Let's Talk Risk! Podcast

Where MedTech professionals gain clarity and confidence to navigate complex decisions.

Let’s Talk Risk! brings together MedTech leaders and practitioners for thoughtful conversations on the challenges that shape risk, quality, innovation, and leadership. With 150+ episodes and more than 30K downloads, it helps professionals gain the clarity and confidence to lead through complex decisions. naveenagarwalphd.substack.com

  1. 2 days ago

    Deep Dive: Designing Safety Into Autonomous Robotic Devices

    The vulnerability of the modern clinical lab is quite literally concentrated at the point of the needle. Clinical laboratories have automated almost everything after the blood reaches the tube. Yet one of the most common invasive procedures in healthcare still depends on a person finding a vein by sight and touch and manually inserting a needle. FDA’s De Novo authorization of Vitestro’s Aletta® may signal that this last major manual bottleneck is beginning to change. But this Deep Dive is about much more than a robot drawing blood. It explores a bigger question for anyone working in risk management, quality, regulatory, clinical, or medical-device development. What does it take to make an autonomous medical device safe enough to perform an invasive clinical procedure on its own? In this audio brief, we unpack how Aletta combines imaging, robotics, software constraints, clinical supervision, and layered fail-safes — and how FDA evaluated a technology for which no predicate existed before. The result is a fascinating case study in how risk management changes when a machine begins doing what previously required a trained human. Key highlights covered in the audio: * De Novo pathway: De Novo authorization was necessary because there was no existing predicate for autonomous robotic phlebotomy. * Risk controls built around autonomy: imaging, software constraints, movement detection and supervisory intervention create multiple layers of protection. * Clinical performance: the ADOPT study reported a 94.5% first-stick success rate when a suitable vein was identified, including strong performance in patients with obesity and difficult venous access. * Specimen quality: robotically collected samples demonstrated analytical equivalence for the laboratory parameters evaluated. * Patient acceptance: 90% reported similar or less pain than manual phlebotomy, while 82% preferred the robotic system or had no preference. * A different workforce model: FDA-authorized use allows one trained phlebotomist to supervise up to three devices simultaneously. Keywords: FDA De Novo, Aletta, Vitestro, autonomous medical devices, robotic phlebotomy, artificial intelligence, medical robotics, risk management, clinical evidence, human oversight, diagnostic testing, automation 🎧Click Play above to listen to a brief audio summary about this groundbreaking technology. Thanks for reading Let's Talk Risk!. If you liked this post, share with others. Note: The audio summary was prepared using Google NotebookLM, an AI-enabled research tool. Here are a few key resources used for this analysis: * Giesen LFP, Roest JA, et al. (2026, April 14). Performance, Safety, and Patient Experience of an Autonomous Robotic Phlebotomy Device: A Multicenter Trial, Clinical Chemistry (hvag029), Oxford Academic * FDA (2026, August 19). FDA Authorizes First-Of-Its-Kind Robotic Blood Draw Device, FDA News Release, FDA * Evidence-Based Medical Insight (2026, August 19). Clinical, Regulatory, and Operational Analysis of the Aletta Autonomous Robotic Phlebotomy System: A New Paradigm in Preanalytical Automation, Evidence-Based Medical Insight * Bristow, H. (2026, May 27). Robotic Phlebotomy Trial: What the Patients Said, The Pathologist This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit naveenagarwalphd.substack.com/subscribe

    Deep Dive: Designing Safety Into Autonomous Robotic Devices
  2. 14 Aug

    LTR 163: FDA’s New Risk Lens Under QMSR

    Summary “I don't think it's as easy to outsource risk as it used to be. Risk is pervasive now.” In this episode of the Let’s Talk Risk! conversation, host Naveen Agarwal speaks with Allyson Mullen, Director at Hyman, Phelps & McNamara, P.C., about what FDA’s early enforcement activity under the Quality Management System Regulation (QMSR) may tell medical device manufacturers about the agency’s evolving expectations. Using the first warning letter discussed in the episode as a starting point, Allyson examines how FDA is citing risk management under ISO 13485 Clause 7.1 and, increasingly, looking at the broader requirement to apply risk-based thinking across QMS processes under Clause 4.1.2. The conversation explores why companies already certified to ISO 13485 should not assume they are fully prepared for an FDA inspection, how FDA inspections may differ from notified-body audits, and why post-market information must feed back into risk management. Naveen and Allyson also discuss the legal and contractual implications of the transition, particularly the importance of reviewing quality agreements and clearly defining responsibilities when activities are outsourced. Finally, Allyson offers practical perspective on responding to FDA 483 observations and warning letters during a period when both regulators and industry are adapting to a new inspection framework. Listen to the full 25-minute podcast or jump to a section of interest listed below. Chapters 01:17 – Introduction and Allyson Mullen’s Regulatory and Legal Background02:17 – FDA’s First QMSR Warning Letter and Its Risk Management Findings03:46 – How FDA’s Language Around Risk Is Changing Under QMSR05:10 – Risk Beyond Design Control: ISO 13485 Clause 4.1.207:42 – When FDA May Look Beyond Product Realization12:48 – Why ISO 13485 Certification May Not Be Enough14:59 – Legal Risks and the Importance of Updating Quality Agreements17:19 – What to Do When FDA May Have Gotten an Observation Wrong21:21 – Warning Letters and the Challenges of the QMSR Transition23:40 – Allyson’s Journey from Regulatory Affairs to Law26:10 – Key Takeaways: Risk, Outsourcing, and Quality Agreements If you enjoyed this podcast, consider subscribing to the Let’s Talk Risk! newsletter. Suggested links: FDA Law Blog: FDA’s First QMSR Warning Letters. LTR Deep Dive: First FDA Warning Letter Under QMSR. LTR: LTR Risk Coach - AI-Powered Decision Support Tool. Key Takeaways * Risk is becoming more pervasive under QMSR. FDA now has clearer regulatory pathways for examining risk beyond traditional design-control activities. * Clause 7.1 may only be the beginning. Product realization provides an obvious entry point, while ISO 13485 Clause 4.1.2 allows FDA to examine whether risk-based thinking is embedded throughout the QMS. * Post-market feedback must close the loop. Complaints, adverse events, recalls, and other post-market information need a defined pathway back into risk management. * ISO 13485 certification does not guarantee an easy FDA inspection. FDA may challenge the methods and reasoning behind risk-based decisions more deeply than organizations have experienced in traditional notified-body audits. * Risk cannot simply be outsourced. Manufacturers remain responsible for understanding and managing risk even when product-realization activities are performed by suppliers or contract manufacturers. * Review quality agreements now. Older agreements may assign responsibilities using the former QSR structure and may not adequately address obligations under ISO 13485 and QMSR. * A 483 is not necessarily the final word. Companies should carefully evaluate FDA observations, provide missing context, correct the record where appropriate, and respond with a complete factual narrative. * The transition creates challenges for both FDA and industry. Early warning letters and inspection observations will be important signals for understanding how FDA applies QMSR in practice. Keywords QMSR, FDA, ISO 13485, Risk Management, Quality Systems, FDA Inspections, Warning Letters, Quality Agreements, Post-Market Surveillance, Medical Devices About Allyson Mullen Allyson Mullen is a Director at Hyman, Phelps & McNamara, P.C., where her work brings together deep experience in FDA regulatory matters and law. Before joining the firm, she served as a Corporate Attorney and Principal Regulatory Affairs Specialist at Waters Corporation, a Senior Regulatory Affairs Specialist at Boston Scientific, and a Regulatory Affairs Associate at DePuy Mitek. She earned her J.D. from New England Law | Boston and began her career in regulatory affairs before transitioning into legal practice—giving her experience on both sides of regulatory and legal decision-making. Let’s Talk Risk! with Dr. Naveen Agarwal is a bi-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 other 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. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit naveenagarwalphd.substack.com/subscribe

    LTR 163: FDA’s New Risk Lens Under QMSR
  3. 7 Aug

    Deep Dive: First FDA Warning Letter Under QMSR

    Under QMSR, FDA is not only looking for individual quality failures. It is examining how failures connect across the entire quality system. FDA’s warning letter to Linemaster Switch Corporation provides an early look at QMSR enforcement in practice. The cited deficiencies extend across risk management, rework, corrective action, environmental controls, calibration, and software validation. The individual expectations are not entirely new. What has changed is the regulatory structure through which FDA evaluates them. By citing specific ISO 13485:2016 clauses, FDA can follow the connections between manufacturing risk, quality data, operational controls, and postmarket feedback rather than treating each deficiency as an isolated compliance issue. The warning letter also demonstrates how a seemingly simple documentation gap—such as a blank root-cause field—may reveal a much broader failure of investigation, escalation, management oversight, and corrective action. Key highlights covered in the audio: * Why risk management must extend beyond the design file and into product realization * FDA’s citation of a missing process FMEA under ISO 13485 Clause 7.1 * How undocumented rework exposed weaknesses in production control and reevaluation * Why a blank root-cause field represented a failed corrective-action feedback loop * How environmental conditions, calibration accuracy, and software validation became interconnected findings * What earlier warning letters reveal about continuity between QSR and QMSR expectations * Practical areas QA and RA leaders should reassess in legacy quality-system records Keywords: FDA QMSR warning letter, Linemaster Switch Corporation, ISO 13485 enforcement, FDA medical device inspections, QMSR risk management, process FMEA, medical device rework, corrective action, software validation, quality system regulation. 🎧Click Play above to listen to a brief audio summary examining what this warning letter may reveal about FDA’s evolving QMSR inspection approach. Thanks for reading Let's Talk Risk!. If you liked this post, share with others. Note: The audio summary was prepared using Google NotebookLM, an AI-enabled research tool. Here are a few key resources used for this analysis: * FDA (2026, May 27). Linemaster Switch Corporation, Warning Letter (CMS 730215), FDA * FDA (2025, November 11). Envoy Medical Inc., Warning Letter (CMS 718762), FDA * FDA (2026, April 30). ZOLL Medical Corporation, Warning Letter (CMS 711320), FDA. * FDA (2026, February 26). Longhorn Vaccines and Diagnostics LLC, Warning Letter (CMS 721702), FDA. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit naveenagarwalphd.substack.com/subscribe

    Deep Dive: First FDA Warning Letter Under QMSR
  4. 31 Jul

    LTR 162: Using HHE for Risk-Based Decisions

    Summary “When done well, HHE evolves from a procedural requirement into a strategic tool that reflects how your organization makes risk-based decisions.” In this episode of the Let’s Talk Risk! conversation, host Naveen Agarwal speaks with Kerry Flecknoe, Senior Manager, Global Quality – HHE at Getinge, about the role of Health Hazard Evaluations in postmarket risk management. Kerry explains that although organizations may use terms such as HHE, HHA, or HRA, the terminology is less important than having a structured and documented process for evaluating health risk. In the QMSR era, organizations must be able to demonstrate that risk-based decisions are made consistently and intentionally—not only within formal risk management activities, but across the quality management system. The conversation explores how ISO 14971 can provide a defensible framework for HHEs, why field actions should themselves be evaluated as risk control measures, and how teams can make responsible decisions when complaint data, probability estimates, or other evidence are incomplete. Kerry also shares practical guidance for smaller manufacturers, cross-functional teams, and distributors of third-party products. Listen to the full 25-minute podcast or jump to a section of interest listed below. Chapters 00:00 – Introduction and Why HHE Matters in the QMSR Era01:24 – What HHE Is, FDA Terminology, and the Need for Documentation05:04 – Building an HHE Process Around ISO 1497106:18 – HHE as Postmarket Risk Management and Field Action as a Risk Control08:41 – Evaluating Probability When Postmarket Data Are Limited14:08 – Cross-Functional Roles and the Mechanics of an HHE16:49 – Feeding Postmarket Evidence Back into the Risk Management File18:42 – Building a Lean HHE Process and Defining Clear Triggers21:11 – Responsibilities of Legal Manufacturers and Distributors23:39 – Career Development and Final Takeaways If you enjoyed this podcast, consider subscribing to the Let’s Talk Risk! newsletter. Suggested links: LTR: Risk-Based Assurance, FDA Expectations Under QMSR. LTR: The Missing Step in Risk Decisions. LTR: TR Risk Coach - AI-Powered Decision Support Tool. Key Takeaways * An HHE is a structured, risk-based assessment used to evaluate a known or potential issue affecting products in the market. * Organizations do not have to use a particular name or standardized format. What matters is demonstrating a systematic and documented conclusion about health risk. * ISO 14971 provides a strong framework for defining the problem, identifying hazards and hazardous situations, estimating and evaluating risk, and considering risk control options. * A field correction, product removal, recall, or decision to leave a product in the market should be treated as a risk-based decision. The action itself may introduce additional risks, including product shortages or reduced access to alternative therapies. * Complaint history alone may not provide an adequate probability estimate. Teams should also consider service records, bench testing, production data, inspection results, scrap, nonconformances, and the possibility of underreporting. * When reliable probability data are unavailable, organizations may need conservative estimates, statistical models, cross-functional judgment, or greater emphasis on the potential severity of harm. * Quality, R&D, Medical, Regulatory, Legal, and senior management should be involved early enough to provide appropriate expertise and oversight. Medical personnel should retain independence when making the clinical assessment. * HHE severity and probability classifications should remain consistent with the organization’s risk management system and product-specific risk acceptability criteria. * Postmarket evidence identified through an HHE should feed back into the Risk Management File so that assumptions, failure modes, controls, and benefit-risk conclusions remain aligned with actual device performance. * Every HHE should end with a clear, documented decision for or against field action. Regulators need to understand how the organization reached its conclusion—not simply what it decided. Keywords AI governance, responsible AI, digital health, systems engineering, risk-based decision-making, quality management systems, third-party AI, model drift, regulatory compliance, critical thinking About Kerry Flecknoe Kerry Flecknoe is Senior Manager, Global Quality – HHE at Getinge, where she provides strategic leadership and end-to-end process ownership for the company’s enterprise-wide Health Hazard Evaluation program. Her work includes HHE governance, methods, digital tools, audit readiness, metrics, process improvement, and support of correction and removal decisions across Getinge's global network of medical device manufacturing sites. Kerry is a quality and regulatory compliance leader and Board Certified Medical Affairs Specialist with more than 20 years of medical device experience spanning quality, medical affairs, clinical support, postmarket surveillance, risk management, and product development. Before her current role, she held senior medical affairs positions at Getinge and spent more than a decade supporting cardiac rhythm management products at Boston Scientific. She holds bachelor’s degrees in Biomedical Engineering and Electrical Engineering from Duke University. Let’s Talk Risk! with Dr. Naveen Agarwal is a bi-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 other 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. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit naveenagarwalphd.substack.com/subscribe

    LTR 162: Using HHE for Risk-Based Decisions
  5. 24 Jul

    Deep Dive: FDA's RWE Guidance

    Real-world data does not become regulatory evidence simply because it is large, current, or readily available. FDA’s December 2025 final guidance, Use of Real-World Evidence to Support Regulatory Decision-Making for Medical Devices, supersedes the 2017 guidance and provides a more detailed framework for determining when real-world data can generate evidence suitable for a medical device regulatory decision. One important change is FDA’s recognition that a sponsor’s inability to obtain participant-level data does not automatically prevent the Agency from evaluating the evidence. But this flexibility does not lower the evidentiary bar. Sponsors must explain the limits of data access and demonstrate—through rigorous, traceable documentation—that the data and resulting analysis are credible. Key highlights covered in the audio: * The difference between real-world data and real-world evidence * How FDA evaluates relevance, including data availability, timeliness, and generalizability * How FDA evaluates reliability, including data provenance, completeness, consistency, quality controls, and traceability * Why protocols and analysis plans should be established before reviewing outcomes * How sponsors should address bias, confounding, missing data, and data-linkage methods * New documentation recommendations for cover letters, study protocols, reports, and eSTAR submissions * When studies using routinely collected data may—or may not—require an IDE Keywords: FDA real-world evidence guidance, real-world data for medical devices, real-world evidence regulatory strategy, RWE relevance and reliability, medical device regulatory submissions, post-market surveillance data, total product lifecycle. 🎧Click Play above to listen to a brief audio summary for a practical examination of FDA’s evolving expectations for real-world evidence. Thanks for reading Let's Talk Risk!. If you liked this post, share with others. Note: The audio summary was prepared using Google NotebookLM, an AI-enabled research tool. Here are a few key resources used for this analysis: * FDA (2025, December 18), Use of Real-World Evidence to Support Regulatory Decision-Making for Medical Devices, Final Guidance, FDA. * Castor Report (2026, April 26). Beyond the EHR: meeting the FDA’s new real-world evidence standards. * IQVIA. (2026, February 06). FDA Updates Guidance on Real-World Evidence for Medical Devices. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit naveenagarwalphd.substack.com/subscribe

    Deep Dive: FDA's RWE Guidance
  6. 17 Jul

    LTR 161: AI Governance by Design

    Summary “Let’s treat AI governance by design as the connective tissue of a product lifecycle ecosystem.” AI governance is often introduced as another layer of oversight—more procedures, approvals, documentation, and checklists. Ankita Mishra offers a different way to think about it: governance should be designed into the digital health product lifecycle from the beginning. In this episode of the Let’s Talk Risk! conversation, host Naveen Agarwal and Ankita Mishra explore how systems thinking and risk-based decision-making can help organizations innovate responsibly without applying the same level of rigor to every product or use case. They discuss flexible quality systems, the importance of defensible rationale, third-party AI solutions, supplier dependencies, privacy and security, model performance, and the need to monitor AI after deployment. The conversation also addresses what AI means for quality, regulatory, and risk professionals. Rather than making human expertise less relevant, Ankita argues that AI increases the need for critical thinking, judgment, collaboration, and continuous learning. Listen to the full 25-minute podcast or jump to a section of interest listed below. Chapters 00:00 – Introduction and Welcome01:04 – Ankita Mishra’s Career Journey04:36 – Reframing AI Governance by Design06:40 – Shifting Critical Thinking Upstream09:11 – Matching Development Rigor to Risk12:20 – Building Defensible Risk-Based Rationales14:17 – AI Governance Across the Product Lifecycle16:03 – Evaluating Third-Party AI and eQMS Solutions18:22 – Preparing Quality and Regulatory Professionals for AI23:00 – Closing Takeaways on Responsible AI If you enjoyed this podcast, consider subscribing to the Let’s Talk Risk! newsletter. Suggested links: LTR: Proactive AI Governance in MedTech. LTR: Building Trustworthy AI and MedTech Readiness. LTR: Evolving Regulatory Landscape for AI in MedTech. Key Takeaways * AI governance should begin with the design decision—not after the technology has already been selected or deployed. * Start with the intended use and the underlying problem. The first question is not simply how to use AI, but whether AI is necessary. * The level of lifecycle rigor should reflect product risk, regulatory status, and the consequences of failure. Not every requirement needs to be applied identically to every solution. * A flexible, risk-based quality system depends on clear reasoning. Organizations must be able to justify both why a requirement applies and why it may not apply. * Responsible AI governance extends beyond the algorithm. It includes privacy, cybersecurity, infrastructure, suppliers, contracts, deployment, maintenance, performance monitoring, and drift. * Organizations evaluating third-party AI tools should understand whether their data will be retained or used for training, what information may be disclosed, and what additional controls may be needed. * A sandbox approach can reduce uncertainty: start with a controlled, lower-risk application, evaluate whether it produces meaningful value, and scale based on evidence. * AI will change professional responsibilities, but it will not eliminate the need for experienced judgment. Critical thinking, systems thinking, collaboration, and organizational knowledge will become even more valuable. * Lifelong learning is no longer limited to formal training. Professionals can learn by engaging with thought leaders, attending conferences, following emerging standards, sharing ideas publicly, and allowing others to challenge their thinking. Keywords AI governance, responsible AI, digital health, systems engineering, risk-based decision-making, quality management systems, third-party AI, model drift, regulatory compliance, critical thinking About Ankita Mishra Ankita Mishra is the Digital Health Quality Director at Evinova, where her work focuses on AI governance and responsible innovation in healthcare, digital health product strategy, lifecycle management, GCP compliance, global standards, and quality systems. She brings more than 20 years of experience spanning software development, biomedical engineering, medical devices, systems engineering, and software quality. Her career has included roles at AstraZeneca, Senseonics, Medtronic, Terumo Cardiovascular Systems, Integra LifeSciences, and Infosys. Ankita holds a master’s degree in public health from Johns Hopkins University, an MS in biomedical engineering from Drexel University, and a BE in electronics from Nagpur University. Her work centers on enabling innovation and regulatory rigor to advance together rather than treating them as competing objectives. Let’s Talk Risk! with Dr. Naveen Agarwal is a bi-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 other 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. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit naveenagarwalphd.substack.com/subscribe

    LTR 161: AI Governance by Design
  7. 10 Jul

    Case Study: Why FDA Cybersecurity Expectations Are Really QMS Expectations

    You cannot bolt cybersecurity onto a medical device at the end of development. FDA’s cybersecurity guidance makes a clear shift: cyber risk is now a quality system issue, a patient safety issue, and a lifecycle management issue. For connected and software-enabled devices, it is not enough to show that the software works as intended. Manufacturers also need to show how cybersecurity risks were identified, controlled, verified, traced to patient harm, and managed after release. In this audio summary, we walk through why FDA’s expectations go beyond submission documentation and why QA/RA teams need to understand the practical connections between SPDF, threat modeling, SBOMs, vulnerability management, postmarket patching, and the medical device QMS. Key highlights covered in the audio: * Why cybersecurity now needs to be treated as part of the medical device QMS * How Section 524(b) changes expectations for “cyber devices” * Why cyber risk needs to connect to patient harm, not just IT vulnerability * How SPDF, threat modeling, architecture views, and testing evidence fit together * Why machine-readable SBOMs and VEX documentation matter for vulnerability management * How postmarket patching, CVD, and cybersecurity management plans create lifecycle obligations Keywords: FDA cybersecurity guidance, medical device cybersecurity, cyber device, SPDF, SBOM, medical device QMS, cybersecurity risk management, patient safety, postmarket cybersecurity. 🎧Click Play above to listen to a brief audio summary about this case and lessons QA/RA and Clinical professionals can apply in practice using the newly released FDA Guidance. Thanks for reading Let's Talk Risk!. If you liked this post, share with others. Note: The audio summary was prepared using Google NotebookLM, an AI-enabled research tool. Here are a few key resources used for this analysis: * FDA (2026, February 3), Cybersecurity in Medical Devices: Quality Management System Considerations and Content of Premarket Submissions, Final Guidance, FDA. * Apotech Consulting. (2026, May 14). The Software Bill of Materials (SBOM): What Every SaMD Manufacturer Needs to Know. Apotech Consulting. * Espinosa, C. (2026). 12 Reasons the FDA Rejects Cybersecurity Submissions. Blue Goat Cyber. * Al-Faruque, F. (2026, February 4). FDA reissues cybersecurity guidance to align with QMSR. Regulatory Affairs Professionals Society (RAPS). * Exponent. (2026, April 6). Navigating FDA's Cybersecurity in Medical Devices Guidance. Exponent. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit naveenagarwalphd.substack.com/subscribe

    Case Study: Why FDA Cybersecurity Expectations Are Really QMS Expectations
  8. 3 Jul

    LTR 160: IMSC26 Highlights - From Compliance to Proactive MedTech Safety

    Summary “The biggest takeaway was realizing that our perspectives on risk and safety are not isolated. They are shared, validated, and strengthened by others in the field.” In this special episode of the Let’s Talk Risk! conversation, host Naveen Agarwal brings together a panel of medtech safety and risk management leaders to discuss key takeaways from IMSC26 in Boston. The conversation highlights why the conference has become a unique gathering place for the medtech safety community: a forum where risk, quality, regulatory, clinical, and engineering professionals can speak a shared language and challenge each other’s thinking. The panel explores several major themes: moving beyond compliance, bringing patient perspective into risk management, understanding QMSR as a shift toward risk-based quality systems, strengthening judgment and critical thinking, and using AI as a thinking partner rather than a replacement for expertise. Listen to the full 47-minute podcast or jump to a section of interest listed below. Chapters 00:00 – Introduction and Panel Overview01:23 – Bijan Elahi on the Growth and Vision of IMSC06:23 – Proactive Safety from Clinic to Home08:28 – Patient Safety as the Central Stakeholder Theme10:15 – FDA, QMSR, and the Shift Toward Risk-Based Thinking18:53 – Design Control, Agile Software, and Surgical Robotics22:11 – Hidden Influences, Judgment, and Psychological Safety34:26 – AI as a Tool, Not a Replacement for Expertise40:00 – Career Day, Final Takeaways, and IMSC27 Preview If you enjoyed this podcast, consider subscribing to the Let’s Talk Risk! newsletter. Suggested links: LTR: Tips for Improving Collaboration in Risk Management. LTR: From Procedures to Judgment - Leading Through QMSR Inspections. LTR: LTR Risk Coach - AI-Powered Decision Support Tool. Key Takeaways * IMSC has become a true medtech safety community.The conference gives risk professionals a rare space to connect, compare experiences, and realize they are not alone in the challenges they face. * Patient safety must be more than a slogan.The panel emphasized that patient perspective needs to show up directly in risk management, especially where traditional harm categories may miss emotional, psychological, or lived-experience impacts. * Risk management is not just a compliance exercise.It is a human practice that requires collaboration, judgment, shared language, and cross-functional maturity. * QMSR raises the bar for risk-based thinking.The discussion framed QMSR as a move toward connected quality systems where FDA may look at whether decisions, processes, and subsystems work together around patient safety. * Judgment cannot be fully proceduralized.Procedures matter, but good risk decisions also require critical thinking, psychological safety, leadership, and comfort with ambiguity. * AI can strengthen risk thinking, but it cannot replace expertise.The panel warned against over-reliance on AI while recognizing its value as a tool to organize thinking, challenge assumptions, and preserve institutional knowledge. Keywords IMSC26, medtech safety, medical device risk management, patient safety, QMSR, FDA, risk-based thinking, quality culture, critical thinking, AI in medtech, design control, safety architecture, patient perspective, regulatory strategy, risk management maturity Guest Speakers Bijan Elahi as an award-winning medical device risk management author, professor and consultant. Dr. Olaf Hedrich is the Chief Medical Safety Officer at Medtronic. Michelle Lott is an executive advisor in regulatory strategy, principal and founder at LeanRAQA, LLC. Aaron Joseph is a principal consultant at Sunstone Pilot. Let’s Talk Risk! with Dr. Naveen Agarwal is a bi-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 other 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. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit naveenagarwalphd.substack.com/subscribe

    LTR 160: IMSC26 Highlights - From Compliance to Proactive MedTech Safety

About

Let’s Talk Risk! brings together MedTech leaders and practitioners for thoughtful conversations on the challenges that shape risk, quality, innovation, and leadership. With 150+ episodes and more than 30K downloads, it helps professionals gain the clarity and confidence to lead through complex decisions. naveenagarwalphd.substack.com

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