For investors in Hong Kong

Keeping perspective on AI’s role in biotech

Portfolio Managers Andy Acker and Agustin Mohedas say artificial intelligence (AI) has the potential to speed drug development, but ultimately, the value of the technology will have to be borne out by clinical data.

Andy Acker, CFA

Andy Acker, CFA

Portfolio Manager

Agustin Mohedas, PhD

Agustin Mohedas, PhD

Portfolio Manager | Research Analyst

15 Jun 2023
3 minute read

Key takeaways:

  • Enthusiasm for AI has spilled into biotech, with numerous accounts of how the advanced technology will revolutionize the sector.
  • But drug development is multifaceted, and some stages of the process, such as regulatory filings and clinical testing, may see limited benefit from AI in the near term.
  • In our view, investors should keep perspective and stay focused on what matters most to the value of biotech companies: approved products backed by clinical data.

The excitement bubbling up around artificial intelligence (AI) has been spilling into the biotech sector, with a steady flow of stories about how AI is helping facilitate drug discovery – from an antibiotic that shows promise against drug-resistant bacteria to a new psoriasis treatment with multibillion-dollar sales potential. These accounts have piqued investor interest given claims that AI can speed drug development, reduce costs, and improve outcomes. In fact, a Morgan Stanley report last year estimated AI and machine learning (a subset of AI) could lead to 50 additional novel drugs worth more than $50 billion in sales over a 10-year period.1

Early signs of AI’s potential

The excitement has some merit. AI is being deployed throughout the sector and showing early signs of its potential. COVID-19 mRNA vaccines, for example, were developed in record time thanks to AI algorithms that helped design synthetic mRNA, identify drug/vaccine targets, and automate quality control steps. In breast cancer screening, AI-based 3D imaging is improving the chances of detecting invasive breast cancer earlier and reducing the number of images radiologists must review. And in a recent report, the Food and Drug Administration said it is seeing a significant increase in drug submissions with AI-based components and expects the number to accelerate from here.2

Keeping perspective

However, as with any new technology, we believe it is important for investors to remember the bottom line. While AI may appear to be accelerating medical breakthroughs, these advances are often rooted in extensive research and development, with AI playing a supporting role. Moderna, which developed one of the mRNA COVID vaccines, spent years fine-tuning synthetic mRNA and collecting and analyzing data that later could be harnessed to fight COVID. And when it comes to drug development, certain time-intensive aspects will be difficult for AI to change drastically. These include clinical development (the phase 1, 2, and 3 clinical trials that test efficacy and safety on patients) and regulatory filings and review, which together can take many years to complete.

Today, it is possible to invest in so-called digital biotech companies that use AI to develop new molecules. And while these firms are making progress in building drug pipelines, it may be many years before the companies bring a therapy to market – even as some of these stocks get lifted by AI enthusiasm.

That said, more tangible progress has been made when it comes to computational tools and methods to help enhance preclinical drug development. Today, the best biotech companies are taking advantage of these tools, benefiting the firms that provide them.

In short, we believe AI has an important future in biotech, with the potential to speed drug discovery and facilitate effective and targeted treatments for patients. But ultimately, the value of firms behind the technology will be derived from the products created – the success of which depends on clinical data that will take years to produce. Until such data are available, we believe investors should approach AI in biotech with caution.

1 Morgan Stanley, “Why Artificial Intelligence Could Speed Drug Discovery,” 9 September 2022.
2 U.S. Food and Drug Administration, “Using artificial Intelligence & Machine Learning in the Development of Drug & Biological Products,” 16 May 2023.

Any reference to individual companies is purely for the purpose of illustration and should not be construed as a recommendation to buy or sell or advice in relation to investment, legal or tax matters.

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