Saeed Alqahtani1, Amal Kaddoumi2. 1. Department of Basic Pharmaceutical Sciences, School of Pharmacy, University of Louisiana at Monroe, 1800 Bienville Dr., Monroe, LA, 71201, USA. 2. Department of Basic Pharmaceutical Sciences, School of Pharmacy, University of Louisiana at Monroe, 1800 Bienville Dr., Monroe, LA, 71201, USA. kaddoumi@ulm.edu.
Abstract
BACKGROUND: Genetic polymorphisms are major determinants of individual variability in a drug's efficacy and safety, which is one of the main challenges in current clinical practice and drug development. The aim of this work was to develop a physiologically based pharmacokinetic (PBPK)/pharmacodynamic (PD) model to predict changes in the PK parameters associated with genetic polymorphisms and the impact of these changes on drugs' PD effect. METHODS: We developed PBPK models for two central nervous system (CNS) medications, namely quetiapine and fluvoxamine that are substrates for polymorphic enzymes by incorporating the corresponding alterations in the enzyme activity and/or abundance. Then, the PBPK models were linked to PD models to predict the influence of these changes on the drugs' PD effect. RESULTS: Application of the PBPK models for prediction of phenotypic differences in the PKs compared favorably with reported clinical data. In addition, the PBPK/PD models were able to describe the relationship between the drugs' PD effect and their unbound fractions in the brain and predict changes in receptor/transporter occupancy percentages, obtained from positron emission tomography occupancy studies, associated with genetic variations. CONCLUSIONS: This work provides a simplified approach to predict the influence of genetic polymorphisms on the PK parameters and associated PD effect for CNS drugs. The impact of these polymorphisms on the drugs' PD requires further in vivo validation.
BACKGROUND: Genetic polymorphisms are major determinants of individual variability in a drug's efficacy and safety, which is one of the main challenges in current clinical practice and drug development. The aim of this work was to develop a physiologically based pharmacokinetic (PBPK)/pharmacodynamic (PD) model to predict changes in the PK parameters associated with genetic polymorphisms and the impact of these changes on drugs' PD effect. METHODS: We developed PBPK models for two central nervous system (CNS) medications, namely quetiapine and fluvoxamine that are substrates for polymorphic enzymes by incorporating the corresponding alterations in the enzyme activity and/or abundance. Then, the PBPK models were linked to PD models to predict the influence of these changes on the drugs' PD effect. RESULTS: Application of the PBPK models for prediction of phenotypic differences in the PKs compared favorably with reported clinical data. In addition, the PBPK/PD models were able to describe the relationship between the drugs' PD effect and their unbound fractions in the brain and predict changes in receptor/transporter occupancy percentages, obtained from positron emission tomography occupancy studies, associated with genetic variations. CONCLUSIONS: This work provides a simplified approach to predict the influence of genetic polymorphisms on the PK parameters and associated PD effect for CNS drugs. The impact of these polymorphisms on the drugs' PD requires further in vivo validation.
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