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De Carlo A, Tosca EM, Melillo N, Magni P. A two-stages global sensitivity analysis by using the δ sensitivity index in presence of correlated inputs: application on a tumor growth inhibition model based on the dynamic energy budget theory. J Pharmacokinet Pharmacodyn 2023; 50:395-409. [PMID: 37422844 PMCID: PMC10460734 DOI: 10.1007/s10928-023-09872-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 06/16/2023] [Indexed: 07/11/2023]
Abstract
Global sensitivity analysis (GSA) evaluates the impact of variability and/or uncertainty of the model parameters on given model outputs. GSA is useful for assessing the quality of Pharmacometric model inference. Indeed, model parameters can be affected by high (estimation) uncertainty due to the sparsity of data. Independence between model parameters is a common assumption of GSA methods. However, ignoring (known) correlations between parameters may alter model predictions and, then, GSA results. To address this issue, a novel two-stages GSA technique based on the δ index, which is well-defined also in presence of correlated parameters, is here proposed. In the first step, statistical dependencies are neglected to identify parameters exerting causal effects. Correlations are introduced in the second step to consider the real distribution of the model output and investigate also the 'indirect' effects due to the correlation structure. The proposed two-stages GSA strategy was applied, as case study, to a preclinical tumor-in-host-growth inhibition model based on the Dynamic Energy Budget theory. The aim is to evaluate the impact of the model parameter estimate uncertainty (including correlations) on key model-derived metrics: the drug threshold concentration for tumor eradication, the tumor volume doubling time and a new index evaluating the drug efficacy-toxicity trade-off. This approach allowed to rank parameters according to their impact on the output, discerning whether a parameter mainly exerts a causal or 'indirect' effect. Thus, it was possible to identify uncertainties that should be necessarily reduced to obtain robust predictions for the outputs of interest.
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Affiliation(s)
- Alessandro De Carlo
- Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Elena Maria Tosca
- Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Nicola Melillo
- Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
- Systems Forecasting UK Ltd, Lancaster, UK
| | - Paolo Magni
- Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
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2
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Sun L, Mi K, Hou Y, Hui T, Zhang L, Tao Y, Liu Z, Huang L. Pharmacokinetic and Pharmacodynamic Drug-Drug Interactions: Research Methods and Applications. Metabolites 2023; 13:897. [PMID: 37623842 PMCID: PMC10456269 DOI: 10.3390/metabo13080897] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 07/24/2023] [Accepted: 07/25/2023] [Indexed: 08/26/2023] Open
Abstract
Because of the high research and development cost of new drugs, the long development process of new drugs, and the high failure rate at later stages, combining past drugs has gradually become a more economical and attractive alternative. However, the ensuing problem of drug-drug interactions (DDIs) urgently need to be solved, and combination has attracted a lot of attention from pharmaceutical researchers. At present, DDI is often evaluated and investigated from two perspectives: pharmacodynamics and pharmacokinetics. However, in some special cases, DDI cannot be accurately evaluated from a single perspective. Therefore, this review describes and compares the current DDI evaluation methods based on two aspects: pharmacokinetic interaction and pharmacodynamic interaction. The methods summarized in this paper mainly include probe drug cocktail methods, liver microsome and hepatocyte models, static models, physiologically based pharmacokinetic models, machine learning models, in vivo comparative efficacy studies, and in vitro static and dynamic tests. This review aims to serve as a useful guide for interested researchers to promote more scientific accuracy and clinical practical use of DDI studies.
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Affiliation(s)
- Lei Sun
- National Reference Laboratory of Veterinary Drug Residues, Huazhong Agricultural University, Wuhan 430000, China; (L.S.); (K.M.); (Y.H.); (T.H.); (L.Z.); (Y.T.)
- MAO Key Laboratory for Detection of Veterinary Drug Residues, Huazhong Agricultural University, Wuhan 430000, China;
| | - Kun Mi
- National Reference Laboratory of Veterinary Drug Residues, Huazhong Agricultural University, Wuhan 430000, China; (L.S.); (K.M.); (Y.H.); (T.H.); (L.Z.); (Y.T.)
- MOA Laboratory for Risk Assessment of Quality and Safety of Livestock and Poultry Products, Huazhong Agricultural University, Wuhan 430000, China
| | - Yixuan Hou
- National Reference Laboratory of Veterinary Drug Residues, Huazhong Agricultural University, Wuhan 430000, China; (L.S.); (K.M.); (Y.H.); (T.H.); (L.Z.); (Y.T.)
- MAO Key Laboratory for Detection of Veterinary Drug Residues, Huazhong Agricultural University, Wuhan 430000, China;
| | - Tianyi Hui
- National Reference Laboratory of Veterinary Drug Residues, Huazhong Agricultural University, Wuhan 430000, China; (L.S.); (K.M.); (Y.H.); (T.H.); (L.Z.); (Y.T.)
- MAO Key Laboratory for Detection of Veterinary Drug Residues, Huazhong Agricultural University, Wuhan 430000, China;
| | - Lan Zhang
- National Reference Laboratory of Veterinary Drug Residues, Huazhong Agricultural University, Wuhan 430000, China; (L.S.); (K.M.); (Y.H.); (T.H.); (L.Z.); (Y.T.)
- MAO Key Laboratory for Detection of Veterinary Drug Residues, Huazhong Agricultural University, Wuhan 430000, China;
| | - Yanfei Tao
- National Reference Laboratory of Veterinary Drug Residues, Huazhong Agricultural University, Wuhan 430000, China; (L.S.); (K.M.); (Y.H.); (T.H.); (L.Z.); (Y.T.)
- MAO Key Laboratory for Detection of Veterinary Drug Residues, Huazhong Agricultural University, Wuhan 430000, China;
| | - Zhenli Liu
- MAO Key Laboratory for Detection of Veterinary Drug Residues, Huazhong Agricultural University, Wuhan 430000, China;
- MOA Laboratory for Risk Assessment of Quality and Safety of Livestock and Poultry Products, Huazhong Agricultural University, Wuhan 430000, China
| | - Lingli Huang
- National Reference Laboratory of Veterinary Drug Residues, Huazhong Agricultural University, Wuhan 430000, China; (L.S.); (K.M.); (Y.H.); (T.H.); (L.Z.); (Y.T.)
- MAO Key Laboratory for Detection of Veterinary Drug Residues, Huazhong Agricultural University, Wuhan 430000, China;
- MOA Laboratory for Risk Assessment of Quality and Safety of Livestock and Poultry Products, Huazhong Agricultural University, Wuhan 430000, China
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3
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Vasilogianni AM, Al-Majdoub ZM, Achour B, Peters SA, Rostami-Hodjegan A, Barber J. Proteomic quantification of receptor tyrosine kinases involved in the development and progression of colorectal cancer liver metastasis. Front Oncol 2023; 13:1010563. [PMID: 36890818 PMCID: PMC9986493 DOI: 10.3389/fonc.2023.1010563] [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: 08/03/2022] [Accepted: 02/06/2023] [Indexed: 02/22/2023] Open
Abstract
Introduction Alterations in expression and activity of human receptor tyrosine kinases (RTKs) are associated with cancer progression and in response to therapeutic intervention. Methods Thus, protein abundance of 21 RTKs was assessed in 15 healthy and 18 cancerous liver samples [2 primary and 16 colorectal cancer liver metastasis (CRLM)] matched with non-tumorous (histologically normal) tissue, by a validated QconCAT-based targeted proteomic approach. Results It was demonstrated, for the first time, that the abundance of EGFR, INSR, VGFR3 and AXL, is lower in tumours relative to livers from healthy individuals whilst the opposite is true for IGF1R. EPHA2 was upregulated in tumour compared with histologically normal tissue surrounding it. PGFRB levels were higher in tumours relative to both histologically normal tissue surrounding tumour and tissues taken from healthy individuals. The abundances of VGFR1/2, PGFRA, KIT, CSF1R, FLT3, FGFR1/3, ERBB2, NTRK2, TIE2, RET, and MET were, however, comparable in all samples. Statistically significant, but moderate correlations were observed (Rs > 0.50, p < 0.05) for EGFR with INSR and KIT. FGFR2 correlated with PGFRA and VGFR1 with NTRK2 in healthy livers. In non-tumorous (histologically normal) tissues from cancer patients, there were correlations between TIE2 and FGFR1, EPHA2 and VGFR3, FGFR3 and PGFRA (p < 0.05). EGFR correlated with INSR, ERBB2, KIT and EGFR, and KIT with AXL and FGFR2. In tumours, CSF1R correlated with AXL, EPHA2 with PGFRA, and NTRK2 with PGFRB and AXL. Sex, liver lobe and body mass index of donors had no impact on the abundance of RTKs, although donor age showed some correlations. RET was the most abundant of these kinases in non-tumorous tissues (~35%), while PGFRB was the most abundant RTK in tumours (~47%). Several correlations were also observed between the abundance of RTKs and proteins relevant to drug pharmacokinetics (enzymes and transporters). Discussion DiscussionThis study quantified perturbation to the abundance of several RTKs in cancer and the value generated in this study can be used as input to systems biology models defining liver cancer metastases and biomarkers of its progression.
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Affiliation(s)
- Areti-Maria Vasilogianni
- Centre for Applied Pharmacokinetic Research, Division of Pharmacy and Optometry, School of Health Sciences, University of Manchester, Manchester, United Kingdom
| | - Zubida M Al-Majdoub
- Centre for Applied Pharmacokinetic Research, Division of Pharmacy and Optometry, School of Health Sciences, University of Manchester, Manchester, United Kingdom
| | - Brahim Achour
- Centre for Applied Pharmacokinetic Research, Division of Pharmacy and Optometry, School of Health Sciences, University of Manchester, Manchester, United Kingdom.,Department of Biomedical and Pharmaceutical Sciences, College of Pharmacy, University of Rhode Island, Kingston, RI, United States
| | - Sheila Annie Peters
- Translational Quantitative Pharmacology, BioPharma, R&D Global Early Development, Merck KGaA, Darmstadt, Germany.,Translational Medicine and Clinical Pharmacology, Boehringer Ingelheim Pharma GmbH & Co., KG, Ingelheim am Rhein, Germany
| | - Amin Rostami-Hodjegan
- Centre for Applied Pharmacokinetic Research, Division of Pharmacy and Optometry, School of Health Sciences, University of Manchester, Manchester, United Kingdom.,Simcyp Division, Certara Inc., Sheffield, United Kingdom
| | - Jill Barber
- Centre for Applied Pharmacokinetic Research, Division of Pharmacy and Optometry, School of Health Sciences, University of Manchester, Manchester, United Kingdom
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Neuhoff S, Harwood MD, Rostami-Hodjegan A, Achour B. Application of proteomic data in the translation of in vitro observations to associated clinical outcomes. DRUG DISCOVERY TODAY. TECHNOLOGIES 2021; 39:13-22. [PMID: 34906322 DOI: 10.1016/j.ddtec.2021.06.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 04/20/2021] [Accepted: 06/11/2021] [Indexed: 12/12/2022]
Abstract
Translation of information on drug exposure and effect is facilitated by in silico models that enable extrapolation of in vitro measurements to in vivo clinical outcomes. These models integrate drug-specific data with information describing physiological processes and pathological changes, including alterations to proteins involved in drug absorption, distribution and elimination. Over the past 15 years, quantitative proteomics has contributed a wealth of protein expression data, which are currently used for a variety of systems pharmacology applications, as a complement or a surrogate for activity of the corresponding proteins. In this review, we explore current and emerging applications of targeted and global (untargeted) proteomics in translational pharmacology as well as strategies for improved integration into model-based drug development.
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Affiliation(s)
- Sibylle Neuhoff
- Certara UK Limited, Simcyp Division, 1 Concourse Way, Sheffield, S1 2BJ, UK
| | - Matthew D Harwood
- Certara UK Limited, Simcyp Division, 1 Concourse Way, Sheffield, S1 2BJ, UK
| | - Amin Rostami-Hodjegan
- Certara UK Limited, Simcyp Division, 1 Concourse Way, Sheffield, S1 2BJ, UK; Centre for Applied Pharmacokinetic Research (CAPKR), School of Health Sciences, University of Manchester, Stopford Building, Oxford Road, Manchester, M13 9PT, UK
| | - Brahim Achour
- Centre for Applied Pharmacokinetic Research (CAPKR), School of Health Sciences, University of Manchester, Stopford Building, Oxford Road, Manchester, M13 9PT, UK.
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5
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Al-Majdoub ZM, Scotcher D, Achour B, Barber J, Galetin A, Rostami-Hodjegan A. Quantitative Proteomic Map of Enzymes and Transporters in the Human Kidney: Stepping Closer to Mechanistic Kidney Models to Define Local Kinetics. Clin Pharmacol Ther 2021; 110:1389-1400. [PMID: 34390491 DOI: 10.1002/cpt.2396] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 08/03/2021] [Indexed: 12/20/2022]
Abstract
The applications of translational modeling of local drug concentrations in various organs had a sharp increase over the last decade. These are part of the model-informed drug development initiative, adopted by the pharmaceutical industry and promoted by drug regulatory agencies. With respect to the kidney, the models serve as a bridge for understanding animal vs. human observations related to renal drug disposition and any consequential adverse effects. However, quantitative data on key drug-metabolizing enzymes and transporters relevant for predicting renal drug disposition are limited. Using targeted and global quantitative proteomics, we determined the abundance of multiple enzymes and transporters in 20 human kidney cortex samples. Nine enzymes and 22 transporters were quantified (8 for the first time in the kidneys). In addition, > 4,000 proteins were identified and used to form an open database. CYP2B6, CYP3A5, and CYP4F2 showed comparable, but generally low expression, whereas UGT1A9 and UGT2B7 levels were the highest. Significant correlation between abundance and activity (measured by mycophenolic acid clearance) was observed for UGT1A9 (Rs = 0.65, P = 0.004) and UGT2B7 (Rs = 0.70, P = 0.023). Expression of P-gp ≈ MATE-1 and OATP4C1 transporters were high. Strong intercorrelations were observed between several transporters (P-gp/MRP4, MRP2/OAT3, and OAT3/OAT4); no correlation in expression was apparent for functionally related transporters (OCT2/MATEs). This study extends our knowledge of pharmacologically relevant proteins in the kidney cortex, with implications on more prudent use of mechanistic kidney models under the general framework of quantitative systems pharmacology and toxicology.
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Affiliation(s)
- Zubida M Al-Majdoub
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK
| | - Daniel Scotcher
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK
| | - Brahim Achour
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK
| | - Jill Barber
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK
| | - Aleksandra Galetin
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK
| | - Amin Rostami-Hodjegan
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK.,Certara UK (Simcyp Division), Sheffield, UK
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6
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Tsakalozou E, Alam K, Babiskin A, Zhao L. Physiologically-Based Pharmacokinetic Modeling to Support Determination of Bioequivalence for Dermatological Drug Products: Scientific and Regulatory Considerations. Clin Pharmacol Ther 2021; 111:1036-1049. [PMID: 34231211 DOI: 10.1002/cpt.2356] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Accepted: 06/11/2021] [Indexed: 12/30/2022]
Abstract
Physiologically-based pharmacokinetic (PBPK) modeling and simulation provides mechanism-based predictions of the pharmacokinetics of an active ingredient following its administration in humans. Dermal PBPK models describe the skin permeation and disposition of the active ingredient following the application of a dermatological product on the skin of virtual healthy and diseased human subjects. These models take into account information on product quality attributes, physicochemical properties of the active ingredient and skin (patho)physiology, and their interplay with each other. Regulatory and product development decision makers can leverage these quantitative tools to identify factors impacting local and systemic exposure. In the realm of generic drug products, the number of US Food and Drug Administratioin (FDA) interactions that use dermal PBPK modeling to support alternative bioequivalence (BE) approaches is increasing. In this report, we share scientific considerations on the development, verification and validation (V&V), and application of PBPK models within the context of a virtual BE assessment for dermatological drug products. We discuss the challenges associated with model V&V for these drug products stemming from the fact that target-site active ingredient concentrations are typically not measurable. Additionally, there are no established relationships between local and systemic PK profiles, when the latter are quantifiable. To that end, we detail a multilevel model V&V approach involving validation for the model of the drug product of interest coupled with the overall assessment of the modeling platform in use while leveraging in vitro and in vivo data related to local and systemic bioavailability.
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Affiliation(s)
- Eleftheria Tsakalozou
- Division of Quantitative Methods and Modeling (DQMM), Office of Research and Standards (ORS), Office of Generic Drugs (OGD), Center for Drug Evaluation and Research (CDER), US Food and Drug Administration (FDA), Silver Spring, Maryland, USA
| | - Khondoker Alam
- Division of Quantitative Methods and Modeling (DQMM), Office of Research and Standards (ORS), Office of Generic Drugs (OGD), Center for Drug Evaluation and Research (CDER), US Food and Drug Administration (FDA), Silver Spring, Maryland, USA
| | - Andrew Babiskin
- Division of Quantitative Methods and Modeling (DQMM), Office of Research and Standards (ORS), Office of Generic Drugs (OGD), Center for Drug Evaluation and Research (CDER), US Food and Drug Administration (FDA), Silver Spring, Maryland, USA
| | - Liang Zhao
- Division of Quantitative Methods and Modeling (DQMM), Office of Research and Standards (ORS), Office of Generic Drugs (OGD), Center for Drug Evaluation and Research (CDER), US Food and Drug Administration (FDA), Silver Spring, Maryland, USA
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Melillo N, Darwich AS. A latent variable approach to account for correlated inputs in global sensitivity analysis. J Pharmacokinet Pharmacodyn 2021; 48:671-686. [PMID: 34032996 PMCID: PMC8405496 DOI: 10.1007/s10928-021-09764-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Accepted: 05/06/2021] [Indexed: 12/13/2022]
Abstract
In drug development decision-making is often supported through model-based methods, such as physiologically-based pharmacokinetics (PBPK). Global sensitivity analysis (GSA) is gaining use for quality assessment of model-informed inference. However, the inclusion and interpretation of correlated factors in GSA has proven an issue. Here we developed and evaluated a latent variable approach for dealing with correlated factors in GSA. An approach was developed that describes the correlation between two model inputs through the causal relationship of three independent factors: the latent variable and the unique variances of the two correlated parameters. The latent variable approach was applied to a set of algebraic models and a case from PBPK. Then, this method was compared to Sobol’s GSA assuming no correlations, Sobol’s GSA with groups and the Kucherenko approach. For the latent variable approach, GSA was performed with Sobol’s method. By using the latent variable approach, it is possible to devise a unique and easy interpretation of the sensitivity indices while maintaining the correlation between the factors. Compared methods either consider the parameters independent, group the dependent variables into one unique factor or present difficulties in the interpretation of the sensitivity indices. In situations where GSA is called upon to support model-informed decision-making, the latent variable approach offers a practical method, in terms of ease of implementation and interpretability, for applying GSA to models with correlated inputs that does not violate the independence assumption. Prerequisites and limitations of the approach are discussed.
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Affiliation(s)
- Nicola Melillo
- Centre for Applied Pharmacokinetic Research, Division of Pharmacy & Optometry, School of Health Sciences, The University of Manchester, Manchester, UK
| | - Adam S Darwich
- Division of Health Informatics and Logistics, Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology, Stockholm, Sweden.
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Utilizing physiologically based pharmacokinetic modeling to predict theoretically conceivable extreme elevation of serum flecainide concentration in an anuric hemodialysis patient with cirrhosis. Eur J Clin Pharmacol 2020; 76:821-831. [DOI: 10.1007/s00228-020-02861-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Accepted: 03/26/2020] [Indexed: 02/04/2023]
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9
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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: 3.8] [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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10
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Couto N, Al-Majdoub ZM, Gibson S, Davies PJ, Achour B, Harwood MD, Carlson G, Barber J, Rostami-Hodjegan A, Warhurst G. Quantitative Proteomics of Clinically Relevant Drug-Metabolizing Enzymes and Drug Transporters and Their Intercorrelations in the Human Small Intestine. Drug Metab Dispos 2020; 48:245-254. [PMID: 31959703 PMCID: PMC7076527 DOI: 10.1124/dmd.119.089656] [Citation(s) in RCA: 64] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Accepted: 12/23/2019] [Indexed: 01/02/2023] Open
Abstract
The levels of drug-metabolizing enzymes (DMEs) and transporter proteins in the human intestine are pertinent to determine oral drug bioavailability. Despite the paucity of reports on such measurements, it is well recognized that these values are essential for translating in vitro data on drug metabolism and transport to predict drug disposition in gut wall. In the current study, clinically relevant DMEs [cytochrome P450 (P450) and uridine 5′-diphospho-glucuronosyltransferase (UGT)] and drug transporters were quantified in total mucosal protein preparations from the human jejunum (n = 4) and ileum (n = 12) using quantification concatemer–based targeted proteomics. In contrast to previous reports, UGT2B15 and organic anion-transporting polypeptide 1 (OATP1A2) were quantifiable in all our samples. Overall, no significant disparities in protein expression were observed between jejunum and ileum. Relative mRNA expression for drug transporters did not correlate with the abundance of their cognate protein, except for P-glycoprotein 1 (P-gp) and organic solute transporter subunit alpha (OST-α), highlighting the limitations of RNA as a surrogate for protein expression in dynamic tissues with high turnover. Intercorrelations were found within P450 [2C9-2C19 (P = 0.002, R2 = 0.63), 2C9–2J2 (P = 0.004, R2 = 0.40), 2D6-2J2 (P = 0.002, R2 = 0.50)] and UGT [1A1-2B7 (P = 0.02, R2 = 0.87)] family of enzymes. There were also correlations between P-gp and several other proteins [OST-α (P < 0.0001, R2 = 0.77), UGT1A6 (P = 0.009, R2 = 0.38), and CYP3A4 (P = 0.007, R2 = 0.30)]. Incorporating such correlations into building virtual populations is crucial for obtaining plausible characteristics of simulated individuals.
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Affiliation(s)
- Narciso Couto
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, United Kingdom (N.C., Z.M.A.-M., B.A., J.B., A.R.-H.); Gut Barrier Group, Inflammation and Repair, University of Manchester, Salford Royal NHS Trust, Salford, United Kingdom (S.G., P.J.D., G.C., G.W.); and Certara UK Limited (Simcyp Division), Sheffield, United Kingdom (M.D.H., A.R.-H.)
| | - Zubida M Al-Majdoub
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, United Kingdom (N.C., Z.M.A.-M., B.A., J.B., A.R.-H.); Gut Barrier Group, Inflammation and Repair, University of Manchester, Salford Royal NHS Trust, Salford, United Kingdom (S.G., P.J.D., G.C., G.W.); and Certara UK Limited (Simcyp Division), Sheffield, United Kingdom (M.D.H., A.R.-H.)
| | - Stephanie Gibson
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, United Kingdom (N.C., Z.M.A.-M., B.A., J.B., A.R.-H.); Gut Barrier Group, Inflammation and Repair, University of Manchester, Salford Royal NHS Trust, Salford, United Kingdom (S.G., P.J.D., G.C., G.W.); and Certara UK Limited (Simcyp Division), Sheffield, United Kingdom (M.D.H., A.R.-H.)
| | - Pamela J Davies
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, United Kingdom (N.C., Z.M.A.-M., B.A., J.B., A.R.-H.); Gut Barrier Group, Inflammation and Repair, University of Manchester, Salford Royal NHS Trust, Salford, United Kingdom (S.G., P.J.D., G.C., G.W.); and Certara UK Limited (Simcyp Division), Sheffield, United Kingdom (M.D.H., A.R.-H.)
| | - Brahim Achour
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, United Kingdom (N.C., Z.M.A.-M., B.A., J.B., A.R.-H.); Gut Barrier Group, Inflammation and Repair, University of Manchester, Salford Royal NHS Trust, Salford, United Kingdom (S.G., P.J.D., G.C., G.W.); and Certara UK Limited (Simcyp Division), Sheffield, United Kingdom (M.D.H., A.R.-H.)
| | - Matthew D Harwood
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, United Kingdom (N.C., Z.M.A.-M., B.A., J.B., A.R.-H.); Gut Barrier Group, Inflammation and Repair, University of Manchester, Salford Royal NHS Trust, Salford, United Kingdom (S.G., P.J.D., G.C., G.W.); and Certara UK Limited (Simcyp Division), Sheffield, United Kingdom (M.D.H., A.R.-H.)
| | - Gordon Carlson
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, United Kingdom (N.C., Z.M.A.-M., B.A., J.B., A.R.-H.); Gut Barrier Group, Inflammation and Repair, University of Manchester, Salford Royal NHS Trust, Salford, United Kingdom (S.G., P.J.D., G.C., G.W.); and Certara UK Limited (Simcyp Division), Sheffield, United Kingdom (M.D.H., A.R.-H.)
| | - Jill Barber
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, United Kingdom (N.C., Z.M.A.-M., B.A., J.B., A.R.-H.); Gut Barrier Group, Inflammation and Repair, University of Manchester, Salford Royal NHS Trust, Salford, United Kingdom (S.G., P.J.D., G.C., G.W.); and Certara UK Limited (Simcyp Division), Sheffield, United Kingdom (M.D.H., A.R.-H.)
| | - Amin Rostami-Hodjegan
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, United Kingdom (N.C., Z.M.A.-M., B.A., J.B., A.R.-H.); Gut Barrier Group, Inflammation and Repair, University of Manchester, Salford Royal NHS Trust, Salford, United Kingdom (S.G., P.J.D., G.C., G.W.); and Certara UK Limited (Simcyp Division), Sheffield, United Kingdom (M.D.H., A.R.-H.)
| | - Geoffrey Warhurst
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, United Kingdom (N.C., Z.M.A.-M., B.A., J.B., A.R.-H.); Gut Barrier Group, Inflammation and Repair, University of Manchester, Salford Royal NHS Trust, Salford, United Kingdom (S.G., P.J.D., G.C., G.W.); and Certara UK Limited (Simcyp Division), Sheffield, United Kingdom (M.D.H., A.R.-H.)
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11
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Quantitative mass spectrometry-based proteomics in the era of model-informed drug development: Applications in translational pharmacology and recommendations for best practice. Pharmacol Ther 2019; 203:107397. [DOI: 10.1016/j.pharmthera.2019.107397] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Accepted: 07/29/2019] [Indexed: 02/08/2023]
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12
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Prasad B, Achour B, Artursson P, Hop CECA, Lai Y, Smith PC, Barber J, Wisniewski JR, Spellman D, Uchida Y, Zientek MA, Unadkat JD, Rostami-Hodjegan A. Toward a Consensus on Applying Quantitative Liquid Chromatography-Tandem Mass Spectrometry Proteomics in Translational Pharmacology Research: A White Paper. Clin Pharmacol Ther 2019; 106:525-543. [PMID: 31175671 DOI: 10.1002/cpt.1537] [Citation(s) in RCA: 69] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Accepted: 05/22/2019] [Indexed: 12/18/2022]
Abstract
Quantitative translation of information on drug absorption, disposition, receptor engagement, and drug-drug interactions from bench to bedside requires models informed by physiological parameters that link in vitro studies to in vivo outcomes. To predict in vivo outcomes, biochemical data from experimental systems are routinely scaled using protein quantity in these systems and relevant tissues. Although several laboratories have generated useful quantitative proteomic data using state-of-the-art mass spectrometry, no harmonized guidelines exit for sample analysis and data integration to in vivo translation practices. To address this gap, a workshop was held on September 27 and 28, 2018, in Cambridge, MA, with 100 experts attending from academia, the pharmaceutical industry, and regulators. Various aspects of quantitative proteomics and its applications in translational pharmacology were debated. A summary of discussions and best practices identified by this expert panel are presented in this "White Paper" alongside unresolved issues that were outlined for future debates.
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Affiliation(s)
- Bhagwat Prasad
- Department of Pharmaceutics, University of Washington, Seattle, Washington, USA
| | - Brahim Achour
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK
| | - Per Artursson
- Department of Pharmacy, Uppsala University, Uppsala, Sweden
| | | | - Yurong Lai
- Gilead Sciences, Foster City, California, USA
| | - Philip C Smith
- Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Jill Barber
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK
| | - Jacek R Wisniewski
- Biochemical Proteomics Group, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Daniel Spellman
- Pharmacokinetics Pharmacodynamics & Drug Metabolism, Merck & Co., Inc., West Point, Pennsylvania, USA
| | - Yasuo Uchida
- Graduate School of Pharmaceutical Sciences, Tohoku University, Sendai, Japan
| | | | - Jashvant D Unadkat
- Department of Pharmaceutics, University of Washington, Seattle, Washington, USA
| | - Amin Rostami-Hodjegan
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK.,Certara (Simcyp Division), Sheffield, UK
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13
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Accounting for inter-correlation between enzyme abundance: a simulation study to assess implications on global sensitivity analysis within physiologically-based pharmacokinetics. J Pharmacokinet Pharmacodyn 2019; 46:137-154. [PMID: 30905037 DOI: 10.1007/s10928-019-09627-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Accepted: 03/12/2019] [Indexed: 10/27/2022]
Abstract
Physiologically based pharmacokinetic (PBPK) models often include several sets of correlated parameters, such as organ volumes and blood flows. Because of recent advances in proteomics, it has been demonstrated that correlations are also present between abundances of drug-metabolising enzymes in the liver. As the focus of population PBPK has shifted the emphasis from the average individual to theoretically conceivable extremes, reliable estimation of the extreme cases has become paramount. We performed a simulation study to assess the impact of the correlation between the abundances of two enzymes on the pharmacokinetics of drugs that are substrate of both, under assumptions of presence or lack of such correlations. We considered three semi-physiological models representing the cases of: (1) intravenously administered drugs metabolised by two enzymes expressed in the liver; (2) orally administered drugs metabolised by CYP3A4 expressed in the liver and gut wall; (3) intravenously administered drugs that are substrates of CYP3A4 and OATP1B1 in the liver. Finally, the impact of considering or ignoring correlation between enzymatic abundances on global sensitivity analysis (GSA) was investigated using variance based GSA on a reduced PBPK model for repaglinide, substrate of CYP3A4 and CYP2C8. Implementing such correlations can increase the confidence interval for population pharmacokinetic parameters (e.g., AUC, bioavailability) and impact the GSA results. Ignoring these correlations could lead to the generation of implausible parameters combinations and to an incorrect estimation of pharmacokinetic related parameters. Thus, known correlations should always be considered in building population PBPK models.
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14
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Al-Majdoub ZM, Al Feteisi H, Achour B, Warwood S, Neuhoff S, Rostami-Hodjegan A, Barber J. Proteomic Quantification of Human Blood-Brain Barrier SLC and ABC Transporters in Healthy Individuals and Dementia Patients. Mol Pharm 2019; 16:1220-1233. [PMID: 30735053 DOI: 10.1021/acs.molpharmaceut.8b01189] [Citation(s) in RCA: 73] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
The blood-brain barrier (BBB) maintains brain homeostasis by controlling traffic of molecules from the circulation into the brain. This function is predominantly dependent on proteins expressed at the BBB, especially transporters and tight junction proteins. Alterations to the level and function of BBB proteins can impact the susceptibility of the central nervous system to exposure to xenobiotics in the systemic circulation with potential consequent effects on brain function. In this study, expression profiles of drug transporters and solute carriers in the BBB were assessed in tissues from healthy individuals ( n = 12), Alzheimer's patients ( n = 5), and dementia with Lewy bodies patients ( n = 5), using targeted, accurate mass retention time (AMRT) and global proteomic methods. A total of 53 transporters were quantified, 19 for the first time in the BBB. A further 20 novel transporters were identified but not quantified. The global proteomic method identified another 3333 BBB proteins. Transporter abundances, taken together with the scaling factor, microvessel protein content per unit tissue (BMvPGB also measured here), can be used in quantitative systems pharmacology models predicting drug disposition in the brain and permitting dose adjustment (precision dosing) in special populations of patients, such as those with dementia. Even in this small study, we see differences in transporter profile between healthy and diseased brain tissue.
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Affiliation(s)
- Zubida M Al-Majdoub
- Centre for Applied Pharmacokinetic Research (CAPKR) , University of Manchester , Manchester M13 9PT , U.K
| | - Hajar Al Feteisi
- Centre for Applied Pharmacokinetic Research (CAPKR) , University of Manchester , Manchester M13 9PT , U.K
| | - Brahim Achour
- Centre for Applied Pharmacokinetic Research (CAPKR) , University of Manchester , Manchester M13 9PT , U.K
| | - Stacey Warwood
- Biological Mass Spectrometry Core Facility , University of Manchester , Manchester M13 9PT , U.K
| | - Sibylle Neuhoff
- Certara UK Limited , Simcyp Division , Level 2-Acero, 1 Concourse Way , Sheffield S1 2BJ , U.K
| | - Amin Rostami-Hodjegan
- Centre for Applied Pharmacokinetic Research (CAPKR) , University of Manchester , Manchester M13 9PT , U.K.,Certara UK Limited , Simcyp Division , Level 2-Acero, 1 Concourse Way , Sheffield S1 2BJ , U.K
| | - Jill Barber
- Centre for Applied Pharmacokinetic Research (CAPKR) , University of Manchester , Manchester M13 9PT , U.K
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15
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Couto N, Al-Majdoub ZM, Achour B, Wright PC, Rostami-Hodjegan A, Barber J. Quantification of Proteins Involved in Drug Metabolism and Disposition in the Human Liver Using Label-Free Global Proteomics. Mol Pharm 2019; 16:632-647. [DOI: 10.1021/acs.molpharmaceut.8b00941] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Narciso Couto
- Centre for Applied Pharmacokinetic Research, University of Manchester, Stopford Building, Oxford Road, Manchester M13 9PT, U.K
- Department of Chemical and Biological Engineering, ChELSI Institute (Chemical Engineering at the Life Science Interface), University of Sheffield, Sir Robert Hadfield Building, Mappin Street, Sheffield S1 3JD, U.K
| | - Zubida M. Al-Majdoub
- Centre for Applied Pharmacokinetic Research, University of Manchester, Stopford Building, Oxford Road, Manchester M13 9PT, U.K
| | - Brahim Achour
- Centre for Applied Pharmacokinetic Research, University of Manchester, Stopford Building, Oxford Road, Manchester M13 9PT, U.K
| | - Phillip C. Wright
- Department of Chemical and Biological Engineering, ChELSI Institute (Chemical Engineering at the Life Science Interface), University of Sheffield, Sir Robert Hadfield Building, Mappin Street, Sheffield S1 3JD, U.K
| | - Amin Rostami-Hodjegan
- Centre for Applied Pharmacokinetic Research, University of Manchester, Stopford Building, Oxford Road, Manchester M13 9PT, U.K
- Simcyp Ltd. (a Certara company), 1 Concourse Way, Sheffield S1 2BJ, U.K
| | - Jill Barber
- Centre for Applied Pharmacokinetic Research, University of Manchester, Stopford Building, Oxford Road, Manchester M13 9PT, U.K
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16
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Achour B, Dantonio A, Niosi M, Novak JJ, Al-Majdoub ZM, Goosen TC, Rostami-Hodjegan A, Barber J. Data Generated by Quantitative Liquid Chromatography-Mass Spectrometry Proteomics Are Only the Start and Not the Endpoint: Optimization of Quantitative Concatemer-Based Measurement of Hepatic Uridine-5′-Diphosphate–Glucuronosyltransferase Enzymes with Reference to Catalytic Activity. Drug Metab Dispos 2018; 46:805-812. [DOI: 10.1124/dmd.117.079475] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2017] [Accepted: 03/22/2018] [Indexed: 12/17/2022] Open
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17
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Doki K, Darwich AS, Achour B, Tornio A, Backman JT, Rostami-Hodjegan A. Implications of intercorrelation between hepatic CYP3A4-CYP2C8 enzymes for the evaluation of drug-drug interactions: a case study with repaglinide. Br J Clin Pharmacol 2018; 84:972-986. [PMID: 29381228 DOI: 10.1111/bcp.13533] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2017] [Revised: 12/21/2017] [Accepted: 01/21/2018] [Indexed: 12/18/2022] Open
Abstract
AIMS Statistically significant positive correlations are reported for the abundance of hepatic drug-metabolizing enzymes. We investigate, as an example, the impact of CYP3A4-CYP2C8 intercorrelation on the predicted interindividual variabilities of clearance and drug-drug interactions (DDIs) for repaglinide using physiologically based pharmacokinetic (PBPK) modelling. METHODS PBPK modelling and simulation were employed using Simcyp Simulator (v15.1). Virtual populations were generated assuming intercorrelations between hepatic CYP3A4-CYP2C8 abundances derived from observed values in 24 human livers. A repaglinide PBPK model was used to predict PK parameters in the presence and absence of gemfibrozil in virtual populations, and the results were compared with a clinical DDI study. RESULTS Coefficient of variation (CV) of oral clearance was 52.5% in the absence of intercorrelation between CYP3A4-CYP2C8 abundances, which increased to 54.2% when incorporating intercorrelation. In contrast, CV for predicted DDI (as measured by AUC ratio before and after inhibition) was reduced from 46.0% in the absence of intercorrelation between enzymes to 43.8% when incorporating intercorrelation: these CVs were associated with 5th/95th percentiles (2.48-11.29 vs. 2.49-9.69). The range of predicted DDI was larger in the absence of intercorrelation (1.55-77.06) than when incorporating intercorrelation (1.79-25.15), which was closer to clinical observations (2.6-12). CONCLUSIONS The present study demonstrates via a systematic investigation that population-based PBPK modelling incorporating intercorrelation led to more consistent estimation of extreme values than those observed in interindividual variabilities of clearance and DDI. As the intercorrelations more realistically reflect enzyme abundances, virtual population studies involving PBPK and DDI should avoid using Monte Carlo assignment of enzyme abundance.
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Affiliation(s)
- Kosuke Doki
- Centre for Applied Pharmacokinetic Research, Division of Pharmacy & Optometry, University of Manchester, Manchester, UK.,Department of Pharmaceutical Sciences, Faculty of Medicine, University of Tsukuba, Ibaraki, Japan
| | - Adam S Darwich
- Centre for Applied Pharmacokinetic Research, Division of Pharmacy & Optometry, University of Manchester, Manchester, UK
| | - Brahim Achour
- Centre for Applied Pharmacokinetic Research, Division of Pharmacy & Optometry, University of Manchester, Manchester, UK
| | - Aleksi Tornio
- Department of Clinical Pharmacology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Janne T Backman
- Department of Clinical Pharmacology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Amin Rostami-Hodjegan
- Centre for Applied Pharmacokinetic Research, Division of Pharmacy & Optometry, University of Manchester, Manchester, UK.,Simcyp Limited (A Certara Company), Sheffield, UK
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