VC Funding for AI in Drug Development & Clinical Trials Hits $5.2B

CRAWLEY, United Kingdom, Jan. 6, 2020 /PRNewswire/ -- The market for AI in drug development and clinical trials is maturing and entering a new phase; total funding in the industry has reached $5.2B, but investments have slowed down in 2019 and only 4 new companies were formed. Any new start-ups will have to prove themselves able to compete against well-funded first-generation vendors, and existing vendors are under pressure to demonstrate results. Signify Research has analysed the investment landscape and categorised the industry into Information Synthesis, Drug Design and Clinical Trials. To download the full investment analysis in pdf format, click here.

Which Applications are AI Used For?
Nine out of ten new drug candidates never make it through clinical trial and regulatory approval, so the pharmaceutical industry is very open to new ways that can make drug development more efficient. The focus of this analysis has been on applications that are directly involved in optimising drug development by analysing clinically relevant data to guide the discovery of new potential targets, applications that are directly involved in the creation and optimisation of the molecular structure of potential drugs, and applications that help organise, optimise, run and recruit patients for clinical trials.

Within these three product segments, 32% of funding has gone to companies focusing on Information Synthesis, 54% to companies focusing on Drug Design and 14% to companies with a primary focus on Clinical Trials.

AI in Drug Development - More Than Empty Promises?
While the number of companies founded in year 2017 peaked at 28, only 4 new companies were formed in year 2019. In addition, total funding decreased by 23% from 2018 to 2019. Ambitions and expectations have been sky-high for AI use in this sector, but some investors may now start to wonder if they had been too bullish and if the technology is ever going to deliver what has been promised. Even if AI would be able to assist with such a complex task as understanding the cause of disease, it would need access to vast amounts of data that is often not accessible or simply does not exist yet. So, as the market matures past the initial hype, investors, as well as potential new pharma partners, are waiting to see more evidence and proof of concept to demonstrate the functionality and value of these AI solutions.

However, there is already a lot happening in the industry with several AI designed drugs in the pipelines. Partnerships with big pharma vendors will be key to success for start-ups and will support turning proof of concept into potential milestone payments for new drug candidates, sometimes exceeding a billion dollars as seen with the InSitro-Gilead partnership, Exscientia-Celgene partnership and the Atomwise-Hansoh Pharma partnership. And, in addition to revenue, as pharmaceutical companies often are sitting on years of digitised data from research and clinical trials, the pharma partnerships will provide access to a larger pool of data to train the algorithms and discover new valuable connections in disease and treatment mechanisms that wouldn't have been possible otherwise with traditional methods.

For the full analysis including geography, product type, funding type and partnership segmentation, click here.

Contact:
Ulrik Kristensen
+44 1234 436 150
[email protected]

SOURCE Signify Research

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