Programme

Compliance Starts Before the First Brick: Embedding GLP Quality by Design in Facility Development,

In today's evolving regulatory environment, GLP facilities are expected to demonstrate not only compliance during routine operations, but also a clear and defensible approach to how quality and regulatory requirements were considered during facility planning and development. Regulatory inspections frequently identify findings that originate from early design decisions, construction limitations, or insufficient quality oversight during facility development. This session was selected to address this critical yet often underrepresented phase of the GLP lifecycle, emphasizing that compliance truly starts before the first brick is laid.
 

Learning Objectives:

1. Explain how GLP driven quality thinking and Quality by Design principles can be integrated into facility planning, design, construction, and commissioning to minimize downstream compliance risks.
2. Recognize the importance of QA oversight, cross-functional collaboration, and risk-based quality checkpoints in achieving and maintaining inspection-ready GLP facilities.
3. Implement practical, quality-led approaches to embed sustainable compliance into GLP facility development and support long-term regulatory readiness.

Update of GVP Modules in 2026

This session focuses on the upcoming updates to the Good Pharmacovigilance Practice (GVP) modules expected in 2026 and their implications for pharmacovigilance systems across the product lifecycle. GVP modules form the regulatory backbone for pharmacovigilance activities in the EU and beyond, and periodic revisions reflect evolving regulatory expectations, scientific advances, and lessons learned from inspections, safety signals, and public health events. As regulators continue to emphasize data quality, transparency, digitalization, and proactive risk management, staying informed of these updates is essential for maintaining compliance and ensuring patient safety. This presentation will provide an overview of the key GVP modules anticipated to be revised or newly introduced, placing the updates in the context of recent regulatory trends and guidance. The session will translate regulatory updates into practical considerations for marketing authorisation holders and pharmacovigilance professionals. I will discuss the potential impact on pharmacovigilance system master files (PSMFs) and inspection readiness. Particular attention will be given to areas that may require procedural updates, system enhancements, staff training, or cross-functional collaboration to ensure timely and effective implementation. The intended conclusion of this session is to equip participants with a clear, high-level understanding of the 2026 GVP module updates and their anticipated operational impact. Attendees should leave with increased confidence in interpreting the regulatory changes, awareness of potential implementation challenges, and practical insights to support proactive planning and readiness within their organisations.

Learning Objectives:

After attending this session, delegates will be able to: Identify the key updates to the GVP modules planned for 2026 and understand the regulatory drivers behind these changes. Assess the potential impact of the updated GVP modules on pharmacovigilance systems, processes, and compliance activities. Apply practical strategies to support timely implementation and inspection readiness within their organisations.

Good AI Practice in Drug Development: What Does Good Really Look Like?

This session will provide advanced GCP professionals with a structured interpretation of what 'good' AI practice looks like in drug development, aligned with emerging expectations from FDA, EMA, MHRA and ICH E6(R3). Through regulatory framing and practical case-studies, participants will gain the tools to evaluate AI credibility, challenge model outputs and confidently present AI-supported decisions during inspections. 

By the end of the session, attendees will understand how to embed AI within robust GCP governance frameworks - ensuring that innovation accelerates quality rather than undermines it. 

From No Quality System to GLP Recognition: The Journey of an Ivorian Research Center

The Swiss Center for Scientific Research in Cote d'Ivoire (CSRS), a national reference in vector-control research with heavily relied-upon entomology platforms, had no formal quality system at project launch: no written procedures, no equipment tracking, aging infrastructure, and technical/support teams unfamiliar with the OECD GLP standard. This situation evolved through a structuring partnership with the IVCC (UK) and a clear commitment from CSRS leadership, which established a dedicated project governance team (Quality Assurance Manager, deputy, project manager, director of studies). This team delivered a realistic diagnosis, mobilized internal actors, and aligned available resources to launch the key workstreams in parallel.

Session Content
We will demonstrate how that diagnosis triggered the activation of multiple levers: clarification of roles and governance; drafting and rolling out priority procedures (sample reception/identification, laboratory notebooks, document control, equipment tracking and maintenance); intensive training of all technical, administrative, and support staff on the OECD GLP framework; targeted refurbishment of the entomology laboratories (facility upgrades, logistic flows, containment); and rigorous renewal of the equipment fleet (inventory, labeling, maintenance and calibration plans). I will also present the simple, visible tools developed to cascade the practices (operational checklists, equipment and CAPA follow-up tables, GLP roadmap, internal audits aligned with the CAPA system) adapted to the local realities, as well as the change-management approaches (quick wins, live demonstrations, regular communication) that gradually secured team buy-in.

Learning Objectives

AIM 1.    Understand how a realistic diagnostic and structured governance (Quality Assurance Manager, deputy, project manager, director of studies) can mobilize a resource-constrained entomology laboratory toward OECD GLP compliance.
AIM 2.    Apply practical levers - priority procedures, comprehensive training, infrastructure upgrades, and equipment maintenance plans - supported by simple, visible tools (checklists, roadmaps, internal audits, CAPA tracking) tailored to the local context.
AIM 3.    Replicate a sustainable change approach that links leadership engagement, quick wins, and partner support to reinforce GLP culture and data confidence in comparable  research environments.

Workshop - Veterinary Case-Based GCP Masterclass: Applying Quality Principles to Real-World Clinical Scenarios

The AVPC committee will provide dilemmas which will include owner non-compliance, unexpected concomitant treatments, multi-animal households, farm-level deviations, emergency unblinding, and investigator documentation gaps in the contexts of field, companion-animal, and production animal studies, and ask participants to work through these. Each scenario will  invite attendees to explore:

-What VICH GCP requires
-What is scientifically and operationally practical
-How to document decisions clearly and consistently
-How different stakeholders (QA, monitors, investigators, sponsors) may interpret the same event
-How regulators may view the rationale during inspection

By the end of the session, attendees will take away a practical, defensible approach to navigating areas of uncertainty in GCP, improved consistency and clarity in documentation and rationale, and a deeper appreciation of stakeholder perspectives and regulatory expectations.

This workshop is designed for QA professionals of all levels, monitors, and study managers.

By the end of the session, attendees will take away:

• A practical, defensible approach to navigating areas of uncertainty in GCP
• Improved consistency and clarity in documentation and rationale
• A deeper appreciation of stakeholder perspectives and regulatory expectations.

Panel - From Survival to Success: A GCP QA Professional Story to the Startup Biotech Ecosystem

Background: The startup biotech landscape is characterized by rapid growth, evolving processes, and intense pressure to reach milestones. Traditional, large-pharma QA approaches often fail here, perceived as bureaucratic and slowing progress. QA professionals in these settings frequently face isolation, under-resourcing, and the daunting task of building a quality system from the ground up, all while maintaining compliance with international standards. The core challenge is balancing rigorous quality with entrepreneurial agility.
 

Upon completion of this session, participants will be able to:
1.    Design and advocate for a risk-based, phase-appropriate GCP quality system that meets regulatory expectations while supporting startup agility.
2.    Apply effective communication and influencing strategies to champion quality principles to non-QA stakeholders (e.g., executives, investors, R&D staff).
3.    Identify and implement practical tools and methods for efficient trial oversight, vendor management, and documentation in a resource-constrained environment.

Auditing Mindset and Helpful Tips for New Auditors

I am an auditor with close to a decade of experience of auditing  laboratories (GLP, GCLP and ISO15189) and ISAs and vendors for clinical trials (GCP). I began as an internal auditor at laboratories and have moved over to consultancy. I am fortunate in that I have had good mentorship throughout my career and want to share this knowledge. Both tips I received early on and how I worked to overcome obstacles. The right auditing mindset to get the most from the audit. 
 

Learning Objectives:

1.    How to develop the right mindset for auditing

• A.    How to communicate with auditees as an auditor and not an interrogator 
• B.    How more findings does not mean a better audit

2.    How to follow through on issues to identify process deficiencies
3.    How to learn and apply regulations effectively

What No One Tells You When You Move Into QA (But It is Assumed You Know)

Moving into Quality Assurance is often described as a natural career progression for technicians, scientists, study directors, or laboratory professionals. In reality, it represents a fundamental shift in responsibility, authority, and mindset - one that many organisations underestimate and regulators do not excuse.
 

Learning Objectives:

The session provides a practical framework to help new QA professionals:

- Build regulatory confidence without overstepping authority

- Ask better, risk-based questions during reviews and audits

- Understand when to coach, when to escalate, and when to stop work

Debate on the topic (EU Reg 2025/1466) vendor oversight which is the best interpretation of oversight requirements and how can we achieve this?

This session is meant to trigger thoughts on how best different companies will adjust to updated requirements in the EU regulation. Arguments will look at what should be done, impact of increased oversight and achievability. Session will allow for questions from participants who can weigh in on how challenges they are facing.

Learning Objectives:

- EU 2025/1466 regulation impact and management of requirements regarding vendor oversight - Challenges to consider - Opportunities for management

Do Recent Guidance and Regulatory Updates Finally Give Clinical Laboratories More Clarity?

A notable change in UK regulations is the shift from the term ‘trial site’ to ‘trial location’, reflecting a broader recognition that laboratories involved in the analysis or evaluation of human samples are integral to trial conduct. In parallel, sponsors are now explicitly required to select and oversee laboratories. For UK trials, adherence to ICH E6 (R3) is a legal requirement to claim GCP compliance, reinforcing its relevance to laboratory operations.

Learning Objectives:

To understand the impact of recent regulatory and guidance updates on the roles and responsibilities of laboratories involved in clinical trials.
 

Computer Software Assurance (CSA): Caution Still Advised?

Computer Software Assurance (CSA) has been positioned as a modern evolution of validation, promising a more risk based, thoughtful approach that reduces unnecessary effort while protecting safety and data integrity. Since the publication of the final guidance, interest in CSA has continued to increase, but understanding of what it actually says and where it can be applied, varies widely across industry. This session is designed for both those who are new to CSA and those already engaging with it. The presentation will look at what CSA actually is, where it was intended to be applied, and why the FDA felt necessary to put so much focus into this guidance. Rather than promoting CSA as a mandatory change, this presentation will encourage critical thinking and offer a balanced perspective for the audience to make up their own minds. The session will explore whether CSA introduces new skills that QA professionals must develop, or whether it reframes principles that already have long sat at the heart of effective GxP oversight. Ultimately, the session will help the audience decide how CSA fits into their own organisations, roles, and regulatory responsibilities.

Learning Objectives:

• Understand what CSA really is and where it was intended to be applied.
• Explore where CSA may add new value and where it may reframe existing GxP principles.
• Decide whether CSA fits within your own organisation and QA role.

Selecting Risk-Based KPIs that Withstand Regulatory Inspection

Key Performance Indicators (KPIs) are cornerstone of Pharmacovigilance (PV) and Quality Management Systems (QMS), yet organizations frequently receive inspection observations despite extensive KPI monitoring. Common challenges include overly broad KPI sets, limited rationale for selection, limited linkage to risk assessment and metrics that measure activity rather than effectiveness.
 

Learning Objectives:

1.    Selection of Inspection-ready KPI frameworks that support continuous improvement
2.    Effective governance of compliance
3.    Sustained patient safety

Navigating GLP and GCP Challenges in ATMP Development: A CROs Integrated Quality Approach

Advanced Therapy Medicinal Products (ATMPs) represent a rapidly evolving field of preclinical and clinical research, providing innovative therapeutic opportunities for diseases with high unmet medical need. Their development, however, introduces substantial regulatory, operational and quality challenges. 

Learning Objectives:

1. Understand the regulatory, operational, and quality challenges associated with the development of Advanced Therapy Medicinal Products (ATMPs)
 

Beyond Green Dashboards: Are we Designing the PVQA Systems that Matter?

As PV systems become more complex and shift toward a risk‚Äëbased approach, the expectations of regulators and internal stakeholders are evolving. Inspection readiness is no longer demonstrated only through timely metrics, low error rates, or dashboards filled with green indicators. Increasingly, organisations must show the quality of their thinking including how decisions are reached, documented and governed. This emphasis the need of critical thinking, clear decision rationale, and measures that reflect real quality rather than process activity. Now we also have AI which further heightens this need. Those tools support efficiency and consistency, but also require human oversight, thoughtful system design, and clarity around the roles and limits of automation. PVQA teams now play a central role in ensuring that systems are fit for purpose, that risks are understood, and that oversight frameworks capture the outcomes that truly matter.
 

Learning Objectives:

Bring conversation internally to discuss how are they  measuring the quality of their systems.

Death by CAPA - What is Changing with E6(R3)?

Back at the 2023 RQA Conference, I discussed the challenges related to CAPA management in GCP. Since then, the EU CTR was completely implemented in the EU and ICH GCP E6(R3) was published and is being gradually implemented across the globe. 
 

Learning Objectives:

1. I have an issue - should I initiate a CAPA right away?
2. Protocol Deviations - what's new (and not so new), and how should I handle them in the new way?
3. CAPA Effectiveness Check - what is it and why is it not the same as an Action Verification?

Regulatory Evolution in South America: Operational Implications of ICH E6(R3

As global expectations for Good Clinical Practice continue to evolve, South America is undergoing a significant regulatory transformation driven by adoption and integration of ICH E6 (R3), with diverse implementation approaches across countries and regulatory agencies. This shift is redefining how sponsors, CROs, and investigative sites operate across the region, strengthening quality systems and reshaping compliance standards. 
 

Learning Objectives:

Participants will gain a clear understanding of the key regulatory changes and their implications for clinical trial operations; explore where sponsors, CROs and sites should focus to align processes with the revised GCP expectations; and identify essential elements to enhance inspection readiness and reinforce overall GCP compliance in a rapidly evolving regulatory landscape - regardless of where their studies are conducted.

Scaling Regulatory Compliance and Excellence: Challenges and Enablers for Pharmacovigilance Risk-Based Audit Planning

Digital Enablers of Risk-Based Audit Planning explore how technology and smarter collaboration are reshaping regulatory oversight. Many organizations continue to face challenges such as unclear roles, weak agreements, and the absence of a comprehensive scientific and quantitative approach to risk-based audit planning, leaving audit strategies inconsistent and vulnerable.

This session will demonstrate how risk assessment and audit planning tools, digital communication platforms, and innovations can bring structure, transparency, and measurable improvements in compliance, time & cost efficiency, and patient safety.

Through real case studies, we will highlight how affiliates and strategic partners can collaborate effectively with global PV QA teams to build scalable, consistent, and future-ready audit systems. By combining digital enablers with stronger collaboration, companies can create audit programs that are compliant today and resilient for tomorrow.

Learning Objectives

• Introduce a scientific and quantitative approach to strengthen risk-based audit planning.
• Use digital communication and planning tools, along with real-time data and cloud systems, to improve transparency and efficiency.
• Clarify roles and responsibilities through well-defined agreements to support effective oversight.
• Build scalable and consistent audit systems by collaborating with affiliates, strategic partners, and global PV QA teams.

ICH E6(R3) Compliance Using Data-Enabled Risk Intelligence: The Future of GCP Auditing

Learning Objectives

• Understand the importance of data analytics in implementing risk-based quality oversight as required by ICH E6 (R3)
• Use of risk-based strategies to identify potential or actual cases of serious non-compliance with the protocol, GCP and/or applicable regulatory requirements to improve inspection outcomes

Panel - Pick Your Battles: The Audit Scenarios No One Warns You About

Auditing in a GxP environment demands more than technical knowledge  -  it requires judgement, interpersonal skills, and the confidence to navigate situations that don't always have a straightforward answer.

In this session, a panel of QA professionals, representing a spectrum of experience levels and sectors, will discuss the complex and sometimes uncomfortable auditing moments that shaped their practice. From handling resistant auditees and conflicting priorities to determining when to escalate versus when to compromise, each panelist will share real situations that tested their judgement and professionalism.

The discussion will highlight practical tools new auditors can use to assess risk in the moment, maintain composure, reinforce audit integrity, and keep stakeholder relationships constructive  -  even under pressure. Attendees will gain a clearer understanding of the variety of challenges they may encounter, reassurance that difficult situations are normal, and concrete strategies to approach them with confidence and clarity.

Learning Objectives:

The attendees will take away:
1. The skills to identify common types of challenging audit scenarios and understand how experienced auditors evaluate risk and decide on next steps
2. Be able to apply practical judgement frameworks to determine when to escalate concerns, when to hold firm, and when a balanced compromise is appropriate
3. How to use effective communication and stakeholder management techniques to navigate conflict, pushback, or ambiguity during audits.

Audit Ready AI Workflows: Testable Interoperability for Training, RAG and Inference

AI assurance often fails for a simple reason: we validate 'the model' but we do not control the end-to-end data workflow that feeds training, retrieval-augmented generation (RAG) and inference. In practice, the dominant failure modes are not exotic algorithms - they are interoperability defects: schema drift, ambiguous terminology bindings, silent mapping changes, loss of provenance, and unstable retrieval corpora that alter answers without any visible 'model change'.

This session proposes a pragmatic approach that combines (1) an Evidence Package required before use and (2) continuous assurance required during use.

Before use, we show how to specify an evidence package that is procurement-ready and audit-ready: intended use boundaries, asset inventory (data sources, transformations, embeddings index, prompts, model versions), and a versioned interoperability 'mapping manifest' (schemas, terminology/value sets, transformation rules, units, and null semantics). We then turn the manifest into hop-by-hop assertions and negative tests (missing/invalid codes, wrong units, broken referential integrity, timestamp anomalies) so interoperability becomes measurable rather than aspirational.

During use, we show how to monitor both behaviour drift and workflow drift (schema/terminology/provenance), how to treat corpus changes as controlled changes, and how to convert monitoring into continuously collected audit evidence.

Attendees will leave with a reusable evidence-package template, an interoperability test pattern library, and a standards-anchored checklist aligned to ETSI's newest work on baseline AI security, data supply-chain security, AI documentation, and continuous auditing.

Learning Objectives

• Define an AI Evidence Package that covers training + RAG + inference, not just the model.
• Make interoperability testable using mapping manifests, assertions and negative tests.
• Specify and measure provenance survival end to end (including through embeddings + retrieval).
• Implement monitoring for behaviour drift + workflow drift, and turn it into audit evidence.

The Quality Professionals in the Age of AI: How AI Regulations and Cybersecurity Frameworks Will Shape the Future of Quality,

The Quality professionals can expect a ground-breaking shift that will expand their usual scope of work. Two seismic tremors include the emerging AI regulations and mandatory cybersecurity requirements.

This session will explain the most likely scenario for the transformation of the Quality-related roles and will include:

• A complex story of the current state of AI regulations (including, but not limited to, prEN 18286, the Quality Management System for EU AI Act regulatory purposes) and how they can impact risk management, delivery, use, and maintenance of future AI GxP systems.
• How emerging cybersecurity frameworks need to be considered in a regulated setting.
• How the regulatory changes from the FDA's transition to Computer Software Assurance (CSA), the European updates to Annex 11, and the new Annex 22 are closely related to compliance, software quality assurance, and expectations of the regulators.
• The ways to adopt new knowledge and successfully apply it to the GxP landscape, and to change the way Quality is currently considered.

Learning Objectives

• In the modern world of emerging AI regulations and cybersecurity threats, Quality professionals need not only to adapt but also to understand the matter to proficiently lead organisations.
• The new and updated regulations and the expectation of the regulators will require not necessarily a technical but rather a mental shift for many Quality personnel.
• The stronger IT industry focus on emerging cybersecurity frameworks (and their adoption in companies) will require closer collaboration between Quality and IT security experts to achieve a cohesive approach that aligns both perspectives.

Do We Really Need to Validate an e-Signature Tool Used by Half the Industry?

Learning Objectives

• Understand the link between validation, fitness for purpose, and data integrity
• Explain (e.g., to management or budget holders) why validation is needed even for low-risk systems
• Apply flexible approaches to system validation

IQ, OQ, PQ - No More? Driving Value-Adding Records

Learning Objectives

• Understand why IQ, OQ, PQ may not be the best option for most computerised systems, and explore alternative strategies to reduce unnecessary documentation while maintaining control and data integrity.
• Gain confidence in challenging legacy practices and driving cultural change towards value-adding CSV.
• Discover how digital validation tools can streamline CSV and improve traceability without increasing burden.

Quality Challenges in Combination Products: Drug, Device and Biologic Interfaces

Combination products, combining drugs, biologics and devices (such as insulin pens and drug-eluting stents) are increasingly central to modern healthcare but introduce complex post-market quality and compliance challenges. While individual constituents may meet their respective regulatory requirements, compliance gaps frequently arise at the interfaces between drug, device and delivery systems-particularly in post-market surveillance activities.

Regulatory requirement for combination products vary by region. In the United States, the Primary Mode of Action (PMOA) determines the lead FDA center and regulatory pathway, whereas in the European Union, device constituents require Notified Body involvement under EU MDR. These differing regulatory frameworks result in varying timelines, reporting requirements and vigilance thresholds, increasing the risk of misalignment during post-approval oversight.

Presentation will include common interface-related quality issues observed in combination products, to highlight frequent pitfalls between pharmacovigilance and device-vigilance systems. The presentation will focus on how quality teams can identify, assess and manage interface risks across post-market surveillance for building more integrated and connected quality systems to support sustained regulatory compliance and inspection readiness.

Learning Objectives:

• Attendees will learn to recognize common interface-related quality risks in drug-device and biologic combination products.
• Attendees will gain practical approaches to integrate pharmacovigilance and device vigilance activities.
• Strengthen inspection readiness by addressing interface challenges.

AI and the Future of Clinical Research

Ethical and Regulatory Considerations for AI in Clinical Research

This presentation explores current applications of AI in clinical research and examines emerging trends that may define the next decade. It will address the practical and ethical implications of using AI-driven tools, particularly in relation to data privacy, transparency, algorithmic bias, and oversight.
A key focus will be the EU AI Act, the world's first comprehensive legal framework for artificial intelligence, and its relevance to clinical trials. It will also consider guidance from regulators, such as the European Medicines Agency (EMA) and the U.S. FDA, on AI/ML in drug development and the growing demand for explainable and validated AI models.

The session aims to equip attendees with a balanced understanding of both the opportunities and constraints AI introduces, and to highlight what researchers, sponsors, and regulators must consider to ensure that the integration of AI into clinical trials is responsible, ethical, and compliant.

Learning Objectives

• Ethical and Regulatory Considerations for AI in Clinical Research
• Advancements and Future Prospects

The AI Audit Conundrum: A Balanced Debate on the Role of Artificial Intelligence in GxP Auditing

Learning Objectives

• A Pragmatic, Dual Perspective: Leave with a balanced scorecard of AI's Pros and Cons specific to GxP auditing, moving beyond industry buzzwords.
• The Validation Blueprint Challenge: Understand why validating an adaptive AI model is fundamentally different and more complex than traditional software validation, and what that means for resource allocation.
• The "Explainability" Imperative: Grasp why, in a GxP context, the ability to trace an AI's finding back to a clear rationale is non-negotiable, even if it limits the AI's power.
• The Augmentation vs. Automation Decision: A clear heuristic for deciding where AI should assist the human auditor (augmentation) versus where full automation is a regulatory and ethical step too far.
• Actionable Next Steps: A shortlist of "low-hanging fruit" areas for AI pilot projects (e.g., anonymized data trend analysis for audit planning) and "red flag" areas to avoid initially (e.g., final binary compliance decisions).
• Questions for Your Leadership: Prepared elevator pitches to advocate for cautious exploration or to recommend a moratorium, backed by the regulatory and risk-based arguments covered.

Powering QA of Today with the Technology of Tomorrow

Quality Assurance is entering a new era where traditional, document-heavy approaches are increasingly replaced by digital ecosystems that generate useful real-time data. Yet many QA teams still struggle to translate digital quality metrics into meaningful oversight that influence practical decision-making. By looking at the direction of tomorrow's technology supporting quality management, this session will look at how QA professionals can build the future-ready skills needed to confidently navigate, for example, automated testing outputs, digital traceability, and integrated quality dashboards. Delegates will leave with a clear understanding of how digital validation technology is reshaping quality, and the key skills and competencies QA teams will need to thrive. The purpose of this session is to create familiarity with everyday QA activities supported with advancing technology and try to dispel some fears and misinformation about difficulties in adoption and use.

Learning Objectives

Understand how digital validation ecosystems can generate and use quality data. Learn practical advice and skills that QA can use to take advantage of digital quality data. Discuss the future direction of digital quality systems to better prepare for 2027 and beyond.

Environmental Sustainability: Is it the Next Quality Challenge?

Environmental sustainability in pharmaceuticals is evolving, driven not only by legislative reforms but also by wider societal and regulatory expectations for organisations to minimise their environmental footprint. Across sectors such as consumer goods, manufacturing and technology, companies are increasingly expected to measure, reduce and transparently report their environmental impacts. In comparison, the pharmaceutical industry is still catching up, with particular scrutiny emerging around the environmental consequences of medicines throughout their lifecycle  -  from development and production to patient use and disposal. UK and EU initiatives, ranging from environmental reporting and product/packaging measures to proposals that strengthen environmental considerations in medicinal oversight, signal a shift toward structured, traceable, and evidence‚Äëbased environmental practice.

At the same time, there is a continued drive within the sector to embrace digital tools, automation, and AI. While these technologies offer clear operational benefits, they also carry environmental implications in terms of energy use and data infrastructure. As sustainability reporting frameworks expand, the environmental footprint of digital technologies may become part of organisational expectations, requiring a more holistic approach to understanding and managing environmental impacts.
For QA professionals, the convergence of sustainability, system‚Äëbased expectations, and rising transparency means that environmental commitments are increasingly supported by the same controls used in quality systems - traceability, governance, documented processes, data integrity and lifecycle risk thinking. This session provides a forward‚Äëlooking view of where sustainability in pharma is heading, how the regulatory landscape is shifting, and how QA can begin preparing for what is likely to become a more integrated area of responsibility.

Learning Objectives

• Understand how sustainability expectations in pharmaceuticals are evolving
• Recognise how QA professionals may increasingly be involved in sustainability initiatives

How to Validate AI Agents For GxP Purposes

This session will share the key considerations to ensure that you can validate your AI Agents Solution for GxP purposes quickly and easily. 

1)Your Agent Capability Assessment - how to classify agents based on their complexity ranging from simple isolated agents to hierarchical swarms of  autonomous and self evolving Agents.

2)Your AI Agent Risk Assessment -How to assess your AI Agents based on the GxP Intended use combined with the Agents capabilities (as assessed in step 1).

3)The AI Agents Risk and Controls Strategy- the additional controls required for AI Agents e.g. Human in the Loop at key process steps, restricting access to sensitive data, having documented and traceable reasoning  chains for actions taken. Effective up front design of the AI Agents workflow is key.

4) The Overall AI Agents Validation Strategy  - How to Validate the End to End  AI Agents workflow, including the core Computer Systems, the AI /GEN AI elements and finally the AI Agents reasoning, communications and actions taken.

5) How to Test AI Agents- The evidence of testing that will be required which will be the chain of thought  and Large Language Model as a Judge . The use of approved tools by the AI  Agents to perform tasks , and the acceptable performance to pre-specified metrics . 

6) How to Monitor AI Agents - The use of suitable AI Agents Monitoring tools to capture the reasoning of the agents and the actions taken in a searchable audit trail. The tools to monitor approved metrics and to flag if metrics are drifting out of specification. 

7) Some example Use Cases that demonstrate the validation  of AI  Agents in real life.

Learning Objectives

• To understand how to correctly classify and risk assess AI Agents .
• To understand how to test AI Agents to ensure that they are fit for their intended purpose.
• To understand how to monitor AI Agents in routine use.

Site-level Quality Issues: From Knowledge Gaps to Malicious Non-compliance

Learning Objectives

• Identify common causes of clinical study failures at the site level.
• Propose practical preventive measures to ensure adherence to Good Clinical Practice (GCP).
• Apply conflict resolution strategies to maintain study integrity during challenging situations.

Recent CIOMS Updates in Pharmacovigilance

Pharmacovigilance (PV) continues to evolve in response to growing data complexity, increasing regulatory expectations, and rapid technological advances. Among recent developments, two CIOMS Working Group reports provide particularly important guidance for modern safety systems: CIOMS XII, Benefit–Risk Balance for Medicinal Products, and CIOMS XIV, Artificial Intelligence in Pharmacovigilance. This session will focus on the implications of these two reports for current and future pharmacovigilance practice.

The presentation will first review the key concepts and methodological updates introduced in CIOMS XII, emphasising structured and transparent approaches to benefit–risk evaluation across the medicinal product lifecycle. The session will explore how benefit–risk assessment is evolving from static evaluations toward dynamic, evidence-driven processes integrating clinical trial data, real-world evidence, and patient-centered outcomes. Practical considerations for implementing consistent and transparent benefit–risk frameworks in regulatory submissions, safety monitoring, and risk management activities will be discussed.

The session will then examine the recommendations of CIOMS XIV regarding the responsible adoption of artificial intelligence and machine learning technologies in pharmacovigilance. Topics will include the application of AI in case processing, literature screening, signal detection, and data management, alongside challenges related to validation, governance, transparency, data quality, and regulatory compliance. Emphasis will be placed on ensuring that AI tools enhance safety surveillance while maintaining scientific rigor and regulatory trust.

By linking modern benefit–risk methodologies with emerging AI-driven capabilities, the session aims to demonstrate how pharmacovigilance systems can become more proactive, efficient, and patient-focused. Attendees will gain practical insights into how CIOMS guidance can support the development of future-ready PV frameworks that improve decision-making, strengthen patient safety, and support innovation in medicinal product development and monitoring.

Learning Objectives

• Understand the key principles and methodological advances introduced in CIOMS XII for structured and transparent benefit–risk assessment throughout the medicinal product lifecycle.
• Describe the role and applications of artificial intelligence in pharmacovigilance as outlined in CIOMS XIV, including opportunities and implementation challenges.
• Identify practical approaches to integrating benefit–risk evaluation and AI tools into pharmacovigilance systems to enhance safety monitoring and regulatory decision-making.

Workshop - The Decline of Quality in PV Auditing and PV Auditors as Superheroes

Learning Objectives

• Recognise current challenges in PV audit activities, understand the factors contributing to declining audit quality, and evaluate the shift towards SMART auditing.

• Examine “CAPA utopianism”.

• Define the evolving role and capability of PV auditors as superheroes in AI enabled PV ecosystems.

Auditing AI Governance in Clinical Trials: A Practical Framework for Evaluating Compliance Aligned with E6(R3) and FDA-EMA Guidance

Background
Artificial intelligence is rapidly transforming clinical trial operations across all phases - from AI-assisted protocol development and predictive patient recruitment algorithms to remote monitoring platforms, automated data quality checks, and real-time safety signal detection. The January 2026 FDA-EMA joint publication 'Guiding Principles of Good AI Practice in Drug Development' establishes ten foundational principles for AI governance across the medicines lifecycle, while ICH E6(R3), now implemented across major regulatory jurisdictions, emphasizes Quality by Design and risk-based quality management for technology-enabled trials.

However, industry reality reveals significant compliance gaps. Many organisations deploy AI tools through undisclosed 'shadow use' - staff utilising ChatGPT for literature reviews, employing generative AI for protocol drafting, or implementing analytics platforms without formal governance, validation documentation, or change control. Regulatory inspectors are beginning to probe AI use during GCP inspections, yet many quality professionals lack systematic frameworks to identify, evaluate, and audit AI governance effectively.

GCP auditors face unprecedented challenges: How do you systematically discover all AI applications when employees may not recognise AI tools as requiring oversight? What documentation standards apply when regulatory guidance just emerged? How do you distinguish genuine compliance embedded through proactive design from superficial, checkbox-driven approaches? What constitutes adequate validation for predictive algorithms versus deterministic systems? When existing audit checklists don't address AI governance, where do auditors begin?
 

Learning Objectives

• Evaluate AI governance compliance in clinical trials using a systematic audit methodology aligned with E6(R3), FDA-EMA January 2026 AI Principles, and Compliance by Design (CbD) assessment criteria to determine governance maturity and regulatory readiness.
• Identify and assess AI systems across clinical trial operations through shadow use detection techniques, documentation review (validation reports, risk assessments, vendor qualification), and targeted stakeholder interviews that test genuine compliance versus superficial approaches.
• Classify audit findings using risk-based criteria and write observations that drive sustainable AI governance improvement by referencing current regulatory requirements and distinguishing proactive design from reactive remediation.

Quality That Endures: Human Skills Behind Sustainable Quality,

Quality systems are designed to provide structure, consistency, and control, yet long-term quality outcomes depend just as much on how people interpret expectations, exercise judgment, and make decisions in practice. As organizations grow, adopt new technologies, and operate across increasingly complex environments, quality is tested not only by processes, but by the human skills that support clarity, accountability, and sound decision-making over time.

This session explores the human skills behind sustainable quality and why they matter for both those doing the work and those accountable for quality outcomes. Drawing on real-world experience from audits, consulting engagements, and cross-functional quality environments, the discussion examines where quality tends to erode quietly, not through lack of procedures, but through diluted ownership, unclear decision pathways, and hesitation to influence when it matters most. These challenges are familiar across sectors and geographies, yet they are often treated as cultural issues rather than practical quality risks.

Participants will be guided through common scenarios where judgment, influence, and communication play a decisive role in whether quality holds or degrades. The session will highlight how everyday decisions, including how risks are raised, how expectations are clarified, and how trade-offs are navigated, shape the durability of quality systems far more than documentation alone. Attention will be given to how these dynamics show up differently for practitioners embedded in day-to-day execution and for leaders responsible for maintaining quality over time.

Rather than introducing new frameworks or additional process, the session focuses on strengthening awareness and application of existing responsibilities. Practical examples will illustrate how quality professionals can exercise influence without relying on authority, communicate risk with greater confidence, and support clearer decision-making across functions. The emphasis is on reinforcing quality as a lived practice, carried consistently through people, even as systems, tools, and organizational structures evolve.

The session concludes with clear, actionable insights that participants can apply within their own roles to support sustainable quality outcomes. Attendees will leave with a stronger understanding of the human factors that allow quality to endure, and with practical ways to reinforce clarity, judgment, and accountability in environments where quality must remain credible over time.

Learning Objectives

• Identify specific points in quality processes and cross-functional interactions where human judgment and influence most directly affect whether quality outcomes are sustained or erode over time.
• Use practical approaches to clarify expectations, escalate risk, and support sound quality decisions in situations where procedures alone do not provide sufficient direction.
• Apply influence and decision-making strategies appropriate to their role to reinforce accountability for quality outcomes, both in day-to-day practice and at leadership level.

Curious Conversations: Reclaiming Scientific Thinking to Transform Leadership in Pharma

Learning Objectives

• Explain how curiosity-driven communication can improve trust, engagement, and collaboration across teams and stakeholders in pharma and QA environments.
• Identify common leadership pitfalls in regulated environments and consider coaching behaviours that foster accountability and performance.
• Apply simple conversation techniques to promote curiosity, reflection, and growth in 1:1s, audits, meetings, and team development settings.

Risk Management Automation in GCP R3 Era

Since the adoption of GCP R3, risk management in GxP environments has become both more critical and more complex. Organisations are required to demonstrate continuous, risk-based oversight across increasingly interconnected systems, faster delivery cycles, and shared cloud responsibilities. At the same time, risks are often fragmented across project documents, validation records, incident logs, and audits, making them difficult to track and review in a consistent and sustainable way.

This session explores the practical challenges of automating risk management under GCP R3 and why traditional, document-centric approaches are no longer sufficient. It will demonstrate how modern systems and integrated tooling can be used to centralize risks, enable periodic review, support regulatory expectations, and reduce manual effort without adding unnecessary bureaucracy. The session will conclude with practical takeaways on how to 'pull it all together' into a coherent, automated risk management framework that supports compliance, transparency, and continuous improvement.

Learning Objectives

• Understand the key risk management expectations introduced with the adoption of GCP R3 and their impact on GxP systems and processes.
• Identify common challenges and gaps in traditional risk management approaches and recognise where automation and integrated tools add value.
• Apply practical concepts for centralising, reviewing, and maintaining risks using automated systems to support ongoing compliance and control.

What Are We Doing Here? Overcoming GCP QA's Existential Crisis

Learning Objectives

By the end of the session, attendees will:

1. Understand the historical context that led to the current organization, tasks, structure, and approach for Good Clinical Practice-oriented Quality Assurance

2. Be prepared to modify their current approaches to SOP development, auditing, deviation management, CAPA management, and consultation in a way that adds more value to their organizations while adhering to key GCP principles