ModelRefs / Clinical Trial Matching — Architecture Blueprint
Clinical Trial Matching — Architecture Blueprint
Production architecture blueprint for Clinical Trial Matching: components, deployment patterns, cost & latency, failure modes, evaluation and governance, with sources and review dates.
Overview
This is the implementation view of Clinical Trial Matching: the components it requires, where it can run, what it costs in latency and spend, how it fails, and what you must measure before putting it in front of users.
5 components to assemble, 6 documented failure modes, high implementation complexity. Every statement below comes from the canonical workflow record with its sources and review date; where the evidence does not settle a question, the page says so rather than filling the gap.
What this workflow takes in and produces
Takes in
- authorized patient facts
- versioned trial records
- inclusion and exclusion criteria
- site and recruitment status
- consent and access metadata
Produces
- candidate trial lists
- criterion-level match traces
- missing and ambiguous data flags
- coordinator review packets
Applied to
- trial discovery support
- criteria-to-record screening preparation
- missing-data and coordinator-review queues
Components you need to assemble
A working implementation needs 5 distinct components. Each is a build-or-buy decision in its own right.
- versioned trial registry retrieval
- clinical data normalization
- criteria parser
- privacy and consent controls
- coordinator and investigator review workflow
Implementation complexity: high. This describes the integration and evaluation effort, not the difficulty of any single component.
Deployment patterns
Deployment options recorded for this workflow: managed-api, hybrid.
Topologies it has been recorded against: serverless-api, managed-container, hybrid-private-cloud. Each changes the data-residency, scaling and cost profile, so confirm the one you need against current provider documentation.
Cost and latency
- Trial refresh, terminology normalization, chart review, missing-data resolution, coordinator outreach, and adjudication dominate cost.
- Optimize for missed-match and false-assurance risk, not candidate-list volume.
How this workflow fails
Observed failure modes for this class of workflow. Design a check for each one before shipping, not after.
- stale trial status
- wrong criterion parsing
- false candidate match
- missed candidate
- missing patient fact treated as negative
- privacy or consent breach
Risk areas the evidence covers
- trial-record freshness
- criterion parsing
- candidate recall and precision
- missing-data handling
- human eligibility review
- privacy and auditability
Proving it works before you ship
Evaluation readiness: Partial — Criterion extraction, candidate recall, false-match, missed-match, missing-data, traceability, and reviewer measures are defined; disease-, site-, and protocol-specific cases remain required.
Worked evaluation case: Coordinator-reviewed trial prescreening
Screen authorized patient facts against versioned trial criteria while preserving criterion-level evidence, unknowns, and coordinator escalation.
What to measure
- criterion extraction accuracy
- candidate recall and precision
- unknown and missing-data handling
- trial-status and site freshness
- coordinator correction, escalation, and review time
Governance and data handling
- Process patient information only under approved purpose, access, consent, security, retention, and disclosure controls.
- Treat every match as a screening candidate; coordinators and investigators retain eligibility, consent, and enrollment authority.
Implementation notes
- Version each trial record and criterion, preserve the patient-source field for every comparison, and distinguish unknown from false.
- Refresh recruitment and site state and route ambiguous, conflicting, time-sensitive, or clinically interpretive criteria to qualified staff.
What this blueprint does not establish
- Registry records and patient data can be incomplete, stale, ambiguous, or differently encoded.
- This workflow does not guarantee eligibility, enrollment, clinical appropriateness, site capacity, or treatment benefit.
Source coverage: Partial — ClinicalTrials.gov provides structured study records and API access; HHS defines safeguards for electronic protected health information. Neither establishes patient eligibility, consent, site availability, or enrollment.
Sources reviewed 2026-07-02. Revalidate trial records, recruitment and site status, criteria, patient data, privacy controls, and reviewer policy continuously.
Sources
- ClinicalTrials.gov Data API U.S. National Library of Medicine · official · accessed 2026-07-02
- The HIPAA Security Rule U.S. Department of Health and Human Services · official · accessed 2026-07-02
Candidate models and benchmarks
Candidate models with published references, the providers behind them, and the benchmarks whose task shape bears on this workflow are on the Clinical Trial Matching workflow reference. This blueprint covers implementation; that page covers selection.
Continue your research
Use these connected ModelRefs sections to compare alternatives, inspect implementation paths, and review the evidence and governance boundaries relevant to Clinical Trial Matching — Architecture Blueprint.