Article

Predicting rifampicin interaction magnitude from strong CYP3A inhibitor interactions in clinical reports published from 2020 through 2025

Authors

  • Ahad Saqer Alharthi
    • Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia
  • Ahmed Alghamdi
    • King Abdulaziz University, Jeddah, Saudi Arabia
  • Aisha Hadi Alqahtani
    • King Khalid University, Saudi Arabia
  • Albatoul Mohammed Alsheikh
    • King Khalid University, Saudi Arabia

Multidisciplinary Healthcare Journal Vol. 1 No. 6 (2025) Published

Open access CC BY 4.0
Article language: English
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Alharthi, A. S., Alghamdi, A., Alqahtani, A. H., & Alsheikh, A. M. (2025). Predicting rifampicin interaction magnitude from strong CYP3A inhibitor interactions in clinical reports published from 2020 through 2025. Multidisciplinary Healthcare Journal, 1(6). https://doi.org/10.68608/s74xx034
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Abstract

Background: Dedicated clinical interaction studies with the index inducer rifampicin are costly and are often completed late in development. Whether the magnitude of the rifampicin interaction can be anticipated from a strong cytochrome P450 3A (CYP3A) inhibitor study already performed for the same victim drug has not been quantified in the contemporary clinical literature.

Methods: We retrospectively restricted a frozen PubMed search retrieved on 6 November 2026 to reports published by 31 December 2025. Paired inhibitor and rifampicin AUC ratios were available for 48 drugs, of which 44 formed the primary CYP3A analysis. An identifiable one-parameter empirical static model was fitted on the log scale, with 2,000 drug-level bootstrap resamples and leave-one-drug-out cross-validation against log–log regression and a no-covariate predictor. This date-restricted reanalysis does not establish completeness of the underlying single-database search.

Results: The fitted effective parameter K was 9.30 (95% bootstrap CI 7.41–11.65). Under an imposed complete-inhibition assumption, this corresponds to L = 10.30; inhibition completeness and induction strength cannot be estimated separately from these paired ratios. In-sample geometric mean fold error was 1.59 (95% CI 1.41–1.77). Leave-one-drug-out errors were 1.61 for the static model, 1.56 for log–log regression and 1.91 for the no-covariate predictor; 79.5% of static-model predictions were within two-fold and 93.2% within three-fold. The inhibitor AUC-ratio threshold of 2 identified a rifampicin ratio at or below 0.20 with sensitivity 81.8% (95% CI 61.5–92.7) and specificity 77.3% (56.6–89.9).

Conclusions: In this date-restricted exploratory synthesis, inhibitor interaction magnitude carried information about rifampicin exposure loss, but prediction error remained substantial. The effective fitted parameter is not an independently measured biological induction factor. The model does not replace dedicated interaction studies or establish dose-adjustment rules.

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