Abstract
The physiologically based pharmacokinetic (PBPK) models allow for predictive assessment of variability in population of interest. One of the future application of PBPK modeling is in the field of precision dosing and personalized medicine. The aim of the study was to develop PBPK model for amitriptyline given orally, predict the variability of cardiac concentrations of amitriptyline and its main metabolite—nortriptyline in populations as well as individuals, and simulate the influence of those xenobiotics in therapeutic and supratherapeutic concentrations on human electrophysiology. The cardiac effect with regard to QT and RR interval lengths was assessed. The Emax model to describe the relationship between amitriptyline concentration and heart rate (RR) length was proposed. The developed PBPK model was used to mimic 29 clinical trials and 19 cases of amitriptyline intoxication. Three clinical trials and 18 cases were simulated with the use of PBPK-QSTS approach, confirming lack of cardiotoxic effect of amitriptyline in therapeutic doses and the increase in heart rate along with potential for arrhythmia development in case of amitriptyline overdose. The results of our study support the validity and feasibility of the PBPK-QSTS modeling development for personalized medicine.
Highlights
The physiologically based pharmacokinetic (PBPK) modeling approach has been used for various applications such as risk assessment for environmental health, academic research or drug development purposes [1, 2], in short, the safety and efficacy assessment
The physiologically based pharmacokinetic (PBPK) models allow for predictive assessment of variability in population of interest
The future application of PBPK modeling that has already Journal of Pharmacokinetics and Pharmacodynamics (2018) 45:663–677 begun to be explored is in the field of precision dosing and personalized medicine
Summary
The physiologically based pharmacokinetic (PBPK) modeling approach has been used for various applications such as risk assessment for environmental health, academic research or drug development purposes [1, 2], in short, the safety and efficacy assessment. If properly parameterized, mechanistic PBPK models can predict inter-individual variability in drug’s PK profiles resulting from differences in human anatomy and physiology. A profile of certain individual can be differentiated from a specific virtual population according to age, sex, and other specific physiological features [4, 5]. Such in silico models matching real patients, so called ‘virtual twins’, were proposed by Polasek et al [6] in order to predict individual olanzapine exposures and adjust the therapeutic dose. Patel et al [8] simulated ‘virtual twins’, taking into account real patients’ physiology to mimic pharmacodynamics (PD), namely electrophysiological effect of citalopram taken, both in therapeutic and supratherapeutic doses
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