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In Silico Approaches to Predict DDIs

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Enzyme- and Transporter-Based Drug-Drug Interactions

Abstract

This chapter will briefly describe in silico methodologies for the prediction of drug–drug interactions (DDIs) and highlight the broad application of computational tools to study DDIs. This chapter outlines the main methodologies currently applied including QSAR modeling, pharmacophore modeling, docking, and the combination of in silico and experimental approaches. There is an emphasis on cytochrome P450 and how in silico models are used in current drug discovery efforts to reduce the risk of DDIs. The discussion of the limitations associated with the various approaches as well as future aspects of DDI modeling and simulation can give researchers helpful guidance to this useful and growing area.

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Authors and Affiliations

  1. Department of Pharmacokinetics and Drug Metabolism, Pfizer Inc., Global Research & Development, La Jolla, CA, USA

    Chad L. Stoner & Michael R. Wester

  2. Department of Worldwide Medicinal Chemistry, Pfizer Inc., Global Research & Development, La Jolla, CA, USA

    Benjamin J. Burke

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  1. Chad L. Stoner
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  2. Michael R. Wester
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  3. Benjamin J. Burke
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Correspondence to Chad L. Stoner .

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Editors and Affiliations

  1. Leslie Dan Fac. Pharmacy, University of Toronto, College Street 144, Toronto, M5S 3M2, Canada

    K. Sandy Pang

  2. Bristol-Myers Squibb Company, Princeton, 08543, U.S.A.

    A. David Rodrigues

  3. AstraZeneca UK, Alderley Park, Macclesfield, Cheshire, SK10 4TF, United Kingdom

    Raimund M. Peter

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Stoner, C.L., Wester, M.R., Burke, B.J. (2010). In Silico Approaches to Predict DDIs. In: Pang , K., Rodrigues, A., Peter, R. (eds) Enzyme- and Transporter-Based Drug-Drug Interactions. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-0840-7_6

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