AI in healthcare can get post-pandemic boost

The digital skills shortage is one of the main barriers that life sciences companies have to address if the potential of AI in healthcare is to be fully realised.

Attitudes to AI in life sciences

A study undertaken in November last year underlined that, while AI has become more popular across life sciences in recent years, companies remain at varying stages of adoption.

Pinsent Masons commissioned Meridian West to undertake interviews with 52 industry experts from across Europe. Those individuals included senior executives and legal counsel, and respondents were spread across different types of organisations active in the sector, from originator product manufacturers, biotech companies and medtech providers, to generics, biosimilar manufacturers and academic or research organisations.

According to the survey results, 29% of organisations in the life sciences sector are already using AI and big data in key areas of their business, while a similar number of respondents said they have a limited engagement with AI and big data currently but expect it to grow and play a more significant role in the coming years. However, the remaining third said they are unsure how they can use AI and big data in their organisation.

Respondents were also asked where they see the greatest potential for AI and big data to enable innovation in life sciences over the next 10 years.

The overwhelming majority of respondents said they see high potential for AI and big data to enable optimising data and supporting clinical trials (90%), drug discovery (87%), digitalising pathology images (85%), and digital therapeutics – i.e. apps or software (81%). In addition, 63% said they expect it to enable innovation in operations and finance, such as in demand planning, sales and cash flow in the next 10 years.

Asked what could be the single most important change to accelerate longer term innovation in life sciences, one legal counsel at a generic medicines manufacturer in Germany said "IT and artificial intelligence", while a medical director of a Spanish biotech company said "machine learning and artificial intelligence could accelerate innovation a lot".

However, 67% of those surveyed by Meridian West say that data handling and cybersecurity impedes the use of AI and big data in their organisation. In addition, half of the respondents said that a disconnect between the skills and understanding of technology experts and the life science leadership could impede the use of AI and big data in the sector.

AI in healthcare today

Many of the use cases to-date have been focused on bottlenecks and non-clinical processes. Sanofi's partnership with Google to integrate AI into its operations – from developing a better understanding of diseases and patients' experiences to forecasting sales and optimising marketing and supply chain activities – is an example of this. The company has also deployed the technology to inform its recruitment strategy.

A number of organisations have explored the use of AI as a tool to improve disease diagnosis. For instance, Tencent partnered with Medopan in 2019 to trial the use of AI in diagnosing patients with Parkinson’s disease, while Merck entered into an agreement with Janssen last year to develop an AI-based diagnostic tool to improve the detection of the so-called "Neglected Tropical Diseases". The partnership between a number of NHS trusts and DeepMind, now Google Health, since 2016, has enabled doctors to use the power of AI to better diagnose diseases too.

AI has been found to have utility in the field of drug discovery as well. According to data analytics and consultancy business GlobalData, "AI has the potential to dramatically reduce the time and expense of taking a drug to market and can also improve the probability of a drug’s approval".

Exscientia is a prime example of an innovator in this area. It claims that its AI helps cut the typical time it takes to identify new medicines from five years to one, with a knock-on reduction on drug development costs of more than 30%. It has discovered four pre-clinical drug candidates, and last year announced the first drug designed by AI in partnership with Sumitomo Dainippon Pharma to enter human trials. The company recently raised around $100 million in a latest funding round and has collaborated with Bayer, Roche, Celgene, Sanofi, GSK and Evotec.

The number of such partnerships between AI companies and major pharmaceutical manufacturers in the field drug discovery is on the rise, according to GlobalData – its study into the state of the biopharmaceutical industry, published in January this year, reported that the number of such partnerships has risen from four in 2015 to 27 by mid-December 2020.

AI is also being deployed in the fight against Covid-19. The UK's medicines regulator, the Medicines & Healthcare products Regulatory Agency (MHRA), last autumn awarded a contract to GenPact UK to develop AI technology to enable it to process "the expected high volume of Covid-19 vaccine adverse drug reactions". In addition, Oxford-based clinical AI company, Sensyne Health, launched a smartphone app to help automate the reading and analysis of lateral flow tests, such as those used for Covid-19. Eli Lilly accelerated research on a medicine in the pandemic after an AI analysis made the case for the drug.

The full range of possibilities that AI offers to healthcare in future cannot be imagined, but investment in this area is continuing all the time along with technological advances. In just one project, GSK, AstraZeneca and the NHS are working with chip maker Nvidia to build the UK's most powerful supercomputer and dedicate its use to AI research in healthcare, while further sophistication of AI is expected to drive the use of robots in the care setting, with developments already in this area in Japan and Germany to report.

Shorter term, AI and big data are the technologies expected to have the biggest impact on the pharmaceutical industry in 2021, according to a survey GlobalData carried out in late 2020 with 198 senior leaders in the industry from around the world, including C-suite executives. The widespread development of 5G networks is also anticipated to be an enabler of developments in digital healthcare increasing data availability which, in turn, will drive innovation in AI.

The skills gap

The Pinsent Masons study also found that, while access to funding was most commonly identified by the interviewees as the biggest barrier to innovation in life sciences, a lack of digital skills and talent is also a concern of industry. One chief risk officer active in the sector in Ireland said that "expertise is the single biggest barrier".

Many respondents said that their approach to long-term innovation involves addressing skills gaps and securing talent. One legal counsel for a generic medicines manufacturer in the UK specifically identified their plans to "invest in innovative researchers", while a chief medical officer at a biotech company in France said they were "looking forward to new researchers coming out of universities".

The results from the GlobalData survey support the findings of our study. Nearly half of those respondents (46%) said that a lack of specific skills and talents hinder digital transformation and technologies uptake in pharma, which was the most common hindering factor identified ahead of organisational silos, insufficient funding, legacy systems and risk-averse culture.

The future

While the use of AI in life sciences and healthcare continues to increase, it is clear that the sector has been slower to have embraced these technologies than other industries.

Legal and regulatory challenges must be overcome, from questions of liability if things go wrong, to addressing the risk of discriminatory outcomes as a result of inaccurate data or inherent bias in algorithms. Compliance with data protection laws remains a core challenge for businesses seeking to win public trust in the use of new technologies such as AI, while companies will be keen to track whether potential reforms to UK intellectual property laws to account for AI materialise and provide fresh incentives for investing in research into innovative new uses.

The skills gap is another significant barrier to harnessing the potential of AI. The new immigration rules that apply in the UK post-Brexit must be understood by the sector if it wants to attract talent from outside of the UK.

However, there is a real opportunity for the life sciences and healthcare sector to build on the positive attention it has received as it has come together in an unprecedented manner and at record speed to collaborate and innovate during the coronavirus crisis. There is an inspiring story to tell and employers should use the narrative to attract the next generation of talent – with all the digital skills they possess – to the sector. This will help drive AI-related innovation and efficiencies to the benefit of patients, healthcare providers and taxpayers, as well as life sciences companies themselves and their investors.

Pinsent Masons is partnering with the Digital Leadership Forum to establish a new programme of online training to investigate the opportunities AI can provide for leading organisations in the pharmaceutical and digital health sectors to optimise operations, support clinical research and accelerate drug discovery. To sign up for the first session in our AI Healthcare Leadership Academy, taking place on Thursday 1 April at 10am, please register your interest here.