Prediction of Human Distribution Volumes of Compounds in Various Elimination Phases Using Physiologically Based Pharmacokinetic Modeling and Experimental Pharmacokinetics in Animals

Abstract

Predicting the pharmacokinetics of compounds in humans is an important part of the drug development process. In this study, the plasma concentration profiles of 10 marketed compounds exhibiting two-phase elimination after intravenous administration in humans were evaluated in terms of distribution volumes just after intravenous administration (V 1 ), at steady state (V ss ), and in the elimination phase (V b ) using physiologically based pharmacokinetic (PBPK) modeling implemented in a commercially available simulator (Simcyp). When developing human PBPK models, the insight gained from prior animal PBPK models based on nonclinical data informed the optimization of the lipophilicity input of the compounds and the selection of the appropriate mechanistic tissue partition methods. The accuracy of V 1 , V ss , and V b values predicted that using human PBPK models developed in accordance with prior animal PBPK models was superior to using those predicted using conventional approaches, such as allometric scaling, especially for V 1 and V b . By conventional approaches, the V 1 and V b values of 4-5 of 10 compounds were predicted within a 3-fold error of observed values, whereas V ss values for their majority were predicted as such. PBPK models predicted V 1 , V ss , and V b values for almost all compounds within 3-fold errors, resulting in better predictions of plasma concentration profiles than allometric scaling. The distribution volumes predicted using human PBPK models based on prior animal PBPK modeling were more accurate than those predicted without reference to animal models. This study demonstrated that human PBPK models developed with consideration of animal PBPK models could accurately predict distribution volumes in various elimination phases.

Biopharmaceutic In Vitro In Vivo Extrapolation (IVIV_E) Informed Physiologically-Based Pharmacokinetic Model of Ritonavir Norvir Tablet Absorption in Humans Under Fasted and Fed State Conditions

“… a AAFE represents the absolute average fold error and calculated as reported by Shimizu et al b Statistical unpaired t test was applied to compare simulated fasted and predicted fed pharmacokinetic parameter and differences were found to be significant, p < 0.05 …”

“…Statistical Analysis. For statistical comparison of simulated and observed pharmacokinetic parameters, AAFE (average absolute fold error) was calculated as described by Shimizu et al 36 In addition, unpaired student t test was applied to assess the statistical differences between simulated fasted and predicted fed state pharmacokinetic parameters (C max , T max , and AUC 0-t ) obtained by simulation of Ng et al study. 32 Graph Pad Prism software version 8.2 was used for this analysis (GraphPad Software, Inc., San Diego, CA).…”

Physiologically Based Pharmacokinetic Modeling of Transdermal Selegiline and Its Metabolites for the Evaluation of Disposition Differences between Healthy and Special Populations

“…The predicted mean value is the average of the predicted means across the 10 virtual trials and the predicted SD is the standard deviation of the predicted mean across the 10 virtual trials. The overall predictability of the model was evaluated in terms of precision, i.e., AAFE (average absolute fold error), as described in Equation (3), and bias, i.e., AFE (Average fold error) as described in Equation (4) [ 62 , 63 ]. The mean ratio ± SD ratios for the pharmacokinetic parameters were compared between the predicted parameters in special populations to that of healthy subjects: …”

Silver Diamine Fluoride in Children Using Physiologically Based PK Modeling

“…Physiologically based pharmacokinetic (PBPK) modeling allows the absorption and disposition of a xenobiotic (e.g., SDF) to be predicted by incorporating anatomical, physiological, and enzymatic parameters of a model population (Rowland et al 2011; Jones et al 2013; Miller et al 2019; Shimizu et al 2019). In a PBPK model, each organ is viewed as a box that is interconnected by arterial and venous blood flow.…”