Healthcare companies are surprisingly advanced in using AI to diagnose more accurately and speed up drug discovery. This could be the start of something much bigger and more beneficial.

Artificial intelligence (AI) has already proved its worth in some areas of healthcare, such as radiology, where it is used to carry out initial scan assessments and prioritise them for further analysis. This is an area where AI can excel – high-speed pattern recognition and an unflagging focus on detail – but there is much more that it could do.

Since 1970, healthcare stocks have outperformed the S&P Index and provided a mix of solid defensiveness and periodic bursts of innovation-fuelled growth. The 1950s and 1960s saw huge strides being made with small molecules, followed by the arrival of monoclonal antibodies in the 1980s and genomics from the 2000s onwards.

Like most advances, the genomics revolution (which is one of our investment themes) is taking longer to deliver its benefits than people expected after the initial sequencing of the first full human genome in 2003. At the same time, discovery of new drugs has become ever more expensive. Now, however, AI offers the tantalising prospect of a new phase of innovation in healthcare and pharmaceuticals.

Big pharma’s drug problem

In the world of computing, Moore’s Law notes that the number of transistors in circuits has doubled every two years as chip design and production improves [1]. This has enabled huge leaps in technological progress and vastly reduced costs for end users of digital wizardry.

Unfortunately, it appears the pharmaceutical industry labours under the reverse of Moore’s Law – Eroom’s Law. In recent decades the cost of developing new drugs has doubled every nine years.

A study from 2020[2] found that between 2009 and 2018 the median research and development (R&D) investment required to bring a new drug to market was almost $1 billion, with an average lead time of 10-15 years.

Pharma’s increasing R&D bill coincides with mounting demand for treatments for ageing populations and conditions caused by sedentary lifestyles and ultra-processed diets. Many countries are having to pay more to provide healthcare and many individuals are having to pay more to access it.

Like finding a needle – in a stack of needles

Things could now be looking up for big pharma’s drug researchers. Earlier this year, researchers at McMaster University and Massachusetts Institute of Technology (MIT) used an AI approach to identify an antibiotic specifically for Acinetobacter baumannii, one of the World Health Organization’s most-unwanted dangerous antibiotic-resistant bacteria.

A. baumannii is a superbug usually found in hospitals. It can cause pneumonia and meningitis, can survive on surfaces for long periods and is also able to collect antibiotic-resistant genes from other bacteria.

Using AI, the McMasters/MIT team [3] sorted through thousands of potential antibiotic candidates in record time and at a fraction of the cost of traditional research methods. Testing and approval will be slower, but the team’s success highlights the possibility of speeding up drug discovery and assessing the medicinal properties of, potentially, billions of molecules.

That was the easy stuff

As with pattern recognition in radiology, identifying antibiotics is a well-suited task for initial uses of AI in healthcare because it is well-defined, involving matching a specific enemy to its nemesis. By contrast, tackling cancer and dementia – two of the biggest areas of unmet medical need – is much more complicated. Humans are incredibly intricate biological machines: science is not even remotely close to understanding all the interactions involved in how our bodies function.

If AI can be brought to bear on complex areas such as cancer and dementia, the social and financial benefits would be enormous. Dementia alone imposes a brutal burden. Worldwide, it is estimated that around 55 million people live with dementia, implying annual care costs of $1.3 trillion.[4]

As populations in the US, Europe, Japan and China continue to age, these figures will rise dramatically. In the UK alone, the annual care costs of dementia are expected to rise from £34.7 billion to £94.1 billion by 2040 as the number of UK cases rises by 80% [5].

Entering a rough patch, with optimism

The 2024 US presidential election could be a difficult time for the pharmaceuticals industry as Republicans and Democrats vie to get tough on drug prices in what is, by far, pharma’s biggest market. Looking further ahead though, the sector’s prospects could be much brighter.

Following the Covid pandemic, some pharma companies have a high level of cash to deploy. The first six months of 2023 have seen a significant increase in acquisitions of bioscience companies by big pharma, including Pfizer’s $43 billion proposed takeover of Seagen, which focuses on what is known as smart chemotherapy.[6]

A shot in the arm for healthcare

We believe that AI could be highly advantageous for a number of companies that we invest in under our Ageing theme. These include Amgen, which has a strong data advantage over competitors thanks to its vast database of genetic samples. Using AI to analyse these could speed up the development of promising drugs while excluding less promising drugs at an earlier stage. Another example is Sonic Healthcare, which is likely to benefit from applying AI techniques to its diagnostic testing. This has potential to give Sonic Healthcare a competitive advantage over its many smaller competitors in terms of speed of diagnosis and cost.

Applying AI to healthcare and pharmaceuticals offers the prospect of not only longer lifespans but also longer healthspans (healthy life). In the process, it is likely to free up resources for more innovative therapies, creating a virtuous circle that could bring a step change in tackling the enormous challenges posed by ageing demographics.

[1] https://www.britannica.com/technology/Moores-law, 28 September 2023

[2] Estimated Research and Development Investment Needed to Bring a New Medicine to Market, 2009-2018Olivier J. Wouters, PhD, Martin McKee, MD DSc and Jeroen Luyten, PhD; March 2020

[3] MIT News, Using AI, scientists find a drug that could combat drug-resistant infections, 25 May 2023

[4] The worldwide costs of dementia in 2019. From Alzheimer's & Dementia, published by Wiley Periodicals LLC on behalf of Alzheimer's Association, 2023.

[5] Projections of older people with dementia and costs of dementia care in the United Kingdom, 2019–2040 Care Policy and Evaluation Centre, London School of Economics and Political Science.

[6] Pharmaceutical Technology, M&A in pharmaceutical increased in Q2 2023, 16 August 2023

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