AI agents for HEOR and market access
Every new indication and every new market triggers another systematic review, and the launch timeline does not have the months. TrialMind screens at published accuracy with PRISMA-compliant output and a traceable rationale for every inclusion and exclusion — because HTA bodies audit your method, not just your conclusion — and the evidence base is reusable, so the next market is incremental.
Templated by jurisdiction, which is exactly what automates well
Reviews that keep pace with launch
Every new indication and every new market triggers another systematic review, and each one takes months the launch timeline does not have. Screening runs at published accuracy with PRISMA-compliant output — the review is executed, not merely tracked.
An evidence base you reuse, not rebuild
Cost-effectiveness and budget-impact models get rebuilt per jurisdiction from largely the same evidence. TrialMind keeps the evidence base reusable and updatable, so an additional market or a refreshed review is incremental work rather than a fresh start.
One traceable chain across the dossier
Evidence synthesis and real-world analysis stop being two disconnected workstreams. The same platform runs the literature review and the real-world analyses feeding the same submission, in a single chain a reviewer can follow.
Method that survives the audit
Payer evidence requirements keep expanding and every jurisdiction asks differently. What does not change is that the method gets examined.
A rationale for every screening decision
Each inclusion and exclusion carries a traceable, reproducible reason. HTA bodies audit method, not only conclusions, so this is the requirement rather than a nice-to-have.
Built to each jurisdiction's format
NICE, G-BA, CADTH, HAS, and PBAC each want the dossier assembled their own way. Output adapts to the format rather than producing something generic to be reworked.
Reproducible on demand
When a reviewer asks how a study entered or left the review two years later, the answer is recorded rather than reconstructed.
Why not just use a general-purpose model?
An analyst with a general-purpose model can screen abstracts quickly. The difficulty is not speed — it is producing a reproducible rationale for every inclusion and exclusion that will still stand up when an HTA reviewer examines the method rather than the conclusion.
Pick a review you are about to start and run it alongside your usual process. Comparing both against the same PRISMA output is the fairest test we can offer.
Frequently Asked Questions
Will an HTA body accept a review screened this way?
HTA bodies audit method. Every inclusion and exclusion carries a traceable, reproducible rationale, the output is PRISMA-compliant, and the underlying screening accuracy is published in the peer-reviewed literature — so the method can be described and defended rather than asserted.
How is this different from the reviews our competitive intelligence team runs?
Different buyer, different output, and we do not treat them interchangeably. Reviews here feed payer dossiers and get audited by HTA bodies for method. Competitive-intelligence reviews inform portfolio and R&D strategy decisions and are built to a different standard of evidence.
Do you handle indirect treatment comparisons?
Yes. Where no head-to-head trial exists, TrialMind supports building the indirect comparison and documenting the method behind it, which is the part that has to survive scrutiny.
What happens when we take the same product to another market?
The evidence base is reusable and updatable. A new jurisdiction means adapting to its dossier format and adding what is missing, not starting the review from scratch — which is where most of the months currently go.
Can it run the real-world analyses in the same dossier?
Yes, on the same platform and in the same traceable chain. That is the point of running evidence synthesis and RWD analysis together rather than as two disconnected workstreams handed between teams.
Where does our data go?
TrialMind deploys into your environment and runs where your data already lives. Raw records never move, which is what makes governance and privacy review passable.
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