From preclinical to human – prediction of oral absorption and drug–drug interaction potential using physiologically based pharmacokinetic (PBPK) modeling approach in an industrial setting: a workflow by using case example

Abstract

Purpose: A case example is presented in which the physiologically based modeling approach has been used to model the absorption of a lipophilic BCS Class II compound predominantly metabolized by CYP3A4, and to assess the interplay of absorption related parameters with the drug-drug interaction (DDI) potential. Methods: The PBPK model was built in the rat using Gastroplus W to study the absorption characteristics of the compound. Subsequently relevant model parameters were used to predict the non-linear human PK observed during first-in-human study after optimizing the absorption model for colonic absorption, bile micelle solubilization and unbound fraction in gut enterocytes (fu gut ) using SIMCYP W simulator. The model fitted absorption parameters were then used to assess the drug-drug interaction (DDI) potential of the test compound when administered along with multiple doses of a potent CYP 3A4 inhibitor, ketoconazole. The impact of fu gut in the extent of DDI was assessed using parameter sensitivity analysis. Results and Conclusions: After optimizing the preclinical model and taking into consideration bile micelle solubilization and colonic absorption, the non-linear pharmacokinetics of the test compound was satisfactorily predicted in man. Sensitivity analysis performed with the absorption parameter fu gut indicated that it could be an important parameter in predicting oral absorption. In addition, DDI simulations using SIMCYP W suggest that C max and AUC ratios may also be sensitive to the fu gut input in the model. Since fu gut cannot be measured experimentally, sensitivity analysis may help in assessing the importance of fu gut in human PK and DDI prediction using SIMCYP W .

Evaluation of the Use of Static and Dynamic Models to Predict Drug-Drug Interaction and Its Associated Variability: Impact on Drug Discovery and Early Development

“…This study has identified a significant risk for overestimating DDI liability with Simcyp, largely attributable to uncertainty in CYP3A-mediated intestinal DDIs. This result is consistent with a recent report (Sinha et al, 2012). In the gut, CYP3A represents the principal drug-metabolizing P450 enzyme (Paine et al, 1997(Paine et al, , 2006.…”

A Perspective on the Prediction of Drug Pharmacokinetics and Disposition in Drug Research and Development

“…This is important since drug disposition and DDI mechanisms are generally complex, and models need to be calibrated with both in vitro parameters ("bottom-up") and observed in vivo PK or clinical DDI results ("top-down") Rostami-Hodjegan, 2012;Varma et al, 2012c;Gertz et al, 2013;Varma et al, 2013a;. Although PBPK models are useful to predict DDI risk prior to first-in-human studies, there is a significant level of uncertainty around the human PK and efficacious drug concentration in humans, since these parameters are predicted (Chen et al, 2012;Sinha et al, 2012;Zhao et al, 2012). Therefore, the utility of PBPK models are generally fully realized once human PK have been confirmed and human ADME data obtained to calibrate PBPK models, which could be used to inform decisions on allowable concomitant medications or exclusion criteria during phase II studies and beyond.…”

Dose Selection Based on Physiologically Based Pharmacokinetic (PBPK) Approaches

“…The application of PBPK modelling for human PK and hence dose prediction has been more widespread in recent years with a number of publications from the Pharmaceutical Industry (7)(8)(9)(10)(11)(12)(13)16,17). In drug discovery and development, PBPK models can be iteratively refined to incorporate additional information on drug disposition as it becomes available from preclinical and clinical studies.…”

“…The integration of physicochemical, in vitro and in vivo data into a PBPK framework to simulate PK profiles of small molecules in humans has become widespread within the Pharmaceutical Industry with numerous groups publishing on their experience with this approach (7)(8)(9)(10)(11)(12)(13)(16)(17)(18)(19). Although PBPK methods have shown utility in predicting human PK a few major challenges remain that need to be addressed to further increase the success of this approach.…”

“…Commercial PBPK packages have become available and strategies for the application of PBPK in the drug discovery setting have been published and recently evaluated (7,8). For this reason, the methodology has received an increase in attention in the last few years with several reports of its application for the prediction of animal and human PK for small molecules in discovery (7)(8)(9)(10)(11)(12)(13) and development (14)(15)(16)(17)(18)(19).…”