Inference of synergy/antagonism between anticancer drugs from the pooled analysis of clinical trials

Wenfeng Kang, Robert S. Dipaola, Alexei Vazquez

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Background: Drug interactions can have a significant impact on the response to combinatorial therapy for anticancer treatment. In some instances these interactions can be anticipated based on pre-clinical models. However, the anticipation of drug interactions in the clinical context is in general a challenging task. Methods. Here we propose the pooled analysis of clinical trials as a mean to investigate drug interactions in anticancer therapy. To this end we collected 1,163 Phase II clinical trials with response data on over 53,745 subjects. Results: We provide statistical definitions of drugs resulting in clinical synergy and antagonism and identify drug combinations in each group. We also quantify the possibility of inferring interactions between three or more drugs from parameters characterizing the action of single and two-drugs combinations. Conclusions: Our analysis provides a statistical methodology to track the performance of drug combinations in anticancer therapy and to quantify drug interactions in the clinical context.

Original languageEnglish
Article number77
JournalBMC Medical Research Methodology
Issue number1
StatePublished - 2013

Bibliographical note

Funding Information:
WK and AV were sponsored by the RWJ Foundation. WK, RSD and AV were supported by NCI P30 CA072720.


  • Cancer therapy
  • Clinical synergy
  • Clinical trial
  • Combinatorial therapies
  • Overall response rate
  • Systems biology

ASJC Scopus subject areas

  • Epidemiology
  • Health Informatics


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