Identifying targets for drug development is hard with high failure rates in later-stage clinical trials. A new study led by Professor Julian Knight at the Wellcome Centre for Human Genetics and colleagues from the ULTRA-DD Consortium shows how genetics combined with knowledge of network connectivity can help. The new Priority Index or ‘Pi’ pipeline developed by first-author Dr Hai Fang is open-source and scalable, enabling other researchers to capitalise on their findings. A web-based portal to allow others to use and build on the Pi pipeline can be found at http://galahad.well.ox.ac.uk/pi/.
The paper describes findings for 30 different immune-mediated diseases, ranging from rheumatoid arthritis to multiple sclerosis, showing how the drug target prioritisation landscapes for these different diseases relate to each other and identifying novel under-explored targets.
Evidence validating the approach was based on a range of cellular screens. The authors found that disease-specific activity from a compound screen was correlated with the Pi ranking for the target of the compounds tested. They also found that Pi can predict activity for CRISPR and mutagenesis screens, and a panel of epigenetic inhibitors applied to patient-derived cells.
The work was carried out in collaboration with researchers in the Structural Genomics Consortium (Oxford), Botnar Research Centre (Oxford), MRC Weatherall Institute for Molecular Medicine (Oxford), Target Discovery Institute (Oxford), Kennedy Institute of Rheumatology (Oxford), Janssen (Belgium), University of Tartu (Estonia) and the Karolinska Institutet (Sweden).