Toscano Consulting Group’s Post

The buzz word across the sectors has been Artifical Intelligence (AI) throughout the year 2024 🔊 💡 Are you curious to know how AI has been adopted in manufacturing of medical devices, and drug development process 🤔 💊 ⚕ 🏢 FDA's perpective on AI sheds interesting insights and few highlights are ▪ FDA intends to take flexible approach across range of AI models used for administrative healthcare offices vs models embedded in traditional medical devices. ▪ There isn't a Large language model (LLM) authorized by FDA yet and requires proactive engagement among clinicians, developers, regulators to mitigate significant risks posed by clinical decision-making tools. ▪ Focus on health outcomes is need of an hour while we continue to adopt in using AI models to overcome the pressure on the health care systems and not merely looking at as financial return on investment. #AI #Innovation #Regulations #medicaldevices #drugdevelopment #healthcare https://lnkd.in/gzGVQQHg

Transforming Healthcare with Responsible AI: A UniqueMinds.ai Perspective The rapid integration of AI into healthcare is a game changer, with nearly 1,000 FDA-authorized AI-enabled medical devices now shaping patient outcomes. This milestone demonstrates the power of innovation and the responsibility we bear as leaders in this space to ensure AI is developed and deployed ethically and effectively.   At UniqueMinds.ai, we believe this is where our Responsible AI Framework for Healthcare (RAIFH) truly shines. The RAIFH principles—spanning Fit for Use, Accuracy, Transparency, Privacy, Security, Fairness, and Accountability—align seamlessly with the FDA's total product life cycle approach for AI regulation. By embedding these principles into every phase of an AI solution’s journey, from design to post-market monitoring, we not only ensure compliance but also champion trust, equity, and value creation in healthcare innovation.   As FDA Commissioner Dr. Robert M. Califf highlights, a comprehensive strategy that integrates real-world data and global collaboration is key to maintaining the balance between technological advancement and patient safety. RAIFH enhances this vision by offering actionable guidance that empowers healthcare stakeholders to navigate the complexities of responsible AI adoption. The healthcare landscape is evolving rapidly, and we’re proud to lead the way in ensuring that innovation remains grounded in values that prioritize patient safety, equity, and trust.   I invite healthcare leaders and innovators to join the conversation on driving responsible AI adoption—let’s work together to ensure every AI solution is not just innovative but responsible as well.   #InsideUniqueMinds #AIinHealthcare #ResponsibleAI #RAIFH https://lnkd.in/gmiVNk93

*FDA Issues Paper on the Responsible Use of Artificial Intelligence in Medical Research* There are 4 areas of focus in the paper, including fostering collaboration to safeguard public health; advancing the development of regulatory approaches to support innovations; promoting the development of standards, guidelines, best practices, and tools for the medical product life cycle; and supporting research that is related to the evaluation and monitoring of AI performance. https://lnkd.in/dsQ92BsT

Last month, the FDA’s Haider Warraich et al. published a compelling report in JAMA highlighting the approval of nearly 1,000 AI-enabled medical devices under the 510(k) pathway. The report also emphasized the necessity of adopting a lifecycle management framework to ensure AI tools remain safe and effective with continuous monitoring in real-world settings. While this marks significant progress for AI in healthcare, the FDA noted that no large language models (LLMs) or Generative AI models have been approved yet, citing concerns about bias and unpredictable outcomes.

𝐅𝐃𝐀 𝐏𝐞𝐫𝐬𝐩𝐞𝐜𝐭𝐢𝐯𝐞 𝐨𝐧 𝐭𝐡𝐞 𝐑𝐞𝐠𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐀𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 𝐢𝐧 𝐇𝐞𝐚𝐥𝐭𝐡 𝐂𝐚𝐫𝐞 𝐚𝐧𝐝 𝐁𝐢𝐨𝐦𝐞𝐝𝐢𝐜𝐢𝐧𝐞 This paper provides the FDA's perspective on regulating AI in healthcare and biomedicine, addressing both its opportunities and challenges. The FDA reviews its historical approach, beginning with its first AI-based medical device approval in 1995, and highlights key regulatory developments, such as guidance documents and risk-based approaches to AI-enabled devices. As of 2024, nearly 1,000 AI-enabled devices have been approved, particularly in radiology and cardiology. The FDA emphasizes that regulating AI requires flexible, adaptive frameworks to address the fast-paced advancements across health care. It proposes a "total product life cycle" approach, including rigorous premarket assessment, post-market performance monitoring, and adapting existing standards to AI’s unique demands. Special considerations are suggested for large language models (LLMs) due to their complexity and potential to influence clinical decision-making. The agency stresses the importance of collaboration within the U.S. government and internationally for harmonizing AI standards, promoting safety, transparency, and patient-centered outcomes. Additionally, it encourages AI applications that benefit patient health rather than solely optimizing financial outcomes, highlighting a need for robust safeguards, especially in areas like clinical decision support. In conclusion, the FDA underscores the necessity of strong oversight to ensure safe, effective, and trustworthy AI applications, emphasizing that regulatory bodies, developers, and healthcare providers share a collective responsibility in advancing AI safely within clinical contexts. Read the full paper here: https://lnkd.in/gCnEpAC8 #AI #FDA #AIRegulation #DigitalHealth

GenAI meets Clinical Trials: Optimizing patient selection for faster results. Clinical trials are a crucial step in bringing new drugs to market, but they can be slow and expensive. Generative AI (GenAI) is transforming clinical trials by analyzing patient data (textual medical records) and video imaging (MRI scans, X-rays) to identify patients who are more likely to respond to a particular treatment. This multimodal approach is leading to more efficient trials and faster development of new therapies. #genai #clinicaltrials #healthcareinnovation #patientcare #futureofhealthcare Amisha Saxena Shailesh Giri

The FDA is playing a pivotal role in shaping how AI is integrated into health care and biomedicine, ensuring both innovation and patient safety. In a rapidly evolving landscape, regulatory frameworks must adapt to balance technological advancements with health outcomes. 🔄 Flexible, Adaptive Regulation: AI’s unique challenges require a life cycle management approach, ensuring ongoing performance monitoring post-market. The FDA is adopting flexible mechanisms to balance innovation with safety, especially as AI models evolve and influence clinical care. 🌍 Global Coordination and Harmonization: The FDA is working with international organizations to ensure AI regulations are consistent globally, promoting harmonized standards and fostering collaboration in AI's safe adoption across health care. ⚖️ Balancing Health Outcomes vs Financial Optimization: There’s a tension between using AI to enhance patient care and optimizing financial returns. The FDA emphasizes the need to prioritize health outcomes to build trust in AI applications and avoid harmful financial incentives. 😶 Special Oversight for Large Language Models (LLMs): As generative AI, like LLMs, enters health care, new tools for oversight are essential to prevent unforeseen consequences and ensure these technologies improve, rather than complicate, patient care. #AIinHealthcare #HealthTech #FDAGuidelines #AIRegulation #Biomedicine #DigitalHealth #AIInnovation #GenerativeAI #MedicalDevices #PatientSafety https://lnkd.in/gQXyp7uy

Informative update on FDA CDRH's Office of Science and Engineering Laboratories' (OSEL) work on research projects related to AI/ML-enabled medical devices. Be sure to click the links at the bottom of the page to see details of specific projects on limitations of medical data, bias, performance assessment and uncertainty quantification, performance evaluation methods, regulatory evaluation for some new use cases, and post-market monitoring.

Historic advances in AI applied to biomedicine and health care must be matched by continuous complementary efforts to better understand how AI performs in the settings in which it is deployed. This will entail a comprehensive approach reaching far beyond the FDA, spanning the consumer and health care ecosystems to keep pace with accelerating technical progress. If not, there is a risk that AI could disappoint similar to other general-purpose technologies deployed in health care settings or even create significant harm if untended models’ performance deteriorates or focuses on financial return without adequate attention to impact on clinical outcomes.

Many have seen the growth in artificial intelligence and machine learning-based medical devices cleared by the FDA. But how can clinical trial data guide our future outlook? Attorney Bradley Merrill Thompson, RAC, explores the information on clinicaltrials.gov, highlighting AI/ML products under investigation for future clinical use. #ArtificialIntelligence #MachineLearning #MedicalDevices