RESEARCH ARTICLE – Pharmacokinetics, Pharmacodynamics and Drug Transport and Metabolism A Systematic Evaluation of the Use of Physiologically Based Pharmacokinetic Modeling for Cross-Species Extrapolation CHRISTOPH THIEL, 1,2 SEBASTIAN SCHNECKENER, 1 MARKUS KRAUSS, 1,3 AHMED GHALLAB, 4,5 UTE HOFMANN, 6,7 TOBIAS KANACHER, 1 SEBASTIAN ZELLMER, 8 ROLF GEBHARDT, 8 JAN G. HENGSTLER, 4 LARS KUEPFER 1,2 1 Computational Systems Biology, Bayer Technology Services GmbH, Leverkusen, Germany 2 Institute of Applied Microbiology, RWTH Aachen, Aachen, Germany 3 Aachen Institute for Advanced Study in Computational Engineering Sciences, RWTH Aachen, Aachen, Germany 4 IfADo, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany 5 Department of Forensic Medicine and Veterinary Toxicology, Faculty of Veterinary Medicine, South Valley University, Qena, Egypt 6 Dr. Margarete Fischer-Bosch Institute for Clinical Pharmacology, Stuttgart, Germany 7 University of Tuebingen, Tuebingen, Germany 8 Institute of Biochemistry, Faculty of Medicine, University of Leipzig, Leipzig, Germany Received 21 July 2014; revised 22 September 2014; accepted 22 September 2014 Published online 12 November 2014 in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/jps.24214 ABSTRACT: Transfer of knowledge along the different phases of drug development is a fundamental process in pharmaceutical research. In particular, cross-species extrapolation between different laboratory animals and further on to first-in-human trials is challenging because of the uncertain comparability of physiological processes. Physiologically based pharmacokinetic (PBPK) modeling allows translation of mechanistic knowledge from one species to another by specifically considering physiological and biochemical differences in between. We here evaluated different knowledge-driven approaches for cross-species extrapolation by systematically incorporating specific model parameter domains of a target species into the PBPK model of a reference species. Altogether, 15 knowledge-driven approaches were applied to murine and human PBPK models of 10 exemplary drugs resulting in 300 different extrapolations. Statistical analysis of the quality of the different extrapolations revealed not only species-specific physiology as the key determinant in cross-species extrapolation but also identified a synergistic effect when considering both kinetic rate constants and gene expression profiles of relevant enzymes and transporters. Moreover, we show that considering species-specific physiology, plasma protein binding, enzyme and transport kinetics, as well as tissue-specific gene expression profiles in PBPK modeling increases accuracy of cross-species extrapolations and thus supports first-in-human trials based on prior preclinical knowledge. C  2014 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 104:191–206, 2015 Keywords: physiologically based pharmacokinetic (PBPK) modeling; Cross-species extrapolation; Systems pharmacology; First-in-man; Virtual liver; Pharmacokinetic/pharmacodynamic models; Bioinformatics; CYP enzymes; Computational biology; Simulations INTRODUCTION Development of novel drugs is a time-consuming and laborious process. In particular, the translation of preclinical knowledge generated in laboratory animals to first-in-human studies is a critical step with attrition rates above 30%. 1 In this regard, reliable cross-species extrapolations are needed to guarantee safety in human clinical trials. Current approaches for a cross- species extrapolation are often based on empirical allometric scaling techniques. 2 In this context, pharmacokinetic (PK) pa- rameters such as the clearance of administered drugs are cor- related to the body weight by using a power law function. This, however, requires observations of that parameter for a series of reference species. 3 In a similar approach, Dedrick plots may be used to predict the plasma drug concentration–time pro- file based on simple dose normalizations and species-invariant Correspondence to: Lars Kuepfer (Telephone: +49-2143022745; Fax: +49- 2143022745; E-mail: lars.kuepfer@bayer.com) Sebastian Zellmer’s present address is Department of Chemicals and Product Safety, German Federal Institute for Risk Assessment (BfR), Berlin, Germany. This article contains supplementary material available from the authors upon request or via the Internet at http://onlinelibrary.wiley.com/. Journal of Pharmaceutical Sciences, Vol. 104, 191–206 (2015) C  2014 Wiley Periodicals, Inc. and the American Pharmacists Association time methods. 4 In addition, allometric scaling laws have been developed by taking into account the brain weight or the max- imum life span potential in order to improve the predictive accuracy. 5 Such approaches have been used successfully for single compounds such as dolasetron. 6 However, limitations of allometric scaling techniques have also been shown. 7,8 Recent approaches incorporate physiologically based phar- macokinetic (PBPK) models to extrapolate between species. 9,10 PBPK models describe physiological processes governing the fate of a drug in the body. In PBPK models, relevant tissues and organs of an organism are represented as compartments which are connected by blood flow. Organs are further sub- divided into more detailed subcompartments such as blood cells, plasma, interstitium, and intracellular space. Notably, PBPK models are based on prior information regarding species- specific physiology (SP). 11 Mass transfer is described by using so called distribution models which are parameterized based on the physicochemical properties of a drug. 12–15 Because of the large degree of mechanistic information included in PBPK mod- els, they are particularly well suited for extrapolation to new treatment scenarios or specific subgroups of patients. Human PBPK models have been used before, for instance, for pediatric scaling, dose extrapolation, and prediction of adverse events in Thiel et al., JOURNAL OF PHARMACEUTICAL SCIENCES 104:191–206, 2015 191