AI is already at the heart of the pharmaceutical industry, but budgets and expertise are needed
Artificial intelligence is a “priority” for 78 per cent of companies when it comes to improving the recruitment of healthcare professionals and for 48 per cent in supporting research, but limitations remain
Key points
Almost 8 out of 10 pharmaceutical companies now regard artificial intelligence as a strategic priority for improving engagement with healthcare professionals, whilst in around half of them, AI is fully integrated into new drug discovery processes and clinical trials. And when it comes to generative AI, there is a rise in both the use of commercial platforms – such as ChatGPT, Copilot and Gemini – with corporate accounts, and in solutions developed specifically for individual companies, which have increased from 36 per cent to 76 per cent.
A bespoke budget is needed
The latest research from the Life Science Innovation Observatory at the Politecnico di Milano, which will be presented on 16 September in Milan during the conference ‘AI and Digital Technology in Life Sciences: Creating Value Beyond Experimentation’. However, the progress highlighted by the survey has yet to be consolidated, given a number of critical issues. First and foremost, the existence of a specific centralised budget is still limited to less than a third of companies (27 per cent), whilst in 50 per cent of cases no dedicated budget is allocated. This is a weakness: “Whilst it is true that digital technologies – and AI in particular – are increasingly integrated and regulated within the life sciences ecosystem, we must ensure that resources are allocated within a specific budget and not ‘buried’ amongst the various expenses available to a business function,” comments the Observatory’s director, Chiara Sgarbossa.
Tailor-made training
Another area requiring attention is skills: whilst 83 per cent of companies have trained their staff on the opportunities offered by AI and the use of Generative AI, in most cases this ‘training’ only covers certain roles and is not particularly tailored. Furthermore, collaboration between pharmaceutical companies and the public sector in the development of digital solutions remains limited (24 per cent). These factors – with their mixed picture – have been incorporated by the Observatory into a ‘maturity’ matrix, developed in collaboration with the companies themselves and Farmindustria, which breaks down the relationship between the pharmaceutical industry and digital innovation into five areas: strategy, culture and skills; digital and AI governance; digital technology for clinical trials; digital innovation in the relationship between the pharmaceutical industry and doctors; and ‘beyond the pill’ services, ranging from Real World Evidence databases to new digital therapies.
A leap forward for ‘dedicated’ AI
As mentioned, AI is now an investment priority for pharmaceutical companies: 78 per cent consider it strategic for strengthening engagement with healthcare professionals, and 48 per cent for supporting the discovery of new drugs, as well as (56 per cent) the collection of real-world data. The ‘importance’ of other areas is more limited: summary data (37 per cent), ‘in silico’ trials (30 per cent), digital therapies (26 per cent) and health apps and sensors (11 per cent). Barriers to innovation include the reported difficulty in quantifying the benefits of investment (52 per cent), a lack of suitable skills (52 per cent) and complex regulations (48 per cent). However, the responsible use of AI is on the rise: almost half of companies (48 per cent) have introduced global policies for the ethical use of artificial intelligence, and a further 40 per cent have adapted these policies for global use. The surge to 76 per cent in the adoption of dedicated AI solutions is seen as one of the key indicators of maturity, particularly in terms of security and data management.
Research: AI ‘in progress’
As for digitalisation in clinical trials, 64 per cent of companies are still at ‘level 2’ (out of a total of four) of digital maturity, whilst the generation of synthetic data and the creation of synthetic control arms – adopted by 20 per cent of companies – remain at the cutting edge. However, the figure of 70% for the use of AI in the search for and analysis of scientific literature remains unchanged, whilst around half of the companies using AI design their trials.

