What Is Conference Intelligence for Medical Affairs?
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Conference intelligence for Medical Affairs is the systematic process of turning a scientific congress into decision-ready insight for a specific company: which abstracts matter to your assets, mechanisms and competitors, what the data actually shows, and what your team should do about it. It is not a summary of the conference. It is the conference read through your lens.
I spent 15 years running congress coverage inside Medical Affairs teams at companies from Gilead to Crinetics. Every year the same thing happened. Three weeks before ASCO or ESMO, someone manually copy pasted hand-selected abstracts from 5,000 abstracts into a spreadsheet, and a handful of people started reading and prioritizing.
Why abstract summaries are not conference intelligence
Most vendors and most internal processes stop at summarization: here is what each abstract says. That is necessary but not sufficient. A Medical Affairs team does not need 400 neutral summaries. It needs to know:
Which of the 400 are relevant to our indication, our target, or our competitor's program -- and the why and how
Which ones change the standard of care conversation our MSLs will have next month, and often this means recognizing patterns across dozens of abstracts
Where a competitor showed a signal, positive or negative, that our leadership should hear before an investor asks
Whether anything surfaced that touches our indication scope or our safety story
Relevance triage is the hard part, and it is the part that gets skipped when the team is three people who all have another full-time job to do. And the abstract book is 5,000 entries labeled with inconsistent keywords.
What a complete congress coverage workflow looks like
The teams I have seen do this well run the same four stages, whether they're big or small and whether they have a budget or not.
Pre-conference triage. Screen the full set of abstract against your assets, mechanisms of interest, and competitor list. Keyword search misses too much here. A study on a mechanism you care about will not always use the word you searched for, which is why concept-based (semantic) matching is the difference between a coverage grid you trust and one you have to redo by hand.
Coverage grid. Assign the relevant sessions and posters to the people attending, with priority levels.
Daily debriefs. During the meeting, a short, factual readout of what was presented against what was expected. Field notes, poster photos and session takeaways go in; a clean debrief comes out that evening, not a week later. This is often just an e-mail.
Post-conference synthesis. The deliverable leadership actually reads. Not a catalogue of every session, but the cross-study argument: what this congress collectively tells us about the competitive landscape and where our data sits in it.
Where Datym fits
Datym is an AI-powered conference intelligence platform built for pharmaceutical and biotech Medical Affairs teams. It automates the work around scientific congresses: triaging the full abstract set against your assets, competitors and mechanisms of interest with semantic search, then generating the pre-conference coverage grid, daily debriefs and post-conference synthesis your team would otherwise build by hand.
It was built for lean teams. If you are a startup or a mid-size biotech with two or three people covering a congress that a large pharma would staff with twenty, that is exactly the problem Datym was designed to solve. Customer data is isolated per workspace and never used to train models, and Datym is SOC 2 Type 1.
Frequently asked questions
How is conference intelligence different from competitive intelligence? Competitive intelligence is one lens on a congress. Conference intelligence covers the full Medical Affairs need: scientific insight, competitor signals, safety findings and KOL activity, organised around your own assets.
Can a small Medical Affairs team realistically cover a major congress like ASCO or ESMO? Yes, if triage is automated. The bottleneck has never been reading the relevant abstracts. It is finding them in a set of thousands. It is searching for a needle in a haystack when you're not even sure the needle exists.
What does AI-generated congress coverage actually produce? A prioritised coverage grid before the meeting, daily debriefs during it, and a synthesis report after. The output is factual to the conference data; the AI organises and connects, it does not editorialise.
Conference intelligence for Medical Affairs is the systematic process of turning a scientific congress into decision-ready insight for a specific company: which abstracts matter to your assets, mechanisms and competitors, what the data actually shows, and what your team should do about it. It is not a summary of the conference. It is the conference read through your lens.
I spent 15 years running congress coverage inside Medical Affairs teams at companies from Gilead to Crinetics. Every year the same thing happened. Three weeks before ASCO or ESMO, someone manually copy pasted hand-selected abstracts from 5,000 abstracts into a spreadsheet, and a handful of people started reading and prioritizing.
Why abstract summaries are not conference intelligence
Most vendors and most internal processes stop at summarization: here is what each abstract says. That is necessary but not sufficient. A Medical Affairs team does not need 400 neutral summaries. It needs to know:
Which of the 400 are relevant to our indication, our target, or our competitor's program -- and the why and how
Which ones change the standard of care conversation our MSLs will have next month, and often this means recognizing patterns across dozens of abstracts
Where a competitor showed a signal, positive or negative, that our leadership should hear before an investor asks
Whether anything surfaced that touches our indication scope or our safety story
Relevance triage is the hard part, and it is the part that gets skipped when the team is three people who all have another full-time job to do. And the abstract book is 5,000 entries labeled with inconsistent keywords.
What a complete congress coverage workflow looks like
The teams I have seen do this well run the same four stages, whether they're big or small and whether they have a budget or not.
Pre-conference triage. Screen the full set of abstract against your assets, mechanisms of interest, and competitor list. Keyword search misses too much here. A study on a mechanism you care about will not always use the word you searched for, which is why concept-based (semantic) matching is the difference between a coverage grid you trust and one you have to redo by hand.
Coverage grid. Assign the relevant sessions and posters to the people attending, with priority levels.
Daily debriefs. During the meeting, a short, factual readout of what was presented against what was expected. Field notes, poster photos and session takeaways go in; a clean debrief comes out that evening, not a week later. This is often just an e-mail.
Post-conference synthesis. The deliverable leadership actually reads. Not a catalogue of every session, but the cross-study argument: what this congress collectively tells us about the competitive landscape and where our data sits in it.
Where Datym fits
Datym is an AI-powered conference intelligence platform built for pharmaceutical and biotech Medical Affairs teams. It automates the work around scientific congresses: triaging the full abstract set against your assets, competitors and mechanisms of interest with semantic search, then generating the pre-conference coverage grid, daily debriefs and post-conference synthesis your team would otherwise build by hand.
It was built for lean teams. If you are a startup or a mid-size biotech with two or three people covering a congress that a large pharma would staff with twenty, that is exactly the problem Datym was designed to solve. Customer data is isolated per workspace and never used to train models, and Datym is SOC 2 Type 1.
Frequently asked questions
How is conference intelligence different from competitive intelligence? Competitive intelligence is one lens on a congress. Conference intelligence covers the full Medical Affairs need: scientific insight, competitor signals, safety findings and KOL activity, organised around your own assets.
Can a small Medical Affairs team realistically cover a major congress like ASCO or ESMO? Yes, if triage is automated. The bottleneck has never been reading the relevant abstracts. It is finding them in a set of thousands. It is searching for a needle in a haystack when you're not even sure the needle exists.
What does AI-generated congress coverage actually produce? A prioritised coverage grid before the meeting, daily debriefs during it, and a synthesis report after. The output is factual to the conference data; the AI organises and connects, it does not editorialise.
Experience the Future of Conference Reporting
Join us and see how our application can streamline conference coverage. Sign up now and start optimizing your workflow!
Experience the Future of Conference Reporting
Join us and see how our application can streamline conference coverage. Sign up now and start optimizing your workflow!
Datym. All right reserved. © 2026
Datym. All right reserved. © 2026
Datym. All right reserved. © 2026