In the previous Fund Insights of ODDO BHF AM, they have mentioned on numerous occasions the growing and major importance of Artificial Intelligence in Life Sciences as a whole. In the past, for example, they have elaborated the contribution of AI to the development of surgical robots. This edition of Fund Insight focuses on the major contribution that Artificial Intelligence can make to the development of new drugs. In particular, they identify the different types of players involved and the potentially considerable impact on the pharmaceutical market.
Let’s be clear: with Artificial Intelligence, we are entering a new era in drug development. This notable breakthrough has been made possible by the convergence of Technology and Biotechnology.
Technology and biotechnology are now converging in three areas:
- Experimental techniques in the laboratory: for example, the sequencing of a cell’s genes
- Analysis of data from the human body: for example, on the structure of proteins or molecular engineering
- Analytical techniques and engines: this involves exploiting in particular the immense amount of data from the previous two bullet points that is (or will be) available in the public domain. It should be noted that the major advantage of Artificial Intelligence is its ability to analyse large quantities of heterogeneous and unstructured data (stemming from different sources) to detect correlations. The pharmaceutical industry is rich in such data: just imagine for instance the results of the numerous clinical tests and examinations carried out by a wide variety of organisations (pharmaceutical companies, hospitals, laboratories, etc.) on a large number of patients with varying compositions and drug dosages.
This Tech-Biotech convergence is paving the way for precision medicine. This is already happening in the field of oncology. In the upcoming future, it will extend to autoimmune diseases such as lupus. Precision medicine relies on the analysis of these vast quantities of data to better understand and isolate the various molecular and protein determinants of a given disease.
…WHICH SHOULD PRODUCE WINNERS AND LOSERS
In the 1990s, the Internet search engine market was initially characterised by fierce competition (between Google, MSN, Netscape and Yahoo in particular), before eventually leading to Google’s virtual monopoly. In our view, Artificial Intelligence should help to bring about a similar evolution in medicines.
At the current preliminary stage, different types of players are competing for this huge market. In our view, this competition could once again produce a few winners and many losers. For the time being, here’s howwewould classify the forces currently in play:
- Google: the group benefits from a “first mover advantage”, which stems from:
- Its acquisition of DeepMind in the UK in 2014, which can predict the structure of proteins based on their amino acid sequences
- Its launch in 2017 of the “Baseline” study, which involves recruiting and monitoring a cohort of 10,000 volunteers for whom an AI collects all the genetic, medical and behavioural information, with a view to detecting any pathologies that might affect them at a very early stage.
- The world’s 10 biggest pharmaceutical companies: these ten ‘majors’ have all made strategic acquisitions of small artificial intelligence start-ups. These ‘digital’ nuggets have been grafted onto the majors’ internal R&D processes, which had been built for decades on an ‘analogue’ basis. Unsurprisingly, given the major cultural and operational differences, the integration of these acquisitions has not always resulted in the same level of success.
- The 10 largest US biopharmaceutical companies: players such as Amgen, Regeneron and Vertex Pharmaceuticals (to name only the most advanced among the top 10) have understood the benefits of innovation based on the convergence of Technology (i.e. AI) and BioTech. Amgen, for example, has launched its “BioNext” programme, which uses generative AI to develop bettertargeted antibodies (from a universe of more than 100,000 antibodies), more than halving the development time for the corresponding new drugs.
- Companies set up specifically to develop drugs using artificial intelligence: examples include Benevolent AI in Europe, and Recursion, Relay and Schrodinger in the United States.
Discover the full Fund Insight of ODDO BHF AM here.
