AI Revolution in Healthcare: A Regulatory Perspective with Dr. Nirdosh Jagota

The Future of AI in Healthcare: Preparing for 2030 and Beyond

In the season finale of AI Revolution in Healthcare: A Regulatory Perspective, Dr. Nirdosh Jagota reflects on the future of AI in healthcare, looking ahead to 2030 and beyond. This episode brings together key themes from the series to explore how healthcare innovation, regulatory frameworks, and patient safety will evolve in the years to come.
Dr. Jagota highlights emerging trends such as adaptive regulatory frameworks, real-world evidence monitoring, and the integration of patient-generated data into AI systems. He discusses groundbreaking advancements like multimodal AI systems, automated manufacturing governed by AI, and "living protocols" for clinical trials that adapt in real-time—all set to transform the healthcare landscape.
Listeners will gain insights into the potential for AI to democratize healthcare access, the challenges of managing exponential data growth, and the continued importance of ethical AI design and patient privacy. Dr. Jagota emphasizes the need for global regulatory harmonization and collaboration to ensure AI innovations fulfill their promise while safeguarding equity and safety.
Join Dr. Jagota as he concludes this season by envisioning a future where innovation and regulation coexist to improve healthcare outcomes worldwide.
Thank you for joining us on this journey through the AI healthcare revolution! Follow Amazon Music, Spotify, or subscribe on YouTube to stay informed. 
Visit Nirdosh Jagota's Official Website for exclusive resources and insights into the future of AI in healthcare

Ethics and Patient Privacy in the Age of AI Healthcare

In this thought-provoking episode of AI Revolution in Healthcare: A Regulatory Perspective, Dr. Nirdosh Jagota explores the vital topics of ethics and patient privacy in AI-powered healthcare systems. As AI becomes increasingly involved in medical decision-making, issues such as accountability, transparency, and fairness take center stage.
Dr. Jagota discusses real-world cases, including an AI triage system that revealed disparities in performance across demographic groups, underscoring the importance of addressing algorithmic bias and healthcare equity. He also highlights the evolution of privacy frameworks and emerging privacy-preserving AI techniques, such as federated learning, that enable AI training without compromising patient confidentiality.
Listeners will learn about "ethics by design" principles, the growing demand for explainable AI, and the role of robust data governance in ensuring ethical AI deployment. Dr. Jagota delves into the regulatory focus on "algorithmic accountability" and the importance of human oversight in AI-driven decisions.
Finally, he explores forward-looking trends such as dynamic consent models and standardized frameworks for ethical AI assessment, paving the way for a future where innovation and trust go hand in hand.
Join Dr. Jagota as he examines how regulatory frameworks are adapting to protect patient privacy and uphold ethical standards in the age of AI healthcare.
Stay informed about the ethical and privacy considerations shaping AI in healthcare! Follow Amazon Music, Spotify, or subscribe on YouTube to stay informed.
For more resources and insights, visit Nirdosh Jagota's Official Website.

Global Regulatory Framework for AI in Healthcare: A Comparative Analysis

In this episode of AI Revolution in Healthcare: A Regulatory Perspective, Dr. Nirdosh Jagota examines the global regulatory landscape for AI in healthcare. As AI technologies transcend borders, understanding the similarities and differences between regulatory frameworks is critical for innovators seeking worldwide implementation.
Dr. Jagota explores key approaches taken by major regulatory bodies, including the FDA's total product lifecycle management, the EMA's emphasis on risk classification, and Asia's focus on real-world performance evaluation. Using real-world examples, he highlights how differing requirements for validation, data privacy, and post-market monitoring affect AI deployment across regions.
Listeners will gain insights into the ongoing international harmonization efforts, including the role of organizations like the International Medical Device Regulators Forum. Dr. Jagota also discusses forward-looking trends such as regulatory sandboxes and the development of global AI standards, which promise to streamline the approval process for AI-powered healthcare solutions.
Join Dr. Jagota as he provides a comparative analysis of regulatory frameworks and offers practical guidance for navigating the complexities of global AI regulation in healthcare.
Stay informed about the rapidly evolving world of AI healthcare regulation! Follow Amazon Music, Spotify, or subscribe on YouTube to stay informed.
For more resources and insights, visit Nirdosh Jagota's Official Website.

Validation and Verification of AI Systems in Healthcare

In this episode of AI Revolution in Healthcare: A Regulatory Perspective, Dr. Nirdosh Jagota explores the vital process of validation and verification for AI systems in healthcare, emphasizing their role in ensuring safety and effectiveness for patient care.
Dr. Jagota breaks down the unique challenges AI systems present compared to traditional medical devices, focusing on their ability to adapt and evolve. He examines the three fundamental principles of AI validation—analytical validation, clinical validation, and continuous performance monitoring—and shares real-world examples that highlight the importance of robust validation protocols.
Listeners will gain insights into regulatory requirements such as data management, performance evaluation, and continuous validation protocols. Dr. Jagota also discusses emerging trends like "validation by design" and automated validation tools that promise to reshape how AI systems are monitored throughout their lifecycle.
Join Dr. Jagota as he navigates the complexities of AI validation and provides actionable guidance for innovators and professionals ensuring their AI systems meet the highest regulatory standards.
Stay ahead in the rapidly evolving world of AI in healthcare! Follow Amazon Music, Spotify, or subscribe on YouTube to stay informed.
For more resources and insights, visit Nirdosh Jagota's Official Website.

AI in Drug Safety and Pharmacovigilance: The Future of Patient Safety

In this episode of AI Revolution in Healthcare: A Regulatory Perspective, Dr. Nirdosh Jagota dives into the transformative role of artificial intelligence in drug safety and pharmacovigilance. With the ability to process thousands of adverse event reports daily, AI is reshaping how pharmaceutical companies identify and respond to safety signals, ensuring patient safety remains paramount.
Dr. Jagota explores three primary areas of impact: adverse event processing, signal detection, and risk assessment. From automating the classification of adverse events to uncovering rare safety patterns through advanced analytics, AI is enabling faster, more accurate responses. The episode also highlights regulatory requirements for AI-enabled pharmacovigilance systems, including Good Pharmacovigilance Practices (GVP), data quality standards, and continuous learning protocols.
Listeners will learn how AI systems are integrated with global safety databases, adapt to new safety information while maintaining compliance, and enhance risk management strategies. Dr. Jagota provides actionable insights into the evolving regulatory landscape and the balance between innovation and oversight.
Join Dr. Jagota as he examines the future of pharmacovigilance and how AI is elevating patient safety through advanced technology and robust regulation. 
Don’t miss future episodes exploring the cutting edge of AI and healthcare regulation! Follow Amazon Music, Spotify, or subscribe on YouTube to stay informed.
For more resources and insights, visit Nirdosh Jagota's Official Website.

Predetermined Change Control Plans: Managing AI/ML Evolution in Medical Devices

In this episode of AI Revolution in Healthcare: A Regulatory Perspective, Dr. Nirdosh Jagota explores the innovative concept of Predetermined Change Control Plans (PCCPs) for AI and machine learning-enabled medical devices. PCCPs offer a regulatory solution to the challenge of managing evolving AI systems that learn and adapt over time.
Dr. Jagota explains how PCCPs act as a roadmap for AI device modifications, allowing manufacturers to specify anticipated changes, how they’ll be implemented, and how safety and effectiveness will be maintained. He uses a real-world example of an AI diagnostic system to illustrate how this framework ensures controlled evolution while keeping patient safety at the forefront.
The episode also highlights key components of a PCCP: modification description, protocol for implementation, and impact assessment. Dr. Jagota emphasizes the importance of data quality, performance monitoring, and transparency in successful implementation.
Join Dr. Jagota as he examines how PCCPs are shaping the future of AI regulation in medical devices, enabling innovation while ensuring patient safety.
Visit Nirdosh Jagota Official Website for more resources and insights.

Quality Control and AI: Ensuring Safety in Drug Manufacturing

In this episode of AI Revolution in Healthcare: A Regulatory Perspective, Dr. Nirdosh Jagota explores how artificial intelligence is transforming pharmaceutical manufacturing, particularly in quality control. Titled "Quality Control and AI: Ensuring Safety in Drug Manufacturing," this episode delves into the intersection of AI and regulatory compliance, focusing on three key areas: real-time process monitoring, batch release decision-making, and supply chain management.
Dr. Jagota discusses how AI enhances continuous process verification, predictive maintenance, and batch release decisions while maintaining strict adherence to regulatory frameworks such as Current Good Manufacturing Practices (CGMPs). He also explores the growing application of Quality by Design (QbD) principles, where AI systems monitor and predict potential risks in real-time, ensuring product quality and consistency.
With AI playing a critical role in automating and optimizing pharmaceutical manufacturing, Dr. Jagota emphasizes the importance of meeting regulatory standards for model validation, data integrity, and risk management. He highlights the need for AI systems to demonstrate reliability, transparency, and traceability to ensure both product safety and regulatory compliance.
Join Dr. Jagota as he navigates the regulatory complexities of AI in drug manufacturing and its potential to enhance product safety and quality.
 
Visit Nirdosh Jagota Official Website for more resources and insights.

Machine Learning in Medical Imaging: A Regulatory Success Story

In this episode of AI Revolution in Healthcare: A Regulatory Perspective, Dr. Nirdosh Jagota explores the transformative role of machine learning in medical imaging and its regulatory journey. He highlights a Swedish study where AI-assisted breast cancer screening improved detection rates by 4% compared to traditional methods.
Dr. Jagota examines three key aspects of AI in imaging: regulatory frameworks, performance validation, and integration into clinical workflows. He discusses the FDA’s approach to AI imaging devices, including concepts like predetermined change control plans (PCCP) to accommodate AI's ability to learn over time.
Listeners will gain insights into the validation requirements for AI imaging systems, including analytical and clinical validity, and the importance of transparency in AI decision-making. The episode also covers the growing trend of real-world performance monitoring.
Join Dr. Jagota as he discusses how regulatory frameworks are enabling AI to safely innovate medical imaging, paving the way for advancements in other healthcare sectors.

Artificial Intelligence in Clinical Trials: Transforming Drug Development

In this episode of AI Revolution in Healthcare: A Regulatory Perspective, Dr. Nirdosh Jagota dives into the transformative role of artificial intelligence in clinical trials and drug development. Titled "Artificial Intelligence in Clinical Trials: Transforming Drug Development," Dr. Jagota discusses how AI is addressing critical challenges in clinical research, such as the high costs and lengthy timelines of traditional trials.
Dr. Jagota explores three key areas where AI is making an impact: patient selection and recruitment, real-time data monitoring, and adaptive trial designs. AI is revolutionizing patient matching, reducing trial costs, and improving data accuracy, while also enabling adaptive trials that can modify based on real-time results.
He also delves into the regulatory challenges of integrating AI, emphasizing the need for compliance with Good Clinical Practice (GCP) and maintaining data integrity. AI systems must be validated, and AI-driven changes must be documented carefully to meet regulatory standards.
Listeners will gain insights into emerging regulatory frameworks, including FDA guidelines and the concept of "regulatory-grade AI," ensuring AI's safe and ethical use in clinical trials.
Join Dr. Jagota as he examines how AI is reshaping clinical trials and the evolving regulatory landscape that supports this revolution.
 
Visit Nirdosh Jagota Official Website for more resources and insights.

The Dawn of AI in Healthcare: Understanding the Regulatory Landscape

In the very first episode of "AI Revolution in Healthcare: A Regulatory Perspective," Dr. Nirdosh Jagota takes listeners on a journey to explore how artificial intelligence is transforming healthcare and what it means for regulatory processes. In this episode, titled "The Dawn of AI in Healthcare: Understanding the Regulatory Landscape," Dr. Jagota discusses the unprecedented transformation AI is bringing to the healthcare sector—from drug discovery to diagnostics—and the unique regulatory challenges that accompany this revolution.
Listeners will gain an in-depth understanding of how regulatory bodies like the FDA and EMA are adapting to these new advancements, focusing on critical areas such as adaptive algorithms, predetermined change control plans, and real-world performance monitoring. The episode also includes insights into the steps companies need to take to align with evolving regulatory standards, including establishing robust data management practices and post-market surveillance.
Join Dr. Nirdosh Jagota as he unravels how regulations are adapting to foster innovation while ensuring patient safety in this exciting era of AI in healthcare. Subscribe today to stay updated on future episodes where we dive deeper into specific applications of AI across the healthcare spectrum.
Visit our website at https://nirdoshjagota.net/ for more resources and insights.