An automated fitting procedure and software for dose-response curves with multiphasic features

• DOI: 10.1038/srep14701
• Publication Date: 2015-10-01T08:53:12Z
• Authors: Giovanni Y. Di Ve...; Chiara Fornari; Ian Goldlust; Graham Mills; Siang Boon Koh; Jo L Bramhall; Frances M. Richards; Duncan I. Jodrell
• Keywords: 0301 basic medicine; 03 medical and health sciences; Dose-Response Relationship, Drug; Humans; Models, Theoretical; Article; Algorithms; Software; 3. Good health

AbstractIn cancer pharmacology (and many other areas), most dose-response curves are satisfactorily described by a classical Hill equation (i.e. 4 parameters logistical). Nevertheless, there are instances where the marked presence of more than one point of inflection, or the presence of combined agonist and antagonist effects, prevents straight-forward modelling of the data via a standard Hill equation. Here we propose a modified model and automated fitting procedure to describe dose-response curves with multiphasic features. The resulting general model enables interpreting each phase of the dose-response as an independent dose-dependent process. We developed an algorithm which automatically generates and ranks dose-response models with varying degrees of multiphasic features. The algorithm was implemented in new freely available Dr Fit software (sourceforge.net/projects/drfit/). We show how our approach is successful in describing dose-response curves with multiphasic features. Additionally, we analysed a large cancer cell viability screen involving 11650 dose-response curves. Based on our algorithm, we found that 28% of cases were better described by a multiphasic model than by the Hill model. We thus provide a robust approach to fit dose-response curves with various degrees of complexity, which, together with the provided software implementation, should enable a wide audience to easily process their own data.