Sometimes observations are made in drug discovery and target research that are unusual and potentially interesting, or that don’t make sense. We work with organizations to help understand and apply pharmacology assay results (see Testimonials page). For example, some inhibitor compounds reduce the maximal response to agonist/substrate. This mechanism can be a benefit or a hindrance depending on the therapeutic goal and complicates quantification of potency. We can help navigate this and other pharmacology issues in your projects and programs.
Sometimes pharmacology data analysis provides numbers that don’t make sense. We can help scientists troubleshoot their assays and data analysis. For example, in the table here are results from a competition kinetics experiment with physically impossible rate values. This artifact results from very rapid dissociation of the test compound. We worked with a team at the University of Cambridge to develop an analysis that takes this into account to quantify the compound affinity (see paper here)
High throughput data analysis
We can implement and optimize commercial or bespoke software for analyzing pharmacological data. For example, we developed high throughput Excel-based curve fitting for companies to dramatically accelerate data analysis, enabling scientists to focus on science instead of repetitive data handling. On the left is a basic example of a sigmoid curve fitter in Excel, that can be downloaded from here.
Complex data analysis
Sometimes the mechanisms and resulting data in pharmacology can be complex and formidable to analyze. We employ commercial software to analyze and simulate complex pharmacology data. For example, we work with Montana Molecular, designers and providers of very high quality biosensors, to perform analysis of time course data to enhance the value and insight of the sensors to drug discovery (see here). We derive equations for new analysis methods (see here for examples), implement them on curve-fitting software, and can either run the analysis or train you how to do it.
Sometimes we would like to know how a drug property, e.g. binding kinetics, translates to the in vivo drug effect. Or before starting an experiment we want to know how the system behaves, e.g. the effect of target density. Pharmechanics creates easy-to-use simulators to enable investigators to explore their systems. For examples, see here for free PK/PD simulators that incorporate binding kinetics.