profile in fasted state in human. Then, the PBPK model with in vitro adsorption of voclosporin onto food simulated the systemic PK profile in fed state for food effect. In addition, the PBPK model for rats also simulated the plasma profile of voclosporin for the food effect. These results suggest that a possible cause of the negative food effect of voclosporin is the adsorption of voclosporin to food in gastrointestinal tract. These approaches could facilitate understanding of the mechanisms responsible for oral absorption of cyclic peptides.
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Affiliation(s)
- Ayahisa Watanabe
- Laboratory for Medicinal Chemistry Research, Research Division, Shionogi & Co., Ltd., Japan.
| | - Takanori Akazawa
- Laboratory for Medicinal Chemistry Research, Research Division, Shionogi & Co., Ltd., Japan
| | - Motohiro Fujiu
- Laboratory for Medicinal Chemistry Research, Research Division, Shionogi & Co., Ltd., Japan
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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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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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Poulin P, Nicolas JM, Bouzom F. A New Version of the Tissue Composition-Based Model for Improving the Mechanism-Based Prediction of Volume of Distribution at Steady-State for Neutral Drugs. J Pharm Sci 2024; 113:118-130. [PMID: 37634869 DOI: 10.1016/j.xphs.2023.08.018] [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: 07/05/2023] [Revised: 08/18/2023] [Accepted: 08/19/2023] [Indexed: 08/29/2023]
Abstract
In-vitro models are available in the literature for predicting the volume of distribution at steady-state (Vdss) of drugs. The mechanistic model refers to the tissue composition-based model (TCM), which includes important factors that govern Vdss such as drug physiochemistry and physiological data. The recognized TCM published by Rodgers and Rowland (TCM-RR) and a subsequent adjustment made by Simulations Plus Inc. (TCM-SP) have been shown to be generally less accurate with neutral compared to ionized drugs. Therefore, improving these models for neutral drugs becomes necessary. The objective of this study was to propose a new TCM for improving the prediction of Vdss for neutral drugs. The new TCM included two modifications of the published models (i) accentuate the effect of the blood-to-plasma ratio (BPR) that should cover permeated molecules across the biomembranes, which is lacking in these models for neutral compounds, and (ii) use a different approach to estimate the binding in tissues. The new TCM was validated with a large dataset of 202 commercial and proprietary compounds including preclinical and clinical data. All scenario datasets were predicted more accurately with the TCM-New, whereas all statistical parameters indicate that the TCM-New showed significant improvements in terms of accuracy over the TCM-RR and TCM-SP. Predictions of Vdss were frequently more accurate for the TCM-new with 83% within twofold error versus only 50% for the TCM-RR. And more than 95% of the predictions were within threefold error and patient interindividual differences can be predicted with the TCM-New, greatly exceeding the accuracy of the published models. Overall, the new TCM incorporating BPR significantly improved the Vdss predictions in animals and humans for neutral drugs, and, hence, has the potential to better support the drug discovery and facilitate the first-in-human predictions.
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Affiliation(s)
- Patrick Poulin
- Consultant Patrick Poulin Inc., Québec City, Québec, Canada; School of Public Health, Université de Montréal, Montréal, Québec, Canada.
| | | | - François Bouzom
- DMPK, Development Science, UCB Pharma, Braine I'Alleud, Belgium; Current: Simulations Plus, Inc., 42505 10th Street West, Lancaster, CA 93534, USA
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McNamara PJ, Meiman D. Predicting the Effect of Renal Function on Systemic Clearance: Is a simple scaling method sufficient? J Pharm Sci 2023; 112:1724-1732. [PMID: 37023855 DOI: 10.1016/j.xphs.2023.03.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 03/13/2023] [Accepted: 03/13/2023] [Indexed: 04/08/2023]
Abstract
PURPOSE To employ a simple scaling method to predict systemic or oral clearance for drugs that are primarily renally cleared knowing the fraction eliminated in urine (fe) and a patient's renal function relative to healthy controls (SGFR). METHODS Observations evaluating drug clearance as a function of creatinine clearance for renally cleared drugs (fe >0.3) were obtained from literature sources. The analysis comprised of 82 unique drugs from 124 studies including 31 drugs with replicate studies. A simple scaler for renal function was employed and compared to the linear regression of available data. For drugs in which replicate studies were available, the ability of the linear regression (Cl vs ClCR) from one pharmacokinetic study was used to predict observations from an assigned replicate and compared to the scaling approach. RESULTS For patients categorized as severe kidney disease (ClCR fixed at 20 ml/min), the scalar tended to over predict some observations, but 92% of the predictions were within 50 - 200% of the observed data. For drugs with available replicates, the scalar was as good or better in predicting the influence of ClCR on systemic clearance from a separate study when comparing against the linear regression approach. CONCLUSION A scaling approach to account for alterations in drug clearance appears to have its advantages and represents a simple and generalizable method for guiding dose adjustments in patients with decreased renal function for drugs that are renally cleared (fe >0.3). In addition to its use in clinical practice, validation of this approach may have implications in facilitating more efficient drug development processes for designing dose-adjusted pharmacokinetic studies in patients with renal disease.
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Affiliation(s)
- Patrick J McNamara
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Kentucky, 789 S. Limestone, 361. Lexington, KY 40536-0596
| | - Darius Meiman
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN
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Zhang J, Wu K, Liu B, Hou S, Li X, Ye X, Liu J, He Q. Bioequivalence study of ipratropium bromide inhalation aerosol using PBPK modelling. Front Med (Lausanne) 2023; 10:1056318. [PMID: 36824609 PMCID: PMC9941642 DOI: 10.3389/fmed.2023.1056318] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 01/17/2023] [Indexed: 02/10/2023] Open
Abstract
Aims Systemic pharmacokinetic (PK) studies can reflect the overall exposure of orally inhaled drug Products (OIDPs) in the blood after inhalation into the lung and can be used to evaluate the bioequivalence of test and reference products. The aim of this article is: (1) to study the PK characteristics and bioequivalence of ipratropium bromide (IB) inhalation aerosol, reference and test products in healthy Chinese subjects; (2) to establish a physiologically based pharmacokinetic (PBPK) model and verify the accuracy of the model in predicting bioequivalence; (3) attempt to use the model to predict the regional distribution of particles in the lung after inhalation, and discuss the effect of gastrointestinal drug absorption of IB on systemic exposure. Methods The study involved two clinical studies. Clinical study-1 (registration number: CTR20201284) was used with non-clinical data to construct and validate a PBPK model in the B2O simulator, a web-based virtual drug development platform. This model assessed different test and reference products' bioequivalence. Results were compared to a second clinical study (Clinical study-2: registration number CTR20202291). The particles' regional distribution in the lung and the gastrointestinal absorption effect on systemic exposure were discussed based on the simulation results. Results The established PBPK model successfully simulated the in vivo PK characteristics of IB inhalation aerosol, with r 2 close to 1. Gastrointestinal absorption had a negligible effect on systemic exposure. Particles accumulated in the alveolar area were cleared within an hour, followed by particles in the bronchioles and bronchi. Conclusion This model provided a reliable method for exploring the correlation between in vitro and in vivo PK studies of IB inhalation aerosols. According to the simulation results, the test and reference products were bioequivalent.
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Affiliation(s)
- Jisheng Zhang
- Wuxi People’s Hospital Affiliated with Nanjing Medical University, Wuxi, Jiangsu, China
| | - Keheng Wu
- Yinghan Pharmaceutical Technology (Shanghai) Co., Ltd., Shanghai, China
| | - Bo Liu
- School of Chemical Engineering and Pharmacy, Wuhan Institute of Technology, Wuhan, China
| | - Shuguang Hou
- Sichuan Purity Medical Technology Co., Ltd., Sichuan, China
| | - Xue Li
- Yinghan Pharmaceutical Technology (Shanghai) Co., Ltd., Shanghai, China
| | - Xiang Ye
- Yinghan Pharmaceutical Technology (Shanghai) Co., Ltd., Shanghai, China
| | - Jack Liu
- Yinghan Pharmaceutical Technology (Shanghai) Co., Ltd., Shanghai, China
| | - Qing He
- Wuxi People’s Hospital Affiliated with Nanjing Medical University, Wuxi, Jiangsu, China,*Correspondence: Qing He, ✉
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The Application of Virtual Therapeutic Drug Monitoring to Assess the Pharmacokinetics of Imatinib in a Chinese Cancer Population Group. J Pharm Sci 2023; 112:599-609. [PMID: 36202248 DOI: 10.1016/j.xphs.2022.09.028] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 09/28/2022] [Accepted: 09/28/2022] [Indexed: 11/06/2022]
Abstract
PURPOSE Imatinib is used in gastrointestinal stromal tumours (GIST) and chronic myeloid leukaemia (CML). Oncology patients demonstrate altered physiology compared to healthy adults, e.g. reduced haematocrit, increased α-1 acid glycoprotein, decreased albumin and reduced glomerular filtration rate (GFR), which may influence imatinib pharmacokinetics. Given that Chinese cancer patients often report raised imatinib plasma concentrations and wider inter-individual variability reported in trough concentration when compared to Caucasian cancer patients, therapeutic drug monitoring (TDM) has been advocated. METHOD This study utilised a previously validated a Chinese cancer population and assessed the impact of imatinib virtual-TDM in Chinese and Caucasian cancer populations across a dosing range from 200-800 mg daily. RESULTS Staged dose titration to 800 mg daily, resulted in recapitulation to within the target therapeutic range for 50 % (Chinese) and 42.1% (Caucasian) subjects possessing plasma concentration < 550 ng/mL when dosed at 400 mg daily. For subjects with plasma concentrations >1500 ng/mL when dosed at 400 mg daily, a dose reduction to 200 mg once daily was able to recover 67 % (Chinese) and 87.4 % (Caucasian) patients to the target therapeutic range. CONCLUSION Virtual TDM highlights the benefit of pharmacokinetic modelling to optimising treatments in challenging oncology population groups.
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Khalidi H, Onasanwo A, Islam B, Jo H, Fisher C, Aidley R, Gardner I, Bois FY. SimRFlow: An R-based workflow for automated high-throughput PBPK simulation with the Simcyp® simulator. Front Pharmacol 2022; 13:929200. [PMID: 36091744 PMCID: PMC9455594 DOI: 10.3389/fphar.2022.929200] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 07/01/2022] [Indexed: 11/24/2022] Open
Abstract
SimRFlow is a high-throughput physiologically based pharmacokinetic (PBPK) modelling tool which uses Certara’s Simcyp® simulator. The workflow is comprised of three main modules: 1) a Data Collection module for automated curation of physicochemical (from ChEMBL and the Norman Suspect List databases) and experimental data (i.e.: clearance, plasma-protein binding, and blood-to-plasma ratio, from httk-R package databases), 2) a Simulation module which activates the Simcyp® simulator and runs Monte Carlo simulations on virtual subjects using the curated data, and 3) a Data Visualisation module for understanding the simulated compound-specific profiles and predictions. SimRFlow has three administration routes (oral, intravenous, dermal) and allows users to change some simulation parameters including the number of subjects, simulation duration, and dosing. Users are only expected to provide a file of the compounds they wish to simulate, and in return the workflow provides summary statistics, concentration-time profiles of various tissue types, and a database file (containing in-depth results) for each simulated compound. This is presented within a guided and easy-to-use R Shiny interface which provides many plotting options for the visualisation of concentration-time profiles, parameter distributions, trends between the different parameters, as well as comparison of predicted parameters across all batch-simulated compounds. The in-built R functions can be assembled in user-customised scripts which allows for the modification of the workflow for different purposes. SimRFlow proves to be a time-efficient tool for simulating a large number of compounds without any manual curation of physicochemical or experimental data necessary to run Simcyp® simulations.
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Greenblatt DJ, Bruno CD, Harmatz JS, Zhang Q, Chow CR. Drug Disposition in Subjects with Obesity: The Research Work of Darrell R. Abernethy. J Clin Pharmacol 2022; 62:1350-1363. [PMID: 35661375 DOI: 10.1002/jcph.2093] [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: 04/26/2022] [Accepted: 05/27/2022] [Indexed: 11/10/2022]
Abstract
In 1979, the late Dr. Darrell R. Abernethy and colleagues began a series of clinical studies aimed at understanding the pertinent determinants of drug distribution, elimination, and clearance in obesity, and how those variables are interconnected. The studies confirmed that volume of distribution (Vd) and clearance are the principal independent biological variables, which conjointly determine elimination half-life as a dependent variable. For drugs distributed by passive diffusion, their pharmacokinetic Vd - after correcting for plasma protein binding - was increased in obesity, depending in part on the physicochemical lipophilicity of the individual drugs, and the quantitative extent of obesity in overweight individuals. Across all studies, the ratio of mean clearance in obese divided by control groups had an overall median value of 1.21 (range: 0.75 to 3.11), indicating a small and variable effect of obesity on clearance, without clear directionality. Since drug clearance was not clearly related to lipophilicity or degree of obesity, the prolonged half-life of lipophilic drugs in obese patients was largely explained by the increased Vd. Dr. Abernethy further identified delayed attainment of steady-state after initiation of multiple-dose treatment, and delayed washout after termination of dosage, as potential clinical consequences of the extended half-life in obese persons. These consequences for specific drugs have been recently emphasized in contemporary studies of chronic dosage in subjects with obesity. Without data identifying an obesity-related change in clearance for a specific drug, maintenance doses (in milligrams) should be based on ideal weight rather than adjusted upward based on total weight. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- David J Greenblatt
- Program in Pharmacology and Drug Development, Tufts University School of Medicine and Graduate School of Biomedical Sciences, Boston, MA.,the Clinical and Translational Sciences Institute, Tufts Medical Center, Boston, MA
| | - Christopher D Bruno
- Program in Pharmacology and Drug Development, Tufts University School of Medicine and Graduate School of Biomedical Sciences, Boston, MA.,Emerald Lake Safety LLC, Newport Beach, CA
| | - Jerold S Harmatz
- Program in Pharmacology and Drug Development, Tufts University School of Medicine and Graduate School of Biomedical Sciences, Boston, MA
| | - Qingchen Zhang
- Program in Pharmacology and Drug Development, Tufts University School of Medicine and Graduate School of Biomedical Sciences, Boston, MA
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Peng J, Ladumor MK, Unadkat JD. Estimation of Fetal-to-Maternal Unbound Steady-State Plasma Concentration Ratio of P-Glycoprotein and/or Breast Cancer Resistance Protein Substrate Drugs Using a Maternal-Fetal Physiologically Based Pharmacokinetic Model. Drug Metab Dispos 2022; 50:613-623. [PMID: 35149540 PMCID: PMC9073947 DOI: 10.1124/dmd.121.000733] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 01/18/2022] [Indexed: 11/22/2022] Open
Abstract
Pregnant women are frequently prescribed drugs to treat chronic diseases such as human immunodeficiency virus infection, but little is known about the benefits and risks of these drugs to the fetus that are driven by fetal drug exposure. The latter can be estimated by fetal-to-maternal unbound plasma concentration at steady state (Kp,uu,fetal). For drugs that are substrates of placental efflux transporters [i.e., P-glycoprotein (P-gp) or breast cancer resistance protein (BCRP)], Kp,uu,fetal is expected to be <1. Here, we estimated the in vivo Kp,uu,fetal of selective P-gp and BCRP substrate drugs by maternal-fetal physiologically based pharmacokinetic (m-f-PBPK) modeling of umbilical vein (UV) plasma and maternal plasma (MP) concentrations obtained simultaneously at term from multiple maternal-fetal dyads. To do so, three drugs were selected: nelfinavir (P-gp substrate), efavirenz (BCRP substrate), and imatinib (P-gp/BCRP substrate). An m-f-PBPK model for each drug was developed and validated for the nonpregnant population and pregnant women using the Simcyp simulator (v20). Then, after incorporating placental passive diffusion clearance, the in vivo Kp,uu,fetal of the drug was estimated by adjusting the placental efflux clearance until the predicted UV/MP values best matched the observed data (Kp,uu,fetal) of nelfinavir = 0.41, efavirenz = 0.39, and imatinib = 0.35. Furthermore, Kp,uu,fetal of nelfinavir and efavirenz at gestational weeks (GWs) 25 and 15 were predicted to be 0.34 and 0.23 (GW25) and 0.33 and 0.27 (GW15). These Kp,uu,fetal values can be used to adjust dosing regimens of these drugs to optimize maternal-fetal drug therapy throughout pregnancy, to assess fetal benefits and risks of these dosing regimens, and to determine if these estimated in vivo Kp,uu,fetal values can be predicted from in vitro studies. SIGNIFICANCE STATEMENT: The in vivo fetal-to-maternal unbound steady-state plasma concentration ratio (Kp,uu,fetal) of nelfinavir [P-glycoprotein (P-gp) substrate], efavirenz [breast cancer resistance protein (BCRP) substrate], and imatinib (P-gp and BCRP substrate) was successfully estimated using maternal-fetal physiologically based pharmacokinetic (m-f-PBPK) modeling. These Kp,uu,fetal values can be used to adjust dosing regimens of these drugs to optimize maternal-fetal drug therapy throughout pregnancy, to assess fetal benefits and risks of these dosing regimens, and to determine if these estimated in vivo Kp,uu,fetal values can be predicted from in vitro studies.
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Affiliation(s)
- Jinfu Peng
- Department of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, Washington (J.P., M.K.L., J.D.U.) and Department of Pharmacy, The Third Xiangya Hospital, Central South University, Changsha, China (J.P.)
| | - Mayur K Ladumor
- Department of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, Washington (J.P., M.K.L., J.D.U.) and Department of Pharmacy, The Third Xiangya Hospital, Central South University, Changsha, China (J.P.)
| | - Jashvant D Unadkat
- Department of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, Washington (J.P., M.K.L., J.D.U.) and Department of Pharmacy, The Third Xiangya Hospital, Central South University, Changsha, China (J.P.)
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Choi S, Han S, Lee SJ, Lim B, Bae SH, Han S, Yim DS. DallphinAtoM: Physiologically based pharmacokinetics software predicting human PK parameters based on physicochemical properties, in vitro and animal in vivo data. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2022; 216:106662. [PMID: 35151112 DOI: 10.1016/j.cmpb.2022.106662] [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: 09/15/2021] [Revised: 11/12/2021] [Accepted: 01/24/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND AND OBJECTIVES In silico experiments and simulations using physiologically based pharmacokinetic (PBPK) and allometric approaches have played an important role in pharmaceutical research and drug development. These methods integrate diverse data from preclinical and clinical development, and have been widely applied to in vitro-in vivo extrapolation (IVIVE) of absorption, distribution, metabolism, and excretion (ADME). METHODS To develop a user-friendly open tool predicting human PK, we assessed various references on PBPK and allometric methods published so far. They were integrated into a software system named "DallphinAtoM" (Drugs with ALLometry and PHysiology Inside-Animal to huMan), which has a user-friendly platform that can handle complex PBPK models and allometric models with a relatively small amount of essential information of the drug. The models of DallphinAtoM support the integration of data gained during the nonclinical development phase, enable translation from animal to human, and allow the prediction of concentration-time profiles with predicted PK parameters. RESULTS We presented two illustrative applications using DallphinAtoM: (1) human PK simulation of an orally administered drug using PBPK method; and (2) simulation of intravenous infusion following a two-compartment model using the allometric scaling method. CONCLUSIONS We conclude that this is a straightforward and transparent tool allowing fast and reliable human PK simulation based on the latest knowledge on biochemical processes and physiology and provides valuable information for decision making during the early-phase drug development.
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Affiliation(s)
- Suein Choi
- Department of Clinical Pharmacology and Therapeutics, Seoul St. Mary's Hospital, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea; PIPET (Pharmacometrics Institute for Practical Education and Training), College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea
| | - Sungpil Han
- Department of Clinical Pharmacology and Therapeutics, Seoul St. Mary's Hospital, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea; PIPET (Pharmacometrics Institute for Practical Education and Training), College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea
| | - So Jin Lee
- PIPET (Pharmacometrics Institute for Practical Education and Training), College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea; Q-fitter Inc., Seoul 06578, Republic of Korea
| | - Byunghee Lim
- PIPET (Pharmacometrics Institute for Practical Education and Training), College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea
| | | | - Seunghoon Han
- Department of Clinical Pharmacology and Therapeutics, Seoul St. Mary's Hospital, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea; PIPET (Pharmacometrics Institute for Practical Education and Training), College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea
| | - Dong-Seok Yim
- Department of Clinical Pharmacology and Therapeutics, Seoul St. Mary's Hospital, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea; PIPET (Pharmacometrics Institute for Practical Education and Training), College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea.
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Kolli AR, Semren TZ, Bovard D, Majeed S, van der Toorn M, Scheuner S, Guy PA, Kuczaj A, Mazurov A, Frentzel S, Calvino-Martin F, Ivanov NV, O'Mullane J, Peitsch MC, Hoeng J. Pulmonary Delivery of Aerosolized Chloroquine and Hydroxychloroquine to Treat COVID-19: In Vitro Experimentation to Human Dosing Predictions. AAPS J 2022; 24:33. [PMID: 35132508 PMCID: PMC8821864 DOI: 10.1208/s12248-021-00666-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Accepted: 07/23/2021] [Indexed: 01/06/2023] Open
Abstract
In vitro screening for pharmacological activity of existing drugs showed chloroquine and hydroxychloroquine to be effective against severe acute respiratory syndrome coronavirus 2. Oral administration of these compounds to obtain desired pulmonary exposures resulted in dose-limiting systemic toxicity in humans. However, pulmonary drug delivery enables direct and rapid administration to obtain higher local tissue concentrations in target tissue. In this work, inhalable formulations for thermal aerosolization of chloroquine and hydroxychloroquine were developed, and their physicochemical properties were characterized. Thermal aerosolization of 40 mg/mL chloroquine and 100 mg/mL hydroxychloroquine formulations delivered respirable aerosol particle sizes with 0.15 and 0.33 mg per 55 mL puff, respectively. In vitro toxicity was evaluated by exposing primary human bronchial epithelial cells to aerosol generated from Vitrocell. An in vitro exposure to 7.24 μg of chloroquine or 7.99 μg hydroxychloroquine showed no significant changes in cilia beating, transepithelial electrical resistance, and cell viability. The pharmacokinetics of inhaled aerosols was predicted by developing a physiologically based pharmacokinetic model that included a detailed species-specific respiratory tract physiology and lysosomal trapping. Based on the model predictions, inhaling emitted doses comprising 1.5 mg of chloroquine or 3.3 mg hydroxychloroquine three times a day may yield therapeutically effective concentrations in the lung. Inhalation of higher doses further increased effective concentrations in the lung while maintaining lower systemic concentrations. Given the theoretically favorable risk/benefit ratio, the clinical significance for pulmonary delivery of aerosolized chloroquine and hydroxychloroquine to treat COVID-19 needs to be established in rigorous safety and efficacy studies. Graphical abstract.
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Affiliation(s)
- Aditya R Kolli
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000, Neuchâtel, Switzerland
| | - Tanja Zivkovic Semren
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000, Neuchâtel, Switzerland
| | - David Bovard
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000, Neuchâtel, Switzerland
| | - Shoaib Majeed
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000, Neuchâtel, Switzerland
| | - Marco van der Toorn
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000, Neuchâtel, Switzerland
| | - Sophie Scheuner
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000, Neuchâtel, Switzerland
| | - Philippe A Guy
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000, Neuchâtel, Switzerland
| | - Arkadiusz Kuczaj
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000, Neuchâtel, Switzerland
| | - Anatoly Mazurov
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000, Neuchâtel, Switzerland
| | - Stefan Frentzel
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000, Neuchâtel, Switzerland
| | - Florian Calvino-Martin
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000, Neuchâtel, Switzerland
| | - Nikolai V Ivanov
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000, Neuchâtel, Switzerland
| | - John O'Mullane
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000, Neuchâtel, Switzerland
| | - Manuel C Peitsch
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000, Neuchâtel, Switzerland
| | - Julia Hoeng
- PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000, Neuchâtel, Switzerland.
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Mast MP, Modh H, Champanhac C, Wang JW, Storm G, Krämer J, Mailänder V, Pastorin G, Wacker MG. Nanomedicine at the crossroads - A quick guide for IVIVC. Adv Drug Deliv Rev 2021; 179:113829. [PMID: 34174332 DOI: 10.1016/j.addr.2021.113829] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 05/17/2021] [Accepted: 06/10/2021] [Indexed: 02/08/2023]
Abstract
For many years, nanomedicine is pushing the boundaries of drug delivery. When applying these novel therapeutics, safety considerations are not only a key concern when entering clinical trials but also an important decision point in product development. Standing at the crossroads, nanomedicine may be able to escape the niche markets and achieve wider acceptance by the pharmaceutical industry. While there is a new generation of drug delivery systems, the extracellular vesicles, standing on the starting line, unresolved issues and new challenges emerge from their translation from bench to bedside. Some key features of injectable nanomedicines contribute to the predictability of the pharmacological and toxicological effects. So far, only a few of the physicochemical attributes of nanomedicines can be justified by a direct mathematical relationship between the in vitro and the in vivo responses. To further develop extracellular vesicles as drug carriers, we have to learn from more than 40 years of clinical experience in liposomal delivery and pass on this knowledge to the next generation. Our quick guide discusses relationships between physicochemical characteristics and the in vivo response, commonly referred to as in vitro-in vivo correlation. Further, we highlight the key role of computational methods, lay open current knowledge gaps, and question the established design strategies. Has the recent progress improved the predictability of targeted delivery or do we need another change in perspective?
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16
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O'Dwyer PJ, Box KJ, Imanidis G, Vertzoni M, Reppas C. On the usefulness of four in vitro methods in assessing the intraluminal performance of poorly soluble, ionisable compounds in the fasted state. Eur J Pharm Sci 2021; 168:106034. [PMID: 34628003 PMCID: PMC8665220 DOI: 10.1016/j.ejps.2021.106034] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 09/03/2021] [Accepted: 10/05/2021] [Indexed: 01/12/2023]
Abstract
A small-scale two-stage biphasic system, a small-scale two-stage dissolution-permeation system, the Erweka mini-paddle apparatus, and the BioGIT system were evaluated for their usefulness in assessing the intraluminal performance of two low solubility drugs in the fasted state, one with weakly acidic properties (tested in a salt form, diclofenac potassium) and one with weakly alkaline properties [ritonavir, tested as an amorphous solid dispersion (ASD) formulation]. In all in vitro methods, an immediate-release tablet and a powder formulation of diclofenac potassium were both rapidly dissolved in Level II biorelevant media simulating the conditions in the upper small intestine. Physiologically based biopharmaceutics (PBB) modelling for the tablet formulation resulted in a successful simulation of the average plasma profile in adults, whereas for the powder formulation modelling indicated that gastric emptying and transport through the intestinal epithelium limit the absorption rates. Detailed information on the behaviour of the ritonavir ASD formulation under both simulated gastric and upper small intestinal conditions were crucial for understanding the luminal performance. PBB modelling showed that the dissolution and precipitation parameters, estimated from the Erweka mini-paddle apparatus data and the small-scale two-stage biphasic system data, respectively, were necessary to adequately simulate the average plasma profile after administration of the ritonavir ASD formulation. Simulation of the gastrointestinal transfer process from the stomach to the small intestine was necessary to evaluate the effects of hypochlorhydric conditions on the luminal performance of the ritonavir ASD formulation. Based on this study, the selection of the appropriate in vitro method for evaluating the intraluminal performance of ionisable lipophilic drugs depends on the characteristics of the drug substance. The results suggest that for (salts of) acidic drugs (e.g., diclofenac potassium) it is only an issue of availability and ease of operation of the apparatus. For weakly alkaline substances (e.g., ritonavir), the results indicate that the dynamic dissolution process needs to be simulated, with the type of requested information (e.g., dissolution parameters, precipitation parameters, luminal concentrations) being key for selecting the most appropriate method. Regardless of the ionisation characteristics, early in the drug development process the use of small-scale systems may be inevitable, due to the limited quantities of drug substance available.
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Affiliation(s)
- Patrick J O'Dwyer
- Pion Inc. (UK) Ltd., Forest Row, East Sussex, United Kingdom; Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, Zografou, Greece; School of Pharmacy, University College Cork, College Road, Cork, Ireland
| | - Karl J Box
- Pion Inc. (UK) Ltd., Forest Row, East Sussex, United Kingdom
| | - Georgios Imanidis
- University of Applied Sciences Northwest. Switzerland. School of Life Sciences, Institute of Pharma Technology, Hofackerstrasse 30, 4132 Muttenz, Switzerland; University of Basel, Department of Pharmaceutical Sciences, Basel, Switzerland
| | - Maria Vertzoni
- Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, Zografou, Greece
| | - Christos Reppas
- Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, Zografou, Greece.
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17
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Kane Z, Picetti R, Wilby A, Standing JF, Grassin-Delyle S, Roberts I, Shakur-Still H. Physiologically based modelling of tranexamic acid pharmacokinetics following intravenous, intramuscular, sub-cutaneous and oral administration in healthy volunteers. Eur J Pharm Sci 2021; 164:105893. [PMID: 34087356 PMCID: PMC8299544 DOI: 10.1016/j.ejps.2021.105893] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 04/20/2021] [Accepted: 05/29/2021] [Indexed: 11/15/2022]
Abstract
Tranexamic acid (TXA) as a treatment for post-partum haemorrhage (PPH) depends on early intervention and rapid systemic exposure. This study uses PBPK modelling to evaluate the pharmacokinetics of TXA given by different routes of administration; intravenous, intramuscular, sub-cutaneous and oral. Intramuscular administration of 1000 mg TXA is predicted to achieve >15 mg/L in plasma in <15 min and exceed this level for approximately 3 h post dose. Background : Tranexamic acid (TXA) is an antifibrinolytic drug that reduces surgical blood loss and death due to bleeding after trauma and post-partum haemorrhage. Treatment success is dependant on early intervention and rapid systemic exposure to TXA. The requirement for intravenous (IV) administration can in some situations limit accessibility to TXA therapy. Here we employ physiologically based pharmacokinetic modelling (PBPK) to evaluate if adequate TXA exposure maybe achieved when given via different routes of administration. Methods : A commercially available PBPK software (GastroPlus®) was used to model published TXA pharmacokinetics. IV, oral and intramuscular (IM) models were developed using healthy volunteer PK data from twelve different single dose regimens (n = 48 participants). The model was verified using separate IV and oral validation datasets (n = 26 participants). Oral, IM and sub-cutaneous (SQ) dose finding simulations were performed. Results : Across the different TXA regimens evaluated TXA plasma concentrations varied from 0.1 to 94.0 µg/mL. Estimates of the total plasma clearance of TXA ranged from 0.091 to 0.104 L/h/kg, oral bioavailability from 36 to 67% and Tmax from 2.6 to 3.2 and 0.4 to 1.0 h following oral and intramuscular administration respectively. Variability in the observed TXA PK could be captured through predictable demographic effects on clearance, combined with intestinal permeability and stomach transit time following oral administration and muscle blood flow and muscle/plasma partition coefficients following intra-muscular dosing. Conclusions : This study indicates that intramuscular administration is the non-intravenous route of administration with the most potential for achieving targeted TXA exposures. Plasma levels following an IM dose of 1000 mg TXA are predicted to exceed 15 mg/mL in < 15 min and be maintained above this level for approximately 3 h, achieving systemic exposure (AUC0–6) of 99 to 105 µg*hr/mL after a single dose. Well-designed clinical trials to verify these predictions and confirm the utility of intramuscular TXA are recommended.
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Affiliation(s)
- Zoe Kane
- Quotient Sciences, Mere Way, Ruddington, Nottingham, United Kingdom; Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
| | - Roberto Picetti
- Clinical Trials Unit, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Alison Wilby
- Quotient Sciences, Mere Way, Ruddington, Nottingham, United Kingdom
| | - Joseph F Standing
- Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
| | - Stanislas Grassin-Delyle
- 3 Hôpital Foch, Suresnes, and Université Paris-Saclay, UVSQ, INSERM, Infection et inflammation, Montigny le Bretonneux, France
| | - Ian Roberts
- Clinical Trials Unit, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Haleema Shakur-Still
- Clinical Trials Unit, London School of Hygiene & Tropical Medicine, London, United Kingdom.
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18
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Abduljalil K, Pan X, Pansari A, Jamei M, Johnson TN. A Preterm Physiologically Based Pharmacokinetic Model. Part I: Physiological Parameters and Model Building. Clin Pharmacokinet 2021; 59:485-500. [PMID: 31583613 DOI: 10.1007/s40262-019-00825-6] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
BACKGROUND Developmental physiology can alter pharmacotherapy in preterm populations. Because of ethical and clinical constraints in studying this vulnerable age group, physiologically based pharmacokinetic models offer a viable alternative approach to predicting drug pharmacokinetics and pharmacodynamics in this population. However, such models require comprehensive information on the changes of anatomical, physiological and biochemical variables, where such data are not available in a single source. OBJECTIVE The objective of this study was to integrate the relevant physiological parameters required to build a physiologically based pharmacokinetic model for the preterm population. METHODS Published information on developmental preterm physiology and some drug-metabolising enzymes were collated and analysed. Equations were generated to describe the changes in parameter values during growth. RESULTS Data on organ size show different growth patterns that were quantified as functions of bodyweight to retain physiological variability and correlation. Protein binding data were quantified as functions of age as the body weight was not reported in the original articles. Ontogeny functions were derived for cytochrome P450 1A2, 3A4 and 2C9. Tissue composition values and how they change with age are limited. CONCLUSIONS Despite the limitations identified in the availability of some tissue composition values, the data presented in this article provide an integrated resource of system parameters needed for building a preterm physiologically based pharmacokinetic model.
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Affiliation(s)
- Khaled Abduljalil
- Simcyp Division Level 2-Acero, Certara UK Limited, 1 Concourse Way, Sheffield, S1 2BJ, UK.
| | - Xian Pan
- Simcyp Division Level 2-Acero, Certara UK Limited, 1 Concourse Way, Sheffield, S1 2BJ, UK
| | - Amita Pansari
- Simcyp Division Level 2-Acero, Certara UK Limited, 1 Concourse Way, Sheffield, S1 2BJ, UK
| | - Masoud Jamei
- Simcyp Division Level 2-Acero, Certara UK Limited, 1 Concourse Way, Sheffield, S1 2BJ, UK
| | - Trevor N Johnson
- Simcyp Division Level 2-Acero, Certara UK Limited, 1 Concourse Way, Sheffield, S1 2BJ, UK
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19
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Poulin P, Haddad S. A New Guidance for the Prediction of Hepatic Clearance in the Early Drug Discovery and Development from the in Vitro-to-in Vivo Extrapolation Method and an Approach for Exploring Whether an Albumin-Mediated Hepatic Uptake Phenomenon Could be Present Under in Vivo Conditions. J Pharm Sci 2021; 110:2841-2858. [PMID: 33857483 DOI: 10.1016/j.xphs.2021.04.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 04/03/2021] [Accepted: 04/04/2021] [Indexed: 11/18/2022]
Abstract
The in vitro-to-in vivo extrapolation (IVIVE) methods for predicting the hepatic clearance (CL) of drugs based on microsomal or hepatocyte data have certainly advanced; however, there is still place for improving the extrapolations from in vitro assays containing no plasma proteins. Accordingly, there is a discussion on whether the free drug hypothesis or an albumin (ALB)-mediated hepatic uptake phenomenon is the best scaling method. Therefore, the objectives of this study were to guide the prediction of CL and to diagnose which scaling method between the free drug hypothesis and ALB-mediated uptake could be more accurate; this, irrespective of the mechanism(s) governing CL if the drugs can get to the hepatocyte membrane. The analysis of several datasets demonstrated that almost all values of CL in vivo fall within the two calculated values of CL use as boundaries from: 1) the free drug hypothesis, and 2) ALB-mediated uptake. The average value from these two CL boundaries predicted the CL in vivo with an incredible accuracy. Validating these boundaries in preclinical species prior going to human as well as considering the fractional binding in plasma increased the accuracy. Overall, this study is another step towards guiding the CL prediction in drug discovery and development.
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Affiliation(s)
- Patrick Poulin
- Consultant Patrick Poulin Inc., Québec City, Québec, Canada; School of Public Health, Université de Montréal, Montréal, Québec, Canada.
| | - Sami Haddad
- School of Public Health, Université de Montréal, Montréal, Québec, Canada; Centre de Recherche en Santé Publique (CReSP), Montréal, Québec, Canada
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20
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Hsu F, Chen YC, Broccatelli F. Evaluation of Tissue Binding in Three Tissues across Five Species and Prediction of Volume of Distribution from Plasma Protein and Tissue Binding with an Existing Model. Drug Metab Dispos 2021; 49:330-336. [PMID: 33531412 DOI: 10.1124/dmd.120.000337] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Accepted: 01/25/2021] [Indexed: 11/22/2022] Open
Abstract
Volume of distribution (Vd) is a primary pharmacokinetic parameter used to calculate the half-life and plasma concentration-time profile of drugs. Numerous models have been relatively successful in predicting Vd, but the model developed by Korzekwa and Nagar is of particular interest because it utilizes plasma protein binding and microsomal binding data, both of which are readily available in vitro parameters. Here, Korzekwa and Nagar's model was validated and expanded upon using external and internal data sets. Tissue binding, plasma protein binding, Vd, physiochemical, and physiologic data sets were procured from literature and Genentech's internal data base. First, we investigated the hypothesis that tissue binding is primarily governed by passive processes that depend on the lipid composition of the tissue type. The fraction unbound in tissues (futissue) was very similar across human, rat, and mouse. In addition, we showed that dilution factors could be generated from nonlinear regression so that one futissue value could be used to estimate another one regardless of species. More importantly, results suggested that microsomes could serve as a surrogate for tissue binding. We applied the parameters from Korzekwa and Nagar's Vd model to two distinct liver microsomal data sets and found remarkably close statistical results. Brain and lung data sets also accurately predicted Vd, further validating the model. Vd prediction accuracy for compounds with log D7.4 > 1 significantly outperformed that of more hydrophilic compounds. Finally, human Vd predictions from Korzekwa and Nagar's model appear to be as accurate as rat allometry and slightly less accurate than dog and cynomolgus allometry. SIGNIFICANCE STATEMENT: This study shows that tissue binding is comparable across five species and can be interconverted with a dilution factor. In addition, we applied internal and external data sets to the volume of distribution model developed by Korzekwa and Nagar and found comparable Vd prediction accuracy between the Vd model and single-species allometry. These findings could potentially accelerate the drug research and development process by reducing the amount of resources associated with in vitro binding and animal experiments.
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Affiliation(s)
- Frederick Hsu
- Drug Metabolism and Pharmacokinetics, Genentech, Inc., South San Francisco, California
| | - Yi-Chen Chen
- Drug Metabolism and Pharmacokinetics, Genentech, Inc., South San Francisco, California
| | - Fabio Broccatelli
- Drug Metabolism and Pharmacokinetics, Genentech, Inc., South San Francisco, California
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21
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Physiologically based pharmacokinetic (PBPK) modeling of RNAi therapeutics: Opportunities and challenges. Biochem Pharmacol 2021; 189:114468. [PMID: 33577889 DOI: 10.1016/j.bcp.2021.114468] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 02/03/2021] [Accepted: 02/04/2021] [Indexed: 02/06/2023]
Abstract
Physiologically based pharmacokinetic (PBPK) modeling is a powerful tool with many demonstrated applications in various phases of drug development and regulatory review. RNA interference (RNAi)-based therapeutics are a class of drugs that have unique pharmacokinetic properties and mechanisms of action. With an increasing number of RNAi therapeutics in the pipeline and reaching the market, there is a considerable amount of active research in this area requiring a multidisciplinary approach. The application of PBPK models for RNAi therapeutics is in its infancy and its utility to facilitate the development of this new class of drugs is yet to be fully evaluated. From this perspective, we briefly discuss some of the current computational modeling approaches used in support of efficient development and approval of RNAi therapeutics. Considerations for PBPK model development are highlighted both in a relative context between small molecules and large molecules such as monoclonal antibodies and as it applies to RNAi therapeutics. In addition, the prospects for drawing upon other recognized avenues of PBPK modeling and some of the foreseeable challenges in PBPK model development for these chemical modalities are briefly discussed. Finally, an exploration of the potential application of PBPK model development for RNAi therapeutics is provided. We hope these preliminary thoughts will help initiate a dialogue between scientists in the relevant sectors to examine the value of PBPK modeling for RNAi therapeutics. Such evaluations could help standardize the practice in the future and support appropriate guidance development for strengthening the RNAi therapeutics development program.
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The use of PBPK/PD to establish clinically relevant dissolution specifications for zolpidem immediate release tablets. Eur J Pharm Sci 2020; 155:105534. [DOI: 10.1016/j.ejps.2020.105534] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 07/28/2020] [Accepted: 08/24/2020] [Indexed: 11/21/2022]
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Yim DS, Choi S. Predicting human pharmacokinetics from preclinical data: volume of distribution. Transl Clin Pharmacol 2020; 28:169-174. [PMID: 33425799 PMCID: PMC7781809 DOI: 10.12793/tcp.2020.28.e19] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Accepted: 12/15/2020] [Indexed: 11/21/2022] Open
Abstract
This tutorial introduces background and methods to predict the human volume of distribution (Vd) of drugs using in vitro and animal pharmacokinetic (PK) parameters. The physiologically based PK (PBPK) method is based on the familiar equation: Vd = Vp + ∑ T (VT × ktp ). In this equation, Vp (plasma volume) and VT (tissue volume) are known physiological values, and ktp (tissue plasma partition coefficient) is experimentally measured. Here, the ktp may be predicted by PBPK models because it is known to be correlated with the physicochemical property of drugs and tissue composition (fraction of lipid and water). Thus, PBPK models' evolution to predict human Vd has been the efforts to find a better function giving a more accurate ktp. When animal PK parameters estimated using i.v. PK data in ≥ 3 species are available, allometric methods can also be used to predict human Vd. Unlike the PBPK method, many different models may be compared to find the best-fitting one in the allometry, a kind of empirical approach. Also, compartmental Vd parameters (e.g., Vc, Vp, and Q) can be predicted in the allometry. Although PBPK and allometric methods have long been used to predict Vd, there is no consensus on method choice. When the discrepancy between PBPK-predicted Vd and allometry-predicted Vd is huge, physiological plausibility of all input and output data (e.g., r2-value of the allometric curve) may be reviewed for careful decision making.
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Affiliation(s)
- Dong-Seok Yim
- Department of Clinical Pharmacology and Therapeutics, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea
- PIPET (Pharmacometrics Institute for Practical Education and Training), College of Medicine, The Catholic University of Korea, Seoul 06591, Korea
| | - Suein Choi
- Department of Clinical Pharmacology and Therapeutics, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea
- PIPET (Pharmacometrics Institute for Practical Education and Training), College of Medicine, The Catholic University of Korea, Seoul 06591, Korea
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Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling to Predict the Impact of CYP2C9 Genetic Polymorphisms, Co-Medication and Formulation on the Pharmacokinetics and Pharmacodynamics of Flurbiprofen. Pharmaceutics 2020; 12:pharmaceutics12111049. [PMID: 33147873 PMCID: PMC7693160 DOI: 10.3390/pharmaceutics12111049] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Revised: 10/23/2020] [Accepted: 10/26/2020] [Indexed: 02/01/2023] Open
Abstract
Physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) models can serve as a powerful framework for predicting the influence as well as the interaction of formulation, genetic polymorphism and co-medication on the pharmacokinetics and pharmacodynamics of drug substances. In this study, flurbiprofen, a potent non-steroid anti-inflammatory drug, was chosen as a model drug. Flurbiprofen has absolute bioavailability of ~95% and linear pharmacokinetics in the dose range of 50–300 mg. Its absorption is considered variable and complex, often associated with double peak phenomena, and its pharmacokinetics are characterized by high inter-subject variability, mainly due to its metabolism by the polymorphic CYP2C9 (fmCYP2C9 ≥ 0.71). In this study, by leveraging in vitro, in silico and in vivo data, an integrated PBPK/PD model with mechanistic absorption was developed and evaluated against clinical data from PK, PD, drug-drug and gene-drug interaction studies. The PBPK model successfully predicted (within 2-fold) 36 out of 38 observed concentration-time profiles of flurbiprofen as well as the CYP2C9 genetic effects after administration of different intravenous and oral dosage forms over a dose range of 40–300 mg in both Caucasian and Chinese healthy volunteers. All model predictions for Cmax, AUCinf and CL/F were within two-fold of their respective mean or geometric mean values, while 90% of the predictions of Cmax, 81% of the predictions of AUCinf and 74% of the predictions of Cl/F were within 1.25 fold. In addition, the drug-drug and drug-gene interactions were predicted within 1.5-fold of the observed interaction ratios (AUC, Cmax ratios). The validated PBPK model was further expanded by linking it to an inhibitory Emax model describing the analgesic efficacy of flurbiprofen and applying it to explore the effect of formulation and genetic polymorphisms on the onset and duration of pain relief. This comprehensive PBPK/PD analysis, along with a detailed translational biopharmaceutic framework including appropriately designed biorelevant in vitro experiments and in vitro-in vivo extrapolation, provided mechanistic insight on the impact of formulation and genetic variations, two major determinants of the population variability, on the PK/PD of flurbiprofen. Clinically relevant specifications and potential dose adjustments were also proposed. Overall, the present work highlights the value of a translational PBPK/PD approach, tailored to target populations and genotypes, as an approach towards achieving personalized medicine.
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Komasaka T, Dressman J. Simulation of oral absorption from non-bioequivalent dosage forms of the salt of raltegravir, a poorly soluble acidic drug, using a physiologically based biopharmaceutical modeling (PBBM) approach. Eur J Pharm Sci 2020; 157:105630. [PMID: 33122010 DOI: 10.1016/j.ejps.2020.105630] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2020] [Revised: 10/13/2020] [Accepted: 10/23/2020] [Indexed: 11/24/2022]
Abstract
Non-bioequivalent plasma concentration profiles among different dosage forms of the salt of raltegravir, a poorly soluble acidic drug, were investigated using biorelevant in vitro testing combined with the commercial in silico software, Simcyp®. A suspension and a tablet dosage forms of raltegravir potassium were selected as the test formulations. While dissolution from the suspension was rapid, dissolution from the tablets was slow and delayed by pre-exposure to an acidic environment. Although the tablet was expected to have complex in vivo performance, plasma concentration profiles were successfully simulated when gastric emptying was taken into account as a key physiological factor in in vitro and in silico trials. The effect of pre-exposure to acid in the stomach on dissolution behavior in the intestine was estimated by two-stage in vitro dissolution testing. Based on these results, theoretical in vivo dissolution profiles for different gastric emptying times were inputted into the in silico model and plasma concentration profiles were simulated taking the distribution of individual gastric emptying times into account. The in vitro and in silico method presented in this report would be a practical approach to simulate oral absorption from various formulations of poorly soluble weak acids and their salts.
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Affiliation(s)
- Takao Komasaka
- Pharmaceutical Research Department, Mitsubishi Tanabe Pharma Corporation, 3-16-89, Kashima, Yodogawa-ku, Osaka 532-8505, Japan.
| | - Jennifer Dressman
- Fraunhofer Institute of Molecular Biology and Applied Ecology (IME), Division of Translational Pharmacology and Medicine (TMP), and Goethe University, Max-von-Laue Straße 9, D-60438 Frankfurt am Main, Germany
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Utsey K, Gastonguay MS, Russell S, Freling R, Riggs MM, Elmokadem A. Quantification of the Impact of Partition Coefficient Prediction Methods on Physiologically Based Pharmacokinetic Model Output Using a Standardized Tissue Composition. Drug Metab Dispos 2020; 48:903-916. [PMID: 32665416 DOI: 10.1124/dmd.120.090498] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Accepted: 07/06/2020] [Indexed: 02/13/2025] Open
Abstract
Tissue:plasma partition coefficients are key parameters in physiologically based pharmacokinetic (PBPK) models, yet the coefficients are challenging to measure in vivo. Several mechanistic-based equations have been developed to predict partition coefficients using tissue composition information and the compound's physicochemical properties, but it is not clear which, if any, of the methods is most appropriate under given circumstances. Complicating the evaluation, each prediction method was developed, and is typically employed, using a different set of tissue composition information, thereby making a controlled comparison impossible. This study proposed a standardized tissue composition for humans that can be used as a common input for each of the five frequently used prediction methods. These methods were implemented in R and were used to predict partition coefficients for 11 drugs, classified as strong bases, weak bases, acids, neutrals, and zwitterions. PBPK models developed in R (mrgsolve) for each drug and each set of partition coefficient predictions were compared with respective observed plasma concentration data. Percent root mean square error and half-life percent error were used to evaluate the accuracy of the PBPK model predictions using each partition coefficient method as summarized by strong bases, weak bases, acids, neutrals, and zwitterions characterization. The analysis indicated that no partition coefficient method consistently yielded the most accurate PBPK model predictions. As such, PBPK model predictions using all partition coefficient methods should be considered during drug development. SIGNIFICANCE STATEMENT: Several mechanistic-based methods exist to predict tissue:plasma partition coefficients critical to PBPK modeling. Controlled comparisons are confounded by the use of different tissue composition values for each method; a standardized tissue composition was proposed. Resulting assessments indicated that no method was consistently superior; therefore, sensitivity of PBPK predictions to each method may be warranted prior to model optimization.
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Affiliation(s)
- Kiersten Utsey
- Metrum Research Group, Tariffville, Connecticut (K.U., M.S.G., S.R., R.F., M.M.R., A.E.); University of Utah, Salt Lake City, Utah (K.U.); University of Connecticut, Storrs, Connecticut (M.S.G.); University of Michigan, Ann Arbor, Michigan (S.R.); and Cornell University, Ithaca, New York (R.F.)
| | - Madeleine S Gastonguay
- Metrum Research Group, Tariffville, Connecticut (K.U., M.S.G., S.R., R.F., M.M.R., A.E.); University of Utah, Salt Lake City, Utah (K.U.); University of Connecticut, Storrs, Connecticut (M.S.G.); University of Michigan, Ann Arbor, Michigan (S.R.); and Cornell University, Ithaca, New York (R.F.)
| | - Sean Russell
- Metrum Research Group, Tariffville, Connecticut (K.U., M.S.G., S.R., R.F., M.M.R., A.E.); University of Utah, Salt Lake City, Utah (K.U.); University of Connecticut, Storrs, Connecticut (M.S.G.); University of Michigan, Ann Arbor, Michigan (S.R.); and Cornell University, Ithaca, New York (R.F.)
| | - Reed Freling
- Metrum Research Group, Tariffville, Connecticut (K.U., M.S.G., S.R., R.F., M.M.R., A.E.); University of Utah, Salt Lake City, Utah (K.U.); University of Connecticut, Storrs, Connecticut (M.S.G.); University of Michigan, Ann Arbor, Michigan (S.R.); and Cornell University, Ithaca, New York (R.F.)
| | - Matthew M Riggs
- Metrum Research Group, Tariffville, Connecticut (K.U., M.S.G., S.R., R.F., M.M.R., A.E.); University of Utah, Salt Lake City, Utah (K.U.); University of Connecticut, Storrs, Connecticut (M.S.G.); University of Michigan, Ann Arbor, Michigan (S.R.); and Cornell University, Ithaca, New York (R.F.)
| | - Ahmed Elmokadem
- Metrum Research Group, Tariffville, Connecticut (K.U., M.S.G., S.R., R.F., M.M.R., A.E.); University of Utah, Salt Lake City, Utah (K.U.); University of Connecticut, Storrs, Connecticut (M.S.G.); University of Michigan, Ann Arbor, Michigan (S.R.); and Cornell University, Ithaca, New York (R.F.)
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Klumpp L, Dressman J. Physiologically based pharmacokinetic model outputs depend on dissolution data and their input: Case examples glibenclamide and dipyridamole. Eur J Pharm Sci 2020; 151:105380. [PMID: 32442630 DOI: 10.1016/j.ejps.2020.105380] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Revised: 04/05/2020] [Accepted: 05/13/2020] [Indexed: 01/22/2023]
Abstract
A plethora of dissolution tests exists for oral dosage forms, with variations in selection of the dissolution medium, the hydrodynamics and the dissolution equipment. This work aimed at determining the influence of media composition, the type of dissolution test and the method for entering the data into a PBPK model on the ability to simulate the in vivo plasma profile of an immediate release formulation. Using two rDCS IIa substances, glibenclamide and dipyridamole, housed in immediate-release formulations as model dosage forms, dissolution tests were performed in USP apparatus II with the biorelevant media FaSSGF, FaSSIF V1, V2 and V3 using both single-stage and two-stage test designs. The results were then integrated into the PBPK software SimcypⓇ either as the observed release profile (dissolution rate model, DRM) or using a semi-mechanistic model (diffusion layer model, DLM) and compared with in vivo plasma profiles. The selection of the FaSSIF version did not appear to have any relevant influence on the dissolution of the weakly basic dipyridamole, while the weakly acidic glibenclamide was sensitive to the difference in pH between FaSSIF V1, V2 and FaSSIF V3. Since both compounds have pKa values close to the pH of biorelevant media representing conditions in the small intestine, these results may be specific to compounds with similar ionization behavior. Single-stage and two-stage testing led to equivalent simulations for glibenclamide. Only results from the single-stage test in FaSSGF led to a close simulation of the pharmacokinetic profile of dipyridamole when data were inputted using the DRM, while simulations from two-stage testing were most similar to the observed pharmacokinetic profile when DLM with selection of a dynamic pH profile in the small intestine was selected as the data input method. These results emphasize the importance of data input to the simulation results.
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Affiliation(s)
- Lukas Klumpp
- Institute of Pharmaceutical Technology, Goethe University and Fraunhofer Institute of Molecular Biology and Applied Ecology (IME) Division of Translational Medicine and Pharmacology (TMP), Frankfurt am Main, Germany
| | - Jennifer Dressman
- Institute of Pharmaceutical Technology, Goethe University and Fraunhofer Institute of Molecular Biology and Applied Ecology (IME) Division of Translational Medicine and Pharmacology (TMP), Frankfurt am Main, Germany.
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Williamson B, Colclough N, Fretland AJ, Jones BC, Jones RDO, McGinnity DF. Further Considerations Towards an Effective and Efficient Oncology Drug Discovery DMPK Strategy. Curr Drug Metab 2020; 21:145-162. [PMID: 32164508 DOI: 10.2174/1389200221666200312104837] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 01/06/2020] [Accepted: 02/25/2020] [Indexed: 12/21/2022]
Abstract
BACKGROUND DMPK data and knowledge are critical in maximising the probability of developing successful drugs via the application of in silico, in vitro and in vivo approaches in drug discovery. METHODS The evaluation, optimisation and prediction of human pharmacokinetics is now a mainstay within drug discovery. These elements are at the heart of the 'right tissue' component of AstraZeneca's '5Rs framework' which, since its adoption, has resulted in increased success of Phase III clinical trials. With the plethora of DMPK related assays and models available, there is a need to continually refine and improve the effectiveness and efficiency of approaches best to facilitate the progression of quality compounds for human clinical testing. RESULTS This article builds on previously published strategies from our laboratories, highlighting recent discoveries and successes, that brings our AstraZeneca Oncology DMPK strategy up to date. We review the core aspects of DMPK in Oncology drug discovery and highlight data recently generated in our laboratories that have influenced our screening cascade and experimental design. We present data and our experiences of employing cassette animal PK, as well as re-evaluating in vitro assay design for metabolic stability assessments and expanding our use of freshly excised animal and human tissue to best inform first time in human dosing and dose escalation studies. CONCLUSION Application of our updated drug-drug interaction and central nervous system drug exposure strategies are exemplified, as is the impact of physiologically based pharmacokinetic and pharmacokinetic-pharmacodynamic modelling for human predictions.
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Affiliation(s)
- Beth Williamson
- Drug Metabolism and Pharmacokinetics, Research and Early Development, Oncology R&D, AstraZeneca, Cambridge, United Kingdom
| | - Nicola Colclough
- Drug Metabolism and Pharmacokinetics, Research and Early Development, Oncology R&D, AstraZeneca, Cambridge, United Kingdom
| | - Adrian John Fretland
- Drug Metabolism and Pharmacokinetics, Research and Early Development, Oncology R&D, AstraZeneca, Boston MA, United States
| | - Barry Christopher Jones
- Drug Metabolism and Pharmacokinetics, Research and Early Development, Oncology R&D, AstraZeneca, Cambridge, United Kingdom
| | - Rhys Dafydd Owen Jones
- Drug Metabolism and Pharmacokinetics, Research and Early Development, Oncology R&D, AstraZeneca, Cambridge, United Kingdom
| | - Dermot Francis McGinnity
- Drug Metabolism and Pharmacokinetics, Research and Early Development, Oncology R&D, AstraZeneca, Cambridge, United Kingdom
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Litou C, Turner DB, Holmstock N, Ceulemans J, Box KJ, Kostewicz E, Kuentz M, Holm R, Dressman J. Combining biorelevant in vitro and in silico tools to investigate the in vivo performance of the amorphous solid dispersion formulation of etravirine in the fed state. Eur J Pharm Sci 2020; 149:105297. [PMID: 32151705 DOI: 10.1016/j.ejps.2020.105297] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Revised: 01/26/2020] [Accepted: 03/05/2020] [Indexed: 02/08/2023]
Abstract
INTRODUCTION In the development of bio-enabling formulations, innovative in vivo predictive tools to understand and predict the in vivo performance of such formulations are needed. Etravirine, a non-nucleoside reverse transcriptase inhibitor, is currently marketed as an amorphous solid dispersion (Intelence® tablets). The aims of this study were 1) to investigate and discuss the advantages of using biorelevant in vitro setups to simulate the in vivo performance of Intelence® 100 mg and 200 mg tablets in the fed state, 2) to build a Physiologically Based Pharmacokinetic (PBPK) model by combining experimental data and literature information with the commercially available in silico software Simcyp® Simulator V17.1 (Certara UK Ltd.), and 3) to discuss the challenges of predicting the in vivo performance of an amorphous solid dispersion and identify the parameters which influence the pharmacokinetics of etravirine most. METHODS Solubility, dissolution and transfer experiments were performed in various biorelevant media simulating the fasted and fed state environment in the gastrointestinal tract. An in silico PBPK model for etravirine in healthy volunteers was developed in the Simcyp® Simulator, using in vitro results and data available from the literature as input. The impact of pre- and post-absorptive parameters on the pharmacokinetics of etravirine was investigated by simulating various scenarios. RESULTS In vitro experiments indicated a large effect of naturally occurring solubilizing agents on the solubility of etravirine. Interestingly, supersaturated concentrations of etravirine were observed over the entire duration of dissolution experiments on Intelence® tablets. Coupling the in vitro results with the PBPK model provided the opportunity to investigate two possible absorption scenarios, i.e. with or without implementation of precipitation. The results from the simulations suggested that a scenario in which etravirine does not precipitate is more representative of the in vivo data. On the post-absorptive side, it appears that the concentration dependency of the unbound fraction of etravirine in plasma has a significant effect on etravirine pharmacokinetics. CONCLUSIONS The present study underlines the importance of combining in vitro and in silico biopharmaceutical tools to advance our knowledge in the field of bio-enabling formulations. Future studies on other bio-enabling formulations can be used to further explore this approach to support rational formulation design as well as robust prediction of clinical outcomes.
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Affiliation(s)
- Chara Litou
- Institute of Pharmaceutical Technology, Goethe University, Frankfurt am Main, Germany
| | - David B Turner
- Certara UK Limited, Simcyp Division, Level 2-Acero, 1 Concourse Way, Sheffield, S1 2BJ, United Kingdom
| | - Nico Holmstock
- Drug Product Development, Janssen R&D, Johnson & Johnson, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Jens Ceulemans
- Drug Product Development, Janssen R&D, Johnson & Johnson, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Karl J Box
- Pion Inc. (UK) Ltd., Forest Row, East Sussex, United Kingdom
| | - Edmund Kostewicz
- Institute of Pharmaceutical Technology, Goethe University, Frankfurt am Main, Germany
| | - Martin Kuentz
- University of Applied Sciences and Arts Northwestern Switzerland, Hofackerstr. 30, 4132, Switzerland
| | - Rene Holm
- Drug Product Development, Janssen R&D, Johnson & Johnson, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Jennifer Dressman
- Institute of Pharmaceutical Technology, Goethe University, Frankfurt am Main, Germany; Fraunhofer Institute of Translational Pharmacology and Medicine, Frankfurt, Germany.
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Yau E, Olivares-Morales A, Gertz M, Parrott N, Darwich AS, Aarons L, Ogungbenro K. Global Sensitivity Analysis of the Rodgers and Rowland Model for Prediction of Tissue: Plasma Partitioning Coefficients: Assessment of the Key Physiological and Physicochemical Factors That Determine Small-Molecule Tissue Distribution. AAPS JOURNAL 2020; 22:41. [PMID: 32016678 DOI: 10.1208/s12248-020-0418-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Accepted: 01/07/2020] [Indexed: 12/14/2022]
Abstract
In physiologically based pharmacokinetic (PBPK) modelling, the large number of input parameters, limited amount of available data and the structural model complexity generally hinder simultaneous estimation of uncertain and/or unknown parameters. These parameters are generally subject to estimation. However, the approaches taken for parameter estimation vary widely. Global sensitivity analyses are proposed as a method to systematically determine the most influential parameters that can be subject to estimation. Herein, a global sensitivity analysis was conducted to identify the key drug and physiological parameters influencing drug disposition in PBPK models and to potentially reduce the PBPK model dimensionality. The impact of these parameters was evaluated on the tissue-to-unbound plasma partition coefficients (Kpus) predicted by the Rodgers and Rowland model using Latin hypercube sampling combined to partial rank correlation coefficients (PRCC). For most drug classes, PRCC showed that LogP and fraction unbound in plasma (fup) were generally the most influential parameters for Kpu predictions. For strong bases, blood:plasma partitioning was one of the most influential parameter. Uncertainty in tissue composition parameters had a large impact on Kpu and Vss predictions for all classes. Among tissue composition parameters, changes in Kpu outputs were especially attributed to changes in tissue acidic phospholipid concentrations and extracellular protein tissue:plasma ratio values. In conclusion, this work demonstrates that for parameter estimation involving PBPK models and dimensionality reduction purposes, less influential parameters might be assigned fixed values depending on the parameter space, while influential parameters could be subject to parameters estimation.
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Affiliation(s)
- Estelle Yau
- Centre for Applied Pharmacokinetic Research (CAPKR), The University of Manchester, Manchester, UK.,Roche Pharma and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Andrés Olivares-Morales
- Roche Pharma and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Grenzacherstrasse 124, 4070, Basel, Switzerland.
| | - Michael Gertz
- Roche Pharma and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Neil Parrott
- Roche Pharma and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Adam S Darwich
- Centre for Applied Pharmacokinetic Research (CAPKR), The University of Manchester, Manchester, UK.,Logistics and Informatics in Health Care, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), KTH Royal Institute of Technology, Stockholm, Sweden
| | - Leon Aarons
- Roche Pharma and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Kayode Ogungbenro
- Roche Pharma and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Grenzacherstrasse 124, 4070, Basel, Switzerland
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Loisios-Konstantinidis I, Cristofoletti R, Fotaki N, Turner DB, Dressman J. Establishing virtual bioequivalence and clinically relevant specifications using in vitro biorelevant dissolution testing and physiologically-based population pharmacokinetic modeling. case example: Naproxen. Eur J Pharm Sci 2020; 143:105170. [DOI: 10.1016/j.ejps.2019.105170] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Revised: 11/25/2019] [Accepted: 11/26/2019] [Indexed: 01/19/2023]
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Holt K, Ye M, Nagar S, Korzekwa K. Prediction of Tissue-Plasma Partition Coefficients Using Microsomal Partitioning: Incorporation into Physiologically based Pharmacokinetic Models and Steady-State Volume of Distribution Predictions. Drug Metab Dispos 2019; 47:1050-1060. [PMID: 31324699 PMCID: PMC6750188 DOI: 10.1124/dmd.119.087973] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Accepted: 07/09/2019] [Indexed: 11/22/2022] Open
Abstract
Drug distribution is a necessary component of models to predict human pharmacokinetics. A new membrane-based tissue-plasma partition coefficient (K p) method (K p,mem) to predict unbound tissue to plasma partition coefficients (K pu) was developed using in vitro membrane partitioning [fraction unbound in microsomes (f um)], plasma protein binding, and log P The resulting K p values were used in a physiologically based pharmacokinetic (PBPK) model to predict the steady-state volume of distribution (V ss) and concentration-time (C-t) profiles for 19 drugs. These results were compared with K p predictions using a standard method [the differential phospholipid K p prediction method (K p,dPL)], which differentiates between acidic and neutral phospholipids. The K p,mem method was parameterized using published rat K pu data and tissue lipid composition. The K pu values were well predicted with R 2 = 0.8. When used in a PBPK model, the V ss predictions were within 2-fold error for 12 of 19 drugs for K p,mem versus 11 of 19 for Kp,dPL With one outlier removed for K p,mem and two for K p,dPL, the V ss predictions for R 2 were 0.80 and 0.79 for the K p,mem and K p,dPL methods, respectively. The C-t profiles were also predicted and compared. Overall, the K p,mem method predicted the V ss and C-t profiles equally or better than the K p,dPL method. An advantage of using f um to parameterize membrane partitioning is that f um data are used for clearance prediction and are, therefore, generated early in the discovery/development process. Also, the method provides a mechanistically sound basis for membrane partitioning and permeability for further improving PBPK models. SIGNIFICANCE STATEMENT: A new method to predict tissue-plasma partition coefficients was developed. The method provides a more mechanistic basis to model membrane partitioning.
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Affiliation(s)
- Kimberly Holt
- Department of Pharmaceutical Sciences, Temple University School of Pharmacy, Philadelphia, Pennsylvania
| | - Min Ye
- Department of Pharmaceutical Sciences, Temple University School of Pharmacy, Philadelphia, Pennsylvania
| | - Swati Nagar
- Department of Pharmaceutical Sciences, Temple University School of Pharmacy, Philadelphia, Pennsylvania
| | - Ken Korzekwa
- Department of Pharmaceutical Sciences, Temple University School of Pharmacy, Philadelphia, Pennsylvania
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Holt K, Nagar S, Korzekwa K. Methods to Predict Volume of Distribution. CURRENT PHARMACOLOGY REPORTS 2019; 5:391-399. [PMID: 34168949 PMCID: PMC8221585 DOI: 10.1007/s40495-019-00186-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
PURPOSE OF REVIEW Prior to human studies, knowledge of drug disposition in the body is useful to inform decisions on drug safety and efficacy, first in human dosing, and dosing regimen design. It is therefore of interest to develop predictive models for primary pharmacokinetic parameters, clearance, and volume of distribution. The volume of distribution of a drug is determined by the physiological properties of the body and physiochemical properties of the drug, and is used to determine secondary parameters, including the half-life. The purpose of this review is to provide an overview of current methods for the prediction of volume of distribution of drugs, discuss a comparison between the methods, and identify deficiencies in current predictive methods for future improvement. RECENT FINDINGS Several volumes of distribution prediction methods are discussed, including preclinical extrapolation, physiological methods, tissue composition-based models to predict tissue:plasma partition coefficients, and quantitative structure-activity relationships. Key factors that impact the prediction of volume of distribution, such as permeability, transport, and accuracy of experimental inputs, are discussed. A comparison of current methods indicates that in general, all methods predict drug volume of distribution with an absolute average fold error of 2-fold. Currently, the use of composition-based PBPK models is preferred to models requiring in vivo input. SUMMARY Composition-based models perfusion-limited PBPK models are commonly used at present for prediction of tissue:plasma partition coefficients and volume of distribution, respectively. A better mechanistic understanding of important drug distribution processes will result in improvements in all modeling approaches.
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Affiliation(s)
- Kimberly Holt
- Department of Pharmaceutical Sciences, Temple University School of Pharmacy, 3307 N. Broad Street, Philadelphia, PA 19140, USA
| | - Swati Nagar
- Department of Pharmaceutical Sciences, Temple University School of Pharmacy, 3307 N. Broad Street, Philadelphia, PA 19140, USA
| | - Ken Korzekwa
- Department of Pharmaceutical Sciences, Temple University School of Pharmacy, 3307 N. Broad Street, Philadelphia, PA 19140, USA
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Paraiso RLM, Watanabe A, Andreas CJ, Turner D, Zane P, Dressman J. In-vitro–in-silico investigation of the negative food effect of zolpidem when administered as immediate-release tablets. J Pharm Pharmacol 2019; 71:1663-1676. [DOI: 10.1111/jphp.13161] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Accepted: 08/10/2019] [Indexed: 12/14/2022]
Abstract
Abstract
Objectives
The main objective of the present work was to combine in-vitro and in-silico tools to better understand the in-vivo behavior of the immediate release (IR) formulation of zolpidem in the fasted and fed states.
Methods
The dissolution of zolpidem was evaluated using biorelevant media simulating the gastric and intestinal environment in the fasted and fed states. Additionally, the influence of high viscosity and high fat content on the release of zolpidem under fed state conditions was investigated. The in-vitro results were combined with a physiologically based pharmacokinetic (PBPK) model constructed with Simcyp® to simulate the zolpidem pharmacokinetic profile in both prandial states.
Key findings
In vitro biorelevant dissolution experiments representing the fasted and fed states, combinedwith PBPKmodelling, were able to simulate the plasma profiles from the clinical food effect studies well. Experiments reflecting the pH and fat content of themeal led to a good prediction of the zolpidem plasma profile in the fed state, whereas increasing the viscosity of the gastricmedia led to an under-prediction.
Conclusions
This work demonstrates that the combination of biorelevant dissolution testing and PBPK modelling is very useful for understanding the in-vivo behavior of zolpidem in the fasted and fed states. This approach could be implemented in the development of other drugs exhibiting negative food effects, saving resources and bringing new drug products to the market faster.
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Affiliation(s)
| | - Ayahisa Watanabe
- Research Laboratory for Development, Shionogi & Co., Ltd., Osaka, Japan
| | - Cord J Andreas
- Institute of Pharmaceutical Technology, Goethe University, Frankfurt am Main, Germany
| | - David Turner
- Simcyp Division, Certara UK Limited, Sheffield, UK
| | - Patricia Zane
- Drug Disposition, Safety, and Animal Research (DSAR), Sanofi U.S., Bridgewater, NJ, USA
| | - Jennifer Dressman
- Institute of Pharmaceutical Technology, Goethe University, Frankfurt am Main, Germany
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Predicting Drug Binding to Human Serum Albumin and Alpha One Acid Glycoprotein in Diseased and Age Patient Populations. J Pharm Sci 2019; 108:2737-2747. [PMID: 30905706 DOI: 10.1016/j.xphs.2019.03.018] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Revised: 03/12/2019] [Accepted: 03/14/2019] [Indexed: 01/02/2023]
Abstract
Plasma protein binding, namely the fraction unbound (fu), can be an important determinant of the disposition and response of drugs. The primary objective of this study was to predict fu values of 183 drugs utilizing either a single binding protein model, where the predominant binding protein had been established, or a multiple binding protein model (MBPM), where the relative binding contribution of human serum albumin (HSA) or alpha 1 acid glycoprotein (AAG) is known. Mean protein concentrations, dependent on disease or age, were used to account for changes in fu. A simple scaling approach for binding protein concentration was employed to account for quantitative changes in molar concentrations of either HSA or AAG in their respective conditions. The MBPM predictive model works best if the relative binding contribution of HSA and AAG is known, and a scaler for the change in protein concentration can be adjusted accordingly. The value of MBPM was most evident when considering reported changes in lidocaine binding because of increasing AAG concentration in response to trauma. The present approach enhances the ability to predict fu in diseased and age populations because of quantitative changes in major binding proteins.
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Isoherranen N, Madabushi R, Huang S. Emerging Role of Organ-on-a-Chip Technologies in Quantitative Clinical Pharmacology Evaluation. Clin Transl Sci 2019; 12:113-121. [PMID: 30740886 PMCID: PMC6440571 DOI: 10.1111/cts.12627] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Accepted: 01/26/2019] [Indexed: 12/28/2022] Open
Abstract
The recently enacted Prescription Drug User Fee Act (PDUFA) VI includes in its performance goals "enhancing regulatory science and expediting drug development." The key elements in "enhancing regulatory decision tools to support drug development and review" include "advancing model-informed drug development (MIDD)." This paper describes (i) the US Food and Drug Administration (FDA) Office of Clinical Pharmacology's continuing efforts in developing quantitative clinical pharmacology models (disease, drug, and clinical trial models) to advance MIDD, (ii) how emerging novel tools, such as organ-on-a-chip technologies or microphysiological systems, can provide new insights into physiology and disease mechanisms, biomarker identification and evaluation, and elucidation of mechanisms of adverse drug reactions, and (iii) how the single organ or linked organ microphysiological systems can provide critical system parameters for improved physiologically-based pharmacokinetic and pharmacodynamic evaluations. Continuous public-private partnerships are critical to advance this field and in the application of these new technologies in drug development and regulatory review.
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Affiliation(s)
- Nina Isoherranen
- Office of Clinical Pharmacology (OCP)Office of Translational SciencesCenter for Drug Evaluation and ResearchUS Food and Drug Administration (FDA)Silver SpringMarylandUSA
- Department of PharmaceuticsSchool of PharmacyUniversity of WashingtonSeattleWashingtonUSA
| | - Rajanikanth Madabushi
- Office of Clinical Pharmacology (OCP)Office of Translational SciencesCenter for Drug Evaluation and ResearchUS Food and Drug Administration (FDA)Silver SpringMarylandUSA
| | - Shiew‐Mei Huang
- Office of Clinical Pharmacology (OCP)Office of Translational SciencesCenter for Drug Evaluation and ResearchUS Food and Drug Administration (FDA)Silver SpringMarylandUSA
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Shimizu H, Yoshida K, Nakada T, Kojima K, Ogasawara A, Nakamaru Y, Yamazaki H. Prediction of Human Distribution Volumes of Compounds in Various Elimination Phases Using Physiologically Based Pharmacokinetic Modeling and Experimental Pharmacokinetics in Animals. Drug Metab Dispos 2019; 47:114-123. [PMID: 30420404 DOI: 10.1124/dmd.118.083642] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Accepted: 11/08/2018] [Indexed: 02/13/2025] Open
Abstract
Predicting the pharmacokinetics of compounds in humans is an important part of the drug development process. In this study, the plasma concentration profiles of 10 marketed compounds exhibiting two-phase elimination after intravenous administration in humans were evaluated in terms of distribution volumes just after intravenous administration (V 1), at steady state (V ss), and in the elimination phase (Vβ ) using physiologically based pharmacokinetic (PBPK) modeling implemented in a commercially available simulator (Simcyp). When developing human PBPK models, the insight gained from prior animal PBPK models based on nonclinical data informed the optimization of the lipophilicity input of the compounds and the selection of the appropriate mechanistic tissue partition methods. The accuracy of V 1, V ss, and Vβ values predicted that using human PBPK models developed in accordance with prior animal PBPK models was superior to using those predicted using conventional approaches, such as allometric scaling, especially for V 1 and Vβ By conventional approaches, the V 1 and Vβ values of 4-5 of 10 compounds were predicted within a 3-fold error of observed values, whereas V ss values for their majority were predicted as such. PBPK models predicted V 1, V ss, and Vβ values for almost all compounds within 3-fold errors, resulting in better predictions of plasma concentration profiles than allometric scaling. The distribution volumes predicted using human PBPK models based on prior animal PBPK modeling were more accurate than those predicted without reference to animal models. This study demonstrated that human PBPK models developed with consideration of animal PBPK models could accurately predict distribution volumes in various elimination phases.
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Affiliation(s)
- Hidetoshi Shimizu
- Mitsubishi Tanabe Pharma Corporation, Toda, Saitama, Japan (H.S., K.Y., T.N., K.K., A.O., Y.N.); and Showa Pharmaceutical University, Machida, Tokyo, Japan (H.Y.)
| | - Kosuke Yoshida
- Mitsubishi Tanabe Pharma Corporation, Toda, Saitama, Japan (H.S., K.Y., T.N., K.K., A.O., Y.N.); and Showa Pharmaceutical University, Machida, Tokyo, Japan (H.Y.)
| | - Tomohisa Nakada
- Mitsubishi Tanabe Pharma Corporation, Toda, Saitama, Japan (H.S., K.Y., T.N., K.K., A.O., Y.N.); and Showa Pharmaceutical University, Machida, Tokyo, Japan (H.Y.)
| | - Koki Kojima
- Mitsubishi Tanabe Pharma Corporation, Toda, Saitama, Japan (H.S., K.Y., T.N., K.K., A.O., Y.N.); and Showa Pharmaceutical University, Machida, Tokyo, Japan (H.Y.)
| | - Akihito Ogasawara
- Mitsubishi Tanabe Pharma Corporation, Toda, Saitama, Japan (H.S., K.Y., T.N., K.K., A.O., Y.N.); and Showa Pharmaceutical University, Machida, Tokyo, Japan (H.Y.)
| | - Yoshinobu Nakamaru
- Mitsubishi Tanabe Pharma Corporation, Toda, Saitama, Japan (H.S., K.Y., T.N., K.K., A.O., Y.N.); and Showa Pharmaceutical University, Machida, Tokyo, Japan (H.Y.)
| | - Hiroshi Yamazaki
- Mitsubishi Tanabe Pharma Corporation, Toda, Saitama, Japan (H.S., K.Y., T.N., K.K., A.O., Y.N.); and Showa Pharmaceutical University, Machida, Tokyo, Japan (H.Y.)
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Interethnic scaling of fraction unbound of a drug in plasma and volume of distribution: an analysis of extrapolation from Caucasians to Chinese. Eur J Clin Pharmacol 2018; 75:543-551. [DOI: 10.1007/s00228-018-02610-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2018] [Accepted: 12/10/2018] [Indexed: 10/27/2022]
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Prieto Garcia L, Janzén D, Kanebratt KP, Ericsson H, Lennernäs H, Lundahl A. Physiologically Based Pharmacokinetic Model of Itraconazole and Two of Its Metabolites to Improve the Predictions and the Mechanistic Understanding of CYP3A4 Drug-Drug Interactions. Drug Metab Dispos 2018; 46:1420-1433. [PMID: 30068519 DOI: 10.1124/dmd.118.081364] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2018] [Accepted: 07/27/2018] [Indexed: 02/13/2025] Open
Abstract
Physiologically based pharmacokinetic (PBPK) modeling for itraconazole using a bottom-up approach is challenging, not only due to complex saturable pharmacokinetics (PK) and the presence of three metabolites exhibiting CYP3A4 inhibition, but also because of discrepancies in reported in vitro data. The overall objective of this study is to provide a comprehensive mechanistic PBPK model for itraconazole in order to increase the confidence in its drug-drug interaction (DDI) predictions. To achieve this, key in vitro and in vivo data for itraconazole and its major metabolites were generated. These data were crucial to developing a novel bottom-up PBPK model in Simcyp (Simcyp Ltd., Certara, Sheffield, United Kingdom) for itraconazole and two of its major metabolites: hydroxy-itraconazole (OH-ITZ) and keto-itraconazole (keto-ITZ). Performance of the model was validated using prespecified acceptance criteria against different dosing regimens, formulations for 29 PK, and DDI studies with midazolam and other CYP3A4 substrates. The main outcome is an accurate PBPK model that simultaneously predicts the PK profiles of itraconazole, OH-ITZ, and keto-ITZ. In addition, itraconazole DDIs with midazolam and other CYP3A4 substrates were successfully predicted within a 2-fold error. Prediction precision and bias of DDI expressed as geometric mean fold error were for the area under the concentration-time curve and peak concentration, 1.06 and 0.96, respectively. To conclude, in this paper a comprehensive data set for itraconazole and its metabolites is provided that enables bottom-up mechanism-based PBPK modeling. The presented model is applicable for studying the contribution from the metabolites and allows improved assessments of itraconazole DDI.
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Affiliation(s)
- Luna Prieto Garcia
- Drug Metabolism and Pharmacokinetics; Cardiovascular, Renal and Metabolism (L.P.G., D.J., K.P.K., A.L.) and Quantitative Clinical Pharmacology; Early Clinical Development (H.E.), IMED Biotech Unit, AstraZeneca, Gothenburg, Sweden; and Department of Pharmacy, Uppsala University, Uppsala, Sweden (H.L.)
| | - David Janzén
- Drug Metabolism and Pharmacokinetics; Cardiovascular, Renal and Metabolism (L.P.G., D.J., K.P.K., A.L.) and Quantitative Clinical Pharmacology; Early Clinical Development (H.E.), IMED Biotech Unit, AstraZeneca, Gothenburg, Sweden; and Department of Pharmacy, Uppsala University, Uppsala, Sweden (H.L.)
| | - Kajsa P Kanebratt
- Drug Metabolism and Pharmacokinetics; Cardiovascular, Renal and Metabolism (L.P.G., D.J., K.P.K., A.L.) and Quantitative Clinical Pharmacology; Early Clinical Development (H.E.), IMED Biotech Unit, AstraZeneca, Gothenburg, Sweden; and Department of Pharmacy, Uppsala University, Uppsala, Sweden (H.L.)
| | - Hans Ericsson
- Drug Metabolism and Pharmacokinetics; Cardiovascular, Renal and Metabolism (L.P.G., D.J., K.P.K., A.L.) and Quantitative Clinical Pharmacology; Early Clinical Development (H.E.), IMED Biotech Unit, AstraZeneca, Gothenburg, Sweden; and Department of Pharmacy, Uppsala University, Uppsala, Sweden (H.L.)
| | - Hans Lennernäs
- Drug Metabolism and Pharmacokinetics; Cardiovascular, Renal and Metabolism (L.P.G., D.J., K.P.K., A.L.) and Quantitative Clinical Pharmacology; Early Clinical Development (H.E.), IMED Biotech Unit, AstraZeneca, Gothenburg, Sweden; and Department of Pharmacy, Uppsala University, Uppsala, Sweden (H.L.)
| | - Anna Lundahl
- Drug Metabolism and Pharmacokinetics; Cardiovascular, Renal and Metabolism (L.P.G., D.J., K.P.K., A.L.) and Quantitative Clinical Pharmacology; Early Clinical Development (H.E.), IMED Biotech Unit, AstraZeneca, Gothenburg, Sweden; and Department of Pharmacy, Uppsala University, Uppsala, Sweden (H.L.)
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Poulin P, Collet SH, Atrux-Tallau N, Linget JM, Hennequin L, Wilson CE. Application of the Tissue Composition-Based Model to Minipig for Predicting the Volume of Distribution at Steady State and Dermis-to-Plasma Partition Coefficients of Drugs Used in the Physiologically Based Pharmacokinetics Model in Dermatology. J Pharm Sci 2018; 108:603-619. [PMID: 30222978 DOI: 10.1016/j.xphs.2018.09.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Revised: 09/05/2018] [Accepted: 09/06/2018] [Indexed: 11/25/2022]
Abstract
The minipig continues to build a reputation as a viable alternative large animal model to predict humans in dermatology and toxicology studies. Therefore, it is essential to describe and predict the pharmacokinetics in that species to speed up the clinical candidate selection. Essential input parameters in whole-body physiologically based pharmacokinetic models are the tissue-to-plasma partition coefficients and the resulting volume of distribution at steady-state (Vss). Mechanistic in vitro- and in silico-based models used for predicting these parameters of tissue distribution of drugs refer to the tissue composition-based model (TCM). Robust TCMs were initially developed for some preclinical species (e.g., rat and dog) and human; however, there is currently no model available for the minipig. Therefore, the objective of this present study was to develop a TCM for the minipig and to estimate the corresponding tissue composition data. Drug partitioning into the tissues was predominantly governed by lipid and protein binding effects in addition to drug solubilization and pH gradient effects in the aqueous phase on both sides of the biological membranes; however, some more complex tissue distribution processes such as drug binding to the collagen-laminin material in dermis and a restricted drug partitioning into membranes of tissues for compounds that are amphiphilic and contain sulfur atom(s) were also challenged. The model was validated by predicting Vss and the dermis-to-plasma partition coefficients (Kp-dermis) of 68 drugs. The prediction of Kp-dermis was extended to humans for comparison with the minipig. The results indicate that the extended TCM provided generally good agreements with observations in the minipig showing that it is also applicable to this preclinical species. In general, up to 86% and 100% of the predicted Vss values are respectively within 2-fold and 3-fold errors compared to the experimentally determined values, whereas these numbers are 78% and 94% for Kp-dermis when the anticipated outlier compounds are not included. Binding data to dermis are comparable between minipigs and humans. Overall, this study is a first step toward developing a mechanistic TCM for the minipig, with the aim of increasing the use of physiologically based pharmacokinetic models of drugs for that species in addition to rats, dogs, and humans because such models are used in preclinical and clinical transdermal studies.
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Affiliation(s)
- Patrick Poulin
- Consultant Patrick Poulin Inc., Québec City, Québec, Canada; School of Public Health, University of Montréal, Montréal, Québec, Canada.
| | | | | | | | | | - Claire E Wilson
- DMPK - Research, Nestlé Skin Health R & D, Sophia-Antipolis, France
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Nigade PB, Gundu J, Sreedhara Pai K, Nemmani KVS. Prediction of Tissue-to-Plasma Ratios of Basic Compounds in Mice. Eur J Drug Metab Pharmacokinet 2018; 42:835-847. [PMID: 28194579 DOI: 10.1007/s13318-017-0402-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
BACKGROUND Majority of reported studies so far developed correlation regression equations using the rat muscle-to-plasma drug concentration ratio (Kp-muscle) to predict tissue-to-plasma drug concentration ratios (Kp-tissues). Use of regression equations derived from rat Kp-muscle may not be ideal to predict the mice tissue-Kps as there are species differences. OBJECTIVES (i) To develop the linear regression equations using mouse tissue-Kps; (ii) to assess the correlation between organ blood flow and/or organ weight with tissue-Kps and (iii) compare the observed tissue-Kps from mice with corresponding predicted tissue-Kps using Richter's rat-Kp specific equations. METHOD Disposition of 12 small molecules were investigated extensively in mouse plasma and tissues after a single oral dose administration. Linear correlation was assessed for each of the tissue with rest of the other tissues, separately for weak and strong bases. RESULT Newly developed regression equations using mice tissue-Kps, predicted 79% data points within twofold. As observed correlation r 2 range was 0.75-0.98 between Kp-muscle and Kp-brain, -spleen, -skin, -liver, -lung, suggesting superior correlation between the tissue-Kps. Order of tissue-Kps, showed that tissue concentrations were directly proportional to the organ blood flow and inversely to the organ weight. Further, the observed tissue-Kps from mice were compared with corresponding predicted tissue-Kps using Richter's rat-Kp specific equations. Overall, 46, 54 and 63% data points were under predicted (<0.5-fold) for liver, spleen and lung, respectively. Whereas 63 and 75% data points were over predicted (>twofold) for skin and brain, respectively. These findings suggest that cross species extrapolation predictability is poor. CONCLUSION All these findings together suggest that mouse specific regression equations developed under controlled experimental conditions could be most appropriate for predicting mouse tissue-Kps for compounds with wide range of volume of distribution.
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Affiliation(s)
- Prashant B Nigade
- Department of Drug Metabolism and Pharmacokinetics, Lupin Limited (Research Park), Pune, India. .,DMPK, Novel Drug Discovery and Development Department, Lupin Limited (Research Park), 46A/47A, Village Nande, Taluka Mulshi, Pune, 412 115, India.
| | - Jayasagar Gundu
- Department of Drug Metabolism and Pharmacokinetics, Lupin Limited (Research Park), Pune, India
| | - K Sreedhara Pai
- Department of Pharmacology, Manipal College of Pharmaceutical Sciences, Manipal University, Manipal, India
| | - Kumar V S Nemmani
- Department of Pharmacology, Lupin Limited (Research Park), Pune, India
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Li GF, Yu G, Li Y, Zheng Y, Zheng QS, Derendorf H. Quantitative Estimation of Plasma Free Drug Fraction in Patients With Varying Degrees of Hepatic Impairment: A Methodological Evaluation. J Pharm Sci 2018. [DOI: 10.1016/j.xphs.2018.02.021] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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Mahmood I, Tegenge MA. Prediction of tissue concentrations of monoclonal antibodies in mice from plasma concentrations. Regul Toxicol Pharmacol 2018; 97:57-62. [PMID: 29894734 DOI: 10.1016/j.yrtph.2018.06.004] [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: 01/24/2018] [Revised: 06/04/2018] [Accepted: 06/05/2018] [Indexed: 11/18/2022]
Abstract
The objectives of this study were to develop and evaluate allometric methods for predicting tissue-to-plasma partition coefficients (Kp) in mice from experimentally determined in-vivo volume of distribution at steady state (Vss) for monoclonal antibodies (mAbs). The Vss was allometrically predicted (using a fixed exponent 1.0 or 0.9) in a given tissue of the mice. The Kp was predicted using Vss and tissue specific physiological parameters. In total, Kp values were predicted for 20 mAbs, 121 tissues, and 665 tissue concentrations. The predicted Kp values and tissue concentrations were compared with the experimental results as well as an empirically predicted antibody biodistribution coefficient (ABC). Comparison of the predicted Kp values by the two proposed methods with experimentally determined Kp values indicated that 64-75% of the predicted Kp values were within two-fold prediction error. For 665 tissue concentrations, 63%, 74%, and 48% tissue concentration ratio were within 0.5-2 fold prediction error by exponent 1.0, exponent 0.9, and ABC, respectively. The proposed allometric methods are better than ABC method for the prediction of tissue Kp values and tissue concentrations. The proposed methods can reasonably predict tissue concentrations of mAbs using plasma concentration gathered at early stage of biologics development.
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Affiliation(s)
- Iftekhar Mahmood
- Office of Tissue & Advanced Therapies (OTAT), Center for Biologics Evaluation and Research, Food & Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD, 20993-0002, USA.
| | - Million A Tegenge
- Office of Biostatistics & Epidemiology, Center for Biologics Evaluation and Research, Food & Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD, 20993-0002, USA.
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Nigade PB, Gundu J, Pai KS, Nemmani KVS, Talwar R. Prediction of volume of distribution in preclinical species and humans: application of simplified physiologically based algorithms. Xenobiotica 2018; 49:528-539. [PMID: 29771166 DOI: 10.1080/00498254.2018.1474399] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Affiliation(s)
- Prashant B. Nigade
- Department of Drug Metabolism and Pharmacokinetics, Lupin Limited (Research Park), Pune, India
| | - Jayasagar Gundu
- Department of Drug Metabolism and Pharmacokinetics, Lupin Limited (Research Park), Pune, India
| | - K. Sreedhara Pai
- Department of Pharmacology, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India
| | | | - Rashmi Talwar
- Department of Pharmacology, Lupin Limited (Research Park), Pune, India
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45
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Wambaugh JF, Hughes MF, Ring CL, MacMillan DK, Ford J, Fennell TR, Black SR, Snyder RW, Sipes NS, Wetmore BA, Westerhout J, Setzer RW, Pearce RG, Simmons JE, Thomas RS. Evaluating In Vitro-In Vivo Extrapolation of Toxicokinetics. Toxicol Sci 2018; 163:152-169. [PMID: 29385628 PMCID: PMC5920326 DOI: 10.1093/toxsci/kfy020] [Citation(s) in RCA: 97] [Impact Index Per Article: 13.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
Prioritizing the risk posed by thousands of chemicals potentially present in the environment requires exposure, toxicity, and toxicokinetic (TK) data, which are often unavailable. Relatively high throughput, in vitro TK (HTTK) assays and in vitro-to-in vivo extrapolation (IVIVE) methods have been developed to predict TK, but most of the in vivo TK data available to benchmark these methods are from pharmaceuticals. Here we report on new, in vivo rat TK experiments for 26 non-pharmaceutical chemicals with environmental relevance. Both intravenous and oral dosing were used to calculate bioavailability. These chemicals, and an additional 19 chemicals (including some pharmaceuticals) from previously published in vivo rat studies, were systematically analyzed to estimate in vivo TK parameters (e.g., volume of distribution [Vd], elimination rate). For each of the chemicals, rat-specific HTTK data were available and key TK predictions were examined: oral bioavailability, clearance, Vd, and uncertainty. For the non-pharmaceutical chemicals, predictions for bioavailability were not effective. While no pharmaceutical was absorbed at less than 10%, the fraction bioavailable for non-pharmaceutical chemicals was as low as 0.3%. Total clearance was generally more under-estimated for nonpharmaceuticals and Vd methods calibrated to pharmaceuticals may not be appropriate for other chemicals. However, the steady-state, peak, and time-integrated plasma concentrations of nonpharmaceuticals were predicted with reasonable accuracy. The plasma concentration predictions improved when experimental measurements of bioavailability were incorporated. In summary, HTTK and IVIVE methods are adequately robust to be applied to high throughput in vitro toxicity screening data of environmentally relevant chemicals for prioritizing based on human health risks.
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Affiliation(s)
| | - Michael F Hughes
- National Health and Environmental Effects Research Laboratory, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, North Carolina 27711
| | - Caroline L Ring
- National Center for Computational Toxicology
- Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee 37831
| | - Denise K MacMillan
- National Health and Environmental Effects Research Laboratory, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, North Carolina 27711
| | - Jermaine Ford
- National Health and Environmental Effects Research Laboratory, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, North Carolina 27711
| | | | - Sherry R Black
- RTI International, Research Triangle Park, North Carolina
| | | | - Nisha S Sipes
- National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina 27717
| | - Barbara A Wetmore
- National Exposure Research Laboratory, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, North Carolina 27711
| | - Joost Westerhout
- The Netherlands Organisation for Applied Scientific Research (TNO), AJ Zeist 3700, The Netherlands
| | | | - Robert G Pearce
- National Center for Computational Toxicology
- Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee 37831
| | - Jane Ellen Simmons
- National Health and Environmental Effects Research Laboratory, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, North Carolina 27711
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Krishnan V, Patel NJ, Mackrell JG, Sweetana SA, Bullock H, Ma YL, Waterhouse TH, Yaden BC, Henck J, Zeng QQ, Gavardinas K, Jadhav P, Saeed A, Garcia-Losada P, Robins DA, Benson CT. Development of a selective androgen receptor modulator for transdermal use in hypogonadal patients. Andrology 2018. [PMID: 29527831 DOI: 10.1111/andr.12479] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
We have identified a non-steroidal selective androgen receptor modulator (SARM), termed LY305, that is bioavailable through a transdermal route of administration while highly cleared via hepatic metabolism to limit parent compound exposure in the liver. Selection of this compound and its transdermal formulation was based on the optimization of skin absorption properties using both in vitro and in vivo skin models that supported PBPK modeling for human PK predictions. This molecule is an agonist in perineal muscle while being a weak partial agonist in the androgenic tissues such as prostate. When LY305 was tested in animal models of skeletal atrophy it restored the skeletal muscle mass through accelerated repair. In a bone fracture model, LY305 remained osteoprotective in the regenerating tissue and void of deleterious effects. Finally, in a small cohort of healthy volunteers, we assessed the safety and tolerability of LY305 when administered transdermally. LY305 showed a dose-dependent increase in serum exposure and was well tolerated with minimal adverse effects. Notably, there were no statistically significant changes to hematocrit or HDL after 4-week treatment period. Collectively, LY305 represents a first of its kind de novo development of a non-steroidal transdermal SARM with unique properties which could find clinical utility in hypogonadal men.
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Affiliation(s)
- V Krishnan
- Lilly Research Laboratories, Lilly Corporate Center, Indianapolis, IN, USA
| | - N J Patel
- Lilly Research Laboratories, Lilly Corporate Center, Indianapolis, IN, USA
| | - J G Mackrell
- Lilly Research Laboratories, Lilly Corporate Center, Indianapolis, IN, USA
| | - S A Sweetana
- Lilly Research Laboratories, Lilly Corporate Center, Indianapolis, IN, USA
| | - H Bullock
- Lilly Research Laboratories, Lilly Corporate Center, Indianapolis, IN, USA
| | - Y L Ma
- Lilly Research Laboratories, Lilly Corporate Center, Indianapolis, IN, USA
| | - T H Waterhouse
- Lilly Research Laboratories, Lilly Corporate Center, Indianapolis, IN, USA
| | - B C Yaden
- Lilly Research Laboratories, Lilly Corporate Center, Indianapolis, IN, USA
| | - J Henck
- Lilly Research Laboratories, Lilly Corporate Center, Indianapolis, IN, USA
| | - Q Q Zeng
- Lilly Research Laboratories, Lilly Corporate Center, Indianapolis, IN, USA
| | - K Gavardinas
- Lilly Research Laboratories, Lilly Corporate Center, Indianapolis, IN, USA
| | - P Jadhav
- Lilly Research Laboratories, Lilly Corporate Center, Indianapolis, IN, USA
| | - A Saeed
- Lilly Research Laboratories, Lilly Corporate Center, Indianapolis, IN, USA
| | - P Garcia-Losada
- Lilly Research Laboratories, Lilly Corporate Center, Indianapolis, IN, USA
| | - D A Robins
- Lilly Research Laboratories, Lilly Corporate Center, Indianapolis, IN, USA
| | - C T Benson
- Lilly Research Laboratories, Lilly Corporate Center, Indianapolis, IN, USA
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Abstract
PURPOSE Volume of distribution at steady state (Vdss) is a fundamental pharmacokinetic (PK) parameter driven predominantly by passive processes and physicochemical properties of the compound. Human Vdss can be estimated using in silico mechanistic methods or empirically scaled from Vdss values obtained from preclinical species. In this study the accuracy and the complementarity of these two approaches are analyzed leveraging a large data set (over 150 marketed drugs). METHODS For all the drugs analyzed in this study experimental in vitro measurements of LogP, plasma protein binding and pKa are used as input for the mechanistic in silico model to predict human Vdss. The software used for predicting human tissue partition coefficients and Vdss based on the method described by Rodgers and Rowland is made available as supporting information. RESULTS This assessment indicates that overall the in silico mechanistic model presented by Rodgers and Rowland is comparably accurate or superior to empirical approaches based on the extrapolation of in vivo data from preclinical species. CONCLUSIONS These results illustrate the great potential of mechanistic in silico models to accurately predict Vdss in humans. This in silico method does not rely on in vivo data and is, consequently, significantly time and resource sparing. The success of this in silico model further suggests that reasonable predictability of Vdss in preclinical species could be obtained by a similar process.
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48
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Da-Silva F, Boulenc X, Vermet H, Compigne P, Gerbal-Chaloin S, Daujat-Chavanieu M, Klieber S, Poulin P. Improving Prediction of Metabolic Clearance Using Quantitative Extrapolation of Results Obtained From Human Hepatic Micropatterned Cocultures Model and by Considering the Impact of Albumin Binding. J Pharm Sci 2018. [PMID: 29524447 DOI: 10.1016/j.xphs.2018.03.001] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
The objective was to compare, with the same data set, the predictive performance of 3 in vitro assays of hepatic clearance (CL), namely, micropatterned cocultures (also referring to HepatoPac®) and suspension as well as monolayer hepatocytes to define which assay is the most accurate. Furthermore, existing in vitro-to-in vivo extrapolation (IVIVE) methods were challenged to verify which method is the most predictive (i.e., direct scaling method without binding correction, conventional method based either on the unbound fraction in plasma (fup) according to the free-drug hypothesis, or based on an fup value adjusted for the albumin [ALB]-facilitated hepatic uptake phenomenon). Accordingly, the role of ALB binding was specifically challenged, and consequently, the ALB production was monitored in parallel to the metabolic stability. The ALB concentration data were used to compare the in vitro assays and to adjust the value of fup of each drug to mimic the ALB-facilitated hepatic uptake phenomenon. The results confirmed that the direct and conventional IVIVE methods generally overpredicted and underpredicted the CL in vivo in humans, respectively. However, the underprediction of the conventional IVIVE method based on fup was significantly reduced from data generated with the HepatoPac® system compared with the 2 other in vitro assays, which is possibly because that system is producing ALB at a rate much closer to the in vivo condition in liver. Hence, these observations suggest that the presence of more ALB molecules per hepatocyte in that HepatoPac® system may have facilitated the hepatic uptake of several bound drugs because their intrinsic CL was increased instead of being decreased by the ALB binding effect. Accordingly, the IVIVE method based on the fup value adjusted for the ALB-facilitated uptake phenomenon gave the lowest prediction bias from the statistical analyses. This study indicated that the HepatoPac® system combined with the adjusted value of fup was the most reliable IVIVE method and revealed the importance of quantifying the in vitro-to-in vivo variation of ALB concentration to improve the CL predictions, which would help any future physiologically based pharmacokinetics modeling exercise.
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Affiliation(s)
- Franck Da-Silva
- Sanofi R&D, Montpellier, France; Institute for Regenerative Medicine and Biotherapy, Université et CHU de Montpellier, INSERM, Montpellier, France
| | | | | | | | - Sabine Gerbal-Chaloin
- Institute for Regenerative Medicine and Biotherapy, Université et CHU de Montpellier, INSERM, Montpellier, France
| | - Martine Daujat-Chavanieu
- Institute for Regenerative Medicine and Biotherapy, Université et CHU de Montpellier, INSERM, Montpellier, France
| | | | - Patrick Poulin
- Consultant, Patrick Poulin Inc., Québec City, Canada; Associate professor, School of Public Health, IRSPUM, Université de Montréal, Canada
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49
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Nigade PB, Gundu J, Pai KS, Nemmani KVS. Prediction of Tumor-to-Plasma Ratios of Basic Compounds in Subcutaneous Xenograft Mouse Models. Eur J Drug Metab Pharmacokinet 2017; 43:331-346. [PMID: 29250739 DOI: 10.1007/s13318-017-0454-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
BACKGROUND Predicting target site drug concentrations is of key importance for rank ordering compounds before proceeding to chronic pharmacodynamic models. We propose generic tumor-specific correlation-based regression equations to predict tumor-to-plasma ratios (tumor-Kps) in slow- and fast-growing xenograft mouse models. METHODS Disposition of 14 basic small molecules was investigated extensively in mouse plasma, tissues and tumors after a single oral dose administration. Linear correlation was assessed and compared between tumor-Kp and normal tissue-to-plasma ratio (tissue-Kps) separately for each tumor xenograft. The developed regression equations were validated by leave-one-out cross-validation (LOOCV) method. RESULT Both slow- and fast-growing tumor-Kps showed good correlation (r 2 ≥ 0.7) with majority of the normal tissue-Kps. Substantial difference was observed in the slopes of developed equations between two xenografts, which was in line with observed difference in tumor distribution. The linear correlations between tumor-Kp and skin- or spleen-Kp were within the acceptable statistical criteria (LOOCV) across xenografts and the class of compounds evaluated. Since > 70% of tumor-Kps from the test data sets were predicted within a factor of twofold for both slow- and fast-growing xenograft mouse models, the results validate the applicability of the developed equations across xenografts. CONCLUSION Tumor-specific correlation-based regression equations were developed and their applicability was adequately validated across xenografts. These equations could be successfully translated to predict tumor concentrations in order to preclude experimental tumor-Kp determination.
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Affiliation(s)
- Prashant B Nigade
- Department of Drug Metabolism and Pharmacokinetics, Lupin Limited (Research Park), 46A/47A, Village Nande, Taluka Mulshi, Pune, 412 115, India.
| | - Jayasagar Gundu
- Department of Drug Metabolism and Pharmacokinetics, Lupin Limited (Research Park), 46A/47A, Village Nande, Taluka Mulshi, Pune, 412 115, India
| | - K Sreedhara Pai
- Department of Pharmacology, Manipal College of Pharmaceutical Sciences, Manipal University, Manipal, India
| | - Kumar V S Nemmani
- Department of Pharmacology, Lupin Limited (Research Park), Pune, India
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50
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Cheung SYA, Rodgers T, Aarons L, Gueorguieva I, Dickinson GL, Murby S, Brown C, Collins B, Rowland M. Whole body physiologically based modelling of β-blockers in the rat: events in tissues and plasma following an i.v. bolus dose. Br J Pharmacol 2017; 175:67-83. [PMID: 29053169 DOI: 10.1111/bph.14071] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2016] [Revised: 09/29/2017] [Accepted: 10/05/2017] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND AND PURPOSE Whole body physiologically based pharmacokinetic (PBPK) models have been increasingly applied in drug development to describe kinetic events of therapeutic agents in animals and humans. The advantage of such modelling is the ability to incorporate vast amounts of physiological information, such as organ blood flow and volume, to ensure that the model is as close to reality as possible. EXPERIMENTAL APPROACH Previous PBPK model development of enantiomers of a series of seven racemic β-blockers, namely, acebutolol, betaxolol, bisoprolol, metoprolol, oxprenolol, pindolol and propranolol, together with S-timolol in rat was based on tissue and blood concentration data at steady state. Compounds were administered in several cassettes with the composition mix and blood and tissue sampling times determined using a D-optimal design. KEY RESULTS Closed-loop PBPK models were developed initially based on the application of open loop forcing function models to individual tissues and compounds. For the majority of compounds and tissues, distribution kinetics was adequately characterized by perfusion rate-limited models. For some compounds in the testes and gut, a permeability rate-limited distribution model was required to best fit the data. Parameter estimates of the tissue-to-blood partition coefficient through fitting of individual enantiomers and of racemic pair were generally in agreement and also concur with those from previous steady-state experiments. CONCLUSIONS AND IMPLICATIONS PBPK modelling is a very powerful tool to aid drug discovery and development of therapeutic agents in animals and humans. However, careful consideration of the assumptions made during the modelling exercise is essential.
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Affiliation(s)
- S Y A Cheung
- Quantitative Clinical Pharmacology, Early Clinical Development, iMED AstraZeneca, Cambridge, UK
| | - T Rodgers
- Icon Development Solutions, Manchester, UK
| | - L Aarons
- Centre for Applied Pharmacokinetic Research, Manchester Pharmacy School, University of Manchester, Manchester, UK
| | | | | | - S Murby
- Centre for Applied Pharmacokinetic Research, Manchester Pharmacy School, University of Manchester, Manchester, UK
| | - C Brown
- Redx Pharma, Macclesfield, UK
| | - B Collins
- Centre for Applied Pharmacokinetic Research, Manchester Pharmacy School, University of Manchester, Manchester, UK
| | - M Rowland
- Centre for Applied Pharmacokinetic Research, Manchester Pharmacy School, University of Manchester, Manchester, UK
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