Predicting clinical outcomes from off-target receptor interactions using Secondary Intelligence™

Abstract

Adverse effects due to off-target activity can be predicted by careful comparison of the relationship between expected plasma concentration and off-target activity of the test compound with that of reference drugs targeting that receptor for their therapeutic efficacy. The ratio between plasma concentration (unbound) and the K_i at the receptor is a surrogate measure reflecting receptor occupancy. Where data are available for reference drugs, we have curated and evaluated this at 100 receptors, 72 of which can involve both negative and positive modulations by drugs: a total of 172 ‘receptor modulations’. This provides a quantitative framework upon which to achieve consistent risk assessment of off-target interactions across receptors, across compounds and between assessors. It therefore represents a significant departure from an opinion-based to an evidence-based approach to secondary pharmacology. Demonstration of proof-of-principle was achieved for one of the receptor interactions (α_1A-adrenoceptor antagonism leading to postural hypotension in clinical use) due to the availability of high-quality off-target K_i data for >30 drugs at this receptor.