AI innovators prefer autonomy to big pharma

AI drug discovery is hot; researchers expect it to reach US$20 billion in the next five years.

Advances in AI see it is being used in numerous areas of research and design, from understanding CT scans to natural language processing, and AI is particularly helpful in medical research as it can speed up and improve the success rates of drug discovery as well as lowering the cost.

Only yesterday, AI innovator Insilico Medicine announced the publication of a paper titled “Deep biomarkers of aging and longevity: from research to applications” in Aging [1] and the issuance of a key patent “Deep transcriptomic markers of human biological aging and methods of determining a biological aging clock” (US20190034581). 

Using AI for drug discovery prompted an explosion in the number of academic publications, start-ups and big pharma developments. With so many innovators appearing to make progress in this field, it could be difficult to separate the buzz from the hype or to distinguish just where investors should be focusing.

AI-driven big biopharma deals disclosed in the market:

AI drug discovery Longevity Technology
Source: Deloitte analysis.(March 2019).

Luckily, Deloitte Centre for Health Solutions has produced a new comprehensive report titled “Intelligent drug discovery Powered by AI”. As well as featuring multiple case studies, the report also delves into some of the recently-published scientific literature and papers as well as building on the vital statistics published by Deep Knowledge Ventures.

Shrewdly noting that: “The AI R&D market increased from US$200 million in 2016 to more than US$700 million in 2018. Researchers expect it to reach US$20 billion in the next five years,” the report looks at how AI can be used to improve target predictions, mine libraries in order to identify new drug candidates, optimise, repurpose, as well as AI’s vital role in pre-clinical testing.

Insightful case studies include Medicines Discovery Catapult, Benevolent AI, Insilico Medicine and Cyclica. The report also looks at Exscientia, “one of the first companies to use AI for the identification of new drug candidates” which “has secured relevant partnerships with a number of big biopharma companies over the past four years” and plays a key role in using AI to “diversify drug pipelines”.

Considering the 4P nature of medicine in the future (personalised, predictive, preventative and participatory), the report notes that “In 2018, the FDA’s approval of 59 new drugs was … the highest number since 1996,” and that” AI drug discovery companies no longer seek to be acquired, preferring to develop their own drugs and maintain autonomy … The increase in availability of venture capital (VC) funds in this sector (VC funding reached US$1.08 billion last year, from US$237 million in 2016) is helping drive this development.”

This reflects the insights from our interview with Dr Alex Zhavoronkov is the CEO and co-founder of Insilico Medicine, he told us. “When you work with big pharma, you need to put a lot more effort into partnering, and it can take up to a year to get a contract. Those contracts are not as lucrative as they might seem to everybody else in the industry and you actually do not get access to their data and if you do, you cannot use it.”


“…the number of companies using AI for drug discovery will increase exponentially…”


 

The report adopts a forward-thinking approach to AI-powered drug discovery, noting that: “The benefits of achieving a better drug discovery process outweigh the risks of sharing knowledge.” It concludes with the opinion that research will be outsourced to external AI companies who will do the work in silico, rather than in live trials, meaning that the results will come a lot faster and cheaper.

And the near future? “In the next five to ten years, the number of companies using AI for drug discovery will increase exponentially and new drugs capable of treating very precise pathologies will become the norm. Significant advances in the techniques used will evolve to produce next generation AI methods and provide the framework for precision medicine to become mainstream.”

Commenting on the report, Alex Zhavoronkov said, “ln my opinion, one of the main challenges in the pharmaceutical industry is the disconnect between the many steps of drug discovery, drug development, and sales & marketing.

“AI can help integrate these previously disconnected areas and trace the patterns across the 10-20 year discovery and development cycles … I am very happy to see that Deloitte managed to take a helicopter view on the industry and performed a cross-sector analysis.”

Image credit: Deloitte Centre for Health Solutions

[1] https://www.eurekalert.org/pub_releases/2019-12/im-ipa120519.php

 

 

Eleanor Garth
Staff Writer and Community Manager Following a degree in Classics, Eleanor organised biomedical engineering conferences and provided research support at Imperial College London and various London hospitals, before working as a science and medicine journalist.

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