Clinical Trial Operating System

The operating layer above every clinical trial.

Every drug approval still passes through manual source data verification, reactive safety monitoring, and software built before the smartphone. wrldOS replaces that stack.

The Problem

Clinical trials are run on software from another era.

Every sponsor pays $500K to $1M per trial for platforms that still require CRAs to compare paper source documents by hand, surface adverse events after the fact, and stitch together data from eight disconnected vendors.

30–40%
of a CRA's time is spent on manual source data verification — repetitive work skilled professionals shouldn't be doing.
Applied Clinical Trials · Journal of Clinical Research Best Practices
$20.6M
median cost of a Phase III oncology trial, with 11–14% of that budget consumed by site monitoring alone.
Medidata 2020 · Tufts Center for the Study of Drug Development
30%
of public biotechs have less than 12 months of cash. Cutting trial costs isn't a nice-to-have — it's existential.
BioPharma Dive · EvaluatePharma Q4 2023 · SVB Healthcare 2024
The Platform

One operating system. The whole trial lifecycle.

wrldOS sits above the incumbent stack and reads from every CTMS, EDC, eTMF, IRT, and safety system you already run. It doesn't replace one tool. It replaces the seams between them.

01

Predictive, not reactive.

AI risk scoring delivers 48–72 hour early warnings on serious adverse events. Enrollment is forecast weeks ahead, not reported weeks behind. Protocol deviations surface themselves.

Incumbents report after the fact. wrldOS predicts before it matters.
02

Unified, not fragmented.

Command Center consolidates signals from every vendor into one pane. The data you need to run a trial stops living in eight dashboards and thirty-seven daily emails.

Veeva is a document system. Medidata is an EDC. wrldOS is the layer that unifies them.
03

AI-native, not bolted on.

Seven integrated ML engines, 120+ API endpoints, full 21 CFR Part 11 audit trail. Built to the FDA's April 2023 AI/ML guidance from day one — not retrofitted onto 2009 software.

The incumbents' AI is a press release. Ours is the architecture.
See It Running

The platform is real. The demo is live.

Not renderings. Not slides. A working front end powered by a production backend — 120+ endpoints, 30+ database tables, 7 ML engines. Walk through it like a sponsor's Chief Medical Officer would on a Monday morning.

Every screen in wrldOS is interactive.

Start at the Command Center — one pane, four predictive KPIs, real-time anomalies. Then drill into the AI Visit Workspace, Site Selection, Patient Screening, or the compliance backbone: Audit Trail, Essential Docs, Deviations, IRT.

11 Views~6 minute walkthroughBest on desktop
Open the demo
Command Center · Study ONC-2047
High-risk SAEs3
Enrolled284 / 480
LPI forecastOct 14 (-18d)
Open anomalies14
Every number is a predictive model output.
AI Visit Workspace · Site 0117
Traditional visit14h 20m
With wrldOS3h 10m
Time saved11h 10m
Auto-verified12 / 14 subjects
75–80% of SDV eliminated · industry ceiling.
Site Selection · 47 sites scored
Top-ranked site0203 · score 94
Predicted enrollment+18% vs CRO pick
Risk flags2 sites · audit history
Feasibility cycle1 afternoon
90 days of CRO Rolodex compressed to one screen.
Why Now

Three forces converged. The window is open.

AI-native clinical trial infrastructure wasn't possible five years ago — and won't be uncontested five years from now. The moment is specific, and it is right now.

01
Regulatory

The FDA gave explicit permission.

The April 2023 AI/ML Discussion Paper stated plainly that FDA supports AI in drug development when appropriately validated. ICH E6(R3) now expects risk-based monitoring, not optional analytics. The “will regulators accept it” excuse is gone.

FDA 2023 · ICH E6(R3) Draft
02
Economic

Biotech funding collapsed 52%.

Sponsors that treated trial software as discretionary now treat it as material to runway. Cutting $700K–$1.9M per trial extends runway by months that matter to whether the program reaches its next milestone.

SVB Healthcare 2024 · BioPharma Dive
03
Technical

The stack is production-ready.

Large language models, ensemble OCR at 95%+ accuracy, mature anomaly detection, HIPAA-compliant cloud. What required $1M and a specialized team to build in 2020 is developer-accessible and deployable now.

Who built this

Built by Kelechi Owunwanne — a Clinical Research Associate and operator-founder who came up across global, mid-size, and specialty CROs. He saw the same structural patterns at every scale, and built what replaces them.

That range matters. Site initiation visits, monitoring visits, close-outs — across multiple operating models, on CTMS, EDC, eTMF, IRT, and safety platforms from every major vendor. He saw the same structural patterns at every scale, and built what replaces them.

Building in the open. Always glad to hear from sponsors, CROs, and investors.

kelechi@wrldos.com