Let's Talk Risk! Podcast

In this audio brief, we unpack a recent Class I recalls of the Boston Scientific Watchman TruSeal Access System. What began as a rare but catastrophic risk of air embolism evolved into a global procedural-safety lesson for the entire MedTech industry.

Key themes:

* Procedural vs. device risk: How the true hazard emerged from workflow variation, not product failure.

* Scale-driven exposure: Commercial success amplified rare risks as adoption expanded to community hospitals.

* Narrative analytics: Text mining of MAUDE reports uncovered 43 % of events that structured codes missed - a three-to-four-month early warning.

* Regulatory blind spot: Substantial-equivalence pathways preserved untested procedural assumptions.

* Strategic mitigation: Boston Scientific chose updating information for safety as the appropriate risk control measure and not product removal.

* Industry-wide signal: Similar Abbott access-system recalls revealed a shared procedural vulnerability, highlighting the need for peer vigilance.

* Evolving vigilance: Turning post-market surveillance from a compliance task into strategic intelligence.

Actionable takeaways for QA/RA leaders:

* Integrate narrative analytics to detect weak procedural signals early.

* Bridge verification gaps with proactive human-factors and workflow validation.

* Adopt cross-manufacturer vigilance: treat competitor recalls as intelligence triggers, not isolated events.

* Align risk management with growth: ensure vigilance capacity scales with commercial expansion.

* Reframe safety as a value driver: invest in foresight tools before crisis forces the case.

🎧Listen to the audio brief above for an overview of this case and lessons learned.

Thanks for reading Let's Talk Risk!. This post is public so feel free to share it.

Note:

This audio brief was prepared using Google NotebookLM, an AI-enabled research tool. Here is the list of resources used in our analysis:

* WATCHMAN TruSeal Access System Class 1 Recall, FDA recalls database entry.

* Boston Scientific Urgent Field Safety Notice, Issued 29 July 2025.

* Boston Scientific WATCHMAN TruSeal Recall Analysis, Unpublished report

The text summary was created using ChatGPT-5 (October 2025) with expert review. It distills publicly available information on the Boston Scientific WATCHMAN TruSeal Access System recall and related regulatory insights. While reviewed for accuracy and relevance, it does not constitute legal, regulatory, or medical advice. Medical-device safety and vigilance practices continue to evolve, and details may change after publication.

We encourage listeners to interpret these findings in the context of these constraints.

Summary

“Risk management is nothing without asking questions. And just as important, we need to create a culture where people aren’t afraid to ask them, because without that, everything grinds to a halt.”

In this Let’s Talk Risk! conversation, host Naveen Agarwal welcomes Edward Ball, Manager of Intelligence and Strategic Execution at RQM+. Ed shares insights from his 20+ years in medical devices, including his unique perspective gained through roles at MHRA, ConvaTec, Fresenius Kabi, and now RQM+. The conversation dives into his role in monitoring regulatory intelligence, supporting clients in navigating evolving global requirements, and making sense of the shifting landscape of risk and compliance.

Ed and Naveen explore key themes from the recent RAPS Euroconvergence Conference, including the growing influence of AI in regulatory processes, the importance of standardized IMDRF coding for vigilance and trending, and the need to bridge gaps between post-market surveillance, risk management, and complaints handling. They also reflect on how language and interpretation such as “indicators,” “benefit-risk ratio,” and “state of the art” are shaping our understanding and regulatory expectations. Ed closes with a reminder that asking the right questions, building systems that deliver actionable answers, and fostering a culture of curiosity are essential to effective risk management.

Listen to the full 30-minute podcast or jump to a section of interest listed below.

Chapters

* 00:10 – Introducing Edward Ball

* 02:41 – Insights from the RAPS Euroconvergence Conference

* 04:41 – AI in MedTech regulation and FDA’s use of AI tools

* 07:00 – AI for vigilance reporting and trending of adverse events

* 09:00 – Importance of IMDRF coding and challenges with standardization

* 12:00 – Disconnect between vigilance, complaints, and risk management files

* 16:20 – Indicators vs. thresholds in post-market surveillance

* 18:30 – Misinterpretations of “benefit-risk ratio” and “state of the art”

* 22:00 – Regulatory expectations vs. manufacturer practices

* 23:47 – Announcements, Key takeaways and Closing Comments

If you enjoyed this podcast, consider subscribing to the Let’s Talk Risk! newsletter.

Suggested links:

LTR: Defining state of the art can be challenging - here are a few tips.

LTR: AI use cases in MedTech regulatory applications.

ACHIEVE: PMS Workshop.

Key Takeaways

* AI is increasingly used by regulators for trending and vigilance, but its outputs are only as reliable as the inputs.

* Standardized IMDRF coding is critical for consistent vigilance reporting and meaningful trend analysis.

* Many companies still struggle to align internal complaints data with standardized codes, creating disconnects in risk management.

* Post-market surveillance (PMS) is not new, but it must be integrated into the quality and risk management system, not treated as a silo.

* “Indicators” in PMS are not always numeric; a single new signal or case can be just as important as statistical thresholds.

* Misinterpretation of terms like “benefit-risk ratio” or “state of the art” can cause regulatory confusion and misaligned expectations.

* Regulators, notified bodies, and manufacturers often use different definitions, underscoring the need for clearer common language.

* Building PMS systems around the questions you need to answer ensures data is actionable for patients, regulators, and companies.

* A culture of curiosity where people feel safe asking questions is essential for effective risk management.

* Continuous learning and diverse perspectives strengthen both regulatory understanding and organizational decision-making.

Keywords

AI in MedTech, Vigilance reporting, IMDRF coding, Post-market surveillance (PMS), Risk management, Regulatory intelligence, Benefit-risk ratio, State of the art, Trend reporting, Complaints handling, Patient safety

About Edward Ball

Edward Ball is a seasoned medical device specialist with over 20 years of experience spanning regulatory compliance, risk management, product safety, quality systems, and post-market surveillance. He has held leadership roles at RQM+, Fresenius Kabi, ConvaTec, and the UK’s MHRA, where he led complex investigations, vigilance reporting, and technical reviews of medical devices.

With a strong foundation in medical engineering (MSc, University of Liverpool), Edward brings deep expertise in design controls, incident investigation, and CAPA systems, helping organizations navigate evolving global regulatory frameworks and ensure patient safety.

Let’s Talk Risk! with Dr. Naveen Agarwal is a weekly live audio event on LinkedIn, where we talk about risk management related topics in a casual, informal way. Join us at 11:00 am EST every Friday on LinkedIn.

Disclaimer

Information and insights presented in this podcast are for educational purposes only, and not as legal advice. Views expressed by all speakers are their own and do not reflect those of their respective organizations.

Parts of this article were created using AI-generated content, which was subsequently reviewed, edited, and fact-checked by the author to ensure accuracy and alignment with our standards.

Summary

“Ethical and compliant AI adoption isn’t a barrier to innovation. It makes your business stronger and more resilient.”

In this Let’s Talk Risk! conversation, host Naveen Agarwal reconnects with longtime friend and Silicon Valley tech leader Ajay Dankar, Co-Founder of Trussed AI. Ajay shares insights from his career at Google, AWS, Adobe, and PayPal, and explains how generative and agentic AI are reshaping industries from healthcare to finance.

Together, they explore the promise and uncertainty of AI adoption, and how regulations like the EU AI Act and America’s new AI Action Plan will shape compliance, why trust and governance are central to enterprise deployment, and what skills QA and RA professionals need to thrive in an AI-driven world. Ajay emphasizes that ethical and proactive AI governance isn’t a barrier to innovation, rather a pathway to building better, more resilient businesses.

Listen to the full 30-minute podcast or jump to a section of interest listed below.

Chapters

* 00:26 – Introducing Ajay Dankar

* 01:12 – How AI is Shaping Everything We Do

* 03:32 – Generative vs. Agentic AI

* 06:02 – Regulations and the U.S. AI Action Plan

* 10:13 – What Senior Executives are Asking

* 16:17– Opportunities for QA/RA Professionals

* 23:32 – Announcements, Key Takeaways and Closing Thoughts

If you enjoyed this podcast, consider subscribing to the Let’s Talk Risk! newsletter.

Suggested links:

LTR: Kevin Schawinski on Building Trustworthy AI and MedTech Readiness.

LTR: Contrasting US and EU approaches to AI regulation.

ACHIEVE: PMS Workshop.

Key Takeaways

* AI is fundamentally reshaping how work gets done across industries.

* Generative AI creates new content, while agentic AI aims for autonomous decision-making.

* The U.S. AI Action Plan offers a blueprint for compliance, innovation, and governance.

* Regulations will require proactive integration of AI governance into development pipelines.

* Trust is a central challenge. Enterprises must ensure compliance, transparency, and reliability.

* Most organizations have moved past AI pilots and now face execution and scaling challenges.

* QA and RA professionals have a unique opportunity to lead enterprise-level AI governance.

* Skills in AI literacy and critical thinking are essential for future career growth.

* Compliance is no longer a “checkpoint”; it must be embedded into workflows from the start.

* Ethical, well-governed AI adoption strengthens business resilience and customer trust.

Keywords

AI governance, generative AI, agentic AI, compliance, trust, regulatory landscape, medtech, enterprise adoption, ethical AI, proactive governance

About Ajay Dankar

Ajay Dankar is a seasoned product and engineering leader with deep expertise in cloud infrastructure, enterprise-grade platforms, and AI-driven innovation. Currently the Co-Founder of Trussed AI, he is focused on making generative and agentic AI trusted and enterprise-ready. Ajay has held senior leadership roles at Google, Amazon Web Services, Adobe, Aviatrix, and PayPal, where he drove large-scale product strategies, cloud transformations, and SaaS platform development.

An entrepreneur and innovator at heart, Ajay has co-founded multiple startups, authored four U.S. patents in multi-factor authentication, and successfully built Finsphere—a fintech company acquired by Visa. With a proven track record of leading multi-geo teams, mentoring talent, and aligning technology with customer needs, he brings a rare blend of business acumen, technical depth, and customer empathy. Ajay holds degrees in Electrical Engineering from the Indian Institute of Technology, Delhi, and the University of Florida.

Let’s Talk Risk! with Dr. Naveen Agarwal is a weekly live audio event on LinkedIn, where we talk about risk management related topics in a casual, informal way. Join us at 11:00 am EST every Friday on LinkedIn.

Disclaimer

Information and insights presented in this podcast are for educational purposes only, and not as legal advice. Views expressed by all speakers are their own and do not reflect those of their respective organizations.

Parts of this article were created using AI-generated content, which was subsequently reviewed, edited, and fact-checked by the author to ensure accuracy and alignment with our standards.

In this audio brief, we unpack the practical implications of the FDA’s Final Guidance on Computer Software Assurance (CSA), issued September 2025.

The debate highlights two perspectives:

* Quality professional’s view: CSA cuts unnecessary documentation, aligns validation with patient safety risk, and supports agile manufacturing.

* Auditor’s view: CSA’s reliance on qualitative judgment, binary risk classification, and vendor dependence creates new challenges for audits, SOPs, and Part 11 compliance.

Key themes include:

* The distinction between CSA process risk vs. ISO 14971 medical device risk.

* The binary “high vs. not high process risk” classification and its audit implications.

* Use of unscripted testing (exploratory, scenario, error guessing) and the challenge of proving rigor.

* Vendor accountability in cloud/SaaS environments and continuous deployment.

* The cultural shift required for manufacturers to define and defend “profound judgment” in risk decisions.

Ultimately, CSA is framed as both an opportunity for efficiency and a test of organizational maturity in risk-based quality management.

🎧Listen to the audio brief above for an overview of the AI/ML device recalls, emerging vulnerabilities and trends to watch.

Thanks for reading Let's Talk Risk!. This post is public so feel free to share it.

Note:

This audio brief was prepared using Google NotebookLM, an AI-enabled research tool. Here is the list of resources used in our analysis:

* Computer Software Assurance for Production and Quality System Software, Final Guidance issued on September 24, 2025.

This summary was created using ChatGPT-5 with expert review. It distills publicly available information on the FDA’s Final Guidance on Computer Software Assurance (CSA). While reviewed for accuracy and relevance, it does not constitute legal, regulatory, or medical advice. Software assurance practices in healthcare are rapidly evolving, and details may change after publication.

We encourage listeners to interpret these findings in the context of these constraints.

Summary

“Compliance can’t just be a once-per-year audit anymore. It has to be continuous, proactive, and built into the way we work every day.”

In this Let’s Talk Risk! conversation, Naveen Agarwal speaks with Adam Foresman, Co-Founder and CEO of Ryden Solutions, about building the first platform for continuous compliance gap analysis in the life sciences industry. Adam shares his journey from leading quality and regulatory affairs at a diagnostic AI startup, where he managed hundreds of requirements as a department of one, to envisioning a “virtual FDA inspector” that continuously highlights QMS health and compliance gaps.

The discussion explores how regulatory bodies like FDA and EU notified bodies are already deploying AI to review submissions, why trust and validation remain critical for adoption, and how companies can prepare their culture and QMS for this shift. Adam emphasizes that while AI can streamline audits, inspections, and submissions, Quality professionals must remain vigilant, collaborative, and open to continuous improvement. The message is clear: proactive compliance, powered by AI, is quickly becoming the new standard for life sciences organizations.

Listen to the full 30-minute podcast or jump to a section of interest listed below.

Chapters

00:08 – Introducing Adam Foresman

01:00 – From Quality Leader to Startup Founder

02:56– What Proactive Compliance Really Means

04:23 – AI Agents for Regulatory Gap Assessments

07:21 – Trust and Validation in AI Systems

13:00 – Real-World Use Cases and Benefits

19:06 – Preparing for an AI-Enabled Future

22:16 – Standardization, Culture Shift & Key Takeaways

If you enjoyed this podcast, consider subscribing to the Let’s Talk Risk! newsletter.

Suggested links:

LTR: Databases and automation tools for clinical evaluation.

LTR: Contrasting US and EU approaches to AI regulation.

ACHIEVE: PMS Workshop.

Key Takeaways

* Proactive compliance shifts QMS from periodic audits to continuous monitoring.

* A “virtual FDA inspector” can highlight compliance gaps in real time.

* Seamless EQMS integration is critical for adoption and user trust.

* AI-driven platforms must be validated with rigorous accuracy testing.

* Regulators like FDA and EU notified bodies are already using AI for submissions.

* Trust in AI systems depends on transparency, validation, and human oversight.

* Real-world use cases show benefits in inspections, audits, and onboarding.

* False positives are manageable if systems allow human review and override.

* Culture shift toward openness and continuous improvement is essential.

* Quality professionals should focus on collaboration and adaptability in an AI-driven future.

Keywords

Proactive Compliance, Continuous Auditing, QMS, Regulatory Affairs, FDA, EU MDR, AI in Quality, Gap Analysis, EQMS Integration, Trust in AI

About Adam Foresman

Adam Foresman is Co-Founder and CEO of Ryden Solutions, a platform that automates compliance gap analysis and audits for life science companies. He has led global quality and regulatory affairs at VideaHealth, driving approvals and compliance for AI/ML diagnostics, and held senior roles at Midmark Corporation, Dentsply, and Hollister. Adam holds engineering degrees from Purdue University, an MBA from Indiana University’s Kelley School of Business, and multiple ASQ certifications, including Six Sigma Black Belt.

Let’s Talk Risk! with Dr. Naveen Agarwal is a weekly live audio event on LinkedIn, where we talk about risk management related topics in a casual, informal way. Join us at 11:00 am EST every Friday on LinkedIn.

Disclaimer

Information and insights presented in this podcast are for educational purposes only, and not as legal advice. Views expressed by all speakers are their own and do not reflect those of their respective organizations.

Parts of this article were created using AI-generated content, which was subsequently reviewed, edited, and fact-checked by the author to ensure accuracy and alignment with our standards.

Summary

“EU MDR is the spiritual ancestor of the EU AI Act”.

In this Let’s Talk Risk! conversation, host Naveen Agarwal welcomes Kevin Schawinski, astrophysicist turned AI entrepreneur and CEO of Modulos AG. Kevin shares his journey from studying black holes to building AI governance solutions, and explains how the EU AI Act is modeled after the EU Medical Device Regulation (MDR). He highlights the parallels between product safety regimes in MedTech and emerging AI regulation, offering practical insights for organizations preparing for compliance.

The conversation explores ISO 42001 as a baseline AI management system standard, the implications of fine-tuning large models, and why medical device professionals may actually be better prepared than most industries to navigate AI regulation. Kevin emphasizes the importance of responsible deployment across culture, processes, and technology, and leaves listeners with a clear message: MedTech organizations already have the tools and mindset to take a leadership role in shaping trustworthy AI.

Listen to the full 30-minute podcast or jump to a section of interest listed below.

Chapters

00:10 Introducing Kevin Schawinski - From Black Holes to AI

03:29 How EU AI Act Parallels EU MDR

07:00 MedTech Readiness for AI Compliance

11:00 Defining and Building Responsible AI

20:13 Managing Risks Across Supply Chain

23:19 Announcements and Key Takeaways

If you enjoyed this podcast, consider subscribing to the Let’s Talk Risk! newsletter.

Suggested links:

LTR: Contrasting US and EU Approaches to AI Regulation.

LTR: Eight Practical Actions to Future-Proof Your AI Enabled Medical Devices.

ACHIEVE: PMS Workshop.

Key Takeaways

* The EU AI Act mirrors MDR’s risk-tiered framework.

* MedTech pros are better prepared than most for AI rules.

* ISO 42001 is the new baseline for AI management.

* 42001 helps, but doesn’t ensure AI Act compliance.

* Fine-tuning AI models shifts full responsibility to you.

* Responsible AI needs culture, process, and tech alignment.

* EU and U.S. AI laws are moving fast but differ in approach.

* U.S. states push ahead, driving calls for federal law.

* AI supply chains create hidden liability risks.

* MedTech can lead in trustworthy AI using existing practices.

Keywords

EU AI Act, MDR, Risk-tiering, ISO 42001, Compliance, Liability, Fine-tuning, Responsible AI, Trustworthy AI, Supply chain, MedTech, Governance

About Kevin Schawinski

Kevin Schawinski is the Co-Founder & CEO of Modulos AG, where he leads the development of AI governance solutions that align with global standards such as the EU AI Act and the U.S. NIST AI Risk Management Framework. An astrophysicist turned entrepreneur, he previously served as an assistant professor at ETH Zurich, published in leading journals like Nature and Science, and pioneered the use of machine learning in astrophysics. Today, Kevin contributes to international AI policy efforts with NIST and the European Commission, advocating for responsible and trustworthy AI innovation.

Let’s Talk Risk! with Dr. Naveen Agarwal is a weekly live audio event on LinkedIn, where we talk about risk management related topics in a casual, informal way. Join us at 11:00 am EST every Friday on LinkedIn.

Disclaimer

Information and insights presented in this podcast are for educational purposes only, and not as legal advice. Views expressed by all speakers are their own and do not reflect those of their respective organizations.

Parts of this article were created using AI-generated content, which was subsequently reviewed, edited, and fact-checked by the author to ensure accuracy and alignment with our standards.

In this audio brief, We unpack an academic study that compares the EU’s MDCG 2019-16 and the FDA’s cybersecurity guidance, benchmarking them against international best practices. Both documents cover the basics, but each leaves troubling gaps, especially in areas like authentication, secure coding, network security, and resilience.

Key points in this audio brief:

* The biggest risks of connected medical devices and why cybersecurity is now inseparable from patient safety.

* Where the EU and FDA guidance converge, and where they diverge.

* Thematic gaps: authentication, cryptography, secure coding (EU) vs. network security and resilience (FDA).

* Why existing vulnerabilities often stem from implementation failures, not policy gaps.

* A proposed structural fix: separating high-level principles from device-specific technical guidance.

* How stronger enforcement or penalties could change manufacturer behavior.

For professionals in regulatory affairs, risk management, and MedTech development, this conversation highlights where guidance is falling short, and what’s needed to drive consistent, secure practices across the industry.

🎧Listen to the audio brief above for an overview of the AI/ML device recalls, emerging vulnerabilities and trends to watch.

Thanks for reading Let's Talk Risk!. This post is public so feel free to share it.

Note:

This audio brief was prepared using Google NotebookLM, an AI-enabled research tool. Here is the list of resources used in our analysis:

* Cybersecurity requirements for medical devices in the EU and US - A comparison and gap analysis of the MDCG 2019–16 and FDA premarket cybersecurity guidance, Research Letter | Computational and Structural Biotechnology Journal, July 2025.

This summary was created using ChatGPT-5 (September 2025) with expert review. It distills publicly available information on EU and FDA cybersecurity guidance for medical devices. While reviewed for accuracy and relevance, it does not constitute legal, regulatory, or medical advice. Cybersecurity in healthcare is a rapidly evolving field, and details may change after publication.

We encourage listeners to interpret these findings in the context of these constraints.

Summary

“Wireless coexistence is not a checkbox. It’s a risk management approach”.

In this Let’s Talk Risk! conversation, Dr. Naveen Agarwal sits down with Omar Al Kalaa, PhD, Founder of Inovectrum and former FDA wireless scientist, to explore the challenges and opportunities of integrating wireless technology into medical devices. Omar shares his journey from academic research on wireless coexistence to leading FDA initiatives on 5G-enabled medical devices, offering a unique perspective at the intersection of MedTech, telecom, and regulatory science.

The conversation covers key issues manufacturers face when adopting wireless connectivity, such as defining quality of service, assessing risk categories, and ensuring coexistence in crowded spectrum environments. Omar explains why medical devices must be viewed as connected systems rather than standalone products, highlighting risks from Bluetooth- and Wi-Fi-enabled devices, lessons from real-world recalls, and the growing need to integrate safety, cybersecurity, and interoperability into design. His takeaways emphasize a holistic, systems-based approach to innovation and evaluation in connected healthcare.

Listen to the full 30-minute podcast or jump to a section of interest listed below.

Chapters

01:00 Omar’s Journey - From Academia to FDA to Entrepreneurship

03:35 Understanding First Principles of Wireless in MedTech

06:14 Risk Categories for Wireless Functions

08:16 Understanding Wireless Coexistence

13:00 Thinking in Systems, Not a Stand Alone Device

15:35 Real-World Recall Example

19:17 Wireless Immunity and 5G

24:42 Announcements, Key Takeaways and Closing Thoughts

If you enjoyed this podcast, consider subscribing to the Let’s Talk Risk! newsletter.

Suggested links:

LTR: A new paradigm for building connected medical devices.

LTR: FDA guidance on interoperable devices.

ACHIEVE: PMS Workshop.

Key Takeaways

* The FDA wireless guidance is crucial for incorporating wireless technology.

* Understanding the risk category for wireless functions is essential.

* Wireless coexistence is a risk management approach, not just a checkbox.

* Medical devices should be viewed as interconnected systems.

* Cybersecurity must be considered alongside other technical aspects.

* Evaluating the end-to-end system is vital for safety and performance.

* Device manufacturers should consult relevant technical documents for guidance.

* The introduction of new technologies requires updated evaluation standards.

* Communication between devices can impact performance and safety.

* A holistic approach is necessary for effective risk management.

Keywords

Medical devices, wireless technology, risk management, FDA guidelines, wireless coexistence, medical systems, cybersecurity, connectivity, healthcare innovation, regulatory compliance

About Omar Al Kalaa

Omar Al Kalaa is the Founder and Principal of Inovectrum, a technology practice bridging MedTech and telecom through wireless innovation. He helps companies design and deploy high-performance connectivity solutions for medical devices, clinical environments, and digital health systems.

Before founding Inovectrum, Omar spent over eight years at the FDA, where he led regulatory science initiatives on 5G-enabled medical devices, developed wireless coexistence standards, and guided industry on complex compliance challenges. With a PhD in Electrical and Computer Engineering from the University of Oklahoma, he combines deep technical expertise with regulatory insight to advance future-ready connected health technologies.

Let’s Talk Risk! with Dr. Naveen Agarwal is a weekly live audio event on LinkedIn, where we talk about risk management related topics in a casual, informal way. Join us at 11:00 am EST every Friday on LinkedIn.

Disclaimer

Information and insights presented in this podcast are for educational purposes only, and not as legal advice. Views expressed by all speakers are their own and do not reflect those of their respective organizations.

Parts of this article were created using AI-generated content, which was subsequently reviewed, edited, and fact-checked by the author to ensure accuracy and alignment with our standards.

Summary

“Management listens when you connect patient risk to product requirements and business goals.”.

In this Let’s Talk Risk! conversation, host Naveen Agarwal and Richard Matt delve into the complexities of communicating risk to senior executives. They explore the common challenges faced by risk practitioners in effectively conveying risks and the importance of framing these discussions in terms of both risks and benefits. Richard shares his experiences and insights on building trust, engaging middle management, and the evolving definitions of benefits in risk management. The discussion emphasizes the need for clear communication, prioritization of patient safety, and the integration of project and patient risks to foster better decision-making and collaboration within organizations.

Listen to the full 30-minute podcast or jump to a section of interest listed below.

Chapters

00:10 Introducing Richard Matt

02:01 Understanding the Communication Breakdown

05:02 Connecting Technical and Management Perspectives

06:16 Effective Communication Strategies in Risk Management

09:12 Navigating Middle Management Dynamics

15:50 The Importance of Framing Risks and Benefits

17:07 Expanding the Definition of Benefits in Risk Management

20:31 Authority and Credibility in Risk Management

23:05 Announcements, Key Takeaways and Conclusion

If you enjoyed this podcast, consider subscribing to the Let’s Talk Risk! newsletter.

Suggested links:

LTR: Communicate to facilitate collaboration, not to impose opinions.

LTR Webinar: Benefit-risk evaluation of an AI/ML enabled device.

ACHIEVE: FMEA workshop.

Key Takeaways

* Communication with management about risks is crucial.

* Integrating project risks with patient risks enhances understanding.

* Building trust is essential for effective collaboration.

* Early communication prevents crises from escalating.

* Understanding leadership concerns helps frame discussions.

* Middle management dynamics can complicate risk communication.

* Framing risks in terms of benefits is vital for engagement.

* Simplifying risk management practices can improve efficiency.

* Authority in risk management comes from expertise, not just position.

* Listening to customer complaints provides valuable insights.

Keywords

Risk communication, senior executives, risk management, patient safety, project management, collaboration, trust, benefits, medical devices, leadership

About Richard Matt

Richard Matt is Principal Consultant at Aspen Medical Risk Consulting, with over 30 years of experience in product development, quality engineering, and risk management. He specializes in innovative methods for benefit–risk assessment, FMEA, and integrated product development, helping medical device companies strengthen compliance and improve patient safety.

He is also the inventor of a patented “risk algebra” approach that enables clear, defensible comparisons of benefit and risk, a breakthrough with wide implications for devices, biologics, and combination products.

Let’s Talk Risk! with Dr. Naveen Agarwal is a weekly live audio event on LinkedIn, where we talk about risk management related topics in a casual, informal way. Join us at 11:00 am EST every Friday on LinkedIn.

Disclaimer

Information and insights presented in this podcast are for educational purposes only, and not as legal advice. Views expressed by all speakers are their own and do not reflect those of their respective organizations.

Parts of this article were created using AI-generated content, which was subsequently reviewed, edited, and fact-checked by the author to ensure accuracy and alignment with our standards.

Note: this is an updated version of the original article first published on Sep 8. It has been corrected for an error in the number of AI/ML enabled medical devices cleared by the FDA mentioned in the original article.

In this audio brief, we unpack recalls data on AI/ML enabled medical devices to gain insights on emerging vulnerabilities from a risk management point of view.

Here are a few key highlights

* The Landscape: 1,247 FDA cleared AI/ML devices across 155 product codes; 38 recall events identified for a deep dive.

* Recall Severity: Mostly Class II recalls, no Class I recalls.

* Leading Causes:

* Software and algorithm errors (e.g., incorrect dose calculations).

* Data integrity issues (e.g., misfiled or missing images).

* Hardware failures (e.g., loose CT table bolts).

* Labeling & approval lapses (e.g., unapproved software versions).Four-tier, risk-based system; stringent requirements for high-risk systems (including many medical devices); compliance timelines of 1–3 years.

* Trends to Watch:

* High rate of recalls within 12 months of clearance.

* Devices without clinical validation face more, and larger, recalls.

* Public companies account for nearly all recalled units, suggesting market pressures for faster launches without adequate clinical validation.

* Takeaways for stakeholders:

* Manufacturers: Strengthen lifecycle controls, prioritize pre-market validation, enhance post-market vigilance.

* Regulators: Consider time-limited approvals and stronger oversight of high-volume AI devices.

* Clinicians: Validate AI results with clinical judgment—trust but verify.

* Patients: Benefit from innovation but remain vulnerable; safety must remain paramount.

AI in MedTech is transformative but not without risk. The challenge is moving from compliance - driven recall response to active risk mitigation for robust safety and effectiveness.

🎧Listen to the audio brief above for an overview of the AI/ML device recalls, emerging vulnerabilities and trends to watch.

Thanks for reading Let's Talk Risk!. This post is public so feel free to share it.

Note:

This audio brief was prepared using Google NotebookLM, an AI-enabled research tool. Here is the list of resources used in our analysis:

* JAMA: Early Recalls and Clinical Validation Gaps in Artificial Intelligence - Enabled Medical Devices, Research Letter | AI in Health Policy, August 2025.

* AI/ML Recalls Analysis - Unpublished report, created using ChatGPT.

This summary was created using ChatGPT-5 (September 2025) with expert review. It distills publicly available information on FDA-cleared AI/ML-enabled devices and related recall patterns. While reviewed for accuracy and relevance, it does not constitute legal, regulatory, or medical advice. AI in healthcare is a rapidly evolving area, and details may change after publication.

We encourage listeners to interpret these findings in the context of these constraints.