A risk-based approach to vendor assurance that goes beyond certificates and questionnaires — deciding which vendor evidence to leverage, which claims to challenge, and which controls to independently verify.
Includes live access & recording
AI-enabled and cloud-based GxP systems increasingly depend on vendors for infrastructure, software development, security, data management, AI models, monitoring, and ongoing change. This creates a practical validation question: which vendor evidence can be leveraged, which claims must be challenged, and which controls or outcomes must be independently verified by the regulated company?
This webinar presents a risk-based approach to vendor assurance that goes beyond collecting certificates and supplier questionnaires. It addresses how to evaluate vendor documentation, audit evidence, validation packages, cloud controls, AI lifecycle information, data governance, service-level commitments, and change-management practices.
Particular attention is given to defining the regulated company's responsibilities under shared-responsibility models and to maintaining sufficient control over GxP-relevant data and decisions.
The traditional supplier-qualification approach is often not sufficient for modern cloud and AI-enabled GxP systems. Vendors may provide extensive evidence, but regulated companies remain accountable for determining whether that evidence is relevant, current, complete, and appropriate for the intended use. Participants will learn how to distinguish evidence that can reasonably be leveraged from evidence that requires challenge or independent verification.
The webinar provides a practical framework for assessing vendor assurance without unnecessarily duplicating vendor activities. It also addresses common gaps such as unclear shared responsibilities, insufficient transparency of AI models and changes, weak data-governance controls, and over-reliance on certifications.
The result is a more efficient, defensible, and inspection-ready approach to supplier and system assurance.
By the end of this session, participants will be equipped to run vendor assurance for cloud and AI-enabled GxP systems that is proportionate, defensible, and inspection-ready.
Apply a risk-based framework for vendor assurance of cloud-based and AI-enabled GxP systems.
Distinguish vendor evidence that can be leveraged from evidence that should be challenged or independently verified.
Evaluate shared-responsibility models and identify retained responsibilities of the regulated organization.
Assess vendor controls for data integrity, security, AI lifecycle management, monitoring, and change control.
Define proportionate audit, assessment, and verification activities based on GxP impact and system risk.
Recognize common vendor-assurance weaknesses that can create inspection and validation risks.
Four focused areas that will strengthen how your organization assures vendors of cloud and AI-enabled GxP systems.
Apply a framework that scales audit, assessment, and verification effort to GxP impact and system risk — without duplicating vendor activities.
Separate what the vendor controls from what the regulated company must retain, and keep sufficient control over GxP-relevant data and decisions.
Evaluate model lifecycle, training data, monitoring, drift, transparency, and change management for AI components in GxP systems.
Challenge vendor claims, identify evidence gaps, and judge when independent verification is necessary and how far it should go.
A comprehensive examination of vendor assurance across cloud services and AI components in GxP computerized systems.
Professionals across quality, regulatory, IT, validation, and vendor organizations responsible for cloud and AI-enabled GxP systems.
Quality Assurance Departments
Regulatory Affairs Departments
IT and Digital Transformation Departments
Manufacturing and Operations Departments
CSV and CSA Specialists
System Owners and Subject Matter Experts
Data Integrity Specialists
AI Governance Teams
Compliance and Audit Managers
SaaS and Cloud Service Providers
Vendors and Consultants Supporting GxP Systems
AI-enabled and cloud-based GxP systems increasingly depend on vendors for infrastructure, software development, security, data management, AI models, monitoring, and ongoing change. The traditional supplier-qualification approach — collecting certificates and supplier questionnaires — is often not sufficient for these systems, because regulated companies remain accountable for determining whether vendor evidence is relevant, current, complete, and appropriate for the intended use.
A risk-based approach to vendor assurance evaluates vendor documentation, audit evidence, validation packages, cloud controls, AI lifecycle information, data governance, service-level commitments, and change-management practices — and defines the regulated company's responsibilities under shared-responsibility models so that sufficient control is retained over GxP-relevant data and decisions.
Common gaps include unclear shared responsibilities, insufficient transparency of AI models and changes, weak data-governance controls, and over-reliance on certifications. Addressing them produces a more efficient, defensible, and inspection-ready approach to supplier and system assurance.
Milan Kučera is a senior validation and GxP technology professional focused on computerized systems, laboratory systems, data integrity, cloud environments, and emerging technologies in regulated organizations. His work combines practical validation and compliance expertise with a strong focus on risk-based approaches, quality strategy, and inspection readiness.
He has a particular interest in the application of modern technologies, including cloud computing and AI, within regulated GxP environments, with emphasis on governance, data integrity, validation strategy, lifecycle management, and effective human oversight. His approach is to translate complex regulatory and technological expectations into practical controls, evidence, and implementation strategies that can be applied by Quality, IT, validation, and business teams.
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