A Review of Approaches and Methodologies for Assessing Transporter Drug-Drug Interactions

It is astonishing to think that drug-drug interactions (otherwise known as DDI) account for at least 5% of all hospital admissions. Even more concerning is that this problem can only be expected to worsen due to our aging population and the fact that polypharmacy is becoming common practice (1 in 2 patients over 65 years old being prescribed five or more different drugs). Not only are DDIs a huge economic burden on the healthcare system, they can lead to considerable morbidity, or even mortality, within the patient population.

DDI most frequently occur due to interactions with drug metabolising enzymes or drug transporters. Since 1997, the regulatory authorities (US FDA, EMA and Japanese PMDA) have produced guidelines for testing for DDI prior to administering new investigational drugs to the patient population. Over the past decade, these testing requirements have expanded especially in the area of drug transporters as our knowledge of transporter interactions has developed.

BDDCS Class III compounds are particularly susceptible to drug transporter interactions. This class of compounds, which includes several key therapeutic classes such as the antimicrobial, angiotensin II antagonists and statin drugs, are metabolically stable and have poor permeability, therefore, their disposition is primarily influenced by drug transporters. Of particular note are the statins. Statin usage has rocketed, with annual prescriptions increasing from 0.32 million to 52 million over the decade 1998-2008 in the UK alone. They are currently the most prescribed drug class in the UK. Due to their prevalence and the fact that they are often prescribed to older patients who may be taking other co-medications, the potential for DDI with statins is high.

Traditionally, in vitro transporter DDI studies have been performed around Phase II. Over recent years, many pharmaceutical companies have brought the assessment of DDI earlier in the drug discovery (e.g. candidate selection) or early development (before first time in patients) stage and have developed early testing strategies which typically employ simple hazard identification using the basic static equation as detailed in the regulatory guidance.  However, in order to help mitigate DDI risk and reduce any unexpected clinical findings in patients, we want to move to quantitative prediction of DDI (AUCR) through the use of mechanistic static approaches, which can be refined later in drug development through dynamic (PBPK) approaches as more detailed knowledge of a compounds ADME becomes available.

Dr Rob Elsby, Principal Scientist and Head of Drug Transporter Sciences at Cyprotex, presented at the DDI-2018 conference in Seattle in June 2018. His presentation focused on the findings of a recent Expert Opinion on Drug Metabolism and Toxicology review article by Williamson and Riley (of Evotec DMPK) and compared and contrasted four recent influential publications describing mechanistic static models for predicting complex DDIs. The models varied in their assumptions and input parameters.

View the presentation



Williamson B and Riley R. Hepatic transporter drug-drug interactions: an evaluation of approaches and methodologies (2017) Expert Opin Drug Metab Toxicol 13: 1237-1250.

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