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Artificial intelligence’s role to transform pharmaceutical industry

The availability of big data in life sciences and a rapid progression in deep neural networks led to a wave of AI-based startups
focused on drug discovery sweeping through the biopharma industry over the last three years. A number of significant
AI-big pharma collaborations were announced in 2016-2017, including Pfizer and IBM Watson, Sanofi Genzyme and Recursion Pharmaceuticals, and GSK and Exscientia, among others.

As of today, there are no AI-inspired, FDAapproved drugs on the market. Also, it is important to realise that while AI-based
data analytics can bring innovation at every stage of drug discovery and during the development process, this data will not magically serve as a substitute for chemical synthesis, laboratory experiments, trials, regulatory approvals and production stages.

What AI can do, though, is optimise and speed up R&D efforts, minimise the time and cost of early drug discovery, and help anticipate possible toxicity risks or side effects at late-stage trials to hopefully avoid tragic incidents in human trials.

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