Medtech & Pharma Platform Association’s Post

The US Food and Drug Administration (FDA) has recently announced several updates across different areas. Here’s a summary of the key developments: 𝗲𝗦𝘁𝗮𝗿 𝗧𝗲𝗺𝗽𝗹𝗮𝘁𝗲 𝗨𝗽𝗱𝗮𝘁𝗲  The eStar template has been updated. These updates are driven by revisions in IMDRF documents and a correction of redundant IT security sections. The IMDRF Table of Content was updated simultaneously. https://lnkd.in/gPnEXjgW 𝗲𝗠𝗗𝗥 𝗦𝘆𝘀𝘁𝗲𝗺 𝗜𝗺𝗽𝗿𝗼𝘃𝗲𝗺𝗲𝗻𝘁𝘀  The electronic Medical Device Reporting (eMDR) system is also continuously being improved by the FDA. In June, the FDA announced the timeline for the next set of updates, allowing organisations to adjust their processes and IT systems accordingly. https://lnkd.in/gxYFmwgp 𝗔𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 (𝗔𝗜) 𝗜𝗻𝗶𝘁𝗶𝗮𝘁𝗶𝘃𝗲𝘀  Troy Tazbaz, FDA Director of the Digital Health Center of Excellence (DHCoE), shared insights on AI opportunities in a recent blog post. More importantly, the FDA, in collaboration with Health Canada, updated the “Guiding Principles” for medical devices utilising machine learning. This includes two key documents: ⏺ 𝗚𝗼𝗼𝗱 𝗠𝗮𝗻𝘂𝗳𝗮𝗰𝘁𝘂𝗿𝗶𝗻𝗴 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀: 𝗚𝘂𝗶𝗱𝗶𝗻𝗴 𝗣𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲𝘀 https://lnkd.in/dK-X6-Zw ⏺ 𝗧𝗿𝗮𝗻𝘀𝗽𝗮𝗿𝗲𝗻𝗰𝘆 𝗳𝗼𝗿 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴-𝗘𝗻𝗮𝗯𝗹𝗲𝗱 𝗠𝗲𝗱𝗶𝗰𝗮𝗹 𝗗𝗲𝘃𝗶𝗰𝗲𝘀: 𝗚𝘂𝗶𝗱𝗶𝗻𝗴 𝗣𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲𝘀 https://lnkd.in/ejqWRmV3 These documents provide valuable frameworks for integrating machine learning in medical devices, with the second document detailing principles 7 and 9 from the first in greater depth. #FDAUpdates #MedicalDevices #AIinHealthcare #RegulatoryNews #HealthcareInnovation

Bringing digital health tech on the market is a regulatory challenge (amongst others 😅). We engaged with the FDA very early in the process to lower the regulatory risks. Here is some feedback about how we made it. As innovators, we must meet all necessary regulatory requirements to go on the market. It implies design & development processes, verification, quality assurances and clinical studies. The FDA is publishing plenty of guidances to support innovation in the US. However, the most useful process is the pre-submission meetings. The FDA offers to innovators to hold pre-submission meetings. Those meetings allow to discuss the regulatory requirements and the validation needed. It helped a lot to bring our innovation on the market. Digital Medicine Society (DiMe) assembled 10 use cases to share best practices and lessons learned. One of the use case is our story with the FDA 😉. Thanks for sharing those best practices! 🙏 Learn more here 👇 https://lnkd.in/evuwfytb

Regulation in #artificialintelligence is a hot topic right now. The excitement of the technology and its capabilities is not yet matched by the clarity and rigor of its future regulation. Sounds like 2025 will be the year the #FDA and Health Canada give us further guidance here. Regulation will define how these devices operate over time. Locked, Unlocked, predetermined change control plans (PCCP) and other modification activity options will no doubt be of keen interest to manufacturers in this space and the owners of the ~1000 FDA authorized AI-enabled medical devices. Connect Life Science has a healthy roster of consultants and permanent staff members who have had direct involvement in the development, clearance and approval of those 1000 devices. Need help with yours? https://lnkd.in/eHT7ACnt

FRUSTRATED SEARCHING FDA.Gov for FDA REGULATORY INFORMATION ? YOU SHOULD BE ! NOT A SURPRISE ! How much time would it take to find answer to for questions like: “Who is required to file Annual Reports with DSCSA to FDA mandatory come November 2024? (Drug Supply Chain Security Act) OR “Explain difference of comparative vs non comparative clinical trial design” You could Google it but how many search hit result links do you have to ‘peek’ and ‘poke’ before getting credible answers ? Yikes, a lot !🧝🏃 🚀🐘AI/ML Copilot on FDA.Gov from eSTARHelper.com now comes to the rescue ! 💪 ChatGPT-4 converse FDA.Gov in your own words for answers! Concerned with AI/ML inherent bias 🤖or hallucinations on occasion? No Worries! DON'T BE! 🚀🐘 Our FDA DCSA Copilot is backed by You-the-Human 🤵🧑🍼full-text searching on ACTUAL FDA.gov Guidance (PDFs)📝 and 21 CFRs (Code of Federal Regulafor 💊Drugs (CDER) , Biologics(CBER) 💉 & Medical Devices. (CDRH) 🩻⚕️ No Account/password setups needed, no app store downloads, no credit cards (FREE!)- just point and click! https://lnkd.in/gXGNK4mq 🚀Best of all , its  FREE! ❎💲 Interested in networking and learning more on DSCSA? Attend this event use our code to get 10% OFF the published rate Code is : VI-eSTARHelper@10 Sign up here--> https://lnkd.in/g8qb-AuQ

🚀 NAMSA BLOG! 🚀 The FDA, Health Canada, and MHRA have jointly released the "Transparency of Machine Learning-Enabled Medical Devices: Guiding Principles." This new publication builds upon the 2021 Good Machine Learning Practice (GMLP) principles, emphasizing the importance of transparency in MLMDs. 🧠 Key Highlights: ◾️Principle 7: Focus on the performance of the human-AI team. ◾️Principle 9: Clear, essential information for users. Transparency in MLMDs ensures informed choices, manages risks, and promotes equity by revealing biases. 🔍 Explore the six transparency principles: the audience, importance, relevant info, placement, timing, and human-centered design support. 📢 Read the full blog by Monica R. Montanez, Principal Strategy Consultant, to learn more about these guiding principles and their impact on the medical device industry 👉 https://lnkd.in/gvnCtM6w #MedicalDevices #MachineLearning #Transparency #HealthcareInnovation #NAMSAKnows

ICYMI: Check out this great interview of FDA Commissioner Dr Robert Califf by Ayesha Rascoe (who asked some excellent Qs about trials, validation, bias, autonomy etc.) for NPR in light of our recent paper in JAMA (Paper link: https://lnkd.in/gUimWHrf).

🚀 NAMSA BLOG! 🚀 The FDA, Health Canada, and MHRA have jointly released the "Transparency of Machine Learning-Enabled Medical Devices: Guiding Principles." This new publication builds upon the 2021 Good Machine Learning Practice (GMLP) principles, emphasizing the importance of transparency in MLMDs. 🧠 Key Highlights: ◾️Principle 7: Focus on the performance of the human-AI team. ◾️Principle 9: Clear, essential information for users. Transparency in MLMDs ensures informed choices, manages risks, and promotes equity by revealing biases. 🔍 Explore the six transparency principles: the audience, importance, relevant info, placement, timing, and human-centered design support. 📢 Read the full blog by Monica R. Montanez, Principal Strategy Consultant, to learn more about these guiding principles and their impact on the medical device industry 👉 https://lnkd.in/gvnCtM6w #MedicalDevices #MachineLearning #Transparency #HealthcareInnovation #NAMSAKnows

Bringing digital health tech on the market is a regulatory challenge (amongst others 😅). We engaged with the FDA very early in the process to lower the regulatory risks. Here is some feedback about how we made it. As innovators, we must meet all necessary regulatory requirements to go on the market. It implies design & development processes, verification, quality assurances and clinical studies. The FDA is publishing plenty of guidances to support innovation in the US. However, the most useful process is the pre-submission meetings. The FDA offers to innovators to hold pre-submission meetings. Those meetings allow to discuss the regulatory requirements and the validation needed. It helped a lot to bring our innovation on the market. Digital Medicine Society (DiMe) assembled 10 use cases to share best practices and lessons learned. One of the use case is our story with the FDA 😉. Thanks for sharing those best practices! 🙏 Link in the comments 👇

First Meeting of FDA’s Digital Health Advisory Committee : #aipolicyregulation - The U.S. Food and Drug Administration (FDA) convened its inaugural Digital Health Advisory Committee (DHAC) meeting on November 20-21, 2024, in Gaithersburg, Maryland. This committee was established to provide expert guidance on regulatory issues related to digital health technologies, with a particular focus on generative artificial intelligence (AI) in medical devices.  Key Discussion Points: - Premarket Performance Evaluation: The committee examined the types of data and evidence necessary for the FDA to assess the safety and effectiveness of generative AI-enabled devices. MEDPULSE AI Read More ▶️ https://buff.ly/3OxqF5P 💡 #fda #MedPulseAI #AIinHealthcare #AIinMedicine

Excited to see our Japan CDISC community put forward this well-developed set of articles on the implementation and use of the CDISC standards.