Is AI the answer to the challenges facing drug discovery?

AI and robotics

DDW Editor Reece Armstrong asks whether artificial intelligence (AI) is the magic bullet many think it is.

To reflect on another year in pharma is to think of the major stories and trends that have made impact within the industry.

Often this can be drug approvals, exciting research into hard-to-treat indications, or even regulatory updates that enable players within the sector to utilise the latest technologies and drive therapies to market faster, ultimately benefitting patients.

From a technological perspective, the start of 2023 was characterised by discussions surrounding ChatGPT – a generative artificial intelligence (AI) chatbot that drew controversy for its use-cases, or misuse cases, across industries such as academia and creative sectors.

The attention on this tool brought further waves of interest into how AI could be deployed across the pharmaceutical and drug discovery sectors. AI has long been touted as having the potential to speed up drug development, particularly in the early-drug discovery stages, by helping researchers find suitable drug targets that can better tackle diseases.

It’s no surprise then that a lot of DDW’s coverage this year has been focused on AI and it makes sense that when pharmaceutical companies face so many challenges in getting drugs to market, they’re searching for tools to improve those chances.

But is AI the answer to the industry’s development challenges?

Earlier this year, UK-based BenevolentAI reported disappointing results of its atopic dermatitis drug from a Phase II clinical trial. The company has a varied pipeline, though most of its candidates are currently in the early stages of discovery or development. As such, disappointing results for a company so embedded within the AI space highlight that this technology isn’t the silver bullet that many think it is, indicating that the main barriers to successful drug development lie in the translation stages between animal models and human.

However, that’s not to say the future of drug discovery isn’t exciting, or that AI won’t play a part in it, just that the potential of AI within pharma has yet to be reached. Where conversations on AI used to be on its general use, the industry is now turning to things like generative AI and vertical AI to tackle some of the challenges it has traditionally faced.

These facets of AI have the potential to test and validate millions of molecules, or even design new molecules for diseases that teams can test in silco or through wet lab experiments. Importantly, this offers teams new ways to approach drug discovery, potentially saving years and millions in cost for that pre-clinical discovery process.

To date, no AI-designed molecule has been approved by the FDA, showing that whilst the industry is certainly making strides in using AI to discover therapies, there’s still more work to be done before we see those therapies reach the market.

Progress isn’t stagnant though. Whilst the majority of AI-designed drugs have been focused towards the small molecules space, companies are now leveraging AI tools and platforms to target advanced therapies including monoclonal antibodies and cell and gene therapies. And with major partnerships in 2023 such as the likes of NVIDIA/Genentech, Novo Nordisk/ Valo Heath, and Janssen/Intelligent OMICS, it’s clear that the pharma industry is seriously considering how platforms can help get their therapies to market faster.

There’s certainly more to come from AI in pharma and if 2023 is any indication, the industry is just getting started.

DDW Volume 25 – Issue 1, Winter 2023/2024

Reece ArmstrongAbout the author

Reece Armstrong is Editor of DDW. He has worked in life sciences and pharmaceutical B2B publishing for seven years and was previously Editor of European Pharmaceutical Manufacturer. He has a master’s degree in Journalism from Newcastle University.

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