Elsevier supports Pistoia Alliance to accelerate AI adoption

Elsevier has announced a commitment to support global not-for-profit organisation The Pistoia Alliance, which advocates for greater collaboration in the life sciences.

The commitment sets out to address common challenges in AI adoption facing the pharmaceutical and research community. Elsevier will provide expertise through a joint program of events for Pistoia’s 200+ member organisations, which include top pharmaceutical, biotech, healthcare and R&D organisations as well as regulators. Elsevier has supported the Alliance for more than a decade, helping to equip organisations with the capabilities and tools needed to harness the full potential of AI for effective and efficient drug discovery, in a safe and ethical manner.

The announcement follows Elsevier's recent Attitudes to AI report, which found widespread willingness among corporate researchers to use AI tools, but also concerns about associated risks, such as misinformation, critical errors, and gaps in critical thinking. These concerns are echoed in The Pistoia Alliance’s recent Lab of the Future Report, which also uncovered demand for more educational resources, such as ontologies training – an area of specialism for SciBite, an Elsevier company.

Drawing on these insights, Elsevier has identified the following five key areas for advancing greater AI adoption in drug discovery:

1. Securing trustworthy data – Robust data sourcing drives accurate and effective research results.
2. Structuring data to reveal insights – Leveraging the FAIR data principles and ontologies transforms complex scientific data into accessible and contextualized knowledge structured for AI.
3. Transparent AI – Retaining human oversight and implementing Retrieval-Augmented Generation (RAG) architecture overcomes the issue of 'black box' AI systems and drives transparency and credibility in AI outcomes.
4. Unified governance – Research professionals and legislators must be aligned to effectively navigate AI regulations, such as the new EU AI Act.
5. Bridging the skills gap– Many organizations still cite the lack of internal skills as an AI barrier, accessing a combination of scientific expertise with data science and tech knowledge.

Mirit Eldor, Managing Director, Life Sciences Solutions, Elsevier, said: "The Pistoia Alliance continues to be the ideal forum for productive collaboration. It is clear that coming together to share learnings and best practices can help all navigate the challenges of overcoming data barriers in the life sciences. Ultimately, our goal is to remove barriers so that we can realise the full potential of AI in accelerating the development of safe and effective therapies. We're delighted to continue playing our part in this ecosystem, building on Elsevier’s long history of data expertise to further support the Alliance’s members and the broader R&D community.”

Dr. Becky Upton, President of the Pistoia Alliance, said, "Elsevier and Pistoia Alliance’s recent surveys find there is a drive among researchers to adopt AI. Yet, data from both studies also show that life science organisations are still grappling with challenges ranging from access to data to building trust in AI tools. Elsevier has been a valued member of the Alliance since 2015 and has actively contributed to impactful initiatives that are shaping the future of our industry. The Pistoia Alliance will continue to work with its members to provide tangible deliverables to the life sciences community to help them address these AI challenges.”