Artificial intelligence is set to become big in terms of pharmaceutical product development. A proliferation of players including IBM, Arterys, Houston Methodist Hospital and Harvard University are actively seeking to apply artificial intelligence into the medical field.
The small molecules will be for some 10 disease-related targets. The development process, Pharmaceutical Technology reports, will be driven by Exscientia receiving research payments from GlaxoSmithKline to begin drug discovery programs. The aim of these programs is to come up with suitable pre-clinical drug candidates. The deal is worth upward of $42.6 million, should all ten projects be suitably advanced.
Exscientia deal with artificial intelligence, big data, and experimentation, each harnessed to supporting the drug discovery process. The aim of the artificial intelligence component is to operate systems that can actively learn best practice from vast repositories of discovery data. Together with the use of big data analytics, the company can work with other organizations to design millions of novel, project-specific compounds and pre-assess each selected compound for its predicted potency and selectivity. This approach helps conventional healthcare and pharmaceutical organizations with their digital transformative approach to drug development.
The reason why there’s such an interest in using artificial intelligence for drug discovery is because the discovery process is time-consuming and expensive. PreSocuter estimates that the time taken for preclinical development takes anywhere between one and six years at a cost of $1 billion; plus a further 6 to 12 years for clinical development. This is all before regulatory approval. This second period can cost, on average, $1.4 billion. Add to this the chance of developing a commercially viable medicine through this process is below 10 percent.
Quoted by Fierce Pharma, Andrew Hopkins who is the CEO of Exscientia stated: “Delivering efficiencies to drug discovery has the potential to revolutionize the way early projects are executed, enabling more dynamic target selections from the burgeoning set of opportunities. We look forward to a productive collaboration with GlaxoSmithKline.”
Part of the application of artificial intelligence will be to reduce the number of compounds required for synthesis and assay. This will help GlaxoSmithKline to meets its drug development lead times. The process will be reliant upon artificial intelligence driven algorithms and accessing databases of medicinal chemistry and the requirements of large-scale biological-assays.
