Building a medical device rarely follows the smooth, predictable trajectory presented in investor pitch decks. While regulatory consultants often default to "it depends," medical device teams require concrete figures regarding engineering hours, calendar timelines, and budget allocations to bring a concept to market safely and effectively.

Lisa Voronkova, co-founder of OVA Solutions, draws on a dataset from developing over 200 medical devices to pull back the curtain on hardware engineering realities. She outlines the four structured phases of engineering—Discovery, Proof of Concept, Design, and Development—explaining how disciplined phase-gate management mitigates costly late-stage redesigns and protects capital.

The conversation dives into transparent, real-world case studies ranging from short pre-production hardware tracks to complex, multi-year continuous glucose monitor (CGM) developments. Lisa and host Etienne Nichols explore the true financial scope of Design for Manufacturability (DFM), realistic blended hourly rates across global markets, and why shortcuts in early contextual validation often lead to catastrophic manufacturing overhead.

Takeaways

• Phase-Gate Discipline Controls Financial Risk: Moving into high-cost tooling or manufacturing before proving core function in a low-fidelity mock-up risks turning a $1,500 prototype adjustment into a $150,000 production mold tool rework.
• Validate in the Real Operating Environment: Conducting customer interviews is insufficient if engineers do not observe the actual clinical setting; lighting conditions, sterile field constraints, and physical workflows dictate foundational hardware requirements.
• Benchmark Engineering Hours accurately: Standard hardware projects generally fall into three tiers: 2,000–3,000 hours for simple electronics integrations, 5,000–6,000 hours for multi-system electro-mechanical devices, and 10,000–30,000+ hours for high-complexity Class II/III systems (e.g., CGMs, surgical robotics).
• DFM Accounts for a Massive Secondary Investment: Completing the initial "golden sample" prototype is only half the engineering journey; preparing a device for mass production (assembly sequences, test fixtures, second-sourcing components) can demand an additional 2,500 to 7,000+ engineering hours.

References

• OVA Solutions: Engineering group specializing in full-cycle medical device design, electronics, and firmware development.
• The Hardware Bible: Book authored by Lisa Voronkova detailing practical expectations and framework strategies for medical device development.
• Host LinkedIn: Connect with Etienne Nichols on LinkedIn for ongoing discussions with MedTech industry leaders.

Feedback Call-to-Action

We want to hear from you! What was your biggest takeaway regarding medical device engineering budgets and timelines? Have a guest recommendation or a topic you want us to dissect in an upcoming episode?

Send your feedback, reviews, and topic suggestions directly to [email protected]. Etienne reads every message and responds personally to our listeners!

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This episode is brought to you by Greenlight Guru.

Learn more at www.greenlight.guru.

The transition from academic research to commercial MedTech entrepreneurship requires a strategic mindset shift, particularly when navigating high-risk vascular innovations. Jordi Martorell, CEO and co-founder of Aortyx, shares his journey from mapping arterial blood flow at the Harvard-MIT Biomedical Engineering Center to developing bioresorbable endovascular patches for aortic dissection. Driven by a desire to solve true unmet medical needs, Martorell leveraged his background in fluid mechanics and vascular engineering to build a company capable of transforming clinical outcomes.

Navigating early-stage funding outside major venture capital hubs presents unique structural challenges. Martorell explains how Aortyx sustained a multi-year development timeline prior to Series A by combining friends-and-family rounds, community equity crowdfunding, and non-dilutive European public grants. Maintaining radical transparency regarding investment risk and establishing clean cap table structures were critical components in maintaining investor trust over extended timelines.

Securing a Series A round for a Class III medical device requires managing shifting macroeconomic landscapes, rising clinical costs, and complex regulatory pathways. Martorell reflects on the realities of negotiating with venture capital firms, facing unexpected round restructurings, and adapting to post-pandemic inflation across preclinical and clinical trial execution. The discussion highlights the importance of maintaining core product continuity while remaining flexible in execution strategy.

Takeaways

• Validate Unmet Needs Over Market Incrementalism: Avoid competing in saturated markets where large strategics only seek non-inferiority; focus R&D on clear, unaddressed clinical gaps.
• Structure Clean Cap Tables for Retail Capital: When utilizing equity crowdfunding or large groups of early individual investors, leverage syndication and SPVs to preserve a single point of negotiation for future institutional VCs.
• Prepare for Extended Series A Timelines: Deep-tech Class III devices can face multi-year fundraising cycles, requiring a multi-tiered capital strategy blending non-dilutive grants, bridge rounds, and follow-on commitments.
• Factor Post-Pandemic Inflation into Preclinical Budgets: Account for significant cost increases in animal studies, raw material procurement, and clinical trial execution compared to historical baseline estimates.

References

• Aortyx: Medical device company developing bioresorbable endovascular patches for aortic dissection repair.
• EIC Accelerator Program: European Innovation Council grant initiative providing non-dilutive funding to high-impact European startups.
• Capital Cell: Specialized health-focused equity crowdfunding platform based in Spain.
• Etienne Nichols: LinkedIn Profile

Feedback Call-to-Action

We want to hear from you. What were your key takeaways from this episode? Do you have topics or guest suggestions for future discussions? Send your thoughts, feedback, and questions directly to [email protected]. Every email is reviewed by our team to help shape upcoming episodes.

Sponsors

This episode is brought to you by Greenlight Guru.

Learn how Greenlight Guru's modern QMS and EDC software can support your medical device journey at greenlight.guru.

Many MedTech startups and innovators focus heavily on core technology development, often assuming physical product design is simple polishing once a working concept exists. Michael Sprauve explains that this approach frequently creates a gap between brilliant engineering and a market-ready, commercially viable medical device. Succeeding in hardware requires looking past the technology to consider every individual who will interact with the device throughout its entire lifecycle.

A critical challenge in MedTech design is managing the complex web of user personas involved. Unlike consumer electronics, where design caters to one or two primary end users, medical devices must meet the needs of surgeons, operating room staff, post-surgical nurses, maintenance technicians, disposal personnel, and regulatory bodies. Overlooking support staff—such as nurses managing crowded, alarm-fatigued rooms or technicians handling biological waste and lithium-ion batteries—can derail an otherwise promising device.

As AI image generation tools become widespread, creators increasingly present AI-rendered concepts as finished designs. While these tools offer creative inspiration, they lack awareness of physical constraints, manufacturing rules, and real-world usability. By establishing a non-physical "North Star" based on emotional attributes and sensory cues, design teams can guide products through concepting, engineering, and manufacturing without losing sight of user needs and regulatory mandates.

Takeaways

• Map the Entire User Lifecycle: Design for every individual who touches the product, from the operating surgeon to the maintenance nurse, sterilization technician, and waste handler.
• Mitigate Alarm Fatigue Early: Ensure auditory and visual indicators comply with FDA standards while avoiding chaotic, high-stress clinical environments caused by competing alerts.
• Establish a Non-Physical North Star: Use emotional and sensory attributes to anchor design, engineering, and CMF (Color, Material, Finish) choices, keeping the project aligned across development stages.
• Involve Manufacturing Engineers from Day One: Incorporate Design for Manufacturability (DFM) considerations during initial concept phases rather than waiting until design freeze to prevent expensive re-tooling and regulatory delays.

References

• Speck Design: Hardware design and engineering firm specializing in taking complex medical and life science concepts to market.
• Intuitive Surgical (DaVinci & Ion Platforms): Advanced robotic-assisted surgical systems highlighting high-precision hardware requirements discussed in the episode.
• Microport MedBot (Toumai System): Four-arm laparoscopic surgical robot referenced as a key benchmark for international regulatory clearances.
• Etienne Nichols' LinkedIn: Etienne Nichols on LinkedIn

Feedback Call-to-Action

We want to hear from you! What challenges have you faced when balancing user feedback against clinical and regulatory requirements? Send your thoughts, topic suggestions, or questions to [email protected]. Every email goes directly to our team, and we personally review listener notes for future episodes.

Sponsors

This episode is brought to you by Greenlight Guru.

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Medical device cybersecurity is no longer an optional feature or a last-minute checkbox prior to market entry. Hosted by Etienne Nichols, this episode features Chris Gates, founder and CEO of arsMedSecurity, who delivers a practical, engineering-first perspective on embedding security directly into the development lifecycle. Gates highlights that deferring cybersecurity efforts until the end of development leads to severe financial penalties, extended regulatory delays, and potential company failure.

The discussion demystifies common misconceptions held by executive teams and "bean counters," such as the myth that off-network devices or small companies are exempt from cyber threats. Under current FDA expectations and the eStar submission process, any medical device containing software is subject to stringent pre-market cybersecurity requirements. Gates illustrates how unexpected 180-day regulatory holds impact a company's daily burn rate, showing that proactive security measures are far cheaper than reactive fixes.

Looking ahead, the conversation explores the evolving threat landscape driven by Large Language Models (LLMs) and advanced exploits that reduce vulnerability exploitation windows from years to minutes. Gates provides concrete steps for medical device manufacturers to take control of their product security, emphasizing early threat modeling, continuous risk management, and the alignment of software development SOPs with recognized international standards.

Takeaways

• Calculate Delay Impact via Burn Rate: Evaluate cybersecurity risk against your organization's daily burn rate multiplied by a potential 180-day FDA submission delay to understand the true financial cost of non-compliance.
• Software Triggers Cyber Requirements: Do not assume a device is exempt from cybersecurity requirements because it lacks active internet connectivity; any device running software falls under FDA pre-market expectations.
• Perform Threat Modeling Before Hardware Freeze: Execute system-level threat modeling (e.g., STRIDE methodology) during the initial design phase before finalizing active hardware components and component selections.
• Adopt Recognized SDLC Standards: Establish standard operating procedures (SOPs) that map secure development activities directly to ISO/IEC 81001-5-1 and ISO 62304 frameworks.

References

• Medical Device Cybersecurity for Engineers and Manufacturers (2nd Edition): Practical reference handbook authored by Chris Gates detailing implementation techniques for device developers.
• ISO/IEC 81001-5-1: Health software and health IT systems safety, effectiveness, and security standard for secure development lifecycles.
• STRIDE Threat Model: A system decomposition methodology developed by Microsoft to identify data-in-motion and data-at-rest security threats per system element.
• Host LinkedIn Profile: Connect with Etienne Nichols on LinkedIn.

Feedback Call-to-Action

We want to hear from you! What cybersecurity challenges is your team currently navigating during product development? Send your questions, feedback, or topic suggestions directly to us at [email protected]. Every email is reviewed by our team, and we regularly incorporate listener-submitted questions into upcoming episodes and expert Q&A segments.

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In this episode of the Global Medical Device Podcast, host Etienne Nichols sits down with Nikhil Mangale, Vice President of Quality at Kapstone Medical, to discuss the real-world impact of the FDA's Quality Management System Regulation (QMSR). Seven months post-implementation, the industry is seeing actual inspection data that shifts the focus away from superficial documentation updates and directly onto core quality system operations.

Nikhil breaks down the top five areas where the FDA is issuing citations under the new regulation: risk management, supplier controls, complaint handling, Unique Device Identification (UDI), and corrective actions. The discussion highlights how the industry spent years worrying about renaming documents like Design History Files (DHFs) to Design and Development Files (DDFs), yet inspectors are bypassing mere translation projects to evaluate how information flows across living quality processes.

The conversation offers actionable guidance on conducting thorough, multi-layered gap assessments for both active and legacy products. Nikhil provides strategic advice for small companies and startups on prioritizing risk management, handling supplier audit visibility, navigating ISO 13485 alignment, and weighing the benefits of participating in programs like MDSAP.

Takeaways

• Prioritize Risk as a Living Process: Risk management must continuously integrate post-market feedback, complaint data, and nonconformances rather than remaining a static file archived after design release.
• Re-evaluate Supplier Audits for External Scrutiny: Routine supplier audit records are now accessible to FDA inspectors; ensure reports are well-documented, audit schedules are risk-proportionate, and findings are formally resolved.
• Implement a Three-Layer Mapping Strategy: Move beyond surface-level terminology updates (Layer 1) to establish subclause conformity (Layer 2) and verify operational evidence across interrelated processes (Layer 3).
• Maintain Open Design and Development Files (DDF): Unlike legacy DHFs that were closed at commercial launch, DDFs must remain active throughout the product lifecycle to evaluate ongoing design changes.
• Formulate a Defensible Quality Plan: When addressing gaps, document a risk-prioritized, sequential quality plan to show objective evidence of a structured compliance roadmap during an inspection.

References

• FDA Compliance Program CP 7382.045: The FDA inspection guidance replacing QSIT, organizing surveillance around core QMS areas and specific regulations.
• ISO 13485:2016: The international standard for medical device quality management systems incorporated by reference into the FDA's QMSR.
• Etienne Nichols LinkedIn Profile - Connect with the host of the Global Medical Device Podcast.

Feedback Call-to-Action

We want to hear from you! What challenges are you experiencing with your QMSR implementation or risk management files? Send your feedback, reviews, or topic suggestions directly to [email protected]. We personally review and respond to every message from our listeners!

Sponsors

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Medical device startups frequently fall into the trap of developing complex technology first, only to struggle downstream with clinical adoption, regulatory hurdles, and reimbursement. In this episode, host Etienne Nichols sits down with Shai Policker, Managing Partner at Edge Medical Ventures, to explore why reversing this traditional paradigm leads to sustainable, category-defining products.

Policker details how working backward from validated clinical needs—identified directly by multinational corporations, physicians, and health systems—allows developers to map out the regulatory and reimbursement landscapes before building the first prototype. By addressing the commercial critical chain early, ventures avoid costly mid-development pivots and align technical innovation with true market demand.

The conversation covers real-world portfolio examples, including non-invasive urodynamics and smart surgical drains, demonstrating how focused differentiation transforms clinical workflows and patient outcomes. Policker also shares key insights into helping international MedTech companies navigate the nuances of the US healthcare system.

Takeaways

• Validate Reimbursement Before Prototyping: Map existing CPT/HCPCS codes, coverage policies, and economic incentives prior to freezing design specifications.
• Leverage Strategic Partnerships Early: Engage R&D, sales, and clinical leaders at strategic corporations to identify validated gaps in three-to-five-year commercial pipelines.
• Target Dramatic Outcome Improvements: Focus engineering efforts on innovations that yield step-function clinical improvements rather than incremental 5% gains.
• Preserve Familiarity for Pathways: Design physical devices to deliver game-changing outcomes while maintaining predicate-equivalent forms to fit existing 510(k) cleared classes and billing mechanisms.
• Evaluate the Full Critical Chain: Ensure every element—referral patterns, physician time, hospital economics, regulatory constraints, and patient compliance—is fully solved before committing venture capital.

Essential References

• Edge Medical Ventures: Venture creation firm focused on category-defining medical device companies built around validated strategic needs.
• Etienne Nichols LinkedIn: Connect with podcast host and MedTech community leader Etienne Nichols.

Feedback & Community

We want to hear from you! What was your biggest takeaway from Shai Policker's approach to venture creation? Do you have topic suggestions or guests you would like to see on the show?

Send your thoughts, feedback, and questions directly to the team at [email protected]. Every email receives a personalized response from our team!

Episode Sponsors

This episode is brought to you by Greenlight Guru, the only MedTech lifecycle management platform purpose-built for medical device companies.

Learn how to accelerate your medical device journey at www.greenlight.guru.

Most discussions around medical device quality stop at commercial launch. Once a product ships, teams tend to celebrate and move on to the next development cycle. However, the real engineering work often begins the moment a device leaves the manufacturing floor. In this episode of the Global Medical Device Podcast, host Etienne Nichols sits down with Shawnnah Monterrey, founder of Beanstalk Ventures and an FDA-accredited third-party reviewer with 25 years of medical device software experience, to explore what happens after product deployment.

Monterrey shares rare insights gained from evaluating FDA submissions and troubleshooting high-impact field issues across platforms ranging from glaucoma imaging at ZEISS to CTDNA cancer assays at Illumina. The conversation covers the often-overlooked requirements of manufacturing transfer, deployability, and software upgrade mechanisms. Monterrey explains how inadequate upstream characterization—such as neglecting physical shipping stresses or omitting subsystem-level DFMEAs—directly manifests as costly "dead on arrival" (DOA) failures and field complaints.

The discussion also dives deep into the mechanics of defect detection, comparing hardware tolerance stack-ups with complex software root cause analysis. Monterrey illustrates how robust unit testing, clear design documentation, and structural post-market surveillance prevent catastrophic field recalls. Finally, the episode highlights the critical need for open communication channels between R&D, manufacturing, and post-market complaint handling teams to feed field intelligence back into future product iterations.

Key Timestamps

• 00:00 - Introduction to Etienne Nichols and guest Shawnnah Monterrey, CEO of Beanstalk Ventures.
• 01:15 - Crucial pre-shipping checks that first-time medical device founders routinely miss.
• 02:05 - Software transfer to manufacturing, deployability, eStar submissions, and cybersecurity requirements.
• 03:10 - Root causes of "Dead on Arrival" (DOA) product deliveries and shipping reliability testing.
• 04:20 - The concept of injection detection: Why detecting bugs earlier in R&D saves exponential costs.
• 05:45 - Unanticipated failure modes, software-hardware interaction, and the necessity of bottom-up DFMEAs.
• 07:30 - Software defect isolation, unit testing vs. system-level troubleshooting, and simulating user environments.
• 08:15 - Case study: Class 1 ventilator recall, software algorithm flaws, and root cause analysis across 80,000 units.
• 10:40 - Field upgradeability, patchability in legacy firmware devices, and managing regulatory trade-offs.
• 12:15 - Transforming customer complaints from isolated fires into upstream process and product design improvements.
• 14:00 - Usability issues, off-label user behavior, and manufacturer liability regarding indications for use.
• 16:30 - Closing feedback loops: Structuring open communication between R&D, post-market teams, and field service.

Quotes

"The sooner a defect is injected into the product and the later you find it, the more expensive it is going to be to correct. You want to tighten that gap up as close as possible." - Shawnnah Monterrey

"A lot of defects manifest themselves in software, but they are actually electromechanical issues that the software didn't intend to catch." - Shawnnah Monterrey

Takeaways

• Prioritize Software Deployability Upstream: Under current FDA eStar submission standards and cybersecurity guidance, software deployment, upgrade mechanisms, and maintenance processes must be documented and tested well before shipping.
• Execute Bottom-Up DFMEAs: While FDA risk management emphasizes top-down system hazard analysis (ISO 14971), robust subsystem-level DFMEAs are essential to capture unexpected interaction defects between electromechanical hardware and software.
• Unit Testing Accelerates Root Cause Analysis: Simulating inputs via automated software unit tests allows engineering teams to reproduce obscure field defects instantly without needing to replicate complex human-patient variables.
• Design for Field Upgradeability: Building patchable, field-upgradeable firmware and software architectures protects device manufacturers from catastrophic physical recalls across large installed bases.
• Bridge R&D and Complaint Management: Companies must establish formal feedback channels between post-market complaint handling teams and R&D engineers to ensure real-world failure trends drive future design controls.

References

• Etienne Nichols LinkedIn Profile: https://www.linkedin.com/in/etiennenichols/
• FDA eStar Program: The FDA's electronic submission template used to streamline medical device 510(k) and De Novo review processes.
• ISO 14971: The international standard for the application of risk management to medical devices.
• Cardiac Arrest: Five Years as a CEO on the Fed's Hit List by Howard Root: Recommended book detailing off-label use, regulatory enforcement, and legal liability in MedTech.

MedTech 101 Section

Injection Detection Think of building a medical device like baking a cake from a recipe. If you accidentally add salt instead of sugar at the start (injecting a defect), it is easy and cheap to toss out the flour and start over. But if you don't taste the cake until after it is baked, frosted, packaged, and delivered to a customer's party, fixing that mistake requires shipping a whole new cake, apologizing to the buyer, and paying for delivery. In MedTech software and hardware, "injection detection" means testing early and often so you catch design "bugs" while they are still in the mixing bowl rather than after thousands of devices are in patients' hands.

Design Failure Mode and Effects Analysis (DFMEA) Imagine examining every individual part of a car engine—from the biggest piston down to the smallest rubber seal—and asking: "How could this specific part break, and what happens to the driver if it does?" A DFMEA is a systematic, bottom-up engineering blueprint where teams evaluate each component or software line to predict failures before the device is ever built.

Feedback Call-To-Action

What post-market challenges has your medical device team encountered after product launch? We want to hear your thoughts, topic requests, and guest suggestions. Send your feedback directly to [email protected]. Every message is reviewed personally by our team to help shape future episodes.

Sponsors

This episode is brought to you by Greenlight Guru.

Navigating medical device quality from early-stage R&D through post-market surveillance requires tools built specifically for the MedTech industry. Greenlight Guru offers an all-in-one Medical Device Success Platform combining modern Quality Management System (QMS) and Electronic Data Capture (EDC) solutions. Whether you are preparing software documentation for an eStar submission or connecting customer complaint signals back to upstream design controls, Greenlight Guru helps you scale compliance, streamline clinical data, and bring safe devices to market faster. Learn more by visiting www.greenlight.guru.

Navigating the regulatory landscape for combination products requires understanding how primary modes of action (PMOA) dictate oversight pathways. In this episode, host Etienne Nichols sits down with Jim Fentress, Director of Regulatory Affairs at Galero (a Santa Group company), to unpack the structural differences and hidden pitfalls when medical device and pharmaceutical worlds collide. They discuss how the FDA handles lead agency designation across CDRH and CDER using interagency agreements and official Requests for Designation (RFD).

A central theme of the discussion is managing quality management systems under 21 CFR Part 4. The pair explore the friction that occurs when pharmaceutical companies act as lead applicants for drug-led combination products, requiring them to incorporate device design controls (ISO 13485 / QMSR) and CAPA systems into their existing CGMP framework. Jim explains the practical realities of integrating Part 210/211 elements—such as calculation of yield and stability testing—into a single, operational QMS without overcomplicating procedures.

Finally, the conversation delves into critical execution details: risk management under AAMI TIR105 (ISO 14971 vs. ICH Q9), labeling classifications (single entity, co-packaged, and cross-labeled), and strict change control protocols. Jim highlights how post-market design changes to a device constituent part can impact the pharmaceutical partner's NDA or baseline regulatory filings, underscoring the necessity of transparent cross-industry communication from initial development through full commercial release.

Key Timestamps

• 00:00 – Introduction to combination products and guest Jim Fentress.
• 00:48 – Understanding Primary Mode of Action (PMOA) and regulatory pathways (FDA vs. European authorities).
• 01:57 – FDA interagency agreements (CDRH and CDER) and Requests for Designation (RFD).
• 03:00 – 21 CFR Part 4 quality system integration (CGMP Part 210/211 and QMSR/Part 820).
• 05:22 – Navigating the communication gap between pharma companies and device manufacturers.
• 07:44 – Calculation of yield in drug manufacturing vs. medical device production.
• 09:05 – Risk management for combination products (AAMI TIR105: evaluating device-on-drug and drug-on-device risks).
• 12:15 – Bridging ISO 14971 and ICH Q9 framework structures in registration files.
• 13:16 – Design controls, user needs, and human factors validation (Module 5 / Section 3.2.R ECTD filings).
• 15:06 – Labeling pathways: Single Entity (Integral), Co-Packaged, and Cross-Labeled products.
• 18:18 – Change control risks: How minor device modifications affect drug application filings (NDAs, CBER/CDER supplements).
• 20:41 – Advice for device manufacturers partnering with pharma: Alignment on risk, documentation depth, and cleanroom requirements.

Standout Quotes

"There's four aspects of risk that you need to take into account: what is the risk of the drug alone, the risk of the delivery system alone, the risk of the drug on the device, and the risk of the device on the drug." — Jim Fentress

"Before you even think about making a change, you need to talk to your pharmaceutical partners because now what's represented as the co-packaged device constituent element is changing, and they need to inform the FDA." — Jim Fentress

Actionable Takeaways

• Establish Cross-Disciplinary Risk Management Early: Adopt frameworks like AAMI TIR105 to integrate traditional device risk protocols (ISO 14971) with pharmaceutical risk management (ICH Q9). Ensure assessment of cross-interaction hazards (e.g., drug interactions with delivery plastics, viscous drug effects on ejection times).
• Define Clear Part 4 QMS Interfaces: If operating primarily under device rules (QMSR/ISO 13485), build project-specific addenda to account for drug CGMP requirements such as stability testing, container-closure assessments, and calculation of yield limits.
• Align Post-Market Change Control Protocols: Establish explicit notification procedures between the device supplier and the NDA holder. Simple component material updates or geometry changes to a constituent part may require formal NDA supplements or changes-being-effected (CBE) filings with CDER.
• Scope Document Deliverables Upfront: Clarify whether the pharmaceutical partner requires high-level summary reports or the complete device master record (DMR) and design history file (DHF) to populate Section 3.2.R of their eCTD submission.
• Validate Cleanroom and Sterility Assumptions: Discuss cleanroom requirements early to avoid unnecessary cost structures; verify if an ISO 8 or ISO 7 environment is scientifically required for the assembly of non-sterile device constituents before adopting conservative pharma-grade aseptic norms (ISO 5).

Essential References

• 21 CFR Part 4: Regulation governing current good manufacturing practice (CGMP) requirements for combination products.
• AAMI TIR105: Technical Information Report providing guidance on the application of risk management to combination products.
• ICH Q9: International Council for Harmonisation guidelines for Quality Risk Management in pharmaceutical manufacturing.
• eCTD Section 3.2.R: Regional information section of the Electronic Common Technical Document where medical device constituent data is filed.
• Host Contact: Connect with Etienne Nichols on LinkedIn.

MedTech 101

Primary Mode of Action (PMOA)

The primary mode of action is the single mechanism that provides the primary therapeutic effect of a combination product.

Think of a drug-eluting stent:

• The main goal is to physically prop open a blocked artery (a mechanical action performed by the stent device).
• The drug baked into the metal coating slowly releases to prevent scar tissue from re-blocking the artery (an ancillary chemical action).

Because the physical propping open is the primary therapeutic mechanism, the FDA classifies the product as a device-led combination product under CDRH. Conversely, an epinephrine auto-injector's main therapeutic outcome comes from the epinephrine drug working in the bloodstream; the plastic casing and needle are auxiliary delivery mechanisms, making it a drug-led combination product overseen by CDER.

Feedback & Community

We want to hear from you! Have questions about combination product regulatory strategies, or want to suggest a topic for a future episode?

Email us directly at [email protected]. Every message is reviewed personally by our team to help shape upcoming content.

Sponsor Integration

This episode is sponsored by Greenlight Guru.

Navigating the blurred lines of 21 CFR Part 4 between drug CGMPs and device design controls requires dynamic, interconnected quality tools. Greenlight Guru provides purpose-built Quality Management Software (QMS) and Electronic Data Capture (EDC) solutions designed specifically for MedTech teams. Whether you are managing complex design controls, tracking supplier changes, or managing clinical trial data for combination products, Greenlight Guru helps you bring safe, compliant devices to market faster.

Discover how to streamline your regulatory files and risk matrix at www.greenlight.guru.

Many early-stage medical device founders face a major dilemma: how do you prove regulatory maturity to investors and partners before you actually hold a final CE mark or FDA approval? Waiting until the end of a long development cycle creates significant commercial risk. By treating regulatory readiness as a continuous maturity process rather than an all-or-nothing milestone, startups can build trust early and avoid costly late-stage surprises.

In this episode, host Etienne Nichols sits down with Malte Knowles Schmidt, Global Portfolio Lead for Medical Device Software, AI, and Cybersecurity at TÜV SÜD. Drawing from his background as an ICU nurse, an R&D product leader for Class III cardiac implantables at Biotronik, and now a notified body leader, Malte breaks down how startups can step out of their silos. He emphasizes that notified bodies and medical device companies must both "leave the ivory tower" to establish practical, real-world communication long before a formal audit occurs.

The conversation explores concrete strategies for demonstrating regulatory maturity during development, including standing up an enterprise Quality Management System (eQMS), securing partial ISO 13485 certification for core design processes, and leveraging external testing as strategic "breadcrumbs." Malte also cautions founders against chasing "Pyrrhic certifications"—winning regulatory approval at the cost of commercial viability—and shares practical guidance on when and how to initiate early structured dialogues with notified bodies.

Key Timestamps

• 00:00 - 02:15 | Introduction to the "Regulatory Ivory Tower"
• Etienne introduces guest Malte Knowles Schmidt and sets up the challenge of proving regulatory maturity early in the startup lifecycle.
• 02:16 - 05:04 | Why Communication Gap Exists Between Startups & Notified Bodies
• Malte discusses why structured dialogues often feel too abstract for founders and why concrete examples are needed to make early engagement approachable.
• 05:05 - 08:30 | Defining Regulatory Maturity & The Agile QMS
• Exploring how investors view regulatory progress, why build-measure-learn mindsets belong inside a QMS, and how an eQMS acts as a foundational framework.
• 08:31 - 12:10 | Unlocking Value Through Partial ISO 13485 Certification
• A breakdown of how certifying core design and development processes early builds commercial credibility and attracts investor funding before full scope audits.
• 12:11 - 16:45 | Leveraging External Testing & Avoiding "Pyrrhic Certifications"
• How penetration testing and biocompatibility act as evidence breadcrumbs, plus the trap of sacrificing commercial viability just to get a certificate.
• 16:46 - 20:30 | When and How to Initiate Contact with a Notified Body
• Practical advice for founders on overcoming the fear of reaching out, preparing essential homework (intended purpose, risk classification), and taking the first step.

Quotes

"A Pyrrhic certification comes from a Pyrrhic victory, where you win the battle, but the losses are so great that the victory is basically meaningless... startups make the certification their core goal and not the commercial success." - Malte Knowles Schmidt

"If you're asking yourself the question, 'Should I be talking to a notified body?'—then stop right there, because the answer is yes." - Malte Knowles Schmidt

Key Takeaways

• Establish Early Regulatory Breadcrumbs: Investors want to see continuous progression. Utilizing an eQMS, conducting third-party testing (e.g., penetration or biocompatibility testing), and mapping regulatory roadmaps provide tangible proof of maturity long before final approval.
• Consider Partial ISO 13485 Certification: Startups do not need to wait for full scope certification. Certifying core design and development processes first demonstrates organizational discipline and can unlock major funding rounds.
• Avoid the Pyrrhic Certification Trap: Do not sacrifice your core business model or reduce critical product capabilities solely to make certification easier. Always align regulatory strategy with ultimate commercial viability.
• Treat Your QMS as an Agile System: Quality management is not a static set of restrictive rules; it is an iterative framework that should evolve alongside your product and team processes.
• Initiate Dialogue Early: Notified bodies are accessible for preliminary discussions. Reaching out early helps validate your intended purpose, risk classification, and submission assumptions before sinking capital into the wrong pathway.

References

• White Paper: Leaving the Regulatory Ivory Tower: How Early Notified Body Dialogues Reduce Business Risk by Malte Knowles Schmidt (TÜV SÜD).
• ISO 13485 Standard: Quality management systems requirements for regulatory purposes in the medical device sector.
• Host LinkedIn: Etienne Nichols on LinkedIn

MedTech 101 Section

• Pyrrhic Certification: Named after King Pyrrhus of Epirus, whose army won a battle against the Romans but suffered devastating losses in the process. In MedTech, a Pyrrhic certification occurs when a company successfully gets a medical device certified, but had to compromise so many features, intended uses, or commercial claims during the process that the resulting product has no real value in the market.
• Notified Body: An independent organization designated by an EU member state to assess whether a medical device complies with applicable regulatory standards (such as EU MDR) before it can be placed on the European market. Think of them as accredited referee agencies that verify safety and performance.
• Partial ISO 13485 Certification: Instead of waiting until an entire company, manufacturing line, and distribution network are fully operational to get audited, a company can undergo a certified audit specifically for a limited scope—such as its initial design and development processes.

Feedback Call-to-Action

We love hearing from our listeners! Did this episode change how you view early engagement with notified bodies? Do you have questions about implementing an eQMS or navigating partial ISO certification?

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In this episode, host Etienne Nichols sits down with Ali Samiian, founder and managing principal of Popular Access Advisors, to demystify the critical and often misunderstood world of MedTech reimbursement. Far too many early-stage medical device companies treat reimbursement as a secondary, post-launch paperwork exercise, only to find that their brilliant, FDA-cleared technology fails because no one has figured out who will pay for it. Ali draws on his 20-plus years of experience in market access, health economics, and executive leadership to explain why reimbursement must be treated as a core product strategy long before submission.

The conversation explores how commercialization pathways are inherently dictated by the site of care—whether inpatient, outpatient, or home use. Ali highlights common and costly pitfalls, such as designing clinical trials solely for FDA clearance while neglecting the specific evidence endpoints that insurance payers demand. Payers do not just look at safety and efficacy; they look at long-term clinical value, accessibility, durability, and standard-of-care comparisons. Using practical, real-world examples, Ali demonstrates how simple adjustments to product design and clinical study lengths can proactively align a device with existing or novel code requirements.

Finally, the episode highlights the shifting regulatory landscape and new initiatives designed to accelerate market access for breakthrough innovations. Etienne and Ali discuss the FDA’s Total Lifecycle Product Advisory (TAP) program and the emerging CMS Regulatory Alignment for Predictable and Immediate Device (RAPID) program. By understanding these frameworks and embedding payer-relevant outcomes into early-stage research, innovators can significantly compress their revenue cycles, avoid product redesigns, and successfully deliver life-changing technologies into the hands of patients.

Key Timestamps

• 00:03 - Introduction to MedTech reimbursement and guest Ali Samiian.
• 01:46 - The difference between clearing the FDA bar and achieving commercial success.
• 02:16 - Case Study: How product design and classification categories impact commercialization.
• 03:45 - The risk of ignoring durable medical equipment (DME) requirements during design.
• 05:22 - Categorizing sites of care: Inpatient, outpatient, ASCs, and home use (DMEPOS).
• 06:15 - Mistake #1: Postponing reimbursement strategy until after FDA approval.
• 07:35 - Mistake #2: Designing clinical studies for the FDA without considering payer-relevant endpoints.
• 09:02 - Understanding standard of care, durability data, and minimizing study bias for payers.
• 10:30 - Exploring the FDA's TAP program and the new CMS RAPID program for breakthrough devices.
• 12:15 - Mistake #3: Rushing regulatory pathways without assessing commercial and price-point implications.
• 13:50 - Identifying stakeholders and understanding the oblique nature of CMS and payer regulations.
• 14:38 - Deconstructing how to build new codes and establish premium pricing from scratch.

Quotes

"Clearing the FDA bar is not really what gets us to commercialization. We need to have product and clinical differentiation... A lot of reimbursement is actually more of a strategy exercise." - Ali Samiian

"The FDA basically looks at is the product safe and effective? Payers look at is there value and is there accessibility for the product?" - Ali Samiian

Takeaways

• Incorporate Payer Endpoints Early: MedTech innovators should involve a reimbursement advisor during clinical trial design to incorporate payer-relevant endpoints (like durability and standard-of-care comparisons), avoiding the need for an expensive second study.
• Align Design with Code Descriptors: Ensure product features and testing durations match the strict regulatory definitions of your target site of care (e.g., verifying a home-use device meets the three-year durability testing threshold for DME classification).
• Evaluate Pathways Holistically: Assess regulatory pathways (510(k) vs. De Novo vs. PMA) not just by upfront cost or speed to market, but by their long-term implications on pricing, coding, and time-to-reimbursement.
• Leverage Breakthrough Programs: Companies with breakthrough device designation should actively follow and align with collaborative initiatives like the FDA's TAP and CMS's RAPID programs to secure immediate coverage upon clearance.

References

• FDA TAP Program: The Total Lifecycle Product Advisory program designed to provide early, strategic communication with senior FDA leadership for breakthrough devices.
• CMS RAPID Program: Regulatory Alignment for Predictable and Immediate Device program, an initiative aimed at accelerating coverage pathways for breakthrough innovations.
• Etienne Nichols: Connect with the host on LinkedIn.

MedTech 101 Section

• Reimbursement vs. FDA Clearance: Think of FDA clearance as getting a driver's license—it proves your device is safe to be on the road. Reimbursement is like getting a toll pass; it determines who is actually going to pay for the journey so you can keep driving.
• Durable Medical Equipment (DME): This is a category of medical equipment used in the home that can withstand repeated use. Think of it like a sturdy pair of boots—if it isn't designed and tested to last a specific number of years (usually three), payers won't classify it as DME, even if it works perfectly.
• The "Cup" Analogy for Coding: Payers view similar items as identical commodities. A cup is a cup, whether it holds coffee or tea, and they want to pay one standard price for it. To get paid more, an innovator must prove their "cup" has unique technology that provides a fundamentally different, meaningful clinical outcome—like a cup that mechanically prevents spills for patients with tremors.

Feedback Call-to-Action

We love hearing from our community of MedTech innovators! Do you have thoughts on this episode, questions about market access, or suggestions for future topics? Reach out to us directly at [email protected]. Every email is read by our team, and we look forward to providing you with a personalized response.

Sponsors

This episode is brought to you by Greenlight Guru, the only dedicated medical device success platform. Moving from product development to commercial adoption requires absolute precision in data and compliance. Greenlight Guru helps medical device teams smoothly bridge the gap between regulatory approval and commercialization. By integrating both Quality Management Software (QMS) and Electronic Data Capture (EDC) solutions, Greenlight Guru ensures your clinical trial data is flawlessly captured to satisfy the FDA, while keeping your quality systems audit-ready for commercial scaling. Learn more at www.greenlight.guru.

Artificial intelligence has officially entered the mainstream cultural zeitgeist, creating a wave of excitement—and a fair share of fatigue—across the medical device industry. In this episode, host Etienne Nichols sits down with Tyler Harmon, biomedical engineer and CEO of Iaso Automated Medical Systems, to cut through the marketing buzzwords. Together, they explore the technical realities behind the technology stack, shifting the conversation away from generic AI toward specific, actionable engineering frameworks.

The discussion highlights a critical distinction between traditional machine learning models and consumer-oriented Large Language Models (LLMs). Harmon explains that while technologies like convolutional neural networks (CNNs) have successfully processed medical imaging for years, modern LLMs introduce an intentional element of randomness to mimic human conversation. This lack of predictability presents unique challenges for medical device developers who operate in a deterministic, safety-critical environment where reproducibility is paramount.

Looking toward practical deployment, the episode addresses how companies can responsibly govern these tools both within their software architectures and their internal Quality Management Systems (QMS). From classifying external AI models as Software of Unknown Provenance (SOUP) under IEC 62304 to leveraging machine learning for early detection of Acute Respiratory Distress Syndrome (ARDS) in the ICU, this conversation serves as an essential guide for innovators looking to build the next generation of safe, compliant, and effective medical technologies.

Key Timestamps

• 00:05 – Introduction to the dual nature of AI in MedTech: embedded clinical algorithms versus internal process optimization.
• 02:14 – Demystifying the math: Breaking down artificial intelligence into linear and non-linear algorithmic transformations.
• 04:30 – The Turing Test, Markov chains, and why consumer LLMs are mathematically designed to be unpredictable.
• 07:15 – Real-world success stories: How convolutional neural networks (CNNs) revolutionized emergency stroke triage.
• 09:42 – Inside Iaso Automated Medical Systems: Using non-LLM machine learning to identify Acute Respiratory Distress Syndrome (ARDS) in critical care.
• 12:10 – AI Governance in the QMS: Designing specialized Standard Operating Procedures (SOPs) and Machine Learning Management Systems (AIMS).
• 15:35 – Evaluating recent FDA 510(k) clearances for LLM-adjacent technologies and managing third-party stacks as SOUP.

Quotes

"If we as innovators can't explain things to a more general audience, we generally don't understand them ourselves. And if you can't do that, it's probably not the best idea to be implementing it into your products." - Tyler Harmon

"I am probably going to be the biggest advocate you'll ever talk to about 'doctors need enablement, not replacement.' We need to give them the tools, the force multipliers to tackle the challenges they're going to face this century." - Tyler Harmon

Takeaways

• Classify External AI as SOUP: Treat third-party language models and external tech stacks as Software of Unknown Provenance (SOUP) under IEC 62304 frameworks, implementing rigorous risk management boundaries to isolate the core medical device logic.
• Engineer Out Randomness: Recognize that consumer LLMs purposefully integrate randomness layers to maximize user engagement. For clinical safety, developers must utilize architectural harnesses or alternative machine learning methods (like CNNs or random forests) to force more deterministic outcomes.
• Establish an AI Management System: Expand your organizational compliance beyond standard Quality Management Systems (QMS) and Information Security Management Systems (ISMS). Implement specific AI standard operating procedures and work instructions to govern internal token usage and data handling.
• Prioritize Clinical Enablement Over Automation: Focus clinical software engineering on clearing workflow bottlenecks and flagging early-stage critical conditions (such as ARDS) to allow bedside clinicians to deploy their hands-on expertise faster.

References

• Berlin Criteria: The formal, quantitative medical classification standard used by clinicians to diagnose and grade the severity of Acute Respiratory Distress Syndrome.
• IEC 62304: The international standard governing medical device software lifecycle processes, specifically detailing the management of Software of Unknown Provenance (SOUP).
• Connect with Etienne Nichols on LinkedIn to stay updated on the latest episodes and industry insights.

MedTech 101 Section

Understanding Non-Linear Math and LLMs

Think of a traditional medical device software algorithm like a standard thermometer tracking a fever. It follows a straight, predictable line: if the temperature input increases by one degree, the reading on the screen changes by exactly one degree. This is a linear system.

Modern AI, like Large Language Models (LLMs), works more like a seasoned doctor trying to diagnose a complex case by listening to a patient's story. The human brain doesn't just look at variables in a straight line; it connects random pieces of past experiences, reads between the lines, and notes subtle shifts in tone. To replicate this mathematically, software engineers introduce non-linearity.

Instead of a straight line, the math behaves like a web of thousands of intersecting pathways. To make the system feel even more human, creators add a controlled "randomness layer" (similar to a digital coin flipper) so the software doesn't always choose the most obvious, predictable word next. While this makes chatting with a computer feel incredibly natural, it presents an engineering challenge for medical device developers who require identical, reproducible results every single time.

Feedback Call-to-Action

We love hearing from our community of MedTech professionals. Do you have thoughts on how AI governance should evolve, or is there a specific industry topic you want us to tackle next? We read every message and pride ourselves on providing personalized responses to our listeners. Share your feedback, reviews, and topic suggestions directly with our production team at [email protected].

Sponsors

This episode is brought to you by Greenlight Guru, the only dedicated medical device success platform. When building cutting-edge technologies like software as a medical device or machine learning platforms, having an isolated, fragmented tech stack can slow your path to market.

Greenlight Guru seamlessly connects your engineering and quality operations by offering both a comprehensive Quality Management System (QMS) to manage your compliance governance, SOPs, and design controls, alongside robust Electronic Data Capture (EDC) solutions for optimizing your clinical data collection. By integrating your quality workflows with actual clinical data capture, Greenlight Guru helps you scale safely from research and development straight through to successful commercialization.