How agentic AI speeds payables, accruals, and compliance in trials.
Agentic AI is most valuable when it turns trusted operational signals into finance outcomes without manual handoffs. In clinical trials, that means orchestrating site/vendor payables and monthly accruals directly from CTMS, EDC, and eTMF events with evidence attached. Begin by declaring “finance-eligible” triggers in your data model: site activation requires regulatory greenlight, executed contract, and essential-document pack in eTMF; per-visit grants require a completed visit in EDC plus CTMS verification and no open critical queries for that visit; closeout fees require documented completion of closeout tasks.
Encode these as rules so agents can evaluate eligibility deterministically and generate pre-validated payable candidates with links to the governing contract term. For accruals, align methods to cost behavior: unit-of-service for visit-driven lines, percent-complete for long-running services, and straight-line for phase fees. Agents can refresh drivers on fixed cadences (weekly for enrollment and visits; monthly for deliverables), publish assumptions, and calculate confidence bands based on recent variance. Tie outputs to a shared semantic layer so journals are explainable and repeatable. Speed comes from automation, trust comes from evidence.
Every agent action should attach source proofs: CTMS/eTMF readiness artifacts for start-up fees, EDC visit IDs and timestamps for per-visit lines, courier or imaging confirmations for pass-throughs. Make outputs visible in role-based worklists so reviewers focus only on exceptions. With this design, AI becomes the engine of a predictable, audit-ready finance pipeline rather than a black box.
Even robust rules degrade if they are never checked against reality. Use AI to continuously detect anomalies and policy drift—then explain why. Start with a library of controls that matter: three-way matching success (contract term, evidence, invoice line), FX variance versus policy bands, withholding accuracy by country pack, duplicate detection across payees and lines, and latency from event to payable to disbursement.
Train models to spot outliers: amounts outside FMV bands for a site cohort; sudden drops in auto-match rate after a protocol amendment; visit counts that look implausible for a country’s activation curve; or repeated IBAN/BIC rejects in a region. Prioritize explainability. For each alert, present the features that drove the flag—e.g., effective rate exceeded the site’s rate card by X% after applying modifiers; visit dates fall outside allowed windows; FX rate source timestamp missing. Provide “next best actions”: request evidence, correct rate mapping, re-run FX using the declared window, or route to a specific role. Where risks intersect with quality and safety, align detection to risk-based monitoring concepts so financial and operational controls reinforce each other; TransCelerate’s materials on RBM are a helpful touchstone at TransCelerate RBM resources.
Keep models healthy with drift monitoring. When dictionary or policy versions change (e.g., visit names, rate cards, country packs), record effective dates, run regression checks, and compare pre/post behavior. This ensures alerts stay reliable and reviewers aren’t fatigued by false positives.
Governance turns clever agents into trustworthy teammates. Anchor your agent design in recognized expectations for electronic systems—validation, security, attribution, and audit trails. The FDA’s guidance on computerized systems in clinical trials outlines principles relevant to finance automations at FDA computerized systems. Validate intended use: document rules, data sources, test evidence, and change control.
Separate business logic from transport so retries are idempotent and correlation IDs let reviewers trace a payment from trigger to bank confirmation in minutes. Embed segregation of duties (SoD) into workflows. Agents can auto-approve low-risk items under thresholds when all evidence is present, but dual approvals should be required for high-amount or exception cases. Keep immutable audit trails for every action—who approved what, when, why, and which evidence supported it—and present these trails in inspection-ready binders. For validation best practices, align to a risk-based approach that encourages critical thinking; ISPE’s GAMP 5 (2nd ed.) overview is a useful reference at ISPE GAMP 5.
Finally, close the loop with metrics. Publish cycle time from event to payable to disbursement, first-pass auto-approval rate, exception aging by reason, FX variance versus policy, and audit-trail completeness. Run monthly retrospectives to tune rules, retrain models where justified, and update country packs and rate cards. With explainable AI inside a governed operating model, sponsors pay faster, dispute less, and walk into audits with confidence.