Partnership Proposal · Prepared Exclusively for GlaxoSmithKline
Built by clinical operations leaders with eight years supporting GSK Oncology, Aurelyn AI Clinical proposes a partnership to bring protocol‑native AI — validated, governed, and audit‑ready — into GSK's clinical trial lifecycle, from protocol design through inspection‑readiness.
Trial teams operate across a fractured stack of legacy CTMS, static Excel trackers, and manually reconciled eTMF binders. The result is slower activation, inspection risk, and evidence that arrives too late to change a decision.
is consumed by the trial execution lifecycle itself — most of it spent reconciling documents and status across disconnected systems, not on science.
runs through the top ten legacy CTMS vendors — platforms built for record‑keeping, not for AI‑native protocol design or real‑time evidence generation.
Multi‑site, multi‑country oncology, cell & gene, and rare‑disease programs are expanding faster than the operational tooling built to run them.
Aurelyn Trial | OS™ is the core operating layer: it ingests the protocol once and propagates it — as structured, machine‑readable logic — across every downstream workflow, from site activation to eTMF inspection‑readiness.
The Aurelyn Clinical Engines™ plug directly into that core, so every module reasons from the same protocol source of truth instead of a re‑keyed copy of it.
GSK evaluates a lot of "AI for clinical trials" pitches. Most are general‑purpose models wrapped in a clinical skin. Aurelyn is built the other way — from the protocol and the regulation inward.
| Generic AI | Aurelyn |
|---|---|
| General‑purpose models | Protocol‑native clinical intelligence |
| Generates content | Validates compliance and consistency |
| Limited traceability | Governance and auditability |
| Generic workflows | Clinical trial lifecycle focus |
| Broad knowledge | Regulatory‑aligned clinical expertise |
Via REST APIs and HL7 FHIR against existing EDC, CTMS, and eTMF systems, plus SSO/SAML against GSK's identity provider. No forklift replacement of existing infrastructure — Aurelyn sits alongside it.
Encryption in transit (TLS 1.2+) and at rest (AES‑256), tenant‑isolated environments, and role‑based access control mapped to GSK's own permission model.
Every model output is risk‑tiered and mapped to the NIST AI RMF and the FDA–EMA Joint Guiding Principles for AI — the same framework regulators now expect sponsors to document against.
No AI output reaches a trial record without a named human reviewer's sign‑off. Every validation decision is timestamped, attributed, and retained for inspection.
Cloud‑hosted (single‑tenant option available) or deployed into GSK's own environment for data residency‑sensitive workloads. Staged rollout: pilot → validation → enterprise scale.
SOM shown as an illustrative planning assumption (~5% of SAM), not a third‑party estimate. Source: Grand View Research, eClinical Solutions Market & Clinical Trial Management System Market, 2026.
Source: Grand View Research (eClinical Solutions: $13.13B→$35.08B, 15.07% CAGR; CTMS: $2.69B→$7.40B, 15.59% CAGR).
| Revenue Line | Model | Buyer |
|---|---|---|
| Trial | OS™ Platform | Annual SaaS license, per‑trial or enterprise | Sponsors, CROs |
| Clinical Engines™ Add‑Ons | Modular add‑on pricing (CEC, eTMF Intel., TrialSphere, SOP Builder) | Sponsors, CROs |
| Academy Certification | Per‑seat course fees + enterprise licenses | Site staff, CRAs, sponsors |
| Academy Sponsorship | Five‑tier partner program, up to $10K | Vendors, industry partners |
Illustrative target mix at scale — reflects business‑model design, not reported revenue.
| Capability | Aurelyn Trial | OS™ | Legacy CTMS | Manual / Excel |
|---|---|---|---|
| AI‑native protocol authoring | Yes | No | No |
| Real‑time eTMF completeness scoring | Yes | Partial | No |
| Cross‑trial evidence synthesis | Yes | Partial | No |
| Regulatory crosswalk automation (FDA/ICH/CDISC) | Yes | Partial | No |
| Built‑in certification & training | Yes | No | No |
| Auto‑customized SOP library (300+ SOPs) | Yes | Partial | No |
Aurelyn's own strategic assessment; illustrative, not a third‑party analyst placement.
Full‑stack React / Node.js / PostgreSQL SaaS application, seeded from a 563‑activity regulatory‑grade clinical trial lifecycle dataset — the technical foundation Aurelyn Trial | OS™ builds on.
Submitted a complete response to the FDA's Request for Information (Docket FDA‑2026‑N‑4390) on AI‑enabled optimization of early‑phase clinical trials — the RFI underpinning the agency's Real‑Time Clinical Trials (RTCT) pilot program — mapping platform capabilities to all 38 sub‑questions with full regulatory crosswalks and a NIST AI RMF trustworthiness framework.
Delivered "AI‑Powered Clinical Research: From Compliance to Competitive Edge," repurposed into a multi‑channel social content suite to build top‑of‑funnel demand.
Built and published SCORM‑compliant courses spanning eTMF/document intelligence (CDISC eTMF Reference Model), ICH/GCP, AI for clinical project managers, and AI governance leadership — plus a five‑tier sponsorship prospectus.
Go‑to‑market playbook with milestone Gantt roadmap and KPI scorecard; corporate site, lead‑magnet funnel, and outreach infrastructure built for launch.
Keynote address at the All Things Women Summit on mentorship in life sciences leadership, extending Aurelyn's visibility in the clinical AI community.
Every engine is grounded in the frameworks regulators already use: the CDISC eTMF Reference Model, ICH E6(R3), 21 CFR 312.62(b), and the NIST AI Risk Management Framework. That same regulatory grounding is taught directly in the Academy curriculum, so the workforce and the platform speak one language.
Aurelyn is built directly into the direction both agencies are already moving — real‑time data during the trial, not after it, and AI held to a shared, risk‑based standard on both sides of the Atlantic.
FDA unveiled two proof‑of‑concept trials (AstraZeneca, Amgen) reporting endpoints and safety signals to the agency in real time, with a broader pilot program RFI — the same RFI Aurelyn responded to — targeting selections in August 2026.
FDA and EMA aligned on ten shared principles of good AI practice in medicine development — the first joint US–EU AI standard for drug development, underpinning future guidance on both sides.
"Considerations for the Use of AI to Support Regulatory Decision‑Making for Drug and Biological Products" — FDA's first AI‑specific guidance for drug/biologic sponsors, with final guidance expected Q2 2026.
The EU's ACT EU initiative and Clinical Trials Information System (CTIS) are harmonizing trial infrastructure, while EMA's DARWIN EU real‑world evidence network now reaches roughly 250M patients across the bloc.
Sources: FDA, "FDA Announces Major Steps to Implement Real‑Time Clinical Trials" (Apr 28, 2026); EMA, "EMA and FDA Set Common Principles for AI in Medicine Development" (Jan 14, 2026); FDA CDER, Artificial Intelligence for Drug Development guidance page; EMA, Data Analysis and Real World Interrogation Network (DARWIN EU).
20+ years of clinical development leadership — including inside GSK itself.
That operating experience — inside GSK's own oncology and transparency functions, not a retrofit of generic project‑management software — is what shapes every engine in the suite.
Based in the Philadelphia / Bucks County region · Active speaker and thought leader in clinical AI, including a keynote at the All Things Women Summit on mentorship.
Each track can stand alone or combine — sized to where GSK wants to start, from a bounded pilot to full enterprise scale.
For a walkthrough of the platform, the full data room, or to scope a pilot on an active GSK oncology trial, reach out directly.