Applications of Physiologically-Based Pharmacokinetic (PBPK) Modeling in Discovery and Development of Cancer Chemotherapeutic Drugs

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Teerachat - Sae-heng
Kesara Na-Bangchang
Juntra Karbwang


Cancer drug discovery and development has been a particular research interest worldwide and has been rapidly increased over the last two decades.  Although several compounds were evaluated for potential anticancer activities, the number of anticancer drugs approved by U.S. FDA during 2006-2015 tended to decrease and only 5.1% of drug in Phase 1 clinical trials were approved.  Most of the failures occurred during clinical trials were due to inadequate supportive data of pharmacokinetic-pharmacodynamic relationship. Physiologically-based pharmaco-kinetic model (PBPK) is a computational model simulating human physiology that can predict the plasma/blood and the tissue concentrations of the drug of interest. Several PBPK models have been developed and applied to the various phases in order to reduce time and costs of the drug development. This review consists of three main parts. The first part is the classification and the description of model structure. The second part is the description of theories and mathematical model equations, i.e., perfusion-limited model, first-order kinetics, and Michaelis-Menten kinetics. Model parameters include the drug-specific parameters and the human physiological parameters. The examples of drug-specific parameters are the intrinsic clearance, tissue-to-plasma partition ratio, and the fraction of unbound drug. The examples of human physiological parameters are organ volume, and organ weight. The third part is the applications of PBPK model in non-clinical and clinical development phases. The major problem of PBPK model is the physiological differences between animals and humans which affect accuracy and precision of the prediction. This obstacle challenges the future development of the PBPK models.


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Hanahan D. Weinberg RA. Hallmarks of cancer. Cell. 2000;100:57-70

Stratton MR. Campbell PJ, Futreal PA. The cancer genome Nature. 2009;458:719-24

Qingyu Zhou et al. The Pharmacokinetic/Pharmacodynamics: Pipeline: Translating Anticancer Drug Pharmacology to the Clinic. The AAPS Journal. 2011;13(1):111-20

Collins I, Workman P. New approaches to molecular cancer therapeutics. Nat Chem Biol. 2006;2:689-700

Van Montfort R, Workman P. Structure-based design of molecular cancer therapeutics. Trends Biotechnol. 2009;27:315-28

Tothfalusi L, Speidl S, Endrenyi L. Exposure-response analysis reveals that clinically important toxicity difference can exit between bioequivalent carbamazepine tablets. Br J Clin Pharmacol. 2008;65:110-22

Kimko HC, Reele SS, Holford NH, Peck CC. Prediction of the outcome of a phase 3 clinical trial of an antischizophrenic agent (quetiapine fumarate) by simulation with a population pharmacokinetic and pharmacodynamics model. Clin Pharmacol Ther. 2000;68:568-77

Zhou Q, Guo P. Kruth GD, VIcini P, Wang X, Gallo JM. Predicting human tumor drug concentrations from a preclinical pharmacokinetic model of temozolomide brain disposition. Clin Cancer Res. 2007;13:4271-79

Wang S., Zhou Q, Gallo JM. Demonstration of the equivalent pharmacokinetic/pharmacodynamics dosing strategy in a multiple dose study of gefitinib. Mol Cancer Ther. 2009;8:1438-47

Gibaldi M, Perrier D. Pharmacokinetics. 2nd ed. New York: Marcel Dekker; 1982

Michael Block. Physiologically based pharmacokinetic and pharmacodynamics modeling in cancer drug development: status, potential and gaps. Expert Opin. Drug Metab. Toxicol. 2015;11(5):743-56

Sabine Pilari, Wilhelm Huisinga. Lumping of physiologically-based pharmacokinetic models and a mechanistic derivation of classical compartment models. J Pharmacokinet Pharmacodyn. 2010;37:365-405

Krisjansen PE, Brown TJ, Shipley LA, Jain RK. Intratumor pharmacokinetics, flow resistance, and metabolism during gemcitabine infusion in ex vivo perfused human small cell lung cancer. Clin Cancer Res. 1996;2:359-67

Heldin CH, Rubin K, Pietras K, Ostman A. High interstitial fluid pressure-an obstacle in cancer therapy. Nat Rev Cancer. 2004;4:806-13

Ruenraoengsak P, Cook JM, Florence AT. Nanosystem drug targeting: facing up to complex realitites. J Control Release. 2010;141:265-76

Laplanche R, Meno-Tetang GM, Kawai R. Physiologically based pharmacokinetic (PBPK) modeling of everolimus (RAD001) in rats involving non-linear tissue uptake. J Pharmacokinet Pharmacodyn. 2007;34:373-400

Zager MG, Schlosser PM, Tran HT. A delayed nonlinear PBPK model for genistein dosimetry in rats. Bull Math Biol. 2007;69(1):93-117

HM Jones, K Rowland-Yeo. Basic concepts in physiologically based pharmacokinetic modeling in drug discovery and development. Pharmacometric & systems Pharmacology. 2013;2:63

Wang S, Guo P, Wang X, Zhou Q, Gallo JM. Preclinical pharmacokinetic/pharmacodynamics models of gefitinib and the design of equivalent dosing regimens in EGFR wild-type and mutant tumor models. Mol Cancer Ther. 2008;7:407-17

Luo FR, Yang Z, Dong H, Camuso A, McGlinchey K, Fager K, et al. Prediction of active drug plasma concentrations achieved in cancer patients by pharmacodynamics biomarkers identified from the geo human colon carcinoma xenograft model. Clin Cancer Res. 2005;11:5558-65

Sung JH, Dhiman A, Shuler ML. A combined pharmacokinetic-pharmacodynamic (PK-PD) model for tumor growth in the rat with UFT administration. J Pharm Sci. 2009;98:1885-904

Koch G. Walz A, Lahu G, Schropp J. Modeling of tumor growth and anticancer effects of combination therapy. J Pharmacokinet Pharmacodyn. 2009;36:179-97

Dagnino G, Donelli MG, Colombo T, Bertello C, Pacciarini MA, Martini A. Pharmacodynamic model describing the growth of a mammary carcinoma in the mouse under the influence of Adriamycin treatment. Oncology. 1981;38:53-8

Bueno L, de Alwis DP, Pitou C, Yingling J, Lahn M, Glatt S, et al. Semi-mechanistic modeling of the tumor growth inhibitory effects of LY2157299. A new type I receptor TGF-beta kinase antagonist in mice. Eur J Cancer. 2008;44:142-50

Tham LS, Wang L, SOo RA, Lee SC, Lee HS, Young WP, et al. A pharmacodynamics model for the time course of tumor shrinkage by gemcitabine plus carboplatin in non-small cell lung cancer patients. Clin Cancer Res. 2008;14:4213-8

Fetteryl GJ, Grasela TH, Sherman JW, Dul JL, Grahn A. Lecomte D, et al,. Pharmacokinetic/pharmacodynamics modeling and simulation of neutropenia during phase I development of liposome-entrapped paclitaxedl. Clin Cancer Res. 2008;14:5856-63

Salphati L, Wong H, Belvin M, Bradford D, Edgar KA. Prior WW, et al. Pharmacokinetic-pharmacodynamic modeling of tumor growth inhibition and biomarker modulation by the novel PI3K inhibitor 2-(1H-indazol-4-yl)-6-(4-methyanesulfonyl-piperazin-1-ylmethyl)-4-morpholin-4-yl-thienol(3,2-d)pyrimidine (GDC-0941). Drug Metlab Dispos. 2010;38:1436-42

Hannah M. Jones, Neil Parrott, Karin Jorga, Thierry Lave. A novel strategy for physiologically based prediction of human pharmacokinetics. Clin. Pharmacokinet. 2006;45(5):511-42

Tao Zhang, Yanyan Li, Pen Zou, et al. Physiologically based pharmacokinetic and pharmacodynamics modeling of an antagonist (SM-406/AT-406) of multiple inhibitor of apoptosis proteins (IAPS) in a mouse xenograft model of human breast cancer. Biopharm. Drug Disops. 2013;34:328-59

Susan F. Hudachek, Daneil L. Gustafson. Physiologically based pharmacokinetic model of lapatinib developed in mice and scaled to humans. J Pharmacokinet Pharmacodyn. 2013;40:157-76

A. Chen, M.L. Yarmush, T. Maguire. Physiologically based pharmacokinetic models: integration of in silico approaches with micro cell culture analouges. Curr Drug Metab. 2012;13(6):863-80

Maria M. Posada, James A. Bacon, Karen B. Schneck, Rommel G. Tirona, Richard B. Kim, J. William Higgins, Y. Anne Pak, et al. Prediction of renal transporter mediated drug-drug interactions for pemetrexed using physiologically based pharmacokinetic modeling. Drug Metab Dispos. 2015;43:325-34

Yuko Tsukamoto, Yukio Kato, Masako Ura, Ikuo Horii, Tohru Ishikawa, Hideo Ishitsuka, Yuichi Sugiyama. Investigation of 5-FU disposition after oral administration of capecitabine, a triple-prodrug of 5-FU, using a physiologically based pharmacokinetic model in a human cancer xenograft model: comparison of the simulated 5-FU exposure in the tumor tissue between human and xenograft model. Biopharm. Drug Dispos. 2001;22:1-14

Dipti K. Pawaskar, Robert M. Straubinger, Gerald J. Fetterly, Bonnie H. Hylander, Elizabeth A. Repasky, Wen W. Ma, William J. Jusko. Physiologically based pharmacokinetic models for everolimus and sorafenib in mice. Cancer Chemother Pharmacol. 2013;71:1219-29

Lubna Abuqayyas, Joseph P. Balthasar. Application of PBPK modeling to predict monoclonal antibody disposition in plasma and tissues in mouse models of human colorectal cancer. J Pharmacokinet Pharmacodyn. 2012;39:683-710

Susan F. Hudachek, Daniel L. Gustafson. Incorporation of ABCB1-mediated transport into a physiologically based pharmacokinetic model of docetaxel in mice. J Pharmacokinet Pharmacodyn. 2013;40:437-49

Erica L. Bradshaw-Pierce, S. Gail Eckhardt, Daniel L. Gustafson. A physiologically based pharmacokinetic model of docetaxel disposition: from mouse to man. Clin Cancer Res. 2007;13(9):2768-76

Zhe-Yi Hu, Jingtao Lu, Yuansheng Zhao. A physiologically based pharmacokinetic model of alvespimycin in mice and extrapolation to rats and humans. British Journal of Pharmacology. 2014;171:2778-89

Youwei Bi, Jiexin Deng, Daryl J. Murry, Guohua An. A whole-body physiologically based pharmacokinetic model of gefitinib in mice and scale-up to humans. The AAPs Journal. 2015:11;1-10

Xue-Feng Lu, Kaishun Bi, Xiaohui Chen. Physiologically based pharmacokinetic model of docetaxel and interspecies scaling: comparison of simple injection with folate receptor-targeting amphiphilic copolymer-modified liposomes. Xenobiotica. 2016

Gisela Kersting, Stefan Willmann, Gudrun Wurthwein, Jorg Lippert, Joachim Boos, Georg Hempel. Physiologically based pharmacokinetic modelling of high-and-low-dose etoposide: from adults to children. Cancer Chemother Pharmacol. 2012;69:397-405

Binfeng Xia, Tycho Heimbach, Tsu-han Lin, Handan He, Yanfen Wang, Eugene Tan. Novel physiologically based pharmacokinetic modeling of patupilone for human pharmacokinetic predictions. Cancer Chemother Pharmacol. 2012;69:1567-1582

Kayode Ogungbenro, Leo Aarons. Physiologically based pharmacokinetic modelling of methotrexate and 6-mercaptopurine in adults and children .Part 1: methotrexate. J Pharmacokinet Pharmacodyn 2014;41:159-171

Kayode Ogungbenro, Leo Aarons. Physiologically based pharmacokinetic modelling of methotrexate and 6-mercaptopurine in adults and children. Part 2: 6-mercaptopurine and its interaction with methotrexate. J Pharmacokinet Pharmacodyn. 2014;41:173-185

Hoai-Thu Thai, Florent Mazuir, Sylvaine Cartot-Cotton, Christine Veyrat-Follet. Optimizing pharmacokinetic bridging studies in paediatric oncology using physiologically based pharmacokinetic modelling: application to docetaxel. Brithis Journal of Clinical Pharmacology. 2015;80(3):534-37

Christopher Walsh, Jennifer J. Bonner, Trevor N. Johnson, Sibylle Neuhoff, Essam A. Ghazaly, John G. Gribben, Alan V. Boddy, Gareth J. Veal. Development of a physiologically based pharmacokinetic model of actinomycin D in children with cancer. Brithish Journal of Clinical Pharmacology 2016;81:989-998