Yale Certificate in Medical Software and Medical AI: Guest Experts

This video is part of a series of guest expert interviews that we recorded for our new Yale Certificate Program on Medical Software and Medical AI – https://online.yale.edu/medical-software-ai-program. Our guest is Donna-Bea Tillman, a principal consultant at Biologics Consulting Group. She has 30 years of medical device regulatory experience. Prior to joining Biologics Consulting she held numerous positions within FDA’s Center for Devices and Radiological Health, culminating in her 2004 appointment to the position of Director of the Office of Device Evaluation, where she oversaw the medical device premarket review program for non-IVD devices. During her 17-years tenure at FDA, she played a pivotal role in the development of guidance documents, standards, and policy frameworks for medical device software and health IT. In 2010 she joined Microsoft’s Health Solutions Group as the Director of Regulations and Policy, where she was responsible for obtaining the appropriate global premarket registrations and managing Microsoft’s postmarket safety programs. She joined Biologics Consulting in 2012 and over the past 12 years has submitted more than one hundred 510(k) submissions as well as several noteworthy de novos in the digital health space. Donna-Bea received her B.S.E. in Engineering from Tulane University, her Ph.D. in Biomedical Engineering from the Johns Hopkins University, and her Master’s in Public Administration from the American University. 00:10 Introduction 01:37 The origins of FDA’s software regulation 08:44 The PC Era and off-the-shelf (OTS) components 14:34 The Quality Systems Regulation and its antecedents. Bad design not bad manufacturing. 16:56 Software-as-a-Medical Device and the role of imaging 23:02 Medical device data systems. The FDA and EHR systems. 27:43 The role of mobile devices, phones and watches. 30:47 Digital health, wellness and medical devices 37:03 Concluding thoughts. Additional Reading Material U.S. Federal Drug Administration (FDA). FDA POLICY FOR THE REGULATION OF COMPUTER PRODUCTS. 1989. Available from https://drive.google.com/file/d/1_7d2xB3E3ngu9UWPVlqYKRxtJ93gj3cP/view?usp=drive_link U.S. Food and Drug Administration (FDA). Medical Devices; Current Good Manufacturing Practice Final Rule; Quality System Regulation. Fed Regist . 1996;61(195). Available from: https://www.fda.gov/medical-devices/postmarket-requirements-devices/quality-system-qs-regulationmedical-device-good-manufacturing-practices U.S. Food and Drug Administration (FDA). General Principles of Software Validation; Final Guidance for Industry and FDA Staff. 2002. Available from: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/general-principles-software-validation U.S. Food and Drug Administration (FDA): Center for Devices and Radiological Health. Software as Medical Device (SAMD): Clinical Evaluation. Guidance for Industry and Food and Drug Administration Staff . 2017. Available from: https://www.fda.gov/medical-devices/digital-health-center-excellence/software-medical-device-samd Center for Devices and Radiological Health. General Wellness: Policy for Low Risk Devices. Guidance for Industry and Food and Drug Administration Staff . U.S. Food and Drug Administration (FDA); 2019. Available from: https://www.fda.gov/media/90652/download Center for Devices, Radiological Health. Medical Device Data Systems, Medical Image Storage Devices, and Medical Image Communications Devices . U.S. Food and Drug Administration. FDA; 2019. Available from: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/medical-device-data-systems-medical-image-storage-devices-and-medical-image-communications-devices Center for Devices, Radiological Health. Multiple function device products: Policy and considerations . U.S. Food and Drug Administration. FDA; 2020. Available from: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/multiple-function-device-products-policy-and-considerations Center for Devices, Radiological Health. Off-the-shelf software use in medical devices . U.S. Food and Drug Administration. FDA; 2023 . Available from: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/shelf-software-use-medical-devices Apple DeNovo Clearance Photoplethysmograph analysis software for over-the-counter use https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/denovo.cfm?id=DEN180042 09/11/2018 (Ms. Tillman is listed as the contact person for this)

This video is part of a series of guest expert interviews that we recorded for our new Yale Certificate Program on Medical Software and Medical AI – https://online.yale.edu/medical-software-ai-program. Our guest is Eric Henry. Mr. Henry is the Senior Quality Systems & Compliance Advisor at the Law Firm King & Spalding and works from his home in the Cleveland area. He joined King & Spalding in 2018 after 30 years managing global technical and regulatory compliance organizations in various industries and in medical devices in particular over the last 22 years. Eric currently provides advisory and consulting services to corporate management, boards, and staff regarding regulatory compliance, enforcement, and policy matters for regulated life sciences companies. Mr. Henry is a member of the AFDO/RAPS Healthcare Products Collaborative AI Strategic Committee and co-chairs their Good Machine Learning Practices Working Team. He also advises the Coalition for Health AI in their Predictive AI and Assurance Lab Certification Work Groups. 00:10 Introduction. Who is Eric Henry? 06:28 The FDA and AI. 14:45 The state of affairs outside the United States. China and the EU. 19:44 The general state of upheaval in Medical Devices/AI in the EU. 23:44 The current discussion on medical AI at the FDA. Potential issues with a new administration. 29:33 AI Tools development inside Health Systems. Challenges, fears and opportunities 38:34 Concluding Thoughts Additional Readings: European Union. Regulation (EU) 2024/1689 of the European Parliament and of the Council of 13 June 2024 laying down harmonised rules on artificial intelligence [Internet]. Available from: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=OJ:L_202401689 U.S. Food and Drug Administration, Health Canada, Medicine & Helathcare products Regulatory Agency. Good Machine Learning Practice for Medical Device Development. 2021 Oct. Available from: https://www.fda.gov/medical-devices/software-medical-device-samd/good-machine-learning-practice-medical-device-development-guiding-principles U.S. Food and Drug Administration, Health Canada, Medicine & Helathcare products Regulatory Agency. Transparency for machine learning-enabled medical devices: Guiding principles. 2024 Jun. Available from: https://www.fda.gov/medical-devices/software-medical-device-samd/transparency-machine-learning-enabled-medical-devices-guiding-principles U.S. Food and Drug Administration, Health Canada, Medicine & Helathcare products Regulatory Agency. Predetermined Change Control Plans for Machine Learning-Enabled Medical Devices: Guiding Principles 2023. Available from: https://www.fda.gov/medical-devices/software-medical-device-samd/predetermined-change-control-plans-machine-learning-enabled-medical-devices-guiding-principles Readings from Mr. Henry’s own work: AI/ML in Medical Devices: US & EU Regulatory Perspectives (https://array.aami.org/content/news/ai-ml-medical-devices-us-eu-regulatory-perspectives ) Medical Device Cybersecurity for Engineers and Manufacturers, Second Edition (Chapter 3: Global Regulations and Standards) (https://us.artechhouse.com/Medical-Device-Cybersecurity-for-Engineers-and-Manufacturers-Second-Edition-P2416.aspx ) “Bias in Artificial Intelligence In Healthcare Deliverables” (https://healthcareproducts.org/ai/aighi/aio/whitepaper-bias-in-ai-healthcare/ ) Software Under the Regulatory Microscope: The Current and Future State of Enforcement for Regulated Computer Systems (https://www.americanpharmaceuticalreview.com/Featured-Articles/574553-Software-Under-the-Regulatory-Microscope-The-Current-and-Future-State-of-Enforcement-for-Regulated-Computer/ ) You can find a full list of Mr. Henry’s publications, conference presentations, and media interviews on his LinkedIn profile: https://www.linkedin.com/in/eric-henry-519bb48/

This video is part of a series of guest expert interviews that we recorded for our new Yale Certificate Program on Medical Software and Medical AI – https://online.yale.edu/medical-software-ai-program. Our guest is Ian Sutcliffe, who is Principal Solutions Architect at AWS. Prior to that he has many years in the health sciences and tech industry in various software roles as both a developer and architect covering the solution, business and enterprise domains. He also serves on the AAMI Working Group that is developing guidance for the use of public cloud services in medical devices. The video was recorded on September 10, 2024. 00:10 Introduction 02:24 Creating a cloud service at “cloud scale.” 07:22 Dealing with changes in cloud software. 11:25 Automating testing and testing in production 15:00 Distributed systems 16:35 Compliance boundaries, medical device functions and computing environment 20:25 Designing with change in mind (non-monolithic systems) 22:17 Migrating existing systems to the cloud 25:41 Concluding thoughts Links: Association for the Advancement of Medical Instrumentation (AAMI). AAMI/CR510:2021; Appropriate use of public cloud computing for quality systems and medical devices. 2021. Report No.: CR510. Available from: https://array.aami.org/doi/book/10.2345/9781570208225

This video is part of a series of guest expert interviews that we recorded for our new Yale Certificate Program on Medical Software and Medical AI – https://online.yale.edu/medical-software-ai-program. Our guest is Prof Frangi is the Bicentennial Turing Chair in Computational Medicine at the University of Manchester, Manchester, UK, with joint appointments at the Schools of Computer Science and Health Sciences. He is also the Royal Academy of Engineering Chair in Emerging Technologies, with a focus on Precision Computational Medicine for in silico trials of medical devices. He is the Director of the Christabel Pankhurst Institute for Health Technology Research and Innovation (www.pankhurst.manchester.ac.uk). He conducts research in computational medical imaging and computational image-based medicine. Prof Frangi obtained his undergraduate degree in Telecommunications Engineering from the Technical University of Catalonia (Barcelona) in 1996. He pursued his PhD in Medicine at the Image Sciences Institute of the University Medical Centre Utrecht University on model-based cardiovascular image analysis. He leads the InSilicoUK Pro-Innovation Regulations Network (www.insilicouk.org). The video was recorded on July 19, 2024. 00:10 Introduction 10:07 From deep data to deep insights 20:35 Who was Christabel Panhurst? 23:33 In-silico trials: an introduction. 42:30 Regulators and in-silico trials. 50:11 Training people to work in this space and concluding thoughts. Links Frangi AF | Machine Learning for Computational Phenomics and In-Silico Trials: https://youtu.be/K8X9T7wSDqE?si=OdV1lRj0T_CZMYaa Frangi AF | Computational Medicine & Digital Twins Improving Medical Care: https://www.youtube.com/watch?v=afPmHkOjAWo&feature=youtu.be InSilicoUK Pro-Innovation Regulations Network www.insilicouk.org or join LinkedIn Group https://www.linkedin.com/groups/9169266/ Sarrami-Foroushani A, Lassila T, MacRaild M, Asquith J, Roes KCB, Byrne JV, Frangi AF. In-silico trial of intracranial flow diverters replicates and expands insights from conventional clinical trials. Nat Commun [Internet]. Springer Science and Business Media LLC; 2021 Jun 23 [cited 2022 Aug 19];12(1):3861. Available from: https://www.nature.com/articles/s41467-021-23998-w PMCID: PMC8222326 https://www.nature.com/articles/s41467-021-23998-w and https://vimeo.com/578167974 Liu Q, Sarrami-Foroushani A, Wang Y, MacRaild M, Kelly C, Lin F, Xia Y, Song S, Ravikumar N, Patankar T, Taylor ZA, Lassila T, Frangi AF. Hemodynamics of thrombus formation in intracranial aneurysms: An in silico observational study. APL Bioeng. 2023 Jul 7;7(3):036102. doi: 10.1063/5.0144848. https://pubs.aip.org/aip/apb/article/7/3/036102/2900843/Hemodynamics-of-thrombus-formation-in-intracranial Redrup E, Mitchell C, Myles P, Branson R, Frangi AF. Cross-Regulator Workshop: Journeys, experiences and best practices on computer modelled and simulated regulatory evidence— Workshop Report [Internet]. InSilicoUK Pro-Innovation Regulations Network; 2023 [cited 2024 Sep 16]. Available from: https://zenodo.org/records/10121103 Frangi AF, Denison T, Myles P, Ordish J, Brown P, Turpin R, Kipping M, Palmer M, Flynn D, Afshari P, Lane C, de Cunha M, Horner M, Levine S, Marchal T, Bryan R, Tunbridge G, Pink J, Macpherson S, Niederer S, Shipley R, Dall’Ara E, Maeder T, Thompson M. Unlocking the power of computational modelling and simulation across the product lifecycle in life sciences: A UK Landscape Report [Internet]. Zenodo; 2023 [cited 2024 Sep 16]. Available from: https://zenodo.org/records/8325274 and https://vimeo.com/894224258

This video is part of a series of guest expert interviews that we recorded for our new Yale Certificate Program on Medical Software and Medical AI – https://online.yale.edu/medical-software-ai-program. Our guest is Dr. Vishisht Mehta who is the Director of Interventional Pulmonology at the Lung Center of Nevada, a division of Comprehensive Cancer Centers and also the Department Chair of Pulmonology at MountainView Hospital, both in Las Vegas. He is fellowship trained in Interventional Pulmonology, which specializes in the minimally invasive diagnosis and treatment of lung conditions. His interest and expertise lies in the application of artificial intelligence in pulmonology. He is also the founder of the webpage Pulmonary.ai. The video was recorded on July 26, 2024. 00:10 Introduction 02:56 Dr. Mehta’s initial interactions with AI vendors. 06:15 A doctor’s experience talking to engineers. 10:15 Where will we be in 5 years? 13:23 Patients’ reaction to the use of AI. 17:05 Training doctors to use AI 19:58 Presenting results to patients 22:40 Integrating AI technology into healthcare provider systems 30:27 Concerns 35:50 Concluding thoughts Links:Pulmonary.AI

Our guest is Riccardo Lampariello, who is a statistician by training and brings almost 25 years of experience in health. He initially spent 10 years in the pharmaceutical industry and then moved into the not-for-profit sector: GAVI, UICC and Terre des hommes. In 2022 he joined D-tree as their CEO. D-tree’s mission is to expand access to high-quality, essential healthcare by enabling better decision making. His experience includes clinical operations, portfolio management, business development, capacity building, and public health. In the last 10 years, he has focused on adapting digital health solutions to the unique contexts of developing countries and scale them successfully to national level in Burkina Faso, India and Zanzibar. He also acquired substantial experience on data governance. He holds a MSc in Statistics and a MBA specialized in not-for-profit. The interview was recorded on May 17th, 2024. Further Reading and Links The BBC video embedded in this interview can be found at: https://www.bbc.com/storyworks/healthier-together/how-tanzania-is-tackling-the-healthcare-gap A video jointly produced by Yale BIDS and D-Tree on their work in Zanzibar can be found at: https://youtu.be/2i4baqXzapw?feature=shared You can learn more about D-tree’s work: https://www.d-tree.org/ You can sign up to D-tree’s newsletter to stay up to date about their work: https://eepurl.com/dnYta5 WHO guidelines for chatbots for sexual and reproductive guidance https://iris.who.int/bitstream/handle/10665/376294/9789240090705-eng.pdf?sequence=1

Our guest is Prof. Stephen Gilbert (https://www.linkedin.com/in/stephen-gilbert-31ba2587/) who is a Professor of Medical Device Regulatory Science at the Else Kröner Fresenius Center for Digital Health, Technische Universität Dresden where he teaches and conducts research on regulatory science with a team of colleagues. He is also News and Views Editor, Nature Portfolio – Digital Health. He worked in senior MedTech and Digital Heath roles in industry for 5 years, before returning to academia in 2022. His research goals are to advance the regulatory science of software as a medical device and AI-enabled medical devices. Innovative digital approaches to healthcare must be accompanied by innovative approaches in regulation to ensure speed to market, to maximum access of patients to life saving treatments whilst ensuring safety on market. His main research interests are in: (i) data sharing and the European Health Data Space; (ii) approaches to market approval of adaptive AI enabled medical devices; (iii) drugdigital/AI-enabled medical device product realisation; (iv) digital/virtual twins: as an organising concept of the future of healthcare.” Further Reading Derraz B, Breda G, Kaempf C, Baenke F, Cotte F, Reiche K, Köhl U, Kather JN, Eskenazy D, Gilbert S. New regulatory thinking is needed for AI-based personalised drug and cell therapies in precision oncology. NPJ Precis Oncol [Internet]. Nature Publishing Group; 2024 Jan 30 [cited 2024 Jan 30];8(1):1–11. Available from: https://www.nature.com/articles/s41698-024-00517-w Gilbert S, Harvey H, Melvin T, Vollebregt E, Wicks P. Large language model AI chatbots require approval as medical devices. Nat Med [Internet]. Nature Publishing Group; 2023 Jun 30 [cited 2023 Jun 30];1–3. Available from: https://www.nature.com/articles/s41591-023-02412-6 Gilbert S and Kather JN. Guardrails for the use of generalist AI in cancer care. Nature Reviews Cancer [Internet]. Nature Publishing Group; 2024 Apr 16 [cited 2024 Apr 16]. Available from: https://www.nature.com/articles/s41568-024-00685-8

Our guest is Mr. Hirohito Okuda. Mr Okuda has close to 30 years of working experience in the medical device industry. Currently he is a principal AI engineer at Konica Minolta, Japan where he directs AI engineering across the company, leads generative AI adaptation, helps to establish AI guidelines and is also a member of the AI ethics review committee that reviews all AI products across the company. Prior to that, he was for 2 years an AI R&D division manager at DeNa and for 10 years prior he was a software engineering division manager at General Electric, Japan. Before that, he spent two years as a research software engineer at Yale. The interview was recorded on Dec 6, 2023.

Our guest is Mr. Bernhard Kappe (https://www.linkedin.com/in/bernhardkappe/) who is the founder and CEO of Orthogonal (https://orthogonal.io/), a medical device consulting company. He is also a member of the AAMI working group AAMI SW WG-10 Cloud Computing. This interview was recorded on Nov 16, 2023. Further Reading: Kappe B. Accelerating Medical Product Development: Applying Agile Methods to Shorten Timelines, Reduce Risk and Improve Quality [Internet]. Orthogonal; 2020. Available from: https://orthogonal.io/insights/agile/ebook-agile-in-an-fda-regulated-environment/ Association for the Advancement of Medical Instrumentation (AAMI). AAMI TIR45: 2023; Guidance on the use of agile practices in the development of medical device software. Arlington VA: Association for the Advancement of Medical Instrumentation; 2023. Report No.: TIR45. https://webstore.ansi.org/standards/aami/aamitir452012r2018?gad_source=1 Agile Lego Game: https://www.youtube.com/watch?v=0lA00lDs_R4 https://www.youtube.com/watch?v=7BKPDScVb5U

Our guest is Mr Larkin Lowrey (https://www.linkedin.com/in/larkinlowrey/). Mr Lowrey has spent the past 30 years in the Software Engineering Product Development space building new product development organizations but also turning around organizations which had fallen into traps resulting in poor quality, execution and products which did not resonate in the marketplace. Most of his career has been in IoT and, notably, he built a telematics platform that was sold to Verizon and now operates as Verizon Networkfleet. Recently he moved into MedTech. He states that there is a lot of overlap between these areas given how medical devices, sensors increasingly make heavy use of cloud analytics platforms. This interview was recorded on Dec 7, 2023. Further Reading/watching: Webinar: Crossing the Chasm: Growing Tech Professionals into MedTech Professionals | Orthogonal: https://www.youtube.com/watch?v=nB645qIuLFA Code Generation AI: • Github Copilot: https://github.com/features/copilot Image Generation AI: • Midjourney https://www.midjourney.com/ • DALL·E https://openai.com/research/dall-e

Our guest is Prof. Anat Lior (https://drexel.edu/law/faculty/fulltime_fac/Anat%20Lior/) who is an assistant professor at Drexel University’s Thomas R. Kline School of Law, an AI Schmidt affiliated Scholar with the Jackson School at Yale and an affiliated fellow at the Yale Information Society Project. Her research interests include AI governance and liability, quantum computing policy, and the intersection of insurance and emerging technologies. The interview was recorded on Dec 5, 2023. Further Reading: EU AI Act: https://artificialintelligenceact.eu/the-act/ Biden AI Executive Order: https://www.whitehouse.gov/briefing-room/presidential-actions/2023/10/30/executive-order-on-the-safe-secure-and-trustworthy-development-and-use-of-artificial-intelligence/ Lior A. Insuring Ai: The role of insurance in artificial intelligence regulation. Harv J Law Technol. 2002;35(2):467–530. Available from: https://jolt.law.harvard.edu/assets/articlePDFs/v35/2.-Lior-Insuring-AI.pdf

Our guest is Mr. Oleg Yusim (https://www.linkedin.com/in/olegyusim/) who is a currently vice-president and Chief Product Security Officer at Illumna. At the time we recorded this video, he was Senior Director of Information Security at Edwards Lifesciences. He has many years of experience in the area cybersecurity in medical devices. This video was recorded Dec 11, 2023. Further Reading: U.S. Food and Drug Administration (FDA). Center for Devices and Radiological Health. Cybersecurity in Medical Devices: Quality Systems and Premarket Submissions. Sep 2023. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/cybersecurity-medical-devices-quality-system-considerations-and-content-premarket-submissions Healthcare Vulnerability Scoring System (HVSS) Version 1.0 Calculator: https://hvss.online/

Our guest is Elad Walach (https://www.linkedin.com/in/elad-walach/) who is a founder and CE of AIDoc (https://www.aidoc.com/) Based in Tel Aviv, Aidoc is a leading provider of medical AI solutions. It has 13 algorithms cleared by the U.S. Food and Drug Administration, with over 1,000 hospitals using its products across the globe. Further Reading: Elad Walach. An AI model is NOT An AI Product. January 31, 2024 https://www.linkedin.com/pulse/ai-model-product-elad-walach-abemf AIDoc. Understanding Recent AI Regulations and Guidelines. January 29, 2024. https://www.aidoc.com/blog/ai-regulations-guidelines/

Our guest is Dr. Andrea Biasiucci (https://www.linkedin.com/in/andreabiasiucci/) who is the CEO of confinis (https://www.confinis.com/), a worldwide medical device regulatory consulting company based in Switzerland. Dr. Biasiucci received his Ph.D. in Brain-Computer Interfaces from EPFL in Lausanne, and has been an AI-based neurotech innovator for over a decade. The video was recorded on Nov 22, 2023. This is a follow up interview to a previous discussion recorded with Dr. Biasiucci for the Yale Medical Software Coursera Class: https://www.youtube.com/watch?v=OhK6AQ3Qyfk (June 2021). Further Reading: EU AI Act: https://artificialintelligenceact.eu/the-act/ Gilbert S, Harvey H, Melvin T, Vollebregt E, Wicks P. Large language model AI chatbots require approval as medical devices. Nat Med [Internet]. Nature Publishing Group; 2023 Jun 30. Available from: https://www.nature.com/articles/s41591-023-02412-6

Our guest is Mr. Korey Johnson (https://www.linkedin.com/in/koreyrjohnson/), Managing Partner at Bold Insight (https://boldinsight.com/), which is a consulting company focusing on User Experience and Human Factors research. The interview was recorded on Dec 15, 2023. Further Reading/watching: International Electrotechnical Commission (IEC). IEC 62366-1 Medical devices – Part 1: Application of usability engineering to medical devices. Geneva, CH; 2015. Available from: https://www.iso.org/standard/63179.html International Electrotechnical Commission (IEC). IEC 62366-2 Medical devices – Part 2: Guidance on the application of usability engineering to medical devices. Geneva, CH; 2016. Available from: https://www.iso.org/standard/69126.html U.S. Food and Drug Administration (FDA): Center for Devices and Radiological Health. Applying Human Factors and Usability Engineering to Medical Devices; Guidance for Industry and Food and Drug Administration Staff. 2016. Available from: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/applying-human-factors-and-usability-engineering-medical-devices U.S. Food and Drug Administration. FDA; 2023[Office of the Commissioner. Application of Human Factors Engineering Principles for Combination Products: Questions and Answers Available from: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/application-human-factors-engineering-principles-combination-products-questions-and-answers American National Standards Institute. ANSI/AAMI HE 75:2009 (r2018). 2018. Report No.: 75. Available from: https://webstore.ansi.org/standards/aami/ansiaamihe752009r2018?gad_source=1 Lew G, Schumacher RM Jr. AI and UX: Why Artificial Intelligence Needs User Experience. 1st ed. Apress; 2020. Available from: https://www.amazon.com/AI-UX-Artificial-Intelligence-Experience/dp/148425774X/ U.S. Food and Drug Administration (FDA) Center for Devices, Radiological Health. Digital Health Software Precertification (Pre-Cert) Pilot Program. 2023 May. Available from: https://www.fda.gov/medical-devices/digital-health-center-excellence/digital-health-software-precertification-pre-cert-pilot-program

Our guest is Mr. Randy Horton, who is the Chief Solutions Officer of Orthogonal (https://orthogonal.io/), a medical device consulting company. He also co-chairs the AAMI working group AAMI SW WG-10 Cloud Computing. The video was recorded on Dec 7, 2023 Further Reading/watching: Association for the Advancement of Medical Instrumentation (AAMI). AAMI/CR510:2021; Appropriate use of public cloud computing for quality systems and medical devices. 2021. Report No.: CR510. Available from: https://array.aami.org/doi/book/10.2345/9781570208225 Securing SaMD & Medical Device Safety on the Ever Changing Cloud: A Conversation With AAMI. Robert Burroughs and Joseph Lewelling of AAMI interviewed Orthogonal’s Randy Horton and Philips’ Pat Baird on their work drafting and standardizing guidance on integrating the #cloud with SaMD. Nov 11, 2022 https://www.youtube.com/watch?v=wJqmuxiOrAo. Randy Horton. How AI is turning your smartphone into the Swiss Army knife of clinical diagnostics. Bioimaging Sciences Seminar, Yale School of Medicine, April 2023. https://www.youtube.com/watch?v=YXDp4Kf0n8E

Our guest is Ms. Megan Graham who is an experienced medical software quality and regulatory consultant, focusing on digital health. Ms. Graham also serves on a number of international standards committees including most recently AAMI SW WG-10 Cloud Computing. She is also an adjunct faculty member at the University of Minnesota where she teaches in the Master of Science Software Engineering Program. This interview was recorded Dec 14, 2023. Further Reading: Good Machine Learning Practice for Medical Device Development: Guiding Principles (ÒGMLPÓ). October 2021, Food & Drug Administration, Health Canada, and Medicines and Healthcare Products Regulatory Agency. Available from: https://www.fda.gov/medical-devices/software-medical-device-samd/good-machine-learning-practice-medical-device-development-guiding-principles ISO 13485:2016, Medical devices – Quality management systems – requirements for regulatory purposes. March 2016, International Organization for Standardization. Available from : https://www.iso.org/standard/59752.html ISO 14971:2019, Medical devices – Application of risk management to medical devices. December 2019, International Organization for Standardization. Available from: https://www.iso.org/standard/72704.html AAMI TIR 34971:2023, Application Of ISO 14971 To Machine Learning In Artificial IntelligenceÑGuide. March 2023, Association for the Advancement of Medical Instrumentation. Available from: https://doi.org/10.2345/9781570208669.ch1 NIST Risk Management Framework. National Institute of Standards and Technology. Available from: https://csrc.nist.gov/projects/risk-management NIST Secure Product Development Framework. National Institute of Standards and Technology. Available from: https://csrc.nist.gov/projects/ssdf Overgaard SM, Graham MG, Brereton T, Pencina MJ, Halamka JD, Vidal DE, Economou-Zavlanos NJ. Implementing quality management systems to close the AI translation gap and facilitate safe, ethical, and effective health AI solutions. NPJ Digit Med. Nov 25;6(1):218. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10676432/ This interview is also available in video form on YouTube: https://youtu.be/POd0LQ80t4w

Our guest is Attorney Bradley Merrill Thompson RAC (https://www.linkedin.com/in/bradleymerrillthompson/) who is a partner at Epstein Becker and Green P.C. At the firm, he leads the AI practice and serves in the medical device, digital health, and combination product practices. This video was recorded on Nov 28, 2023. Further Reading: Thompson BM, Snyder LS. FDA Oversight of AI Software Developed by Health Care Providers . Epstein, Becker and Green. 2023. Available from: https://www.healthlawadvisor.com/2023/08/10/fda-oversight-of-ai-software-developed-by-health-care-providers/ Thompson BM. FDA’s Final Guidance on Clinical Decision Support Violates the Law. LinkedIn. 2022. Available from: https://www.linkedin.com/pulse/fdas-final-guidance-clinical-decision-support-law-thompson-rac/?trackingId=K7vHT91EEExEN%2BqrezASkg%3D%3D U.S. Food and Drug Administration (FDA) Center for Devices, Radiological Health. Clinical Decision Support Software – Guidance for Industry and Food and Drug Administration Staff. 2022. Available from: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/clinical-decision-support-software This episode is also available to watch on Youtube: https://www.youtube.com/watch?v=58-2IG9aY2U

Our guest is Dr. Kicky van Leeuwen, who is the founder of AIforRadiology.com, a webpage providing objective insights into what AI products for healthcare professionals are on the market. She is also a cofounder and consultant at Romion Health, a company that aids AI procurement and implementation. This video is part of a series of guest expert interviews that we recorded for the new Yale Certificate Program on Medical Software and Medical AI. The interview was conducted on Nov 30, 2023. For more information about the Yale Certificate Program in Medical Software and Medical AI please visit https://online.yale.edu/medical-software-ai-program