Enterprise · Pharmaceutical Companies
See how your medication really works
once it leaves the trial.
After a medication is approved, it's surprisingly hard to know how it's actually doing — who's still taking it, who's struggling, and whether it works as well in everyday patients as it did in the trial. MetAi follows real patients on therapy and tells you, continuously.
RWE Study Summary , GLP-1 Cohort 2024
Study cohort size6,990 membersCompleted
Weighted mean lean loss16.9%vs 25 to 39% published
Measurement frequency3× weeklyBIA methodology
Adherence documentationWeekly attestationRequired for inclusion
Data formatPublication-readyAvailable on request
Full methodology and de-identified dataset available , contact research@metai.health
Getting approved is half the job.
We help with the other half.
The problem
Getting a medication approved is only half the work.
Getting a medication approved is only half the work. The harder part comes next: showing it works for real patients, keeping people on it, and proving its value to the insurers who decide whether to pay for it.
You find out about problems too late
Today, safety issues get reported slowly — and usually only the serious ones. By the time a pattern is clear, months have already passed.
Patients quietly stop taking it
Many patients stop within months. You usually only find out when a refill doesn't happen — long after they'd already given up.
Proving value to insurers takes years
Insurers want proof the medication works for real-world patients — especially the older or sicker ones the trial left out. Building that proof the old way takes years.
Your teams only have trial data
The people who meet with insurers can only show trial results, not how the medication performs in everyday patients. That's a weaker case to make.
How it works
Reads. Synthesizes.
Acts.
How the synthesis layer works for a pharmaceutical company, step by step.
01
Reads
MetAi follows a group of real patients taking your medication — their body data, their lab results, and whether they're sticking with it.
02
Synthesizes
It spots the early warning signs: a safety pattern starting to form, a patient about to quit, or how the medication does in patients the trial never studied.
03
Acts
It flags those signals as they happen, and turns the results into clear evidence you can share with insurers and regulators.
The synthesis
What MetAi gives a pharmaceutical company
The cross-stream signals fragmented care cannot see in one frame — surfaced and ranked.
Early safety signals
Spot a safety pattern forming across patients weeks before it would show up in the official reporting system.
Catch patients before they quit
See who's likely to stop about a month ahead — and why (side effects, cost, or it isn't working) — so help reaches them in time.
Proof from real patients
Results in the older, sicker, and more complex patients insurers care about most — built continuously, not over years.
Ready to share
Findings organised so your teams can hand them to insurers and regulators without months of cleanup.
What you get
What a pharmaceutical company gets
Early safety warnings
Problems surfaced weeks earlier than the official reporting system would catch them.
Fewer patients quitting
Patients likely to stop are spotted about a month ahead, with the reason already attached.
Real-world proof
Results in the everyday patients — older, sicker, more complex — that insurers ask about.
Evidence that's ready to use
Findings organised for insurer and regulator conversations, not raw data to clean up.
The business case
Faster proof, more patients covered
The payoff shows up in three places: time, coverage, and how long patients stay on the medication.
Proof in months, not years
Following real patients continuously builds your evidence far faster — and costs far less than the old way of running studies.
Covered by more insurers
Strong real-world proof helps win coverage decisions — which means more patients can actually get the medication.
Patients who stay on it
Every patient who keeps taking the medication instead of quitting is continued treatment — and continued value.
New uses, unlocked
Proof in new groups of patients can support expanding what the medication is approved to treat.
The data question
We don't ask for your data.
The patient owns it.
The worry that stalls most enterprise deals, answered up front: you never hand over your data to work with MetAi. Each patient gives permission for their own records — the data flows in to them, not out from you.
The patient gives permission, not you
Each patient allows MetAi to read their own records, a right they have under privacy laws like HIPAA and GDPR. Your organisation never has to make a data-sharing call.
A service, not a data hand-off
You offer your members or employees the MetAi service. New health data is created through that service. The data you already hold stays exactly where it is.
Standard, secure connections
MetAi connects through the same standard, secure links your systems already use — nothing custom to build, and nothing pulled out.
Research with no exposure
Need data for research? We can build a realistic, computer-generated stand-in dataset — with no real patient information in it, and nothing leaving your walls.
You made the medication work.
We help show the world it does.
Book a demo
See what MetAi reads
that you can't.
A personalised, 30-minute walkthrough of the synthesis layer for your practice or partnership type.