Tom Ambrosole hosts Bina Patel, a pharmacovigilance leader with 30+ years' experience, to discuss why AI change management now centers on people rather than technology. Patel explains that organizations have accepted AI is the future, so the key challenge is building confidence and trust by positioning AI as support for scientific judgment, not a replacement. She recommends a clear vision tied to outcomes like patient safety, strong leadership sponsorship via a "sponsorship spine" from executives to frontline managers, early and ongoing communication, and capability building through training and safe experimentation. They discuss creating psychological safety, leaders modeling learning and transparency (including when AI fails), and balancing innovation with governance through clear guardrails, human review, and regulatory compliance. Adoption is evident when language shifts from compliance to value, supported by KPIs for productivity, quality, and time saved on repetitive tasks.

00:00 Welcome and Guest Intro 01:05 Why People Matter Now 02:23 Overcoming Fear and Building Trust 06:41 What AI Ready Means 08:40 Building the Leadership Spine 10:58 Leading Without Being the Expert 15:42 Governance and Compliance Guardrails 17:38 Measuring Adoption After Go Live 20:56 KPIs and Business Outcomes 23:58 Final Advice and Closing

(Note: This episode was recorded on June 22nd 2026) Jason Bryant of ArisGlobal interviews pharmacovigilance consultant Denny Lorenz of Lorenz Bratti GmbH about the CIOMS XIV expert working group guidance on safely operating AI in pharmacovigilance.

Lorenz explains the group began before ChatGPT and had to rework the guidance after November 2022, shifting from proprietary-model practices to enduring, principle-based guidance developed with regulators, academia, and industry. The principles are linked and anchored in a risk-based approach; "human oversight" is often misunderstood as sufficient on its own, but must be complemented by privacy, transparency, documentation, and governance. They discuss why AI requires ongoing monitoring and regression testing, including monitoring human–machine interaction and overtrust risk, and why many pilots stall due to unclear guardrails and metrics. An open question is how regulators will respond to reduced 100% human review once performance data is robust.

00:00 Meet the Hosts

00:55 CIOMS XIV Sets the Stage

01:49 Before and After ChatGPT

03:11 Stakeholders at the Table

03:58 Principles Over Technology

04:47 Risk Based Foundation

05:22 Human Oversight Explained

08:29 From Hype to Governance

09:36 Guardrails and Metrics

10:48 Enterprise Tools and Ad Hoc Use

11:32 Making Guidance Implementable

12:37 Why Monitoring Matters

13:19 Regression Testing Prompts

14:06 When AI Gets Too Good

15:07 Inspecting AI Reasoning

16:39 Pilot to Production Checklist

18:40 Dynamic Risk Governance

19:15 Oversight Without 100% Review

21:08 SMEs From Day One

23:10 Working Group Next Steps

24:07 Guidance Enables Trust

In this AI Exchange podcast episode, Jason Bryant (ArisGlobal) and Sam Wallace (BMS) discuss how the conversation in life sciences has shifted from whether AI works to whether organizations are ready to trust it as it moves beyond workflow automation into judgment-heavy pharmacovigilance work. They describe progress at BMS in adverse event processing, including strong and improving F1 accuracy scores, expanded data extraction coverage, and the challenge of reducing 100% QC as trust, governance, and change management lag behind rapidly advancing technology. They explore perception gaps about AI maturity, the limits of pursuing "perfection" in probabilistic systems, and the promise of agentic AI, evaluators, and human-in/on-the-loop models to enable risk-based, regulator-friendly oversight, aiming toward touchless, explainable processing while prioritizing people, process simplification, and durable customer value over model novelty. 00:00 Welcome and Introductions 00:18 From Works to Trust 01:37 Agentic AI vs Humans 02:46 18 Months of Change 04:52 Perception vs Reality 07:13 Value Over Perfection 10:34 Why BMS Started 11:58 Scaling and Agentic QC 15:18 Trust in Practice 17:09 Designing for Trust 19:18 Agentic Work Delegation 19:56 Benchmarking Long Tasks 21:09 Redesigning Complex Workflows 22:52 Separating Hype From Reality 23:57 Vision Execution Governance 25:32 Touchless Safety Processing 27:08 Ask Me Anything Reflections 28:46 Fear Doubt And Trajectory 30:49 Predictability And Hybrid AI 11:17 People Over Technology 34:58 Closing Takeaways Trust

The episode of the Life Sciences, AI Exchange features Hans Van Leeuwen (a regulatory consultant at ArisGlobal) and Ian Crone (Head of Regulatory Strategy and Growth at ArisGlobal) discussing how regulatory affairs (RA) is changing as pharma moves from document-based submissions to structured data. They note that companies still lack a true "single source of truth," relying on fragmented systems, manual handoffs, Excel trackers, and costly reconciliation that can create duplication, inconsistencies, and errors—pressures intensified by faster development and accelerated reviews post-COVID. They argue structured regulatory data (including IDMP) improves standardization, data quality, and internal communication, while enabling earlier detection of discrepancies as agencies increasingly use AI/ML to analyze submissions. They propose RA evolve from a submission-focused function to a product-data steward leading master data governance, API-enabled integrations, and unified RIM approaches, with structured master data hubs helping speed time to market and reduce delays. 00:00 Podcast Overview 00:38 Meet the Hosts 01:10 Data Everywhere in Pharma 02:37 No Single Source of Truth 04:51 Shift to Structured Submissions 07:06 IDMP as a Data Standard 09:08 RA as Data Steward 10:51 Culture Shift and AI Fears 12:30 Future RA in Development 15:16 Master Data Strategy and RIM 17:15 Wrap Up and Thanks

Moderator: Ian Crone, ArisGlobal

Panellists:

• Remco Munnik (Arcana Life Sciences)
• Peter Brandstetter (Accenture)
• Frits Stulp (Implement Consulting Group)

In this episode, the focus is on IDMP and its role in transitioning from document-based to data-driven regulatory affairs. Key points include the status of IDMP adoption within the EU, the readiness and challenges of current systems, and the potential of structured data to empower AI applications.

The conversation highlights how structured, high-quality product data can enhance regulatory processes, from signal detection to submission automation. Participants stress the importance of robust data foundations, referencing examples from other industries and emphasizing the transformative potential of data governance. The discussion concludes with actionable steps for companies to make meaningful progress, emphasizing the alignment of leadership, structure, tooling, and mindset in embracing data and AI for improved healthcare delivery.

00:42 Episode Overview: IDMP in Motion 01:04 Guest Introductions 01:35 Current State of EU IDMP Adoption 03:01 EMA's Role and Data Management 08:04 AI Applications in Regulatory Affairs 12:22 The Importance of Data Quality 13:07 Future of AI and IDMP in Regulatory Affairs 17:35 Challenges and Solutions for Implementation 23:39 Predictions for the Future 28:45 Actionable Steps for Companies 32:12 Conclusion and Final Thoughts

In this episode of the Life Sciences Gen AI Exchange Podcast, host Lucinda Smith, Chief Safety Product Officer at ArisGlobal, talks with Claudia Lehmann Head of Global PSPV Operations at Boehringer Ingelheim.

They discuss the journey and practical application of AI in pharmacovigilance, the benefits of AI and automation over the past five years, and the current use of Gen AI to further improve processes. The conversation covers the decision-making process behind adopting AI, overcoming technical hurdles, change management, and the impact on roles and processes within the organization. Claudia highlights the importance of starting small, understanding and assessing risks, continuous learning, and evolving with technology in a highly regulated industry.

00:00 Introduction to the Life Sciences Gen AI Exchange Podcast

00:42 Guest Introduction and Episode Focus

01:02 Journey into AI in Pharmacovigilance

03:06 Challenges and Successes in AI Implementation

05:56 Decision-Making and Project Structure

15:18 Technical Hurdles and Model Validation

18:37 Change Management and Building Trust in AI

29:31 Lessons Learned and Recommendations

33:11 Conclusion and Future Outlook

In this episode of the Life Sciences Gen I Exchange podcast, host Agnes Cwienczek from ArisGlobal discusses the impact of AI on regulatory affairs with Preeya Beczek, a regulatory affairs and compliance expert. They explore the use of AI in regulatory impact assessments, emphasizing the importance of speeding up the process, ensuring compliance, and managing complex data flows. The conversation covers the need for governance, accurate data, and prioritizing use cases to derive maximum value. They also highlight the importance of starting small, involving human elements, and the need for the industry to embrace AI technology actively.

00:00 Introduction to Regulatory AI 00:20 Meet the Experts: Agnes and Priya 01:49 The Growing Importance of AI in Regulatory Affairs 04:23 Challenges in Regulatory Impact Assessment 07:27 AI Solutions for Regulatory Challenges 11:07 End-to-End Regulatory Processes 19:22 The Future of AI in Regulatory Affairs 25:44 Final Thoughts and Advice 28:32 Closing Remarks and Next Steps

Host:

· Emmanuel "Manny" Belabe

• Global Head, Operational Excellence at ArisGlobal

Guest:

• Michelle Bridenbaker, RN, BSN, MS, MBA
• COO of Unbiased Science, VP of MILE (Medical Information Leaders in Europe)

Episode Overview:

AI is revolutionizing healthcare by enhancing patient safety, streamlining medical communications, and driving improved health outcomes. However, as technology takes center stage, the human element must remain a cornerstone of healthcare delivery.

In this episode, we'll hear from Michelle Bridenbaker, a patient-focused leader with deep expertise in healthcare operations, communication, and technology integration. Michelle will explore how AI is shaping the future of healthcare, discuss the importance of maintaining empathy and expertise alongside innovation, and share real-world examples of AI's transformative impact on patient safety and communication.

In this episode of The Life Sciences Gen AI Exchange podcast, host Jason Bryant is joined by Daniel Berglund from Nordic Capital and Aman Wasan of Aris Global to explore the growing impact of generative AI and automation on life sciences research and development.

The discussion covers economic pressures facing the industry, the importance of leveraging the latest technologies, and strategies for effectively driving innovation while managing costs. The experts share insights on practical steps companies can take to implement these technologies to ensure business success amidst competitive and regulatory challenges.

00:00 Introduction to the Life Sciences Gen AI Exchange 00:51 Meet the Experts: Daniel Berglund and Aman Wasson 02:48 Economic Challenges in Life Sciences 05:42 The Role of Automation and Gen AI 07:59 Navigating the Hype and Realities of Gen AI 12:35 Balancing Cost Efficiency and Innovation 17:55 Small Biotech Companies and Automation 18:57 Leveraging Technology for Problem Solving 20:43 Understanding and Addressing Customer Concerns 22:30 Collaborative Problem Solving in Pharma 24:12 Success Stories and Business Cases 26:29 Practical Steps for Leveraging Automation and Gen AI 30:53 Managing Change in Digital Transformations 32:51 Modularity in Modern Technology 33:33 Conclusion and Future Discussions