A functional analysis-based strategy for early-stage drug safety evaluation

Abstract

Early assessment of candidate drug safety is critical in pharmaceutical development to mitigate post-market withdrawals and reduce potential risks. Approximately 75% of Adverse Drug Reactions (ADRs) are dose-dependent (Type A), often mediated by interactions with unintended off-target proteins. Traditional binding assays have limitations in predicting functional biological effects. To address this challenge, this study aims to investigate how an in vitro secondary pharmacology screening strategy, utilizing a functional assay format, can enable more accurate identification of potential safety liabilities early in drug discovery.

A high-throughput strategy integrating functional technologies (e.g., FLIPR, HTRF, ADP-Glo) was employed, combining single-point and multi-concentration dose-response screening. Automated instrumentation supported efficient profiling against a panel of 77 safety-related targets using pergolide and antidepressants.

The screening strategy effectively delineated compound-specific off-target risk profiles. Evaluation of representative antidepressants from different classes—amitriptyline (tricyclic), citalopram (SSRI), and bupropion (NDRI)—using the ICESTP SAFETYPANEL® 77 successfully quantified their off-target interaction risks. Amitriptyline exhibited potent off-target activity against 22 safety-related targets. Citalopram showed interactions with 6 off-targets, whereas bupropion demonstrated the cleanest profile, with activity limited solely to DAT, its intended primary target. These in vitro findings are highly consistent with the established clinical safety profiles of each compound. Furthermore, the functional format enabled discrimination of agonist types, detection of non-linear responses, and reduced false results. Physiological ATP (1 mM) improved predictive accuracy in kinase assays, and automation enhanced throughput.

This study confirms that a secondary pharmacology screening strategy employing a functional assay format, multi-concentration dose-response curves, and integrated automation provides more comprehensive and predictive data for drug safety assessment. This strategy facilitates the early identification and mitigation of potential safety risks mediated by off-target effects during compound optimization, thereby increasing the overall success rate and cost-effectiveness of new drug development and advancing the discovery of safer and more effective therapeutics.