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

Prof. Stephen Gilbert, a leading expert in Medical Device Regulatory Science, dives into the intersection of AI and medical regulation. He discusses the challenges of adapting traditional frameworks for AI chatbots and large language models, emphasizing the need for updated regulations to ensure patient safety. Gilbert compares LLMs to an unpredictable genie, highlighting their potential and risks. He also explores the evolving responsibilities of physicians in a tech-driven landscape, advocating for collaboration to advance innovations while maintaining safety.

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