A Mechanistic, Model-Based Approach to Safety Assessment in Clinical Development

Assessing the safety of pharmacotherapies is a primary goal of clinical trials in drug development. The low frequency of relevant side effects, however, often poses a significant challenge for risk assessment. Methodologies allowing robust extrapolation of safety statistics based on preclinical data and information from clinical trials with limited numbers of patients are hence needed to further improve safety and efficacy in the drug development process. Here, we present a generic systems pharmacology approach integrating prior physiological and pharmacological knowledge, preclinical data, and clinical trial results, which allows predicting adverse event rates related to drug exposure. Possible fields of application involve high‐risk populations, novel drug candidates, and different dosing scenarios. As an example, the approach is applied to simvastatin and pravastatin and the prediction of myopathy rates in a population with a genotype leading to a significantly increased myopathy risk.

[1]  K. Bischoff,et al.  Generalized solution to linear, to-compartment, open model for drug distribution. , 1970, Journal of theoretical biology.

[2]  K. Goa,et al.  Simvastatin. A review of its pharmacological properties and therapeutic potential in hypercholesterolaemia. , 1990, Drugs.

[3]  S. Singhvi,et al.  Disposition of pravastatin sodium, a tissue-selective HMG-CoA reductase inhibitor, in healthy subjects. , 1990, British journal of clinical pharmacology.

[4]  S. Singhvi,et al.  Biotransformation of pravastatin sodium in humans. , 1991, Drug metabolism and disposition: the biological fate of chemicals.

[5]  Y. Nagahama,et al.  Involvement of an inhibitory G-protein in the signal transduction pathway of maturation-inducing hormone (17 alpha,20 beta-dihydroxy-4-pregnen-3-one) action in rainbow trout (Oncorhynchus mykiss) oocytes. , 1994, Developmental biology.

[6]  R. Pardi,et al.  Simvastatin Modulates Cytokine-Mediated Endothelial Cell Adhesion Molecule Induction: Involvement of an Inhibitory G Protein1 , 2000, The Journal of Immunology.

[7]  S. Yusuf MRC/BHF Heart Protection Study of cholesterol lowering with simvastatin in 20536 high-risk individuals: a randomised placebo-controlled trial. Commentary , 2002 .

[8]  Patrick Poulin,et al.  Prediction of pharmacokinetics prior to in vivo studies. II. Generic physiologically based pharmacokinetic models of drug disposition. , 2002, Journal of pharmaceutical sciences.

[9]  Patrick Poulin,et al.  Prediction of pharmacokinetics prior to in vivo studies. 1. Mechanism-based prediction of volume of distribution. , 2002, Journal of pharmaceutical sciences.

[10]  A. Sánchez Navarro,et al.  Clinical pharmacokinetics of statins. , 2003, Methods and findings in experimental and clinical pharmacology.

[11]  Walter Schmitt,et al.  PK-Sim®: a physiologically based pharmacokinetic ‘whole-body’ model , 2003 .

[12]  Steffen Bauer,et al.  Evidence for Inverse Effects of OATP‐C (SLC21A6) *5 and *1b Haplotypes on Pravastatin Kinetics , 2004, Clinical pharmacology and therapeutics.

[13]  Michael D. Waters,et al.  Toxicogenomics and systems toxicology: aims and prospects , 2004, Nature Reviews Genetics.

[14]  Walter Schmitt,et al.  A physiological model for the estimation of the fraction dose absorbed in humans. , 2004, Journal of medicinal chemistry.

[15]  Kaoru Kobayashi,et al.  Functional characterization of SLCO1B1 (OATP-C) variants, SLCO1B1*5, SLCO1B1*15 and SLCO1B1*15+C1007G, by using transient expression systems of HeLa and HEK293 cells , 2005, Pharmacogenetics and genomics.

[16]  M. Rowland,et al.  Physiologically based pharmacokinetic modeling 1: predicting the tissue distribution of moderate-to-strong bases. , 2005, Journal of pharmaceutical sciences.

[17]  Jörg Lippert,et al.  From physicochemistry to absorption and distribution: predictive mechanistic modelling and computational tools , 2005, Expert opinion on drug metabolism & toxicology.

[18]  Ryosei Kawai,et al.  Physiologically based pharmacokinetic study on a cyclosporin derivative, SDZ IMM 125 , 1994, Journal of Pharmacokinetics and Biopharmaceutics.

[19]  M. Niemi,et al.  Influence of Drug Transporter Polymorphisms on Pravastatin Pharmacokinetics in Humans , 2007, Pharmaceutical Research.

[20]  J. Nedelman,et al.  Physiologically based pharmacokinetic modeling as a tool for drug development , 1995, Journal of pharmacokinetics and biopharmaceutics.

[21]  P. Neuvonen,et al.  Frequencies of single nucleotide polymorphisms and haplotypes of organic anion transporting polypeptide 1B1 SLCO1B1 gene in a Finnish population , 2006, European Journal of Clinical Pharmacology.

[22]  P. Neuvonen,et al.  SLCO1B1 polymorphism and sex affect the pharmacokinetics of pravastatin but not fluvastatin , 2006, Clinical pharmacology and therapeutics.

[23]  Mikko Niemi,et al.  SLCO1B1 polymorphism markedly affects the pharmacokinetics of simvastatin acid , 2006, Pharmacogenetics and genomics.

[24]  J. Stelling,et al.  Ensemble modeling for analysis of cell signaling dynamics , 2007, Nature Biotechnology.

[25]  Ivan Nestorov,et al.  Whole-body physiologically based pharmacokinetic models , 2007, Expert opinion on drug metabolism & toxicology.

[26]  Walter Schmitt,et al.  Development of a Physiology-Based Whole-Body Population Model for Assessing the Influence of Individual Variability on the Pharmacokinetics of Drugs , 2007, Journal of Pharmacokinetics and Pharmacodynamics.

[27]  George Loizou,et al.  Development of good modelling practice for physiologically based pharmacokinetic models for use in risk assessment: the first steps. , 2008, Regulatory toxicology and pharmacology : RTP.

[28]  S. Feasson,et al.  MRC/BHF heart protection study of cholesterol lowering with simvastatin in 20536 high-risk individuals : a randomised placebo-controlled trial. , 2008 .

[29]  R. Collins,et al.  SLCO1B1 variants and statin-induced myopathy--a genomewide study. , 2008, The New England journal of medicine.

[30]  Amy D. Kyle,et al.  Meeting Report: Moving Upstream—Evaluating Adverse Upstream End Points for Improved Risk Assessment and Decision-Making , 2008, Environmental health perspectives.

[31]  Ikumi Chisaki,et al.  Association between risk of myopathy and cholesterol-lowering effect: a comparison of all statins. , 2008, Life sciences.

[32]  Luis G Valerio,et al.  In silico toxicology for the pharmaceutical sciences. , 2009, Toxicology and applied pharmacology.

[33]  G. Ginsburg,et al.  The SLCO1B1*5 genetic variant is associated with statin-induced side effects. , 2009, Journal of the American College of Cardiology.

[34]  P. Moriarty,et al.  Does Simvastatin Cause More Myotoxicity Compared with Other Statins? , 2009, The Annals of pharmacotherapy.

[35]  S. Willmann,et al.  Risk to the Breast‐Fed Neonate From Codeine Treatment to the Mother: A Quantitative Mechanistic Modeling Study , 2009, Clinical pharmacology and therapeutics.

[36]  Charles C. Persinger,et al.  How to improve R&D productivity: the pharmaceutical industry's grand challenge , 2010, Nature Reviews Drug Discovery.

[37]  M. Niemi Transporter Pharmacogenetics and Statin Toxicity , 2010, Clinical pharmacology and therapeutics.

[38]  M. Jamei,et al.  PBPK modelling of inter-individual variability in the pharmacokinetics of environmental chemicals. , 2010, Toxicology.

[39]  Yiannis S. Chatzizisis,et al.  Risk Factors and Drug Interactions Predisposing to Statin-Induced Myopathy , 2010, Drug safety.

[40]  C. G. Mohan Impact of computational structure-based predictive toxicology in drug discovery. , 2011, Combinatorial chemistry & high throughput screening.

[41]  P. Neuvonen,et al.  Organic Anion Transporting Polypeptide 1B1: a Genetically Polymorphic Transporter of Major Importance for Hepatic Drug Uptake , 2011, Pharmacological Reviews.

[42]  J. Arrowsmith Trial watch: Phase II failures: 2008–2010 , 2011, Nature Reviews Drug Discovery.

[43]  S. Szeinbach,et al.  Market withdrawal of new molecular entities approved in the United States from 1980 to 2009 , 2011, Pharmacoepidemiology and drug safety.

[44]  Wolfgang Weiss,et al.  A Computational Systems Biology Software Platform for Multiscale Modeling and Simulation: Integrating Whole-Body Physiology, Disease Biology, and Molecular Reaction Networks , 2011, Front. Physio..

[45]  Yasushi Okuno,et al.  Statin-Associated Muscular and Renal Adverse Events: Data Mining of the Public Version of the FDA Adverse Event Reporting System , 2011, PloS one.

[46]  Harvey J Clewell,et al.  Quantitative in vitro to in vivo extrapolation of cell-based toxicity assay results , 2012, Critical reviews in toxicology.

[47]  Nina Jeliazkova,et al.  Web tools for predictive toxicology model building , 2012, Expert opinion on drug metabolism & toxicology.

[48]  Stefan Willmann,et al.  Pharmacogenomics of Codeine, Morphine, and Morphine-6-Glucuronide , 2012, Molecular Diagnosis & Therapy.

[49]  L. Kuepfer,et al.  Using Expression Data for Quantification of Active Processes in Physiologically Based Pharmacokinetic Modeling , 2012, Drug Metabolism and Disposition.

[50]  Stefan Willmann,et al.  Pharmacogenomics of codeine, morphine, and morphine-6-glucuronide: model-based analysis of the influence of CYP2D6 activity, UGT2B7 activity, renal impairment, and CYP3A4 inhibition. , 2012, Molecular diagnosis & therapy.

[51]  Y. Okuno,et al.  Data Mining of the Public Version of the FDA Adverse Event Reporting System , 2011, International journal of medical sciences.