Tackling two of the buzziest trends in pharma right now; AI and mRNA therapeutics, is high on the agenda of pharma and biotech companies, but scientists at the forefront say reliable data and the capacity to test predictions are needed to realise the full potential of these technologies.
“AI and mRNA are a match made in heaven, and both have been exploding somewhat simultaneously in the last 5 – 10 years”, said McGill University director Mathieu Blanchette at a recent conference. This is fortuitous because RNA therapeutics can now produce a lot of data that AI can use. Gill was speaking at the ongoing BIO International Conference taking place from 3 to 6 June.
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Gill said the area of generative AI in particular has exploded because of foundation models. These models encompass a particular type of AI, where someone can train very large, complex AI approaches, which is technically difficult, said Blanchette.
However, data or lack thereof remains an obstacle. In the mRNA space in particular, data on delivery models for mRNA is “the big open space” right now, said Andrew Giessel, executive director of AI engineering at mRNA giant Moderna. Datasets that can have good in vitro approximates for in-vivo performance of mRNA delivery models would be very valuable, he added.
Moderna, which was the first to get an mRNA vaccine authorised, has evolved from focusing exclusively on research problems to other areas of clinical development and pharmacovigilance, said Geissel. He added that the rise of foundational models has opened up new areas of the company to these tools.
Generating data, not just drug discovery data but also clinical information, for the AI models is the major challenge in the field right now, said the experts. Clinical data used to train AI models is often only from trials that recruited mostly white or Caucasian individuals. Any company that generates data has to consider the data sources to create a predictive model and make sure they are as diverse as possible, said Petrina Kamya, vice president and global head of AI platforms, Insilico Medicine.
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By GlobalDataAgainst this backdrop, several deals are pushing forth investments in both mRNA and AI. In 2021, Sanofi acquired the mRNA tech company Translate Bio, which, according to Ashoka Madduri, head of scientific strategy and CI, mRNA CoE, Sanofi, is now fully integrated with Sanofi. Madduri explained how despite there being different modalities of delivery, the company is continuing to explore and understand lipid nanoparticle delivery models for mRNA therapeutics.
In recent months, the company has made investments in this space in different ways. Last month, Sanofi announced a deal with Formation Bio and OpenAI, and another with Aqemia in December 2023 that focused on AI-led drug discovery and development. In 2021, it also announced an mRNA Center of Excellence and plans to invest €400m every year in the centre.
While the field has seen many high-value deals involving the use of specialised AI or mRNA-based discovery platforms, Christian Barrow, executive director, J P Morgan, said investors still need to see the outcome of this research to put a value on it. Moreover, Barrow acknowledged the ongoing trend in the field where assets that are developed using AI are being given a higher valuation than non-AI ones. The expectation is that AI reduces the time and costs for pharma by shortening the current drug discovery times, but this still needs to be fully validated. In the meantime, Barrow said this trend is likely to continue.
