New GCP Revision Redefines Vendor Oversight and Digital Accountability

At SCOPE Europe 2025, experts underscored that the revised International Council for Harmonisation (ICH) Good Clinical Practice (GCP) guideline, E6(R3), signals a paradigm shift in clinical trial oversight. The new guidance challenges sponsors to rethink traditional models and embrace risk-based, data-driven, and technology-aware oversight. The session emphasized that decentralized and hybrid trial designs, growing vendor complexity, and the proliferation of digital systems demand a fundamentally new operational mindset.

The discussion highlighted that the GCP revision elevates vendor management as a cornerstone of study quality and compliance. As sponsors increasingly rely on multiple niche technology vendors instead of single large CROs, oversight can no longer be one-size-fits-all. The panel explained that the new guidance supports proportional oversight—focusing resources on what is truly critical to quality while ensuring documentation, traceability, and risk transparency throughout the study lifecycle.

From Risk to Action: Building Structured Oversight Frameworks

Speakers outlined how organizations must now integrate vendor management into broader Integrated Quality Management (IQM) frameworks. This begins as early as protocol development, where sponsors should define critical-to-quality factors (CTQs) and link them directly to vendor deliverables and data flows. The process, they explained, involves mapping each vendor’s service against study endpoints, identifying dependencies, and classifying vendors as critical or non-critical.

A formalized risk assessment process—performed before contracting—was presented as essential. Companies are moving toward front-loading risk management, using structured criteria that include vendor qualification outcomes, IT risk evaluation, prior performance data, and alignment with protocol objectives. Once completed, all findings are documented in a Vendor Management Plan (VMP), which is reviewed and updated throughout the trial.

The panel described a three-tiered oversight model emerging from this methodology: in-depth, standard, and low oversight.

• In-depth oversight applies to critical vendors or systems—especially those handling blinded data or supporting patient safety. It demands active sponsor involvement, cross-functional reviews, audit trail verification, and defined governance schedules.
• Standard oversight can rely on CRO-established processes, maintaining sponsor visibility through quality and performance reviews.
• Low oversight covers non-critical vendors whose output does not directly impact primary or secondary endpoints.

Panelists noted that this risk-proportionate approach aligns with regulators’ expectations that sponsors demonstrate oversight even when tasks are delegated to third parties.

Digital Systems and the New Regulatory Expectation

A pivotal focus was the requirement to maintain a full inventory of computerized systems used in each study—an often-overlooked provision of the new guideline. For every system, sponsors must define its intended use, assess its criticality, and document validation and configuration controls. Systems classified as critical are now included in the vendor management plan and subject to documented oversight and testing procedures.

Speakers emphasized that this change represents a concrete regulatory expectation rather than a theoretical recommendation. Computerized system oversight must extend to incident management, ensuring service providers report deviations, failures, or cybersecurity issues promptly. The process also requires bidirectional communication between sponsors, CROs, and vendors to prevent oversight silos.

Organizations are turning to analytics and visualization tools such as Power BI to operationalize these frameworks. Such dashboards enable continuous risk signal detection, trend analysis across studies, and escalation of recurring issues to program-level governance. The panel indicated that the future of oversight lies in centralized monitoring combined with digital analytics—not static spreadsheets or post-hoc audits.

The Rise of AI-Enabled Oversight

The session closed with a forward-looking discussion on artificial intelligence in vendor and data oversight. While the current GCP revision does not explicitly regulate AI, panelists agreed that sponsors should proactively document AI use in study plans for reproducibility and traceability. They suggested that AI’s near-term role lies in automating monitoring signals, summarizing risk reports, and flagging anomalies across large datasets, allowing human reviewers to focus on higher-level interpretation.

Experts cautioned, however, that governance maturity varies widely across organizations. AI should supplement, not replace, human oversight. They emphasized that companies must define a transparent framework outlining where and how AI supports processes such as vendor qualification or data quality review, ensuring that its outputs remain verifiable and auditable.

Toward Continuous, Documented Accountability

The revised GCP E6(R3) guideline ultimately formalizes what many sponsors have already begun—embedding quality into process design rather than inspecting it after the fact. The session underscored several takeaways:

• Documentation is no longer optional. Every decision—vendor classification, oversight intensity, or system validation—must be traceable and risk-justified.
• Oversight extends beyond contracts. Quality agreements and KPIs alone are insufficient; sponsors must monitor real data signals and issue trends.
• Digital oversight is now integral. Maintaining inventories, configurations, and incident logs for all computerized systems is a regulatory necessity.
• AI requires governance. Its use in automation must be recorded in study plans, ensuring transparency and reproducibility.

The panel concluded that the future of clinical vendor management lies in structured, evidence-based oversight ecosystems—ones that link risk assessment, digital accountability, and continuous improvement. Sponsors that embrace this approach will not only meet regulatory expectations but also position themselves for greater agility, data integrity, and operational excellence in the era of decentralized, technology-driven trials.