Quantitative Prediction of Drug-Drug Interactions with Common Statin Co-medications
This September, Cyprotex, along with our colleagues at Genentech and Novartis, are running a complimentary webinar series focusing on drug transporters. If you missed our first instalment, not to worry, as we shall be publishing a summary of each presentation after the event along with the webinar recording.
This blog focuses on the first webinar of the series presented by Hayley Atkinson PhD, entitled ‘Quantitative Prediction of DDIs with Common Statin Co-meds: A Framework for Decision-making within Drug Discovery/Development’.
Drug-drug interactions (DDIs) are important to understand due to the impact they may have on the pharmacokinetics of a victim drug, and can often be a complex mix of multiple mechanisms. At worst, a clinically relevant DDI can result in the termination of drug development, refusal of approval or the withdrawal of a drug from the market.
The prevalence of DDIs is increasing due to an aging population, where it is reported 1 in 2 patients over 65 years old are prescribed ≥5 drugs, and due to the use of combination therapies in conditions such as HIV and cancer. Currently, statins are the most commonly prescribed drug class in the UK and are a common co-medication for many disease areas due to co-morbidities. Therefore, the potential for DDI with statins is high and a matter of great concern in the clinic. In the US and Asian markets, the most commonly prescribed statins are simvastatin, atorvastatin and rosuvastatin, so these are key drugs of focus when examining the impact of DDI and the ones that are focused on in this webinar.
The webinar discusses the need to identify the critical disposition pathways to define better the mechanisms behind statin DDI’s, the contribution of these pathways to the overall absorption and/or clearance of drug, and the key in vitro interaction studies required. In addition, it addresses the drive to move away from overly simple static equations when assessing DDI potential, instead recommending a more holistic approach using quantitative prediction of DDI.
More information on the in-depth reasoning, background and assumptions covered by this presentation can be found in the following research papers:
- Mechanistic In Vitro Studies Indicate that the Clinical Drug-Drug Interaction between Telithromycin and Simvastatin Acid is Driven by Time-Dependent Inhibition of CYP3A4 with Minimal Effect on OATP1B1 (Elsby et al. (2019) Drug Metab Dispos 47: 1-8). Read the publication.
- Understanding the Critical Disposition Pathways of Statins to Assess Drug-Drug Interaction Risk during Drug Development: It’s not just about OATP1B1 (Elsby et al. (2012) Clin Pharmacol Ther 92: 584-598) (https://doi.org/10.1038/clpt.2012.163).
If you missed part 1 of our webinar series or if you would like the opportunity to watch the webinar again, please click on the link below: