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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

2016; Elsevier BV; Volume: 96; Linguagem: Inglês

10.1016/j.ejps.2016.09.037

1879-0720

Adam S. Darwich, Alison Margolskee, Xavier Pépin, Leon Aarons, Aleksandra Galetin, Amin Rostami‐Hodjegan, Sara Carlert, Maria Hammarberg, Constanze Hilgendorf, Pernilla Johansson, Εva Karlsson, Donal B. Murphy, Christer Tannergren, Helena Thörn, Mohammed Yasin, Florent Mazuir, Olivier Nicolas, Sergej Ramusovic, Christine Xu, Shriram M. Pathak, Timo Korjamo, Johanna Laru, J. Malkki, Sari Pappinen, Johanna Tuunainen, Jennifer B. Dressman, Simone Hansmann, Edmund Kostewicz, Handan He, Tycho Heimbach, Fan Wu, Carolin Hoft, Yan Pang, Michael B. Bolger, Eva Huehn, Viera Lukáčová, James M. Mullin, Ke Szeto, Chester Costales, Jian Lin, Mark McAllister, Sweta Modi, Charles J. Rotter, Manthena V. S. Varma, Mei Wong, Amitava Mitra, Jan Bevernage, Jeike Biewenga, Achiel Van Peer, Richard Lloyd, Carole Shardlow, Peter Langguth, Irina Mishenzon, Mai Ánh Nguyễn, Jonathan Brown, Hans Lennernäs, Bertil Abrahamsson,

Pharmaceutical studies and practices

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 (Foral) was underpredicted for compounds with low permeability, suggesting improper estimates of intestinal surface area, colonic absorption and/or lack of intestinal transporter information. Foral 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. Foral 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.