Learn how Medical Affairs teams using governed AI tools are able to meet increasing plain language summary (PLS) expectations without scaling budgets.
Medical publishing has a readability problem, and the numbers are stark. Of the millions of articles indexed in PubMed, just 61 per million include a plain language summary, according to research presented at ISMPP Europe 2022. That's 0.006% of medical literature written in a way patients can actually understand.
The pharmaceutical industry talks constantly about patient-centricity. But the scientific evidence supporting our medicines remains largely inaccessible — buried in jargon, dense statistics, and academic formatting conventions that shut out the very people these treatments are meant to help.
That's starting to shift. And Medical Affairs teams that don't prepare now will find themselves playing catch-up.
In January 2025, the European Union's Clinical Trial Regulation (EU-CTR 536/2014) reached its final implementation milestone: every active trial must now be managed through the Clinical Trials Information System (CTIS). Among its requirements: every clinical trial conducted in Europe must now include a plain language summary of results, written at a 6th-8th grade reading level, following detailed Good Lay Summary Practice guidelines.
This isn't a suggestion. It's a mandate. Sponsors must submit these summaries through the CTIS within 12 months of trial completion (six months for pediatric trials). The regulation specifies 10 required elements, from trial identification to adverse event descriptions to implications for the public.
The rationale is straightforward: patients who volunteer for clinical trials deserve to understand what their participation revealed. Transparency builds trust. Informed patients make better healthcare decisions.
Here's what Medical Affairs leaders should be asking: If this logic applies to clinical trials, why wouldn't it apply to publications?
The same patients reading about a Phase III trial on ClinicalTrials.gov will search for the published results in peer-reviewed journals. The same advocacy groups pushing for trial transparency are watching what happens when that data reaches publication. The same regulators who mandated lay summaries for trials are observing how the industry treats accessibility in its broader scientific communications.
→ Evaluate your Medical Affairs team's current PLS capabilities. Take our PLS Readiness Assessment to identify gaps before they become problems.
"There is a growing demand of patients and nonspecialists to understand the potential implications of clinical and medical research," notes Thomas Schindler in the AMWA Journal. This isn't abstract. Patient advocacy groups are increasingly sophisticated, increasingly vocal, and increasingly influential in regulatory and HTA discussions.
Research validates their push. A randomized trial published in the Journal of Clinical Epidemiology found that plain language formats improved understanding by approximately 20%, significantly increased reader satisfaction, and made people more likely to act on health information. Plain language isn't just a nice-to-have. It changes behavior and outcomes.
The CDC puts it bluntly: "Choosing to use jargon is an act of exclusion."
The infrastructure for plain language summaries in publications is expanding rapidly. More than 250 medical journals now facilitate PLS, up from around 50 just a few years ago. Taylor & Francis, SAGE, and other major publishers have created standalone Plain Language Summary of Publication (PLSP) article types with their own DOIs. The ICMJE now recognizes PLSPs as "Acceptable Secondary Publications."
Some companies aren't waiting for mandates. Ipsen committed in 2022 to publishing plain language summaries alongside all company-sponsored journal publications from human studies, the first pharmaceutical company to make such a comprehensive pledge.
Here's the uncomfortable truth: even organizations that produce plain language summaries often produce poor plain language summaries.
A study of over 1,200 plain language summaries from the UK's National Institute for Health Research found an average Flesch Reading Ease score of 39, well below the 60-70 range considered accessible to general audiences. Only 2.8% met the standard for "plain English." Not a single one achieved readability levels matching the average reading age of the UK population.
This isn't a failure of intent. It's a failure of execution at scale.
Let's be honest about the challenge facing Medical Affairs teams.
The scope of Medical Affairs responsibilities has expanded dramatically: publication planning, MSL programs, medical information services, KOL engagement, real-world evidence generation, medical education, HTA support, scientific communication, pharmacovigilance collaboration. The function has evolved from a support role to a strategic pillar, yet budgets haven't always kept pace.
Now add "produce high-quality plain language summaries for every publication" to that list.
The math is daunting. Creating quality PLS isn't simple work. As one industry guide notes: "The biggest misconception about PLS is that because they are easy to read, they should be easy to write. This couldn't be further from the truth."
Effective plain language summary writers need to:
Medical writers with this specialized skill set are in short supply. Translation needs multiply the burden for global organizations. And every hour spent on PLS is an hour not spent on other Medical Affairs priorities.
The industry faces a choice: dramatically increase Medical Affairs budgets, accept that plain language summaries will remain rare, or find a way to fundamentally change the efficiency equation.
Before exploring how AI changes the equation, it's worth taking stock of your current PLS capabilities.
Our Plain Language Summary Readiness Scorecard helps Medical Affairs teams identify gaps in coverage, capacity, and workflow integration — so you know where to focus.
Take the 2-minute assessment →
Large language models have matured to the point where they can meaningfully address this challenge.
The evidence is compelling. Research published in Nature Digital Medicine found that LLM-generated clinical summaries achieved strong inter-rater reliability with human expert evaluators. Physician assessments of AI-generated summaries consistently rated them "Very Good" or "Excellent." And the efficiency gains are striking: AI completed evaluations in 22 seconds versus 600 seconds for human reviewers, a 27x improvement.
Studies of LLMs in healthcare applications highlight their particular strengths in exactly the capabilities PLS demands: converting complex technical content to accessible language, maintaining scientific accuracy while simplifying structure, and operating at scale with consistency.
This doesn't mean AI replaces human judgment. Research on generative AI for plain language medical information appropriately flags risks including potential oversimplification and the need for accuracy validation. Medical review remains essential. The ethical principles governing PLS (accuracy, impartiality, scientific integrity) require human oversight.
But AI fundamentally changes what's possible. Instead of Medical Affairs teams starting from a blank page for every publication, they can start from a high-quality first draft. Instead of PLS being a luxury reserved for priority publications, it becomes a scalable standard operating procedure. Instead of choosing between accessibility and resource constraints, teams can pursue both.
The BP Logix team has spent years working with Life Sciences Medical Affairs teams on the unique challenges of managing complex, regulated workflows through our PubPro platform. When EU-CTR created the plain language summary mandate for clinical trials, we saw both the precedent being set and the resource challenge it would create as expectations expanded to publications.
Our response has been to build plain language summary generation directly into the publication management workflow. Not as a separate tool, but as an integrated capability within the systems Medical Affairs teams already use.
What this means in practice:
We call our AI capabilities Approvia AI. For plain language summaries specifically, the goal is straightforward: make it operationally feasible for Medical Affairs teams to meet rising accessibility expectations without breaking their budgets or their teams.
The direction here is unmistakable. EU-CTR proved that regulators will mandate plain language accessibility when transparency is at stake. Patient advocates are paying attention. Publishers are expanding their PLS infrastructure. Industry leaders are making public commitments.
Plain language summaries for publications aren't a matter of if — they're a matter of when. The real question is whether your organization will lead or scramble to keep pace.
Medical Affairs teams that address this challenge now will position their companies as genuinely patient-centric — not just in messaging, but in practice. They'll develop the operational capability for accessibility before it becomes a requirement. And they'll do it sustainably, using AI to amplify what their teams can deliver rather than simply adding headcount.
Request a demo today to see how we integrate PLS generation directly into PubPro.