The FDA just launched its first real-time clinical trials. If you’re running product or strategy at an eClinical vendor, this should be keeping you up tonight.
On April 28, the FDA announced two live proof-of-concept trials where safety signals and clinical endpoints stream to FDA reviewers in real time as the trial runs. AstraZeneca’s Phase 2 TRAVERSE trial for mantle cell lymphoma is already operational at MD Anderson and Penn. Amgen is in site selection for a Phase 1b trial in small cell lung cancer.
The technology partner making this work? Paradigm Health. Not Medidata. Not Veeva. Not Oracle.
That detail alone tells you something important about where the FDA thinks the future is.
What Actually Happened
Commissioner Makary opened the press conference with a number that should bother anyone in clinical operations: 45% of the time between a Phase 1 trial starting and the FDA application being filed is dead time. No trial running. Staff doing paperwork, entering data into multiple systems, repackaging the same information across phases. Some of that gap is genuine scientific deliberation: analyzing results between phases, deciding whether to proceed, amending protocols based on what you learned. Not all dead time is waste. But the FDA clearly believes the ratio is off, and the direction of the fix tells you where the pressure lands.
He described one application that was 66 million pages. His proposed fix: “a radical modern concept called the page limit.”
The real-time trial model works differently. Paradigm Health’s platform captures data directly from electronic health records and other structured sources, algorithmically evaluates FDA-defined data points, and transmits only the signals the FDA needs to make regulatory decisions. The FDA doesn’t get raw patient records. It gets aggregated signals: adverse event rates, tumor response percentages, safety thresholds. The data is traceable, auditable, and privacy-preserving.
Jeremy Walsh, the FDA’s Chief AI Officer, was blunt about the philosophy: “Can we make a decision off of less information? Can we make a decision off of signals information?”
To be clear: no regulatory decision has been made based on this model yet. The AstraZeneca trial has transmitted and validated signals through Paradigm Health’s platform, but the FDA hasn’t approved or rejected a drug using real-time data. It’s a proof of concept, not a proven pathway. But the direction it signals matters more than its current status, because it tells you what the FDA is optimizing for next.
That question should be reverberating through every product roadmap meeting at the major eClinical vendors right now.
The Stack That’s Exposed
The eClinical market is projected at roughly $13 billion in 2025, growing to $25 billion by 2030. It’s dominated by a handful of players: Medidata (Dassault Systemes), Veeva Systems, Oracle Health Sciences, IQVIA, and Signant Health. The core revenue driver across all of them is the same workflow: capture clinical data in an EDC system, clean it, manage it through a CDMS, package it, and submit it to the FDA at the end of each trial phase.
That’s the workflow Makary just called tedious, wasteful, and outdated on national television.
Here’s where the specific exposure sits:
EDC (Electronic Data Capture). If trial data increasingly flows from EHRs directly into an FDA-visible cloud dashboard, the standalone EDC’s role as a data capture tool gets compressed. But an EDC isn’t just a data capture tool. It’s a protocol execution engine: it enforces visit schedules, eligibility criteria, edit checks, query management, and adverse event grading per CTCAE criteria. An EHR knows a patient had a fever. An EDC knows that fever was a Grade 2 adverse event that occurred 14 days post-dose and triggered a dose modification per Section 6.2 of the protocol. That protocol enforcement layer still needs to live somewhere. The question is whether it continues to live in a standalone EDC, gets absorbed into the EHR, or moves into the middleware. That’s an architectural question, not a foregone conclusion, and it’s the one that determines how much pricing power EDC vendors retain.
CDMS (Clinical Data Management Systems). The entire value proposition of a CDMS is cleaning, reconciling, and structuring data for submission. If the FDA moves toward signal-based review where it receives pre-agreed data points in real time, a significant portion of the data management workload becomes unnecessary. You don’t need to clean and reconcile 66 million pages if the FDA only wants 12 defined signals.
Submission and regulatory publishing tools. McCary’s press conference was basically a 45-minute argument against the batch submission model. If regulators can see what they need in the cloud while a trial is running, the multi-month packaging and publishing cycle at the end of each phase gets compressed or eliminated. And this pressure isn’t just coming from the FDA side. Accumulus Technologies, spun out from a nonprofit backed by major pharma sponsors in 2025, has built a cloud platform that connects sponsors to 70+ national regulatory authorities for real-time submission, collaboration, and review. Their Accumulus Connector, launched in March 2026, plugs directly into sponsors’ existing systems so submissions flow to regulators without manual reconciliation. The traditional regulatory publishing workflow isn’t just being questioned by the real-time trial model. It’s being replaced by infrastructure that already exists and is already in use.
Safety and pharmacovigilance systems. The FDA also announced it’s consolidating seven internal adverse event reporting systems into one, after finding that 60% of people who started filing an adverse event report gave up before finishing. The incumbents who’ve built integrations into CARES, FAERS, and MAUDE now face a moving target.
What the Incumbents Still Do That Matters
Before anyone reads this as an obituary for Medidata: the incumbent eClinical stack does things that a two-trial proof of concept at US academic medical centers does not replace.
21 CFR Part 11 compliance. CDISC mapping. ICH E6(R2) audit trails. Multi-country regulatory alignment across the EU, Japan, China, and dozens of other jurisdictions. The ability to run a 300-site global Phase 3 trial across Southeast Asia and Latin America where half the sites are still working with paper source documents and fragmented IT infrastructure. That infrastructure took decades to build, and it doesn’t become irrelevant because the FDA stood up a dashboard at two of the best-resourced cancer centers in the country. Though it’s worth noting that even the global regulatory alignment moat is being tested: Accumulus Technologies has already run simultaneous multi-regulator submission pilots across six continents, which is the exact capability the incumbents would point to as their strongest defensive position.
The real-time trial model works at Penn and MD Anderson because those institutions have world-class Epic implementations, mature research IT teams, and decades of experience running complex trials. Most trial sites globally don’t have that. Community oncology practices, rural hospitals, sites in emerging markets where much of the growth in clinical trial activity is happening, these are environments where the existing eClinical stack still solves real problems.
So let’s be precise about the threat. The near-term exposure is concentrated in early-phase oncology trials at large US academic medical centers. That’s a specific wedge, not the whole market. And the infrastructure gap between Penn and a community oncology practice in rural Tennessee took EHR vendors the better part of two decades to close. Nobody should assume real-time trials scale to 300-site global programs in the next three years.
But wedges are how disruption works. They don’t stay contained. And the reason this one won’t stay contained is that it’s not a standalone experiment. It’s converging with at least four other shifts happening simultaneously.
This Isn’t Happening in Isolation
The real-time trial announcement doesn’t land in a vacuum. It’s the latest in a sequence of moves that, taken together, point in the same direction, even if they weren’t designed as a single strategy.
December 2025: RWE de-identification. The FDA updated its guidance to allow sponsors to submit real-world evidence without requiring identifiable patient-level data. De-identified data from registries, claims databases, and EHR networks is now acceptable for medical device submissions, and the FDA signaled it intends to extend this to drugs and biologics. This opens the door for massive de-identified datasets to supplement or, in some cases, replace traditional trial data. Only 35 drugs, biologics, or vaccines have incorporated RWE into their applications since 2016. That number is about to change.
September 2024: Finalized DCT guidance. The FDA’s decentralized clinical trial guidance clarified that trial activities can happen at locations other than traditional clinical trial sites, including home-based visits, telehealth, and mobile research units. This pushes data collection closer to the patient and further from the centralized site model that EDC systems were designed for.
PDUFA VIII negotiations (ongoing). The reauthorization talks include an “America First” fee incentive that would reduce application fees for sponsors conducting Phase 1 trials domestically while potentially adding fees for those who don’t. The FDA and industry hit an impasse on this in February, but the direction is clear: the FDA wants more early-phase trials running in the US. McCary said explicitly that more Phase 1 trials are starting in China than in the US. If PDUFA VIII succeeds in pulling trials back onshore, it increases the pressure to make domestic trial execution faster and cheaper, which means less tolerance for the current data management overhead.
System consolidation. Beyond the clinical trial reforms, the FDA is collapsing 40 application intake systems into one and consolidating three safety monitoring systems into one. The agency estimates this saves $120 million annually, which it’s reinvesting in hiring 3,000 scientists. The message: the FDA is simplifying its own infrastructure and expects the industry to keep up.
What I’d Be Doing If I Were Still Inside
I spent years inside clinical trial technology at a 500-person eClinical platform company with a huge footprint across the who’s who of biopharma and a scrappy startup. I know what the data management workflow looks like from inside the machine: the same safety and efficacy data getting entered, cleaned, reconciled, packaged, and resubmitted at the end of every phase because that’s what the regulatory process required. Not because it was the best way to evaluate whether a drug works. Because the filing structure demanded it.
To be fair, the industry has been reforming these workflows for years. Risk-based monitoring, central statistical monitoring, adaptive trial designs. RBQM has been in ICH E6(R2) since 2016. Sophisticated sponsors don’t manage data the way they did a decade ago. But those are incremental improvements to a batch-submission architecture. What the FDA announced this week isn’t incremental. It’s a different model entirely: continuous signal review instead of phase-gated data packages. That’s the gap between optimization and redesign.
Here’s what I’d be telling the product leadership team if I were still in that world:
Stop treating this as a feature request. The instinct at most eClinical companies will be to add a “real-time signals” module to the existing platform and call it innovation. That’s the wrong move. The FDA isn’t asking for a new feature on top of the old workflow. It’s questioning whether the old workflow needs to exist in its current form. Building a real-time dashboard on top of a batch-submission architecture is putting a coat of paint on a structural problem.
The EHR integration question is existential. Paradigm Health’s entire approach is EHR-native. Data flows from Penn and MD Anderson’s health records into the FDA’s view. If that model scales, the EDC is no longer the system of record for clinical data. The EHR is. Every eClinical vendor needs a credible answer to the question: what is our role when the source of truth is the health record, not our platform?
The real competitor isn’t another eClinical company. Paradigm Health isn’t in the Medidata/Veeva/Oracle competitive set. It’s a clinical operations company that built technology for a specific workflow problem the FDA wanted solved. The incumbents are competing against the workflow itself becoming obsolete, not against a rival platform.
The people who installed the stack are leaving to replace it. I recently spoke with a founder who spent years as a Veeva implementation consultant for enterprise pharma accounts, deploying CTMS, eTMF, and SiteConnect across large clinical programs. She then moved to the CRO side and led implementations of Medidata and Oracle for Syneos Health. She saw the stack from both angles, vendor and operator, and left to build a protocol design tool because the workflow she’d been installing for years was still producing the same problems: amendment cycles, design rework, operational delays that cascade downstream. When the people who implement the incumbent platforms start building alternatives to them, that’s a leading indicator worth paying attention to.
Watch the RFI. The FDA is accepting public comments on the real-time clinical trial pilot program until May 29, 2026. This isn’t a theoretical framework. They’re designing the pilot that will run this summer. The FDA is genuinely asking for input from the companies that have managed clinical trial data at scale for decades, because those companies know things about implementation complexity that the agency doesn’t. Any eClinical company that isn’t contributing to that RFI is missing a chance to shape the pilot based on what they know about the operational reality.
The Uncomfortable Zoom-Out
I want to be honest about something. These initiatives, the real-time trials, the RWE guidance, the DCT framework, the PDUFA VIII negotiations, the system consolidation, did not emerge from a single coordinated FDA strategy. The real-time trial is Walsh’s project. The RWE guidance came out of CDRH. The PDUFA VIII talks are being run by CDER and the Office of the Commissioner. They were developed independently by different parts of the agency with different mandates.
But the cumulative effect is the same regardless of whether it was coordinated. When you line up all five moves, the picture that emerges is a fundamental rethinking of how clinical evidence gets generated, transmitted, and reviewed.
The eClinical stack was built for a world where clinical data is captured in proprietary systems, cleaned by specialized teams, packaged into massive submissions, and delivered to the FDA months or years after the trial ends.
The world taking shape is one where data flows from EHRs and real-world sources upstream, gets algorithmically filtered into signals during the trial, and feeds into real-time regulatory collaboration platforms downstream. The batch-submission model that sits in the middle, the part the incumbent eClinical stack was designed to power, is being hollowed out from both ends simultaneously.
Where the Value Migrates
The question the VC community and corporate strategy teams should be asking isn’t just “who loses?” It’s “where does the value go?” These aren’t independent, parallel opportunities. They’re a dependency chain, and the sequencing matters:
First, EHR vendors become the new system of record. Nothing else in this chain works until clinical trial data flows reliably from health records. If trial data increasingly originates in the EHR rather than being double-entered into a standalone EDC, the EHR platform gains leverage. Epic and Oracle Health (via Cerner) are the obvious beneficiaries. Epic’s research module is already being used in pragmatic trials, and Oracle’s 2025 roadmap explicitly includes EHR interoperability and AI-enabled data capture for clinical research. The question is whether they build the clinical trial layer themselves or whether they partner with companies like Paradigm Health to do it. The biggest risk factor for every other layer in this chain is Epic’s posture toward third-party data access. Epic has historically preferred to build rather than partner, and if Epic decides real-time clinical trial data is a feature rather than a partner opportunity, the middleware market described below gets compressed before it forms. Anyone investing in this space needs to have a thesis on what Epic does next.
Then, new middleware companies that sit between EHRs and regulators. Once EHR data flows, someone has to make it regulatory-grade. Paradigm Health is the first visible example, but it won’t be the last. The company that can reliably extract, validate, and transmit regulatory-grade signals from messy EHR data into a format the FDA trusts has a durable business. That’s a hard technical problem, and whoever solves it at scale across multiple EHR systems and site configurations controls a critical chokepoint. One caveat: Paradigm’s path into this market was through a direct FDA collaboration, which is not a go-to-market motion other startups can copy. The next entrants will likely face standard pharma procurement, which means SOC 2 Type II reports, validated environments, and reference clients. The door is open, but the line to walk through it is harder than Paradigm’s experience suggests.
At the submission end, regulatory collaboration platforms are already live. Accumulus Technologies, spun out from a nonprofit backed by major pharma sponsors in 2025, has built a cloud platform connected to 70+ national regulatory authorities that enables real-time submission, collaboration, and simultaneous multi-country review. Their Connector, launched in March 2026, integrates directly with sponsors’ existing systems so data flows to regulators without manual reconciliation. They’ve already run multi-regulator submission pilots across six continents and claim up to 90% reduction in approval timelines. This is the downstream complement to Paradigm’s upstream signal streaming: if Paradigm changes how the FDA sees trial data during the trial, Accumulus changes how sponsors interact with regulators at the submission and review stage. Together, they compress the batch-submission model from both sides. The eClinical vendors who currently own the submission and regulatory publishing workflow should be paying close attention to Accumulus’s adoption curve, because the “should incumbents build an FDA portal” question is already being answered by someone else.
CROs adapt next, and some come out ahead. The large CROs, IQVIA, ICON, PPD (Thermo Fisher), Parexel, currently license eClinical platforms from the incumbents and mark them up. But technology resale is maybe 15% of CRO margin on a given trial. The bulk of their revenue comes from clinical monitoring, site management, medical writing, biostatistics, and project management. If real-time trials reduce the data management workload, the pressure falls on clinical data management headcount inside CROs, which is a meaningful workforce impact. But the CROs themselves may be net beneficiaries if faster trials mean more volume per year. The ones that redeploy data management capacity into higher-value clinical operations gain margin. The ones that build proprietary EHR integration and signal-reporting technology gain even more. The ones that stay as passive resellers of incumbent platform seats are the ones that get squeezed.
RWE analytics companies scale in parallel. The December 2025 guidance accepting de-identified data opens a lane for companies that can curate, clean, and analyze large real-world datasets at regulatory grade. This was a niche business when only 35 products had used RWE in their applications. If that number grows by an order of magnitude over the next five years, the companies that own the analytic infrastructure become essential partners to both sponsors and the FDA.
The incumbents who pivot fastest survive throughout. This isn’t winner-take-all. Medidata, Veeva, and Oracle have deep client relationships, massive data assets, and the compliance infrastructure that the new entrants lack. The ones who use those advantages to build real EHR integration, not just a checkbox feature but a genuine architectural shift, can protect their position at every stage of this transition. The ones who treat this as a marketing problem and rename their existing products will lose share to companies that don’t carry the legacy architecture.
The market may still grow to $25 billion by 2030. But the composition of that market, who captures the value and what they’re selling, is going to look very different from what the current projections assume.
The Strategy Question
The vendors who move fastest won’t be the ones who add AI features to their existing platforms. They’ll be the ones who ask the harder question: which parts of what we do are still necessary, and which parts exist only because the regulatory process used to require them?
That’s not a product question. It’s a strategy question. And the window to answer it is shrinking.
If you’re running product or strategy at an eClinical company, a CRO, or a healthtech startup entering this space and you want to pressure-test where your roadmap sits against these shifts, I’d welcome that conversation. That’s what my practice does.
Arvita Tripati is the founder and managing director of Vahana Labs, a B2B strategy consulting firm that helps healthtech and AI companies move from pilot to enterprise contract. She has 18+ years of VP-level operating experience across regulated AI, clinical trials, and enterprise healthcare technology, including roles at AliveCor, Vineti, and Endpoint Clinical (LabCorp). You can reach her at arvita@vahanalabs.ai.