ABSTRACT
Introduction: Drug-drug interactions (DDIs) continue to account for 5% of hospital admissions and therefore remain a major regulatory concern. Effective, quantitative prediction of DDIs will reduce unexpected clinical findings and encourage projects to frontload DDI investigations rather than concentrating on risk management (‘manage the baggage’) later in drug development. A key challenge in DDI prediction is the discrepancies between reported models.
Areas covered: The current synopsis focuses on four recent influential publications on hepatic drug transporter DDIs using static models that tackle interactions with individual transporters and in combination with other drug transporters and metabolising enzymes. These models vary in their assumptions (including input parameters), transparency, reproducibility and complexity. In this review, these facets are compared and contrasted with recommendations made as to their application.
Expert opinion: Over the past decade, static models have evolved from simple [I]/ki models to incorporate victim and perpetrator disposition mechanisms including the absorption rate constant, the fraction of the drug metabolised/eliminated and/or clearance concepts. Nonetheless, models that comprise additional parameters and complexity do not necessarily out-perform simpler models with fewer inputs. Further, consideration of the property space to exploit some drug target classes has also highlighted the fine balance required between frontloading and back-loading studies to design out or ‘manage the baggage’.
Article highlights
The impact of polypharmacy on the incidence of DDIs continues to account for 5% of hospital administrations and therefore remains a major health, economic and regulatory concern.
Developments over the last decade have catalysed an explosion in the interest of drug transporters as pivotal determinants of drug disposition and as drug targets in their own right.
Consideration of future trends in preclinical drug discovery is required due the diversity in chemical space required to engage contemporary targets.
Re-invention of established principles and DDI models appear to have hampered progress with hepatic drug transporter studies.
More complex transporter-DDI models that comprise additional disposition parameters do not necessarily out-perform simpler models with fewer inputs.
Effective prediction of transporter mediated-DDIs will reduce unexpected clinical findings and encourage projects to frontload DDI investigations to improve drug discovery success rates.
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Declaration of interest
The authors are employees of Evotec. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.