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Research ArticleSpecial Section on Prediction of Human Pharmacokinetic Parameters from In Vitro Systems

Impact of Physiologically Based Pharmacokinetic Modeling and Simulation in Drug Development

Carole E. Shardlow, Grant T. Generaux, Aarti H. Patel, Guoying Tai, Thuy Tran and Jackie C. Bloomer
Drug Metabolism and Disposition December 2013, 41 (12) 1994-2003; DOI: https://doi.org/10.1124/dmd.113.052803
Carole E. Shardlow
Department of Drug Metabolism and Pharmacokinetics, GlaxoSmithKline, Ware, Hertfordshire, United Kingdom (C.E.S., A.H.P., J.C.B.), King of Prussia, Pennsylvania (T.T., G.T.), and Research Triangle Park, North Carolina (G.T.G.)
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Grant T. Generaux
Department of Drug Metabolism and Pharmacokinetics, GlaxoSmithKline, Ware, Hertfordshire, United Kingdom (C.E.S., A.H.P., J.C.B.), King of Prussia, Pennsylvania (T.T., G.T.), and Research Triangle Park, North Carolina (G.T.G.)
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Aarti H. Patel
Department of Drug Metabolism and Pharmacokinetics, GlaxoSmithKline, Ware, Hertfordshire, United Kingdom (C.E.S., A.H.P., J.C.B.), King of Prussia, Pennsylvania (T.T., G.T.), and Research Triangle Park, North Carolina (G.T.G.)
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Guoying Tai
Department of Drug Metabolism and Pharmacokinetics, GlaxoSmithKline, Ware, Hertfordshire, United Kingdom (C.E.S., A.H.P., J.C.B.), King of Prussia, Pennsylvania (T.T., G.T.), and Research Triangle Park, North Carolina (G.T.G.)
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Thuy Tran
Department of Drug Metabolism and Pharmacokinetics, GlaxoSmithKline, Ware, Hertfordshire, United Kingdom (C.E.S., A.H.P., J.C.B.), King of Prussia, Pennsylvania (T.T., G.T.), and Research Triangle Park, North Carolina (G.T.G.)
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Jackie C. Bloomer
Department of Drug Metabolism and Pharmacokinetics, GlaxoSmithKline, Ware, Hertfordshire, United Kingdom (C.E.S., A.H.P., J.C.B.), King of Prussia, Pennsylvania (T.T., G.T.), and Research Triangle Park, North Carolina (G.T.G.)
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Abstract

Physiologically based pharmacokinetic modeling and simulation can be used to predict the pharmacokinetics of drugs in human populations and to explore the effects of varying physiologic parameters that result from aging, ethnicity, or disease. In addition, the effects of concomitant medications on drug exposure can be investigated; prediction of the magnitude of drug interactions can impact regulatory communications or internal decision-making regarding the requirement for a clinical drug interaction study. Modeling and simulation can also help to inform the design and timings of clinical drug interaction studies, resulting in more efficient use of limited resources and improved planning in addition to promoting mechanistic understanding of observed drug interactions. These approaches have been used in GlaxoSmithKline from drug discovery to registration and have been applied to 41 drugs from a number of therapeutic areas. This report highlights the variety of questions that can be addressed by prospective or retrospective application of modeling and simulation and the impact this can have on clinical drug development (from candidate selection through clinical development to regulatory submissions).

Footnotes

    • Received May 15, 2013.
    • Accepted September 5, 2013.
  • dx.doi.org/10.1124/dmd.113.052803.

  • Copyright © 2013 by The American Society for Pharmacology and Experimental Therapeutics
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Drug Metabolism and Disposition: 41 (12)
Drug Metabolism and Disposition
Vol. 41, Issue 12
1 Dec 2013
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Research ArticleSpecial Section on Prediction of Human Pharmacokinetic Parameters from In Vitro Systems

Impact of PBPK Modeling and Simulation in Drug Development

Carole E. Shardlow, Grant T. Generaux, Aarti H. Patel, Guoying Tai, Thuy Tran and Jackie C. Bloomer
Drug Metabolism and Disposition December 1, 2013, 41 (12) 1994-2003; DOI: https://doi.org/10.1124/dmd.113.052803

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Research ArticleSpecial Section on Prediction of Human Pharmacokinetic Parameters from In Vitro Systems

Impact of PBPK Modeling and Simulation in Drug Development

Carole E. Shardlow, Grant T. Generaux, Aarti H. Patel, Guoying Tai, Thuy Tran and Jackie C. Bloomer
Drug Metabolism and Disposition December 1, 2013, 41 (12) 1994-2003; DOI: https://doi.org/10.1124/dmd.113.052803
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