The talk starts at 12:15.

Please note that due to COVID-19, the participants can watch the streamed talk on Teams with a link (below).

Speaker: Manuela Zucknick

Location: Teams: Click here to join the meeting

Title: bayesynergy: flexible Bayesian modelling of synergistic interaction effects in in-vitro drug combination experiments

Abstract:

The effect of cancer therapies can be tested in vitro via cell viability assays, which allows the screening of large libraries of drugs for their efficacy. Drug interaction studies focus on the quantification of the additional effect encountered when two drugs are combined, as opposed to using the treatments separately. In the bayesynergy R package, we implement a probabilistic approach to this problem, where the observed dose response curve is modelled as a sum of the expected zero-interaction response and an additional interaction effect (synergistic or antagonistic). As this approach is based on a statistical model, it allows the natural inclusion of replicates, handles missing data and uneven concentration grids, and provides uncertainty quantification around the results. The model is implemented in Stan which gives us a computationally efficient sampler, a fast approximation of the posterior through variational inference and parallel processing for large drug combination screens.