Three Ferma agents across one conference, with the time, the money, and the launch risk counted on both sides.
Anyone who has worked Medical Affairs through a major conference knows the week. The abstracts drop, the plenary lands, and within hours leadership wants to know what changed and what it means for our asset. The field needs talking points that are accurate and on-label. Medical Information braces for the questions that always follow. And every output, every summary, every response, every slide, has to be accurate, balanced, and traceable to a source, because in Medical Affairs that is not a nicety. It is the standard we are held to.
The hard part is not finding the science. It is that there is too much of it, arriving too fast, for the people who have to make sense of it. One conference can release thousands of abstracts in days, on top of the publications, trials, and regulatory news that never stop. What runs out is not information. It is the senior scientific time and attention to turn all of it into something the team can act on, before the moment passes.
So we tested that on a single conference, ASCO 2026 in non-small cell lung cancer (NSCLC), and ran three of Ferma's Medical Affairs agents the way a team actually works a conference: making sense of the readouts, pressure-testing the evidence behind the headline, and answering the wave of inquiries that followed the plenary. Then we counted the senior time each one took, by hand and with Ferma.
This is an illustrative worked example. The ASCO 2026 clinical figures are drawn from public disclosures and shown for illustration, pending medical and regulatory review. The per-step times are illustrative and consistent with Ferma's benchmarking, which was developed with Medical Affairs practitioners who have run these functions at leading biopharma; actual times vary by therapeutic area, data volume, and how much review a team builds in. Dollar figures assume a fully loaded senior medical cost of about $175 an hour.
Making sense of the readouts: Real-Time Scientific Intelligence
ASCO 2026 rewrote the NSCLC standard of care on several fronts at once, and the medical team needed a clear read fast. HARMONi-6 showed a PD-1 by VEGF bispecific (ivonescimab) beat an active PD-1 on overall survival in first-line squamous disease (OS hazard ratio 0.66). LIBRETTO-432 was the first positive adjuvant RET trial (event-free survival hazard ratio 0.172, an 83 percent risk reduction). OptiTROP-Lung05 was the first Phase 3 win for an IO-plus-ADC combination in the first-line setting, CROWN showed seven-year durability in ALK-positive disease, and one adjuvant immunotherapy trial (ANVIL) read out negative. The Medical Affairs job is to turn that into a clear, sourced position: what changed, what it means for our asset, and what the field should be saying. Here is where that time goes.
| What the team does | By hand | With Ferma | Time cut |
| Track the abstracts and presentations as they drop | 6h 20m | 4 min | 99% |
| Pick out the practice-changing readouts | 4h 10m | 8 min | 97% |
| Lay them out by target, setting, and result | 3h 35m | 6 min | 97% |
| Check every headline result against its source | 5h 25m | 12 min | 96% |
| Write the scientific takeaway and cited summaries (your review) | 3h 05m | 1h 28m | 52% |
| Total | 22h 35m (≈ 3 days) | 1h 58m | 91% |
The parts that compress hardest are the reading, sorting, and fact-checking. Writing the scientific takeaway stays with the team, which is exactly right: that judgment is the medical voice and should not be automated. And because it runs live, the read is ready while the conference is still on, when the field and leadership actually need it.
Knowing where the evidence is thin: the Evidence Gap Analyzer
A positive headline is where the medical questions begin, not where they end. The strategic question for Medical Affairs is where this evidence is thin, and where a payer, a regulator, or a discerning KOL will press. On ivonescimab in first-line squamous NSCLC, that question has teeth. HARMONi-6 was run entirely in China (around 50 sites, roughly 90 percent male); the overall survival benefit is real but the interim is immature (27.89 versus 23.69 months, hazard ratio 0.66, p=0.0017); and the only global ivonescimab Phase 3 to report so far (HARMONi, in 2L EGFR-mutant disease) missed its primary endpoint (hazard ratio 0.79, p=0.057). With an FDA precedent against China-only data (the 2022 sintilimab ODAC vote, 14 to 1) and a confirmatory global trial (HARMONi-3) still maturing, whether the benefit travels outside China is the question the medical evidence plan has to answer. Mapping that by hand, across geography, population, comparator, safety, and endpoint, is weeks of senior work.
| What the team does | By hand | With Ferma | Time cut |
| Frame the questions that matter (5 dimensions) | 7h 45m | 1h 50m | 76% |
| Pull together all the evidence (pubs, trials, congress, RWE, regulatory) | 38h 30m | 52 min | 98% |
| Place each finding against the framework | 27h 15m | 1h 55m | 93% |
| Find and grade the gaps (High / Med / Low) | 19h 20m | 2h 50m | 85% |
| Prioritize by what threatens the label or launch | 11h 40m | 2h 40m | 77% |
| Build the sourced gap map (your review) | 11h 50m | 3h 50m | 68% |
| Total senior medical time | 116h 20m | 13h 57m | 88% |
And the total understates it. By hand, the gap map is only as current as the last manual refresh, roughly ten weeks. Here it is current within a day, so the team sees the gap while there is still time to shape the confirmatory plan, not after a regulator or payer raises it.
Answering the field and HCPs, with sources: Medical Information
Then the questions arrive. In the 72 hours after the NSCLC plenary, inbound medical inquiries jumped about 240 percent over the prior four-week baseline: 605 inquiries, across eight topics and six targets. Comparative efficacy versus pembrolizumab (142 inquiries) and the management of proteinuria and bleeding (98) led; 12 inquiries crossed an off-label line and had to go to MLR rather than back as a standard reply. For Medical Information, the job is to answer accurately, on-label, and with every statement traceable to source, at volume and under time pressure, which is exactly when mistakes happen.
| What the team does | By hand | With Ferma | Time cut |
| Sort and de-duplicate the 605 inbound inquiries | 9h 10m | 6 min | 99% |
| Group them by topic and rank by volume and intent | 4h 40m | 5 min | 98% |
| Match each to an approved standard response | 12h 30m | 14 min | 98% |
| Flag off-label questions and route them to MLR | 3h 20m | 3 min | 99% |
| Draft cited answers for the rest (your review) | 14h 15m | 2h 40m | 81% |
| Total | 43h 55m | 3h 08m | 93% |
At surge volume, the manual sorting and sourcing is what overwhelms a team. Handling that, while keeping every answer tied to the label and the literature and routing the off-label questions correctly, is the difference between staying compliant and getting caught out.
How it adds up
One conference, three jobs Medical Affairs has to do anyway. The pattern is the same each time: the mechanical work, the reading, sorting, sourcing, and formatting, falls by 90 percent or more, while the scientific judgment that is the team's real contribution stays where it belongs.
| The job | Typical by hand | With Ferma | Time cut |
| Real-Time Scientific Intelligence (conference read) | 22h 35m | 1h 58m | 91% |
| Evidence Gap Analyzer (per therapeutic area) | 116h 20m | 13h 57m | 88% |
| Medical Information (post-plenary surge) | 43h 55m | 3h 08m | 93% |
| Across all three | ≈ 23 working days | ≈ 19 hours | ≈ 90% |
What the time is worth: money, risk, and impact
For a Medical Affairs leader, time saved is only the start. It converts into team capacity, into risk taken off an asset, and into decisions made while they still matter. The figures below use a fully loaded senior medical cost of about $175 an hour.
| What the work is worth | Senior time recovered | Value at ~$175/hr |
| Real-Time Scientific Intelligence (conference read) | ~20.6 hours | ~$3,600 |
| Evidence Gap Analyzer (per therapeutic area) | ~102.4 hours | ~$17,900 |
| Medical Information (post-plenary surge) | ~40.8 hours | ~$7,100 |
| Total from one conference | ~164 hours | ~$28,600 |
From a single conference, the three agents give back about 164 hours of senior medical time, worth roughly $28,600. Across a launch year a team covers many more conferences and refreshes each asset review continuously, so the saving multiplies. At a top-20 pharma the recovered senior time is worth an estimated 1 to 3 million dollars a year, before counting the headcount a team would otherwise need to add.
The risk it takes off the table
The gap you see early. By hand, the picture of where the evidence is thin is only refreshed every ten weeks or so. Ferma keeps it current within a day. On ivonescimab, that means the ex-China extrapolation risk (a China-only trial, a non-US comparator, an immature interim survival, and a global Phase 3 that already missed) is visible while there is still time to shape the confirmatory plan, not after a regulator or payer raises it. For a major oncology asset a delayed or narrowed label is a hundreds-of-millions outcome, so seeing the gap first is worth far more than the hours it saves.
Compliance the team can stand behind. Across the 605 post-plenary inquiries, every response was traceable to label and literature, and all 12 off-label requests were caught and routed to MLR rather than answered as standard replies. The exposure Medical Affairs exists to prevent, an unsourced or off-label statement reaching a healthcare professional, is closed by design rather than by spot-checking.
The capacity it creates
More team, without more headcount. The roughly 164 senior hours given back by one conference are about four weeks of a senior scientist, redirected from collation to interpretation, KOL engagement, and strategy.
In time to matter. The read is ready while the conference is still on, the gap map is current within a day, and the inquiry surge is cleared in hours, so the team's scientific position stays consistent and current while attention is at its peak.
Better for patients. Current, sourced science reaches healthcare professionals sooner.
Why none of this works without rigor
Speed means nothing in Medical Affairs if the science does not hold up. Three things keep the time savings safe rather than risky:
Cited by design. Every statement is traced to its source. In Medical Affairs a citation is not a finishing touch; it is what makes an output usable and compliant in the first place.
Current, not stale. The picture refreshes as new data lands, so the team is working from today's evidence, not last quarter's.
The judgment stays human. Ferma removes the assembly, not the expertise. The medical voice, the interpretation, the position, the sign-off, stays with the team.
For the technically minded: what sits underneath
None of this works without the system beneath it, and it is worth a brief word. Ferma is not a chatbot bolted onto a database, which would just hand the team more to sort. It is built the other way around, as one system: a continuously updated data layer (conference presentations, publications, trials, regulatory sources, including native-language China sources); a knowledge graph that ties every data point to the asset, trial, indication, and person; an analytical methodology encoded by people who ran these functions in Medical Affairs; and agents that carry out that methodology and produce a sourced draft. A person reviews and signs off. The system does the assembly. The team keeps the judgment.
The bigger shift
As generative AI fills every channel with machine-written content, the volume of science will only grow, and so will the noise. The edge for a Medical Affairs team is no longer access to data. It is the ability to find the one insight that matters, quickly, and to stand behind it with sources. The data layer and knowledge graph behind these results are already proven in production, and Ferma is now extending that foundation into the AI era through the agents shown here, so each new capability builds on a base that already works at scale.
What you have seen here is deliberately narrow: one conference and three agents, timed end to end so the value is concrete. The platform is not. Ferma runs continuously across every conference, publication, trial, and regulatory feed a team follows, through a much larger and growing suite of agents, and the three shown here are a sample of what Medical Affairs alone can run. Medical Affairs is also just one of the functions Ferma serves. The same data layer and knowledge graph power its work with Business Development and Licensing, Competitive Intelligence, and Commercial teams across 80+ biopharma companies, so an investment in one function compounds across the rest.
About Ferma. Ferma is the AI-native intelligence platform for life sciences, built by ZoomRx. ZoomRx has partnered with 100+ leading biopharma companies for over 15 years. Ferma serves Medical Affairs, Business Development and Licensing, Competitive Intelligence, and Commercial teams; the three agents and single conference shown here are one illustration of a broader, continuously running suite.