Quantifying Multi‐dimensional Drug Synergy along Axes of Potency and Efficacy in Anti‐Cancer Combinations

Abstract

In the rapidly expanding landscape of quantitative systems pharmacology and personalized medicine, identifying synergistic drug combinations is of paramount interest. Synergistic drugs have the potential to increase the efficacy of the current therapeutic pool at reduced doses, ameliorating off‐target toxicities. However, current methods to quantify drug synergy have limited utility and, consequently, limited adoption. Specifically, we found the current methodological landscape was not amenable to our recently developed metric of drug effect based on the drug‐induced proliferation (DIP) rate. This motivated us to develop a novel drug synergy framework based on a generalized multi‐dimensional Hill‐equation; a framework agnostic to the metric of drug effect. We discovered this framework naturally distinguishes between two intuitive types of drug synergy: synergistic potency and synergistic efficacy, hitherto unresolved by previous methods. We visualize these two types of synergy on Synergy Diagrams which stratify drug combinations along orthogonal axes of synergistic effect. Importantly, these axes correspond to the variables of clinical interest, namely potent dose range (synergistic potency) and maximal reduction in malignant‐cell growth (synergistic efficacy).We demonstrate the importance of distinguishing between these two types synergy in two model systems. First we investigate a panel of anti‐cancer compounds in combination with osimertinib, a 3rd generation mutant‐EGFR inhibitor, in EGFR‐mutant non‐small cell lung cancer. We find anti‐mitotic, vinca alkaloids and drugs targeting epigenetic regulators, such as BET bromodomain and HDAC inhibitors, are synergistically efficacious with osimertinib. Additionally we identify dasatinib, a SFK inhibitor with known off target toxicities in the immune system, to be synergistically potent with osimertinib reducing the required dose and thereby blunting off target toxicities.We also study sixteen combinations of RAF and MEK inhibitors in a panel of eight BRAF‐mutant melanoma cell‐lines. In general, the combination is synergistically efficacious, but antagonistically potent. These results align with intuition based on the clinical result of the combination and the hierarchy of MAPK signaling respectively. Additionally, the rank order of each combinations' synergistic efficacy varied between cell‐lines which has implications for personalized medicine. Finally, using techniques from quantitative systems pharmacology, we demonstrate a link between synergistic efficacy and fatty acid metabolism, suggestive of an avenue for increasing the clinical efficacy.In summary, we have developed a novel framework which differentiates two types of synergy with direct implications for the clinic where there is a fundamental trade‐off between tolerable dose and efficacy. By segregating synergy along distinct axes of potency and efficacy as in our Synergy Diagrams, informed choices can be made about this trade‐off.Support or Funding InformationThis work was funded by National Science Foundation Graduate Research Fellowship Program (Grant #: 1445197) and by National Institutes of Health U01 (Grant #:CA215845‐01).This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.