OpenEvidence was one of the most talked-about topics at ISMPP Annual 2026, sparking debate about how retrieval‑augmented AI could change the way biomedical research is discovered, interpreted and used at the point of care. In this article, we reflect on the insights we heard at ISMPP Annual, outline the questions that remain unanswered and consider the impact for open, trustworthy communication of pharma‑sponsored research.
What is OpenEvidence and why the buzz?
OpenEvidence is a clinician-facing artificial intelligence (AI) knowledge platform that, in the words of founder Daniel Nadler, “help[s] physicians make high-stakes clinical decisions at the point of care”.1 Trained on peer-reviewed content from its partner publishers and organizations – including the New England Journal of Medicine, the Cochrane Database of Systematic Reviews and Clinical Answers, JAMA Network, the National Comprehensive Cancer Network Guidelines and Wiley2–5 – OpenEvidence provides evidence-informed answers to clinical questions for healthcare professionals registered in the USA and is free to access, supported by advertising and venture capital backing.
James Phimister’s (Strategic Advisor to the CEO, National Partnerships at OpenEvidence) keynote titled AI, evidence, and the future of clinical knowledge: how information reaches the point of care at the 2026 Annual Meeting of the International Society for Medical Publication Professionals (ISMPP) became a focal point for broader discussions about how AI‑enabled tools are reshaping the translation of the ever-expanding evidence base and rapidly evolving treatment guidelines into clinical decision‑making. Rather than expecting clinicians to search, read and synthesize multiple sources themselves, retrieval-augmented AI tools such as OpenEvidence aim to surface published data from reputable sources to support clinically relevant, evidence-informed decision-making on demand.
Could retrieval-augmented AI reshape medical publishing?
Alongside general curiosity about OpenEvidence, our conversations around ISMPP Annual repeatedly returned to broader uncertainty about what retrieval-augmented AI could mean for the future of medical publishing and research communication across therapy areas and geographies.
If clinicians increasingly encounter research through AI‑generated summaries rather than directly through journal platforms, how might that change what it means for research to be discoverable, credible and influential? What role do licensing agreements, publisher partnerships and content formats play in determining which evidence is summarized and, ultimately, translated into clinical practice? We know OpenEvidence draws on trusted and reliable sources; however, without access to every journal publishing biomedical research, how can we be confident the generated summaries are truly representative of the full evidence base? In addition, does the hierarchy used to evaluate the clinical relevance of the source guidelines, systematic literature reviews and phase 3 clinical trials risk devaluing real-world evidence publications?
These questions represent only some of the considerations around transparency and publication bias that emerged during our discussions at ISMPP Annual. Taken together, they highlight the need for ongoing cross‑stakeholder dialogue as AI‑enabled platforms continue to evolve and mature within the medical ecosystem.
What does this mean for Open Pharma?
Open Pharma exists to enable the transparent, trustworthy and accessible communication of pharma‑sponsored research, which naturally extends to improved patient care. OpenEvidence provides just one example of why the mission of Open Pharma is more relevant now than ever; when new mechanisms reshape how research evidence is translated into clinical adoption and decision-making, we must come together to continue our drive towards transparency and trust in pharma-funded research.
We encourage our Members, Supporters and Followers to engage with these questions alongside us by sharing your experiences, challenges and emerging practices as we continue to explore what platforms like OpenEvidence mean for medical publishing and research communication.
References
- CNBC. OpenEvidence, the ‘ChatGPT for doctors,’ doubles valuation to $12 billion. 2026. Available from: https://www.cnbc.com/2026/01/21/openevidence-chatgpt-for-doctors-doubles-valuation-to-12-billion.html (Accessed 6 May 2026).
- Wiley. Wiley and OpenEvidence partner to deliver trusted research to physicians at the point of care. 2026. Available from: https://newsroom.wiley.com/press-releases/press-release-details/2026/Wiley-and-OpenEvidence-Partner-to-Deliver-Trusted-Research-to-Physicians-at-the-Point-of-Care/default.aspx (Accessed 6 May 2026).
- EMARKETER. OpenEvidence strikes content partnership deal with JAMA to improve its AI medical search platform for doctors. 2025. Available from: https://www.emarketer.com/content/openevidence-strikes-content-partnership-deal-with-jama-improve-its-ai-medical-search-platform-doctors- (Accessed 6 May 2026).
- Medical Economics. Clinical AI platform to be trained on 30 years of NEJM archives. 2025. Available from: https://www.medicaleconomics.com/view/clinical-ai-platform-to-be-trained-on-30-years-of-nejm-archives (Accessed 6 May 2026).
- National Comprehensive Cancer Network. NCCN and OpenEvidence collaborate to bring clinical oncology guidelines to medical AI. 2025. Available from: https://www.nccn.org/home/news/newsdetails?NewsId=5283 (Accessed 6 May 2026).
The views expressed in this blog post are those of the author(s) and do not necessarily reflect those of Open Pharma or its Members and Supporters.
Note: On 27 April 2026, OpenEvidence withdrew access for domains in the European Union and United Kingdom, citing “mounting regulatory uncertainty regarding the treatment of AI systems” under the EU Artificial Intelligence Act.
