IMI – Oral biopharmaceutics tools project – Evaluation of bottom-up PBPK prediction success part 3: Identifying gaps in system parameters by analysing In Silico performance across different compound classes

Abstract

Three Physiologically Based Pharmacokinetic software packages (GI-Sim, Simcyp® Simulator, and GastroPlus™) were evaluated as part of the Innovative Medicine Initiative Oral Biopharmaceutics Tools project (OrBiTo) during a blinded "bottom-up" anticipation of human pharmacokinetics. After data analysis of the predicted vs. measured pharmacokinetics parameters, it was found that oral bioavailability (F) was underpredicted for compounds with low permeability, suggesting improper estimates of intestinal surface area, colonic absorption and/or lack of intestinal transporter information. F was also underpredicted for acidic compounds, suggesting overestimation of impact of ionisation on permeation, lack of information on intestinal transporters, or underestimation of solubilisation of weak acids due to less than optimal intestinal model pH settings or underestimation of bile micelle contribution. F was overpredicted for weak bases, suggesting inadequate models for precipitation or lack of in vitro precipitation information to build informed models. Relative bioavailability was underpredicted for both high logP compounds as well as poorly water-soluble compounds, suggesting inadequate models for solubility/dissolution, underperforming bile enhancement models and/or lack of biorelevant solubility measurements. These results indicate areas for improvement in model software, modelling approaches, and generation of applicable input data. However, caution is required when interpreting the impact of drug-specific properties in this exercise, as the availability of input parameters was heterogeneous and highly variable, and the modellers generally used the data "as is" in this blinded bottom-up prediction approach.

Physiologically Based Pharmacokinetic Modeling to Evaluate Formulation Factors Influencing Bioequivalence of Metoprolol Extended‐Release Products

“…PBPK modeling and simulation approaches have gained popularity in recent years, particularly for biopharmaceutical analysis of oral drug absorption, predicting the impact of drug-drug interactions, selecting an optimal dose and clinical trial design for pediatric applications, and for characterizing the impact of organ impairment. [3][4][5][6] PBPK models typically consist of 3 distinct components: (1) a drug-specific component characterizing the physicochemical properties of the drug, (2) a system-specific component characterizing the functioning of the underlying biological system, in this case the gastrointestinal (GI) tract, and (3) a trial design component characterizing the impact of intrinsic (eg, demographics) and extrinsic factors (eg, drug-drug interactions) on the drug's pharmacokinetics (PK). As a result, PBPK models provide a platform for evaluating the combined impact of multiple factors, such as different formulations or differences in gastric pH, on a drug's PK and thus for in silico BE testing.…”

The BioGIT System: a Valuable In Vitro Tool to Assess the Impact of Dose and Formulation on Early Exposure to Low Solubility Drugs After Oral Administration

“…Relevant information could be very useful in physiologically based pharmacokinetic (PBPK) modeling. Based on a series of recent publications from the OrBiTo project (39)(40)(41), prospective PBPK modeling of plasma profiles, after oral administration, using a bottom-up approaches is limited by the reliability of estimation of clearance and volume of distribution, quality of intestinal permeability data, quality of solubility data, and characterization of intestinal metabolism or transporter involvement. The development of methodologies for implementing BioGIT data into PBPK models and methodologies for the evaluation of processes taking place in the middle/lower small intestine using the BioGIT system as a basis would greatly improve PBPK modeling approaches and facilitate the development of orally administered drug products.…”

Physiologically Based Pharmacokinetic Modelling for First-In-Human Predictions: An Updated Model Building Strategy Illustrated with Challenging Industry Case Studies

“…The proposed PBPK strategy herein for FIH pharmacokinetic predictions, based on a comprehensive review of recent literature and knowledge and best practices of experienced GastroPlus users, provides flow diagrams guiding through the layers of ADME complexities. Combining QSPR predictions with PBPK models from compound structure allows the assessment of risks based on compound type/properties [91], guides thinking and enables prioritisation of fit-for-purpose resources to support model development.…”