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Research ArticleArticle

A Pharmacokinetic Modeling Approach to Predict the Contribution of Active Metabolites to Human Efficacious Dose

Iain J. Martin, Susan E. Hill, James A. Baker, Sujal V. Deshmukh and Erin F. Mulrooney
Drug Metabolism and Disposition August 2016, 44 (8) 1435-1440; DOI: https://doi.org/10.1124/dmd.116.070391
Iain J. Martin
Pharmacokinetics, Pharmacodynamics, and Drug Metabolism, Merck Research Laboratories, Boston, Massachusetts
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Susan E. Hill
Pharmacokinetics, Pharmacodynamics, and Drug Metabolism, Merck Research Laboratories, Boston, Massachusetts
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James A. Baker
Pharmacokinetics, Pharmacodynamics, and Drug Metabolism, Merck Research Laboratories, Boston, Massachusetts
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Sujal V. Deshmukh
Pharmacokinetics, Pharmacodynamics, and Drug Metabolism, Merck Research Laboratories, Boston, Massachusetts
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Erin F. Mulrooney
Pharmacokinetics, Pharmacodynamics, and Drug Metabolism, Merck Research Laboratories, Boston, Massachusetts
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Abstract

A preclinical drug candidate, MRK-1 (Merck candidate drug parent compound), was found to elicit tumor regression in a mouse xenograft model. Analysis of samples from these studies revealed significant levels of two circulating metabolites, whose identities were confirmed by comparison with authentic standards using liquid chromatography-tandem mass spectrometry. These metabolites were found to have an in vitro potency similar to that of MRK-1 against the pharmacological target and were therefore thought to contribute to the observed efficacy. To predict this contribution in humans, a pharmacokinetic (PK) modeling approach was developed. At the mouse efficacious dose, the areas under the plasma concentration time curves (AUCs) of the active metabolites were normalized by their in vitro potency compared with MRK-1. These normalized metabolite AUCs were added to that of MRK-1 to yield a composite efficacious unbound AUC, expressed as “parent drug equivalents,” which was used as the target AUC for predictions of the human efficacious dose. In vitro and preclinical PK studies afforded predictions of the PK of MRK-1 and the two active metabolites in human as well as the relative pathway flux to each metabolite. These were used to construct a PK model (Berkeley Madonna, version 8.3.18; Berkeley Madonna Inc., University of California, Berkeley, CA) and to predict the human dose required to achieve the target parent equivalent exposure. These predictions were used to inform on the feasibility of the human dose in terms of size, frequency, formulation, and likely safety margins, as well as to aid in the design of preclinical safety studies.

Footnotes

    • Received March 7, 2016.
    • Accepted June 2, 2016.
  • ↵1 Current affiliation: Metabolism and Pharmacokinetics, Novartis Institutes for Biomedical Research, Cambridge, Massachusetts.

  • dx.doi.org/10.1124/dmd.116.070391.

  • ↵Embedded ImageThis article has supplemental material available at dmd.aspetjournals.org.

  • Copyright © 2016 by The American Society for Pharmacology and Experimental Therapeutics
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Drug Metabolism and Disposition: 44 (8)
Drug Metabolism and Disposition
Vol. 44, Issue 8
1 Aug 2016
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Research ArticleArticle

PK Modeling of Active Metabolites

Iain J. Martin, Susan E. Hill, James A. Baker, Sujal V. Deshmukh and Erin F. Mulrooney
Drug Metabolism and Disposition August 1, 2016, 44 (8) 1435-1440; DOI: https://doi.org/10.1124/dmd.116.070391

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Research ArticleArticle

PK Modeling of Active Metabolites

Iain J. Martin, Susan E. Hill, James A. Baker, Sujal V. Deshmukh and Erin F. Mulrooney
Drug Metabolism and Disposition August 1, 2016, 44 (8) 1435-1440; DOI: https://doi.org/10.1124/dmd.116.070391
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