Di Paolo V, Ferrari FM, Poggesi I, Dacasto M, Capolongo F, Quintieri L. A genetic algorithm-based approach for quantitative prediction of drug-drug interactions caused by cytochrome P450 3A inhibitors and inducers in dogs and cats.
Chem Biol Interact 2025;
416:111537. [PMID:
40311857 DOI:
10.1016/j.cbi.2025.111537]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2025] [Revised: 04/16/2025] [Accepted: 04/29/2025] [Indexed: 05/03/2025]
Abstract
A genetic algorithm (GA)-based framework was developed to predict drug-drug interactions (DDIs) caused by cytochrome P450 3A (CYP3A) inhibition or induction in dogs and cats. Area under the plasma concentration-time curve (AUC) ratios, obtained from published in vivo DDI studies, were used to calculate the following parameters: (a) the contribution ratio (CR), which represents the fraction of the dose of the victim drug metabolized via CYP3A, and (b) the inhibitory potency (inhibition ratio; IR) or inducing potency (IC) of the perpetrator drug. AUC ratios of 3 substrates, 4 inhibitors and 1 inducer of CYP3A in cats, and the AUC ratios of 10 substrates, 12 inhibitors and 3 inducers of CYP3A in dogs were successfully predicted and validated by the developed methodology within 50-200 % of observed values. This approach could represent a useful resource to predict the extent of DDIs in clinical scenarios requiring the simultaneous administration of a CYP3A substrate drug with a CYP3A perpetrator.
Collapse