Artificial Intelligence (AI) has been a top trend in many industries lately, attracting massive media attention and investments. Over the last decade, this complex area of research has rapidly progressed from being a "resurrected cool technology from the past" to a full-blown driver of nothing less than a new industrial revolution -- a digital one. As of today, AI is widely commercialized in such applications as manufacturing robots, smart assistants (e.g. Siri), automated financial investing systems, virtual travel booking agents, social media monitoring tools, conversational bots, surveillance systems, online security systems, language translators, self-driving cars, and much more. In some industries, AI (including its many technologies and sub-disciplines, such as deep learning, recommender systems, and natural language processing), is becoming a standardized component rather than a cutting-edge innovation it once was. This rapid progress in AI adoption is also seen in the pharmaceutical industry -- not without caveats, however. Unlike "mainstream" use cases, like image recognition or spam email filtering, drug discovery research appears to be a much harder case for several reasons.
So far, the pharmaceutical industry has contributed more to the well-being of humanity than any other industry. But lately its business model has been under significant pressure since the return on R&D investment has dropped to its lowest level in decades (lack of innovation amid digital disruption, rapid technological advances and other issues such as lack of data reproducibility) and its public reputation in US and around the world (anti vaccine movement in Europe) is worse than ever. This worrisome mix of little growth potential and low reputation is the main reason why investors are increasingly worried, not to mention that the current drug development process needs a big dose of digital innovation to deal with its messy data. As a matter of fact, Stefan Oelrich member of the Board Management of Bayer AG, President Pharmaceuticals, wrote in an article -- that the title perfectly summarises the AI pharma situation "Artificial Intelligence - When we Suddenly Know What we Don't Know" -- the following: "As we open the first doors in this unknown land we start to discover how much more is out there for our entire pharmaceutical value chain spanning from research to product supply. I expect AI to help us know what we have not known so far. Artificial Intelligence will become instrumental in our search for new medicines to better serve patients around the world as we leverage Science For A Better Life".
In 2021 the application of AI enabled advances in many areas of healthcare. We made significant progress in AI for drug discovery, medical imaging, diagnostics, pathology, and clinical trials. Important peer reviewed papers were published and dozens of partnerships were formed. Big Pharma companies and major tech companies became very active in the space. Record amounts of funding were raised, and a few companies even started human clinical trials. Microsoft and NVIDIA launched two of the world's most powerful supercomputers and Microsoft announced Azure OpenAI Service. In 2022 we expect these technologies to converge across the healthcare spectrum. This article summarizes milestones achieved in 2021. This is the first in a series of progress reports I'm writing on the sector that will be supplemented by industry performance data and metrics compiled in partnership with Alliance for Artificial Intelligence in Healthcare (AAIH) and other top tier resources.
AbCellera and Gilead Sciences announced a new multitarget antibody discovery collaboration building on their previous infectious disease partnership from 2019. AbCellera is now starting to reap the fruits of its labor, as its successful antibody discovery programs earned the company $203 million in revenue in the first quarter of this year, including $178 million in milestones and royalties. Gilead Sciences also announced a very interesting partnership during the first half of 2021, this time with Gritstone Oncology to create a vaccine-based immunotherapy as a cure for HIV. Under the terms of the deal, Gilead is paying Gritstone $30 million upfront and a $30 million equity investment, and potentially an additional $725 million in regulatory and commercial milestones and royalties on net sales. BenevolentAI and AstraZeneca have been collaborating closely since 2019 to use AI and machine learning for the discovery and development of new treatments for chronic kidney disease (CKD) and idiopathic pulmonary fibrosis (IPF).
Jan 7 (Reuters) - French drugmaker Sanofi SA (SASY.PA) will partner with British AI firm Exscientia Plc (EXAI.O) to develop up to 15 drug candidates across oncology and immunology, in a deal worth up to $5.2 billion in milestone payments, the two companies said on Friday. Exscientia will get an upfront cash payment of $100 million, leading discovery and design of small molecule drugs up to nomination of the candidate most likely to be viable. After that, Sanofi will take charge of clinical development. Sanofi is among the many pharmaceutical giants venturing into artificial intelligence to improve accuracy and reduce time spent on research, with investment firms like SoftBank (9984.T) also betting big onthe space. Exscientia, which went public on the Nasdaq in October, uses artificial intelligence to discover drug molecules, especially focused on treating cancer and immune disorders, through partnerships with pharma firms such as Roche and Bristol Myers Squibb (BMY.N).