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

被引：38

作者：

Darwich, Adam S. ^{[1
]}

Margolskee, Alison ^{[1
]}

Pepin, Xavier ^{[2
,3
]}

Aarons, Leon ^{[1
]}

Galetin, Aleksandra ^{[1
]}

Rostami-Hodjegan, Amin ^{[1
,4
]}

Carlert, Sara ^{[5
]}

Hammarberg, Maria ^{[5
]}

Hilgendorf, Constanze ^{[5
]}

Johansson, Pernilla ^{[5
]}

Karlsson, Eva ^{[5
]}

Murphy, Donal ^{[2
]}

Tannergren, Christer ^{[5
]}

Thorn, Helena ^{[5
]}

Yasin, Mohammed ^{[2
]}

Mazuir, Florent ^{[3
]}

Nicolas, Olivier ^{[3
]}

Ramusovic, Sergej ^{[6
]}

Xu, Christine ^{[7
]}

Pathak, Shriram M. ^{[4
]}

Korjamo, Timo ^{[8
]}

Laru, Johanna ^{[2
,8
]}

Malkki, Jussi ^{[8
]}

Pappinen, Sari ^{[8
]}

Tuunainen, Johanna ^{[8
]}

Dressman, Jennifer ^{[9
]}

Hansmann, Simone ^{[9
]}

Kostewicz, Edmund ^{[9
]}

He, Handan ^{[10
]}

Heimbach, Tycho ^{[10
]}

Wu, Fan ^{[10
]}

Hoft, Carolin ^{[11
]}

Pang, Yan ^{[11
]}

Bolger, Michael B. ^{[12
]}

Huehn, Eva ^{[12
]}

Lukacova, Viera ^{[12
]}

Mullin, James M. ^{[12
]}

Szeto, Ke X. ^{[12
]}

Costales, Chester ^{[13
]}

Lin, Jian ^{[13
]}

McAllister, Mark ^{[14
]}

Modi, Sweta ^{[13
]}

Rotter, Charles ^{[13
]}

Varma, Manthena ^{[14
]}

Wong, Mei ^{[14
]}

Mitra, Amitava ^{[15
]}

Bevernage, Jan ^{[16
]}

Biewenga, Jeike ^{[16
]}

Van Peer, Achiel ^{[16
]}

Lloyd, Richard ^{[17
]}

机构：

[1] Univ Manchester, Manchester M13 9PL, Lancs, England

[2] AstraZeneca, London, England

[3] Sanofi, Paris, France

[4] Simcyp Ltd, Sheffield, S Yorkshire, England

[5] AstraZeneca, Gothenburg, Sweden

[6] Sanofi, Frankfurt, Germany

[7] Sanofi, Bridgewater, NJ USA

[8] Orion Pharma, Espoo, Finland

[9] Goethe Univ Frankfurt Am Main, Frankfurt, Germany

[10] Novartis, New York, NY USA

[11] AbbVie, Wiesbaden, Germany

[12] Simulat Plus Inc, Lancaster, CA USA

[13] Pfizer, New York, NY USA

[14] Pfizer, Tadworth, Middx, England

[15] Merck Sharp & Dohme Ltd, Hoddesdon, Herts, England

[16] Janssen, Beerse, Belgium

[17] GlaxoSmithKline, Brentford, Middx, England

[18] Johannes Gutenberg Univ Mainz, Mainz, Germany

[19] Bristol Myers Squibb, Uxbridge, Middx, England

[20] Uppsala Univ, Uppsala, Sweden

来源：

EUROPEAN JOURNAL OF PHARMACEUTICAL SCIENCES | 2017年 / 96卷

基金：

英国医学研究理事会;

关键词：

Physiologically-based pharmacokinetics (PBPK); modelling and simulation (M&S); absorption; oral bioavailability (F-oral); biopharmaceutics; drug database; TISSUE DISTRIBUTION; DRUGS; SOLUBILITY; MODELS; VOLUME; BASES;

D O I：

10.1016/j.ejps.2016.09.037

中图分类号：

R9 [药学];

学科分类号：

1007 ;

摘要：

Three Physiologically Based Pharmacokinetic software packages (GI-Sim, Simcyp (R) Simulator, and GastroPlus (TM)) 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-oral) was underpredicted for compounds with low permeability, suggesting improper estimates of intestinal surface area, colonic absorption and/or lack of intestinal transporter information. Foralwas 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-oral 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. (C) 2016 Elsevier B.V. All rights reserved.

引用

页码：626 / 642

页数：17

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