Webinar recap | Real-Time Clinical Trials: Why the FDA's Vision Demands a New Data Foundation

‍The following is a recap of our recent webinar with OmniScience CEO Angela Holmes and VP of Product Michael Bell.

Clinical trials remain the longest, costliest, and most document-heavy part of drug development, marked by an average 30-month gap between phases, roughly 400,000 pages of documentation per submission, and rising pressure on U.S. biotech's global competitiveness. The cost isn't just financial: it's medicines that could reach patients sooner but don't, and rare-disease programs where today's costs and timelines simply don't work.

That's the backdrop for one of the most consequential shifts in clinical development in years: the FDA's emerging vision for real-time clinical trials.

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The Big Idea: Data That Speaks in Real Time

Late last year, the FDA approached OmniScience to explore what a real-time approach could look like in practice - using advanced computational models, real-time analysis, shared infrastructure, and automation to evaluate drugs and biologics faster, at lower cost, and with fewer participants. The vision, in short:

• Unified trial data, continuously, rather than assembled periodically for scheduled reviews
• AI-driven analysis at scale while the trial is running
• Insights shared with regulators in real time, not just at submission
• The long-term possibility of faster approvals based on live data rather than static, retrospective packages
• The ability to stop trials early for efficacy or futility, not just for safety as today's mechanisms allow

OmniScience validated this vision directly with sponsors. The response was consistent: pharma teams wanted the ability to act the moment a drug shows it's working. A pediatric oncology biotech modeled a scenario where earlier phase-transition decisions could bring a therapy to market two years sooner and save $25 million. Large pharma leaders also described board mandates to cut trial timelines by as much as 50% by 2030.

The numbers back up the urgency: analysts estimate 45% of the traditional submission process sits idle between phases, and closing that gap could unlock roughly $100 billion in value industry-wide, freeing capital to fund further innovation.

What Real-Time Oversight Actually Requires

The FDA's receiving infrastructure for real-time data largely already exists. What's missing is pharma's ability to generate a continuously integrated, compliant, real-time data foundation. That foundation needs to:

• Unify data across every source (EDC, labs, COAs, PROs, IRT, safety, CTMS, etc.) with full provenance and version control
• Stay contextualized against the protocol, including pre-agreed monitoring thresholds
• Account for data quality in-flight, before database lock, using a risk-based approach to what actually matters to primary endpoints, safety signals, and operational milestones
• Run modern statistical signal-detection, similar to established pharmacovigilance methods
• Remain fully auditable, transparent, and governed

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In effect, the industry needs to move from static, periodic dashboards to continuous, always-on monitoring to catch data quality issues, protocol deviations, and safety or efficacy signals while there's still time to act, rather than weeks or months after the fact.

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Where the Industry Is Already Headed

This shift isn't only a regulatory conversation. Independent commentary from former FDA AI leadership has echoed the same theme: AI has transformed the back office and trial operations, but the middle of the trial, the in-flight data, remains underexploited, even though the technology to close that gap is mature enough today.

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How OmniScience's Vivo Fits In

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Since putting Vivo into production OmniScience has been building toward exactly this kind of real-time foundation — an operating system for trial data. Capabilities include:

• AI-powered data mapping onboards new data sources by automatically reading protocols, CRFs, and source systems to generate a validated map into a unified data model
• Ask Vivo lets teams query live, guardrailed trial data conversationally — with full audit trails, role-based access, and blind protection — turning multi-system questions (e.g., "who's at risk of dropping out?") into answers in under a minute
• Plain-language monitoring and alerts let teams set their own quality tolerance limits — "alert me if a site hasn't screened a patient in 30 days" — and turn any question into a recurring, agent-monitored check
• Portfolio-level intelligence rolls insights up across trials, addressing the industry's long-standing "run one trial, learn one trial" problem
• Trial planning, informed by historical portfolio performance, closes the loop between planning, execution, and re-planning as real conditions diverge from projections

Every one of these capabilities maps directly onto what the FDA's real-time vision requires: continuous data unification, governed AI-driven signal detection, and traceable, explainable answers grounded in source data rather than a black box.

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The Takeaway

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Real-time clinical trials will be a three-way partnership between regulators, sponsors, and technology platforms. The shift is already underway. Whether or not a given trial team is engaging directly with the FDA's initiative today, the underlying need is the same: a unified, real-time, compliant data foundation that turns clinical trial oversight from a periodic look-back into a continuous, actionable view.

To request a copy of the webinar please contact hello@omniscience.bio.