The margin for error in scientific communications during a launch is quite small. Categories are crowded, the content environment is noisy and budgets rarely stretch as far as the ambition behind them. Medical Affairs is responsible for the scientific groundwork that enables a successful launch and has to get the narrative right from the start.
This is all happening as the evidence needed to support a product’s value narrative grows in both volume and complexity while clinicians have less time to read it and more content competing for their attention. Peer-reviewed data remains the gold standard for healthcare professional decision making, and that places considerable weight on which scientific themes are communicated and which channels carry them.1
Analytics can inform both but only if they come early enough to make a difference. Counting publications and congress sessions afterward says very little about whether the evidence communicated landed with its intended audience. That is why we have been building toward what we call Return on Intelligence: analytics that both shape a communications strategy from the outset and track scientific impact as it develops instead of judging it after the fact. Commercial teams have long worked to a return on investment. Medical Affairs cannot tie its work to revenue and should not try. It can, though, hold itself to a parallel standard.2
Of the measures already in common use, Share of Scientific Voice™ is the most familiar. It captures how much of a category’s scientific conversation a product occupies, measured across the publications, congresses and expert commentary that make up the scientific record. Share of Sentiment sits alongside it, tracking whether those mentions are positive, neutral or negative for a given product and theme. Read together, the two show both how much of a theme a product owns and how that presence is being received.1,3
Working out which themes are worth measuring is a separate problem. A Boolean literature search will find only themes you already know. Large language models and term frequency-inverse document frequency (TF-IDF) analysis work the other way around. Applied to a body of scientific evidence, they surface the themes that actually define a category, and those themes then become the basis for measurement. The resulting map is what we call an evidence Themeprint, a distinctive pattern of themes that identifies a product’s position in the literature in much the way a fingerprint identifies a person.1
Sentiment invites skepticism, and reasonably so, since science rests on objectivity, evidence and rigorous method. Sentiment enters through interpretation, in how a finding is read, repeated and qualified across the literature, and this is something we can measure. Set against an assessment of how rigorous the underlying work is, it also shows how much weight a given position actually carries.1,4
Take rare disease, where scarcity shapes everything. Before 2019 there were no approved pharmacologic treatments for transthyretin amyloid cardiomyopathy (ATTR-CM). A ten-year view shows the scientific conversation peaking around Phase III results, regulatory milestones and long-term data. Theme-level analysis exposes the strategy underneath those peaks. Three positions separate out. The originator kept generating outcomes and long-term safety evidence even after attention moved elsewhere. The first challenger built its narrative far more heavily on mechanistic differentiation. The newest entrant is still establishing and validating its own mechanism of action, so its themes have yet to settle.1
Once a category fills up, the difficulty inverts, as it has in atopic dermatitis, where several products sustain a high share of voice and neither voice nor overall sentiment separates one narrative from another. Differentiation appears at theme level instead, across treatment switching, itch and pain relief, speed of onset, long-term efficacy and safety. Comparing three-year performance against the most recent year then shows where each theme is heading.1
That analysis reveals two findings that can be planned against. Emerging areas of differentiation surface as evidence accumulates, often ones a product has not yet claimed. Sentiment is never uniform across a category, either, and the themes where it thins offer a later entrant an opening. Taking that opening well is a matter of scientific stewardship, which means defining the asset around the category’s unanswered questions and then generating evidence into that space because it serves patients and clinicians, not because it is commercially convenient.
None of that settles how the science reaches its intended audiences, and different scientific themes do not all travel through the same channels. The experts leading discussion on disease progression are not always those focused on long-term safety and efficacy, and the journals and congresses that carry each aspect of a disease differ accordingly. Mapping channel and expert against theme turns a narrative strategy into a plan and gives Scientific Communications teams something concrete to measure against competitors.1
Any such map now has to extend to digital and social channels as well. Digital opinion leaders sit alongside traditional key opinion leaders. Some carry considerable reach without a comparable evidence base behind them, and while that is not a standard Medical Affairs would endorse, it still shapes what clinicians encounter. Knowing who those voices are, and what they are claiming, is part of stewarding the scientific record.
The same goes for the AI tools clinicians increasingly query directly. When a clinician puts a question to a large language model, the answer is assembled from what has been published and how rigorously the work was done. In one competitive assessment, a tool of exactly that kind was sharply critical of a newer entrant’s evidence. Weak evidence no longer sits quietly in the literature, because these tools surface and judge it. Rigor is now a question of distribution as much as of science, and stewarding it well is what keeps the scientific record worth trusting.
Tracking sentiment among named experts over time reveals something we have started to call “network drift.” In one category we examined, a group of experts who had been consistently supportive of an established therapy cooled toward it once a competitor entered. Their sentiment moved toward the newcomer, endorsing its mechanistic plausibility well before anyone had shown what that improved mechanism of action meant clinically against the standard of care. That is an actionable early signal because it identifies precisely to whom field medical teams should be talking and what those conversations need to establish.
It is worth knowing, too, what general-purpose AI assistants cannot see, since teams under pressure increasingly reach for them. Those tools tend to look at published literature alone, leaving out congress material that can add substantially to the evidence base in an active category. Across 307,028 abstracts from biomedical meetings, only 37.3% were ever published in full, so a large share of what is presented at congresses never reaches a tool that reads journals alone.5
For all the analysis involved, none of this works as an off-the-shelf deliverable. It takes the data, analytical tooling and people who have done the job and can translate between a data set and a communications strategy. It also takes a client willing to build something rather than just place an order.
Smaller teams have as much to gain from that as enterprise brands — arguably more. When a budget covers only a few programs, being able to defend why you chose those programs and not others is worth a great deal, and being able to track whether the choice was right is worth more still.
Scientific communications has always run on judgment. That judgment can now be evidenced, tested against the landscape as it shifts and corrected while a correction still counts. Done well, that is what scientific stewardship looks like in practice.
Leverage integrated evidence generation, dissemination, and analytics to transform data into trusted scientific insight—driving informed stakeholder dialogue and accelerating progress toward better patient outcomes.
.svg){kind=icon}
