Preclinical versus clinical drug combination studies

Leuk Lymphoma. 2008 Nov;49(11):2059-80. doi: 10.1080/10428190802353591.


This brief review provides a practical guide for drug combination studies and delineates its essence in terms of the mass-action-based theory, experimental design and automated computerised data analysis. The combination index (CI) method of Chou-Talalay is based on the multiple drug effect equation derived from the median-effect principle of the mass-action law. It provides quantitative determination for synergism (CI < 1), additive effect (CI = 1) and antagonism (CI > 1), and provides the algorithm for computer software for automated simulation for drug combinations. It takes into account both the potency (the D(m) value) and the shape of the dose-effect curve (the m value) of each drug alone and their combination. The best feature is that it allows for small size experiments. The automated computer simulation reveals whether there is a synergism, determines how much synergism (the CI value) at any effect levels (the F(a)-CI plot), or at any dose levels (the isobologram), provides the information regarding how many folds of dose-reduction is allowed for each drug, at a given effect for a synergistic combination, comparing with the dose required for each drug alone (the F(a)-DRI plot), and the optimal combination ratio and schedule dependency for synergy. The 'polygonogram' dissects the component drug interactions or projects the make-ups of cocktails in complicated combinations. Based on scientific, practical and ethical reasons, it is not possible to 'determine' synergism in humans, and thus prior to the drug combination clinical trials, preclinical drug combination studies in vitro and/or in animals should be carried out to obtain the basis and rationale for studies in humans.

Publication types

  • Review

MeSH terms

  • Algorithms
  • Animals
  • Antineoplastic Combined Chemotherapy Protocols / pharmacology*
  • Antineoplastic Combined Chemotherapy Protocols / therapeutic use
  • Computer Simulation*
  • Dose-Response Relationship, Drug
  • Drug Evaluation, Preclinical / methods*
  • Drug Interactions*
  • Humans
  • Models, Theoretical