Evaluating reversible inhibitory drug–drug interactions: enzyme kinetics, and <i>in vitro</i>-to-<i>in vivo</i> scaling models

Analysis based on the equation shows that, for inhibitors with the same inhibition constant (Ki), competitive inhibitors will pose a higher potential for DDIs compared to non-competitive inhibitors, while complete inhibitors will result in a higher potential for DDI than partial inhibitors.

Authors

Philip W Melchert (ORCID: https://orcid.org/0000-0001-8276-6621)
John S. Markowitz (ORCID: https://orcid.org/0000-0002-9830-5392)
Qingchen Zhang (ORCID: https://orcid.org/0009-0006-8919-7429)
David J. Greenblatt

Institutions

Tufts University (US)
University of Florida (US)

Publication Details

Journal: Journal of Pharmacy and Pharmacology
Published: 2025-06-20
DOI: https://doi.org/10.1093/jpp/rgaf029
Citations: 3
Primary Topic: Computational Drug Discovery Methods
Type: article
Field-Weighted Citation Impact: 4.51

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article

Evaluating reversible inhibitory drug–drug interactions: enzyme kinetics, and in vitro-to-in vivo scaling models

Philip W Melchert, John S. Markowitz, Qingchen Zhang, David J. Greenblatt

Jun 20, 2025

3 citations

Journal of Pharmacy and Pharmacology

Computational Drug Discovery Methods

4.51

article

Evaluating reversible inhibitory drug–drug interactions: enzyme kinetics, and in vitro-to-in vivo scaling models

Philip W Melchert, John S. Markowitz, Qingchen Zhang, David J. Greenblatt

June 20, 2025article en

3 citations

Abstract

Analysis based on the equation shows that, for inhibitors with the same inhibition constant (Ki), competitive inhibitors will pose a higher potential for DDIs compared to non-competitive inhibitors, while complete inhibitors will result in a higher potential for DDI than partial inhibitors.

Journal of Pharmacy and PharmacologyVol. 77(8)

Tufts University (US), University of Florida (US)

Good health and well-being

Openalex Percentile: Top 5%

Computational Drug Discovery Methods

4.51

DOI Source OpenAlex

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