Screening
Reducing the PAINS in high throughput screening: assay design as a tool for maximising efficiency
While the quality of the compound collection is frequently described as a key determinant of the success of a high throughput screening campaign, in our opinion equally important is the design and execution of the primary assay and the subsequent confirmatory screens used to establish the authenticity of the hits that are discovered. This article will describe, with examples, how understanding the likely mechanisms of false positives in advance of screening informs the design of the hit triage, thus increasing the likelihood of discovering optimisable chemical matter and avoiding costly wasting of resource. We describe the use of a bespoke ‘Robustness Set’ of nuisance compounds and how it can be used in conjunction with adjusting the conditions of the assay. We also present an example where hit identification was initially confounded by the presence of a common pharmaceutically-acceptable salt and will describe how biophysical data was used to characterise the interactions and triage of the hits.
T
he small-molecule drug discovery ecosys- tem has changed enormously over the past two decades1. Currently only two of the
top 10 best-selling medicines are small molecules, whereas 15-years ago all 10 were in this category2. While, of course, other statistics are arguably more important, such as the number of patients treated, this change has led to challenges in funding small- molecule programmes in many discovery organisa- tions including major pharma, for example: “There was a view that vaccines, antibodies and other biopharmaceuticals were more profitable
Drug Discovery World Fall 2019
than small-molecule drugs, in part because com- petitors were not as adept at bringing generic ver- sions to market.”3 There has been a shift to new modalities in discovery4 and some notable success- es have been scored in the clinic with significant promise of future advances. At the organisational level there have been very significant reductions in staffing in pharma companies, in particular in dis- covery R&D5, which has mirrored the growth in open innovation models where the search for inno- vation relies on increasing interactions with aca- demic groups and biotech6. These structural
By Dr Philip S. Jones and Dr Stuart P. McElroy
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