AI and the Copyright Question for R&D

The Pistoia Alliance, in conjunction with the copyright legislation specialists the Copyright Clearance Center (CCC), has announced the results of a global survey on the impact of AI and copyright legislation on pharma R&D. According to the report, titled “Are Misaligned Incentives Preventing Better Patients In Life Sciences R&D?”, 83 percent of life science professionals are now using generative AI in their research, but concerns about the impact of disparate AI regulations remain. Around 42 percent of respondents said they don’t think about copyright before sharing or using third-party information with AI. 

Becky Upton, President of The Pistoia Alliance, said, “AI is fast becoming commonplace in R&D, yet a fifth of researchers are still not using the technology. The best way to overcome any lingering adoption hurdles is together. We must ensure those remaining researchers have the confidence and expertise to use AI safely, so they can accelerate discovery, and enable better outcomes for patients. Whether it’s copyright compliance, broader AI regulation ambiguities, or data standardization, the Alliance is committed to launching projects that will deliver a tangible impact to the life science industry. As 2025 approaches, we are keen for new project suggestions and are looking forward to broadening the Alliance’s reach even further, with more research and projects, and involving more global regulatory agencies in our communities.”

The report explores the challenges and opportunities in the pharmaceutical and biotech industries, focusing on integrating human health data to improve R&D and patient outcomes, with key points including the seamless integration of research, clinical, and real-world data to enable personalized medicine and innovative drug development, and the potential applications in AI-driven drug discovery.

The technical challenges highlighted in the report include the fragmentation of data systems, a lack of interoperability, and the integration of legacy systems and diverse data formats. Such challenges could generate misaligned incentives within and between organizations, data sharing adversities, and inconsistent data privacy laws hindering collaboration.

The economic challenges found were considered to be caused by inefficiencies in R&D processes, including long drug development timelines, high costs, and low success rates. Better data integration could significantly reduce these inefficiencies, the report suggests, and other recommendations for change include the fostering of cross-functional and cross-industry collaboration with standardized data formats and FAIR principles (Findable, Accessible, Interoperable, Reusable), as well as investments in modified data infrastructures and AI technologies. 

Stakeholders, regulators, and patient advocacy groups are advised to collaborate on data integration initiatives, whilst leveraging existing technologies and data for better patient outcomes.