Innovative Drug Interaction Studies
Drug combinations are critical in many diseases, including cancer. Synergistic drugs allow the use of lower doses in the treatment and therefore the adverse reactions would probably be reduced.
Vivia has developed a workflow including different methods like traditional dose dependant indexes, surface modeling¹ (Greco et al., 1995) and the new MuSyC²,³ algorithm to perform a complete drug interaction study.

Drug interaction study phases

MuSyC algorithm different synergies for drug interaction

Figure 1. MuSyC algorithm is applicable to any metric of drug interaction effect and is able to differentiate between potency (α), efficacy (β) and cooperativity (γ) synergy.

Drug interaction study results dashboard

Figure 2. Drug interaction study analysis results in Spotfire. Combination Indexes, 3D surface model and synergy parameters results are displayed together for a better overview.

Drug interaction 3D surface

Figure 3. 3D interaction surface examples for potency synergy. MuSyC algorithm calculates fold changes in the potency on drug B induced by drug A (α12) and vice versa (α21).

Interactive Demo - Drug interaction 3D surface



  1. Greco, W.R., Bravo, G., and Parsons, J.C. (1995). The search for synergy: a critical review from a response surface perspective. Pharmacol. Rev. 47, 331–385.
  2. Meyer, C.T., Wooten, D.J., Paudel, B.B., Bauer, J., Hardeman, K.N., Westover, D., Lovly, C.M., Harris, L.A., Tyson, D.R., and Quaranta, V. (2019). Quantifying drug combination synergy along potency and efficacy axes. Cell Syst. 8, 97–108.e16.
  3. Wooten, David J, and Albert, Réka. synergy – A Python library for calculating, analyzing, and visualizing drug combination synergy. (2020) Bioinformatics.