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Granda ML, Huang W, Yeung CK, Isoherranen N, Kestenbaum B. Predicting complex kidney drug handling using a physiologically-based pharmacokinetic model informed by biomarker-estimated secretory clearance and blood flow. Clin Transl Sci 2024; 17:e13678. [PMID: 37921258 PMCID: PMC10766039 DOI: 10.1111/cts.13678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 10/04/2023] [Accepted: 10/23/2023] [Indexed: 11/04/2023] Open
Abstract
Kidney function-adjusted drug dosing is currently based solely on the estimated glomerular filtration rate (GFR), however, kidney drug handling is accomplished by a combination of filtration, tubular secretion, and re-absorption. Mechanistic physiologically-based pharmacokinetic (PBPK) models recapitulate anatomic compartments to predict elimination from estimated perfusion, filtration, secretion, and re-absorption, but clinical applications are limited by a lack of empiric individual-level measurements of these functions. We adapted and validated a PBPK model to predict drug clearance from individual biomarker-based estimates of kidney perfusion and secretory clearance. We estimated organic anion transporter-mediated secretion via kynurenic acid clearance and kidney blood flow (KBF) via isovalerylglycine clearance in human participants, incorporating these measurements with GFR into the model to predict kidney drug clearance. We compared measured and model-predicted clearances of administered tenofovir and oseltamivir, which are cleared by both filtration and secretion. There were 27 outpatients (age 55 ± 15 years, mean iohexol-GFR [iGFR] 76 ± 31 mL/min/1.73 m2 ) in this drug clearance study. The mean observed and mechanistic model-predicted tenofovir clearances were 169 ± 102 mL/min and 163 ± 80 mL/min, respectively; estimated mean error of the mechanistic model was 37.1 mL/min (95% confidence interval [CI]: 24-52.9), compared to a mean error of 41.8 mL/min (95% CI: 25-61.6) from regression model. The mean observed and model-predicted oseltamivir carboxylate clearances were 183 ± 104 mL/min and 179 ± 89 mL/min, respectively; estimated mean error of the mechanistic model was 42.9 mL/min (95% CI: 29.7-56.4), versus error of 48.1 mL/min (95% CI: 31.2-67.3) from the regression model. Individualized estimates of tubular secretion and KBF improved the accuracy of PBPK model-predicted tenofovir and oseltamivir kidney clearances, suggesting the potential for biomarker-informed measures of kidney function to refine personalized drug dosing.
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Affiliation(s)
- Michael L. Granda
- Division of Nephrology, Department of MedicineUniversity of WashingtonSeattleWashingtonUSA
- Kidney Research InstituteSeattleWashingtonUSA
| | - Weize Huang
- Clinical PharmacologyGenentech Inc.South San FranciscoCaliforniaUSA
- Department of Pharmaceutics, School of PharmacyUniversity of WashingtonSeattleWashingtonUSA
| | - Catherine K. Yeung
- Kidney Research InstituteSeattleWashingtonUSA
- Department of Pharmacy, School of PharmacyUniversity of WashingtonSeattleWashingtonUSA
| | - Nina Isoherranen
- Department of Pharmaceutics, School of PharmacyUniversity of WashingtonSeattleWashingtonUSA
| | - Bryan Kestenbaum
- Division of Nephrology, Department of MedicineUniversity of WashingtonSeattleWashingtonUSA
- Kidney Research InstituteSeattleWashingtonUSA
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2
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Chang SY, Huang W, Chapron A, Quiñones AJL, Wang J, Isoherranen N, Shen DD, Kelly EJ, Himmelfarb J, Yeung CK. Incorporating Uremic Solute-mediated Inhibition of OAT1/3 Improves PBPK Prediction of Tenofovir Renal and Systemic Disposition in Patients with Severe Kidney Disease. Pharm Res 2023; 40:2597-2606. [PMID: 37704895 DOI: 10.1007/s11095-023-03594-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 08/23/2023] [Indexed: 09/15/2023]
Abstract
BACKGROUND Dose modification of renally secreted drugs in patients with chronic kidney disease (CKD) has relied on serum creatinine concentration as a biomarker to estimate glomerular filtration (GFR) under the assumption that filtration and secretion decline in parallel. A discrepancy between actual renal clearance and predicted renal clearance based on GFR alone is observed in severe CKD patients with tenofovir, a compound secreted by renal OAT1/3. Uremic solutes that inhibit OAT1/3 may play a role in this divergence. METHODS To examine the impact of transporter inhibition by uremic solutes on tenofovir renal clearance, we determined the inhibitory potential of uremic solutes hippuric acid, indoxyl sulfate, and p-cresol sulfate. The inhibition parameters (IC50) were incorporated into a previously validated mechanistic kidney model; simulated renal clearance and plasma PK profile were compared to data from clinical studies. RESULTS Without the incorporation of uremic solute inhibition, the PBPK model failed to capture the observed data with an absolute average fold error (AAFE) > 2. However, when the inhibition of renal uptake transporters and uptake transporters in the slow distribution tissues were included, the AAFE value was within the pre-defined twofold model acceptance criterion, demonstrating successful model extrapolation to CKD patients. CONCLUSION A PBPK model that incorporates inhibition by uremic solutes has potential to better predict renal clearance and systemic disposition of secreted drugs in patients with CKD. Ongoing research is warranted to determine if the model can be expanded to include other OAT1/3 substrate drugs and to evaluate how these findings can be translated to clinical guidance for drug selection and dose optimization in patients with CKD.
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Affiliation(s)
- Shih-Yu Chang
- Department of Pharmacy, School of Pharmacy, University of Washington, 1959 NE Pacific St. H375, Box 357630, Seattle, WA, 98195, USA
- Janssen Research and Development, Raritan, NJ, USA
| | - Weize Huang
- Department of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, WA, 98195, USA
- Genentech Inc, South San Francisco, CA, USA
| | - Alenka Chapron
- Department of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, WA, 98195, USA
| | - Antonio J López Quiñones
- Department of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, WA, 98195, USA
- Revolution Medicines, San Francisco, CA, USA
| | - Joanne Wang
- Department of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, WA, 98195, USA
| | - Nina Isoherranen
- Department of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, WA, 98195, USA
| | - Danny D Shen
- Department of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, WA, 98195, USA
| | - Edward J Kelly
- Department of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, WA, 98195, USA
- Division of Nephrology, Department of Medicine, Kidney Research Institute, University of Washington, Seattle, WA, 98195, USA
| | - Jonathan Himmelfarb
- Division of Nephrology, Department of Medicine, Kidney Research Institute, University of Washington, Seattle, WA, 98195, USA
| | - Catherine K Yeung
- Department of Pharmacy, School of Pharmacy, University of Washington, 1959 NE Pacific St. H375, Box 357630, Seattle, WA, 98195, USA.
- Division of Nephrology, Department of Medicine, Kidney Research Institute, University of Washington, Seattle, WA, 98195, USA.
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Deepika D, Kumar V. The Role of "Physiologically Based Pharmacokinetic Model (PBPK)" New Approach Methodology (NAM) in Pharmaceuticals and Environmental Chemical Risk Assessment. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:3473. [PMID: 36834167 PMCID: PMC9966583 DOI: 10.3390/ijerph20043473] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 02/10/2023] [Accepted: 02/14/2023] [Indexed: 06/18/2023]
Abstract
Physiologically Based Pharmacokinetic (PBPK) models are mechanistic tools generally employed in the pharmaceutical industry and environmental health risk assessment. These models are recognized by regulatory authorities for predicting organ concentration-time profiles, pharmacokinetics and daily intake dose of xenobiotics. The extension of PBPK models to capture sensitive populations such as pediatric, geriatric, pregnant females, fetus, etc., and diseased populations such as those with renal impairment, liver cirrhosis, etc., is a must. However, the current modelling practices and existing models are not mature enough to confidently predict the risk in these populations. A multidisciplinary collaboration between clinicians, experimental and modeler scientist is vital to improve the physiology and calculation of biochemical parameters for integrating knowledge and refining existing PBPK models. Specific PBPK covering compartments such as cerebrospinal fluid and the hippocampus are required to gain mechanistic understanding about xenobiotic disposition in these sub-parts. The PBPK model assists in building quantitative adverse outcome pathways (qAOPs) for several endpoints such as developmental neurotoxicity (DNT), hepatotoxicity and cardiotoxicity. Machine learning algorithms can predict physicochemical parameters required to develop in silico models where experimental data are unavailable. Integrating machine learning with PBPK carries the potential to revolutionize the field of drug discovery and development and environmental risk. Overall, this review tried to summarize the recent developments in the in-silico models, building of qAOPs and use of machine learning for improving existing models, along with a regulatory perspective. This review can act as a guide for toxicologists who wish to build their careers in kinetic modeling.
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Affiliation(s)
- Deepika Deepika
- Environmental Engineering Laboratory, Departament d’Enginyeria Quimica, Universitat Rovira i Virgili, Av. Països Catalans 26, 43007 Tarragona, Catalonia, Spain
- Pere Virgili Health Research Institute (IISPV), Hospital Universitari Sant Joan de Reus, Universitat Rovira i Virgili, 43204 Reus, Catalonia, Spain
| | - Vikas Kumar
- Environmental Engineering Laboratory, Departament d’Enginyeria Quimica, Universitat Rovira i Virgili, Av. Països Catalans 26, 43007 Tarragona, Catalonia, Spain
- Pere Virgili Health Research Institute (IISPV), Hospital Universitari Sant Joan de Reus, Universitat Rovira i Virgili, 43204 Reus, Catalonia, Spain
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Huang W, Stader F, Chan P, Shemesh CS, Chen Y, Gill KL, Jones HM, Li L, Rossato G, Wu B, Jin JY, Chanu P. Development of a pediatric physiologically-based pharmacokinetic model to support recommended dosing of atezolizumab in children with solid tumors. Front Pharmacol 2022; 13:974423. [PMID: 36225583 PMCID: PMC9548535 DOI: 10.3389/fphar.2022.974423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 08/29/2022] [Indexed: 11/16/2022] Open
Abstract
Background: Atezolizumab has been studied in multiple indications for both pediatric and adult patient populations. Generally, clinical studies enrolling pediatric patients may not collect sufficient pharmacokinetic data to characterize the drug exposure and disposition because of operational, ethical, and logistical challenges including burden to children and blood sample volume limitations. Therefore, mechanistic modeling and simulation may serve as a tool to predict and understand the drug exposure in pediatric patients. Objective: To use mechanistic physiologically-based pharmacokinetic (PBPK) modeling to predict atezolizumab exposure at a dose of 15 mg/kg (max 1,200 mg) in pediatric patients to support dose rationalization and label recommendations. Methods: A minimal mechanistic PBPK model was used which incorporated age-dependent changes in physiology and biochemistry that are related to atezolizumab disposition such as endogenous IgG concentration and lymph flow. The PBPK model was developed using both in vitro data and clinically observed data in adults and was verified across dose levels obtained from a phase I and multiple phase III studies in both pediatric patients and adults. The verified model was then used to generate PK predictions for pediatric and adult subjects ranging from 2- to 29-year-old. Results: Individualized verification in children and in adults showed that the simulated concentrations of atezolizumab were comparable (76% within two-fold and 90% within three-fold, respectively) to the observed data with no bias for either over- or under-prediction. Applying the verified model, the predicted exposure metrics including Cmin, Cmax, and AUCtau were consistent between pediatric and adult patients with a geometric mean of pediatric exposure metrics between 0.8- to 1.25-fold of the values in adults. Conclusion: The results show that a 15 mg/kg (max 1,200 mg) atezolizumab dose administered intravenously in pediatric patients provides comparable atezolizumab exposure to a dose of 1,200 mg in adults. This suggests that a dose of 15 mg/kg will provide adequate and effective atezolizumab exposure in pediatric patients from 2- to 18-year-old.
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Affiliation(s)
- Weize Huang
- Genentech Inc, South San Francisco, CA, United States
- *Correspondence: Weize Huang,
| | | | - Phyllis Chan
- Genentech Inc, South San Francisco, CA, United States
| | | | - Yuan Chen
- Genentech Inc, South San Francisco, CA, United States
| | | | | | - Linzhong Li
- Certara UK Limited, Sheffield, United Kingdom
| | | | - Benjamin Wu
- Genentech Inc, South San Francisco, CA, United States
| | - Jin Y. Jin
- Genentech Inc, South San Francisco, CA, United States
| | - Pascal Chanu
- Genentech Inc, South San Francisco, CA, United States
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Beaumont K, Pike A, Davies M, Savoca A, Vasalou C, Harlfinger S, Ramsden D, Ferguson D, Hariparsad N, Jones O, McGinnity D. ADME and DMPK considerations for the discovery and development of antibody drug conjugates (ADCs). Xenobiotica 2022; 52:770-785. [PMID: 36314242 DOI: 10.1080/00498254.2022.2141667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
The therapeutic concept of antibody drug conjugates (ADCs) is to selectively target tumour cells with small molecule cytotoxic drugs to maximise cell kill benefit and minimise healthy tissue toxicity.An ADC generally consists of an antibody that targets a protein on the surface of tumour cells chemically linked to a warhead small molecule cytotoxic drug.To deliver the warhead to the tumour cell, the antibody must bind to the target protein and in general be internalised into the cell. Following internalisation, the cytotoxic agent can be released in the endosomal or lysosomal compartment (via different mechanisms). Diffusion or transport out of the endosome or lysosome allows the cytotoxic drug to express its cell-killing pharmacology. Alternatively, some ADCs (e.g. EDB-ADCs) rely on extracellular cleavage releasing membrane permeable warheads.One potentially important aspect of the ADC mechanism is the 'bystander effect' whereby the cytotoxic drug released in the targeted cell can diffuse out of that cell and into other (non-target expressing) tumour cells to exert its cytotoxic effect. This is important as solid tumours tend to be heterogeneous and not all cells in a tumour will express the targeted protein.The combination of large and small molecule aspects in an ADC poses significant challenges to the disposition scientist in describing the ADME properties of the entire molecule.This article will review the ADC landscape and the ADME properties of successful ADCs, with the aim of outlining best practice and providing a perspective of how the field can further facilitate the discovery and development of these important therapeutic modalities.
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Affiliation(s)
- Kevin Beaumont
- Drug Metabolism and Pharmacokinetics, Early Oncology Research and Development, Cambridge, UK
| | - Andy Pike
- Drug Metabolism and Pharmacokinetics, Early Oncology Research and Development, Cambridge, UK
| | - Michael Davies
- Drug Metabolism and Pharmacokinetics, Early Oncology Research and Development, Cambridge, UK
| | - Adriana Savoca
- Drug Metabolism and Pharmacokinetics, Early Oncology Research and Development, Cambridge, UK
| | - Christina Vasalou
- Drug Metabolism and Pharmacokinetics, Early Oncology Research and Development, AstraZeneca, Boston, MA, USA
| | - Steffi Harlfinger
- Drug Metabolism and Pharmacokinetics, Early Oncology Research and Development, Cambridge, UK
| | - Diane Ramsden
- Drug Metabolism and Pharmacokinetics, Early Oncology Research and Development, AstraZeneca, Boston, MA, USA
| | - Douglas Ferguson
- Drug Metabolism and Pharmacokinetics, Early Oncology Research and Development, AstraZeneca, Boston, MA, USA
| | - Niresh Hariparsad
- Drug Metabolism and Pharmacokinetics, Early Oncology Research and Development, AstraZeneca, Boston, MA, USA
| | - Owen Jones
- Drug Metabolism and Pharmacokinetics, Early Oncology Research and Development, Cambridge, UK
| | - Dermot McGinnity
- Drug Metabolism and Pharmacokinetics, Early Oncology Research and Development, Cambridge, UK
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Law R, Lewis D, Hain D, Daut R, DelBello MP, Frazier JA, Newcorn JH, Nurmi E, Cogan ES, Wagner S, Johnson H, Lanchbury J. Characterisation of seven medications approved for attention-deficit/hyperactivity disorder using in vitro models of hepatic metabolism. Xenobiotica 2022; 52:676-686. [PMID: 36317558 DOI: 10.1080/00498254.2022.2141151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The metabolism of most medications approved for the treatment of attention deficit/hyperactivity disorder (ADHD) is not fully understood.In vitro studies using cryopreserved, plated human hepatocytes (cPHHs) and pooled human liver microsomes (HLMs) were performed to more thoroughly characterise the metabolism of several ADHD medications.The use of enzyme-specific chemical inhibitors indicated a role for CYP2D6 in atomoxetine (ATX) metabolism, and roles for CYP3A4/5 in guanfacine (GUA) metabolism.The 4-hydroxy-atomoxetine and N-desmethyl-atomoxetine pathways represented 98.4% and 1.5% of ATX metabolism in cPHHs, respectively. The 3-OH-guanfacine pathway represented at least 2.6% of GUA metabolism in cPHHs, and 71% in HLMs.The major metabolising enzyme for methylphenidate (MPH) and dexmethylphenidate (dMPH) could not be identified using these methods because these compounds were too unstable. Hydrolysis of these medications was spontaneous and did not require the presence of protein to occur.Clonidine (CLD), amphetamine (AMPH), and dextroamphetamine (dAMPH) did not deplete substantially in cPHHs nor HLMs, suggesting that these compounds may not undergo considerable hepatic metabolism. The major circulating metabolites of AMPH and dAMPH (benzoic acid and hippuric acid) were not observed in either system, and therefore could not be characterised. Additionally, inhibition experiments suggested a very minimal role for CYP2D6 in CLD and AMPH metabolism.
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Affiliation(s)
| | | | | | | | - Melissa P DelBello
- Department of Psychiatry and Behavioral Neuroscience, College of Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Jean A Frazier
- Eunice Kennedy Shriver Center, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | | | - Erika Nurmi
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, USA
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Formulation and Evaluation of Hybrid Niosomal In Situ Gel for Intravesical Co-Delivery of Curcumin and Gentamicin Sulfate. Pharmaceutics 2022; 14:pharmaceutics14040747. [PMID: 35456581 PMCID: PMC9028379 DOI: 10.3390/pharmaceutics14040747] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Revised: 03/24/2022] [Accepted: 03/26/2022] [Indexed: 02/01/2023] Open
Abstract
The current study describes the elaboration of a hybrid drug delivery platform for an intravesical application based on curcumin/gentamicin sulfate simultaneously loaded niosomes incorporated into thermosensitive in situ gels. Series of niosomes were elaborated via the thin film hydration method, evaluating the impact of non-ionic surfactants’, cholesterol’s, and curcumin’s concentration. The formulation composed of equimolar ratio of Span 60, Tween 60, and 30 mol% cholesterol was selected as the optimal composition, due to the high entrapment efficiency values obtained for both drugs, and appropriate physicochemical parameters (morphology, size, PDI, and zeta potential), therefore, was further incorporated into Poloxamers (407/188) and Poloxamers and chitosan based in situ gels. The developed hybrid systems were characterized with sol to gel transition in the physiological range, suitable rheological and gelling characteristics. In addition, the formed gel structure at physiological temperatures determines the retarded dissolution of both drugs (vs. niosomal suspension) and sustained release profile. The conducted microbial studies of selected niosomal in situ gels revealed the occurrence of a synergetic effect of the two compounds when simultaneously loaded. The findings indicate that the elaborated thermosensitive niosomal in situ gels can be considered as a feasible platform for intravesical drug delivery.
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Scotcher D, Galetin A. PBPK Simulation-Based Evaluation of Ganciclovir Crystalluria Risk Factors: Effect of Renal Impairment, Old Age, and Low Fluid Intake. AAPS J 2021; 24:13. [PMID: 34907479 PMCID: PMC8816528 DOI: 10.1208/s12248-021-00654-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 10/02/2021] [Indexed: 11/30/2022] Open
Abstract
Dosing guidance is often lacking for chronic kidney disease (CKD) due to exclusion of such patients from pivotal clinical trials. Physiologically based pharmacokinetic (PBPK) modelling supports model-informed dosing when clinical data are lacking, but application of these approaches to patients with impaired renal function is not yet at full maturity. In the current study, a ganciclovir PBPK model was developed for patients with normal renal function and extended to CKD population. CKD-related changes in tubular secretion were explored in the mechanistic kidney model and implemented either as proportional or non-proportional decline relative to GFR. Crystalluria risk was evaluated in different clinical settings (old age, severe CKD and low fluid intake) by simulating ganciclovir medullary collecting duct (MCD) concentrations. The ganciclovir PBPK model captured observed changes in systemic pharmacokinetic endpoints in mild-to-severe CKD; these trends were evident irrespective of assumed pathophysiological mechanism of altered active tubular secretion in the model. Minimal difference in simulated ganciclovir MCD concentrations was noted between young adult and geriatric populations with normal renal function and urine flow (1 mL/min), with lower concentrations predicted for severe CKD patients. High crystalluria risk was identified at reduced urine flow (0.1 mL/min) as simulated ganciclovir MCD concentrations exceeded its solubility (2.6–6 mg/mL), irrespective of underlying renal function. The analysis highlighted the importance of appropriate distribution of virtual subjects’ systems data in CKD populations. The ganciclovir PBPK model illustrates the ability of this translational tool to explore individual and combined effects of age, urine flow, and renal impairment on local drug renal exposure.
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Affiliation(s)
- Daniel Scotcher
- Centre for Applied Pharmacokinetic Research, School of Health Sciences, University of Manchester, Stopford Building, Oxford Road, Manchester, M13 9PT, UK
| | - Aleksandra Galetin
- Centre for Applied Pharmacokinetic Research, School of Health Sciences, University of Manchester, Stopford Building, Oxford Road, Manchester, M13 9PT, UK.
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Imaoka T, Huang W, Shum S, Hailey DW, Chang SY, Chapron A, Yeung CK, Himmelfarb J, Isoherranen N, Kelly EJ. Bridging the gap between in silico and in vivo by modeling opioid disposition in a kidney proximal tubule microphysiological system. Sci Rep 2021; 11:21356. [PMID: 34725352 PMCID: PMC8560754 DOI: 10.1038/s41598-021-00338-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 09/27/2021] [Indexed: 11/22/2022] Open
Abstract
Opioid overdose, dependence, and addiction are a major public health crisis. Patients with chronic kidney disease (CKD) are at high risk of opioid overdose, therefore novel methods that provide accurate prediction of renal clearance (CLr) and systemic disposition of opioids in CKD patients can facilitate the optimization of therapeutic regimens. The present study aimed to predict renal clearance and systemic disposition of morphine and its active metabolite morphine-6-glucuronide (M6G) in CKD patients using a vascularized human proximal tubule microphysiological system (VPT-MPS) coupled with a parent-metabolite full body physiologically-based pharmacokinetic (PBPK) model. The VPT-MPS, populated with a human umbilical vein endothelial cell (HUVEC) channel and an adjacent human primary proximal tubular epithelial cells (PTEC) channel, successfully demonstrated secretory transport of morphine and M6G from the HUVEC channel into the PTEC channel. The in vitro data generated by VPT-MPS were incorporated into a mechanistic kidney model and parent-metabolite full body PBPK model to predict CLr and systemic disposition of morphine and M6G, resulting in successful prediction of CLr and the plasma concentration–time profiles in both healthy subjects and CKD patients. A microphysiological system together with mathematical modeling successfully predicted renal clearance and systemic disposition of opioids in CKD patients and healthy subjects.
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Affiliation(s)
- Tomoki Imaoka
- Department of Pharmaceutics, School of Pharmacy, University of Washington, HSB Room H272, 1959 NE Pacific Street, Seattle, WA, 98195, USA
| | - Weize Huang
- Department of Pharmaceutics, School of Pharmacy, University of Washington, HSB Room H272, 1959 NE Pacific Street, Seattle, WA, 98195, USA
| | - Sara Shum
- Department of Pharmaceutics, School of Pharmacy, University of Washington, HSB Room H272, 1959 NE Pacific Street, Seattle, WA, 98195, USA
| | - Dale W Hailey
- Lynn and Mike Garvey Imaging Core, Institute for Stem Cell and Regenerative Medicine, Seattle, WA, 98109, USA.,Department of Laboratory Medicine and Pathology, School of Medicine, University of Washington, Seattle, WA, 98195, USA
| | - Shih-Yu Chang
- Department of Pharmacy, School of Pharmacy, University of Washington, Seattle, WA, 98195, USA
| | - Alenka Chapron
- Department of Pharmaceutics, School of Pharmacy, University of Washington, HSB Room H272, 1959 NE Pacific Street, Seattle, WA, 98195, USA
| | - Catherine K Yeung
- Department of Pharmacy, School of Pharmacy, University of Washington, Seattle, WA, 98195, USA.,Division of Nephrology, Department of Medicine, Kidney Research Institute, University of Washington, 1959 NE Pacific Street, HSB Room H272, Seattle, WA, 98195, USA
| | - Jonathan Himmelfarb
- Division of Nephrology, Department of Medicine, Kidney Research Institute, University of Washington, 1959 NE Pacific Street, HSB Room H272, Seattle, WA, 98195, USA
| | - Nina Isoherranen
- Department of Pharmaceutics, School of Pharmacy, University of Washington, HSB Room H272, 1959 NE Pacific Street, Seattle, WA, 98195, USA
| | - Edward J Kelly
- Department of Pharmaceutics, School of Pharmacy, University of Washington, HSB Room H272, 1959 NE Pacific Street, Seattle, WA, 98195, USA. .,Division of Nephrology, Department of Medicine, Kidney Research Institute, University of Washington, 1959 NE Pacific Street, HSB Room H272, Seattle, WA, 98195, USA.
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Jean D, Naik K, Milligan L, Hall S, Mei Huang S, Isoherranen N, Kuemmel C, Seo P, Tegenge MA, Wang Y, Yang Y, Zhang X, Zhao L, Zhao P, Benjamin J, Bergman K, Grillo J, Madabushi R, Wu F, Zhu H, Zineh I. Development of best practices in physiologically based pharmacokinetic modeling to support clinical pharmacology regulatory decision-making-A workshop summary. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2021; 10:1271-1275. [PMID: 34536337 PMCID: PMC8592512 DOI: 10.1002/psp4.12706] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Revised: 08/02/2021] [Accepted: 08/05/2021] [Indexed: 01/03/2023]
Affiliation(s)
- Daphney Jean
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Kunal Naik
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Lauren Milligan
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Stephen Hall
- Eli Lilly and Company, Indianapolis, Indiana, USA
| | - Shiew Mei Huang
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Nina Isoherranen
- School of Pharmacy, University of Washington, Seattle, Washington, USA
| | - Colleen Kuemmel
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Paul Seo
- Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Million A Tegenge
- Office of Tissues and Advanced Therapies, Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Yaning Wang
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Yuching Yang
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Xinyuan Zhang
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Liang Zhao
- Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Ping Zhao
- Bill & Melinda Gates Foundation, Seattle, Washington, USA
| | - Jessica Benjamin
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Kimberly Bergman
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Joseph Grillo
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Rajanikanth Madabushi
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Fang Wu
- Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Hao Zhu
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Issam Zineh
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
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11
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Gaohua L, Miao X, Dou L. Crosstalk of physiological pH and chemical pKa under the umbrella of physiologically based pharmacokinetic modeling of drug absorption, distribution, metabolism, excretion, and toxicity. Expert Opin Drug Metab Toxicol 2021; 17:1103-1124. [PMID: 34253134 DOI: 10.1080/17425255.2021.1951223] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Introduction: Physiological pH and chemical pKa are two sides of the same coin in defining the ionization of a drug in the human body. The Henderson-Hasselbalch equation and pH-partition hypothesis form the theoretical base to define the impact of pH-pKa crosstalk on drug ionization and thence its absorption, distribution, metabolism, excretion, and toxicity (ADMET).Areas covered: Human physiological pH is not constant, but a diverse, dynamic state regulated by various biological mechanisms, while the chemical pKa is generally a constant defining the acidic dissociation of the drug at various environmental pH. Works on pH-pKa crosstalk are scattered in the literature, despite its significant contributions to drug pharmacokinetics, pharmacodynamics, safety, and toxicity. In particular, its impacts on drug ADMET have not been effectively linked to the physiologically based pharmacokinetic (PBPK) modeling and simulation, a powerful tool increasingly used in model-informed drug development (MIDD).Expert opinion: Lacking a full consideration of the interactions of physiological pH and chemical pKa in a PBPK model limits scientists' capability in mechanistically describing the drug ADMET. This mini-review compiled literature knowledge on pH-pKa crosstalk and its impacts on drug ADMET, from the viewpoint of PBPK modeling, to pave the way to a systematic incorporation of pH-pKa crosstalk into PBPK modeling and simulation.
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Affiliation(s)
- Lu Gaohua
- Research & Early Development, Princeton, New Jersey, USA
| | - Xiusheng Miao
- Drug Metabolism and Pharmacokinetics, GlaxoSmithKline, Collegeville, Pennsylvania, USA
| | - Liu Dou
- School of Pharmaceutical Sciences (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China
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12
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Zhang D, Wei C, Hop CECA, Wright MR, Hu M, Lai Y, Khojasteh SC, Humphreys WG. Intestinal Excretion, Intestinal Recirculation, and Renal Tubule Reabsorption Are Underappreciated Mechanisms That Drive the Distribution and Pharmacokinetic Behavior of Small Molecule Drugs. J Med Chem 2021; 64:7045-7059. [PMID: 34010555 DOI: 10.1021/acs.jmedchem.0c01720] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Drug reabsorption following biliary excretion is well-known as enterohepatic recirculation (EHR). Renal tubular reabsorption (RTR) following renal excretion is also common but not easily assessed. Intestinal excretion (IE) and enteroenteric recirculation (EER) have not been recognized as common disposition mechanisms for metabolically stable and permeable drugs. IE and intestinal reabsorption (IR:EHR/EER), as well as RTR, are governed by dug concentration gradients, passive diffusion, active transport, and metabolism, and together they markedly impact disposition and pharmacokinetics (PK) of small molecule drugs. Disruption of IE, IR, or RTR through applications of active charcoal (AC), transporter knockout (KO), and transporter inhibitors can lead to changes in PK parameters. The impacts of intestinal and renal reabsorption on PK are under-appreciated. Although IE and EER/RTR can be an intrinsic drug property, there is no apparent strategy to optimize compounds based on this property. This review seeks to improve understanding and applications of IE, IR, and RTR mechanisms.
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Affiliation(s)
- Donglu Zhang
- Department of Drug Metabolism and Pharmacokinetics, Genentech, 1 DNA Way, South San Francisco, California 94080, United States
| | - Cong Wei
- Drug Metabolism and Pharmacokinetics, Biogen, 225 Binney Street, Cambridge, Massachusetts 02142, United States
| | - Cornelis E C A Hop
- Department of Drug Metabolism and Pharmacokinetics, Genentech, 1 DNA Way, South San Francisco, California 94080, United States
| | - Matthew R Wright
- Department of Drug Metabolism and Pharmacokinetics, Genentech, 1 DNA Way, South San Francisco, California 94080, United States
| | - Ming Hu
- University of Houston College of Pharmacy, 4849 Calhoun Road, Houston, Texas 77204, United States
| | - Yurong Lai
- Drug Metabolism and Pharmacokinetics, Gilead Sciences, 333 Lakeside Drive, Foster City, California 94404, United States
| | - S Cyrus Khojasteh
- Department of Drug Metabolism and Pharmacokinetics, Genentech, 1 DNA Way, South San Francisco, California 94080, United States
| | - W Griff Humphreys
- Aranmore Pharma Consulting, 11 Andrew Drive, Lawrenceville, New Jersey 08648, United States
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Huang W, Isoherranen N. Novel Mechanistic PBPK Model to Predict Renal Clearance in Varying Stages of CKD by Incorporating Tubular Adaptation and Dynamic Passive Reabsorption. CPT Pharmacometrics Syst Pharmacol 2020; 9:571-583. [PMID: 32977369 PMCID: PMC7577018 DOI: 10.1002/psp4.12553] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Accepted: 07/22/2020] [Indexed: 11/13/2022] Open
Abstract
Chronic kidney disease (CKD) has significant effects on renal clearance (CLr ) of drugs. Physiologically-based pharmacokinetic (PBPK) models have been used to predict CKD effects on transporter-mediated renal active secretion and CLr for hydrophilic nonpermeable compounds. However, no studies have shown systematic PBPK modeling of renal passive reabsorption or CLr for hydrophobic permeable drugs in CKD. The goal of this study was to expand our previously developed and verified mechanistic kidney model to develop a universal model to predict changes in CLr in CKD for permeable and nonpermeable drugs that accounts for the dramatic nonlinear effect of CKD on renal passive reabsorption of permeable drugs. The developed model incorporates physiologically-based tubular changes of reduced water reabsorption/increased tubular flow rate per remaining functional nephron in CKD. The final adaptive kidney model successfully (absolute fold error (AFE) all < 2) predicted renal passive reabsorption and CLr for 20 permeable and nonpermeable test compounds across the stages of CKD. In contrast, use of proportional glomerular filtration rate reduction approach without addressing tubular adaptation processes in CKD to predict CLr generated unacceptable CLr predictions (AFE = 2.61-7.35) for permeable compounds in severe CKD. Finally, the adaptive kidney model accurately predicted CLr of para-amino-hippuric acid and memantine, two secreted compounds, in CKD, suggesting successful integration of active secretion into the model, along with passive reabsorption. In conclusion, the developed adaptive kidney model enables mechanistic predictions of in vivo CLr through CKD progression without any empirical scaling factors and can be used for CLr predictions prior to assessment of drug disposition in renal impairment.
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Affiliation(s)
- Weize Huang
- Department of PharmaceuticsSchool of PharmacyUniversity of WashingtonSeattleWashingtonUSA
| | - Nina Isoherranen
- Department of PharmaceuticsSchool of PharmacyUniversity of WashingtonSeattleWashingtonUSA
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