Drug synergy scoring using minimal dose response matrices

Abstract Objective Combinations of pharmacological agents are essential for disease control and prevention, offering many advantages over monotherapies, with one these being drug synergy. The state-of-the-art method to profile synergy in preclinical research is by using dose–response matrices disease-appropriate models, however this approach frequently labour intensive cost-ineffective, particularly when performed a medium- high-throughput fashion. Thus, study, we set out optimise parameter methodology, determining the minimal matrix size that can be used robustly detect quantify between two drugs. Results We reduction workflow allowed identification capable detecting quantifying These utilise substantially less reagents data processing power than their typically larger counterparts. Focusing on antileukemic efficacy chemotherapy combination cytarabine inhibitors ribonucleotide reductase, could show detection quantification three common models was well-tolerated despite reducing from 8 × 4 4. Overall, optimisation scoring as presented here inform future screening strategies pre-clinical research.