Precision Healthcare Powered by Artificial Intelligence: A Global Regulatory Perspective

Artificial Intelligence (AI) in Precision Medicine

The true potential of precision or personalized medicine has been unlocked with the integration of Artificial Intelligence (AI) [4]. AI has turned the concept of precision medicine into a reality with the advent of technology, promising to enhance diagnosis and cure [5]. Below are few key areas where AI is being used in precision medicine or personalized healthcare:

Diagnosis, Disease Prediction and Preventive Medicine

Algorithms powered by AI, such as machine learning and deep learning, can analyze vast amounts of patient data, such as genetic information, medical histories, and medical imaging results. These algorithms can detect subtle changes and anomalies that may be overlooked by human clinicians, leading to earlier and more precise disease diagnoses [6, 7]. Additionally, AI’s analysis of patient data can aid in predicting disease progression, identifying individuals at high risk, thereby facilitating proactive interventions and preventive measures [8]. AI can enhance precision preventive medicine by examining information from wearable technology, digital health records, and environmental monitoring devices. By continuously tracking a person's health metrics, AI systems can detect early indications of illness or declining health, allowing for prompt interventions and preventive actions [8].

Personalized Treatment Planning and Treatment Optimization

By analyzing genetic information, patient histories, and clinical outcomes, AI algorithms can predict how different individuals will respond to various treatments, allowing for personalized treatment planning and the development of tailored therapeutic strategies. AI-powered pharmacogenomics helps identify genetic markers associated with specific diseases and treatment responses, enabling personalized medication dosages and therapies. This reduces the trial-and-error approach traditionally used in prescribing medications, thereby enhancing drug efficacy and reducing the incidence of adverse drug reactions (ADRs) [4, 5, 9, 10,11]. AI-driven personalized treatment plans can complement traditional approaches by offering more targeted and effective care, improving patient outcomes while also helping to reduce the financial burden on healthcare systems [12].

Drug Discovery. Repurposing and Development

AI accelerates drug discovery and development by leveraging advanced algorithms to analyze large quantities of biological and chemical data. AI helps in identifying potential drug targets, biomarker discovery, protein structure prediction, de novo drug design, and virtual screening of promising compounds to generate novel drug candidates tailored to specific therapeutic targets. AI predicts drug-drug interactions and optimizes clinical trial design, helps in patient population selection and stratification during clinical trials, improves data collection and analysis from clinical trials including real-time health monitoring, enhancing efficiency and success rates of clinical trials [13, 14]. These advancements not only reduce the time and cost associated with drug development but also improve the precision and effectiveness of new therapies.

The advent of AI has also revolutionized drug repositioning or repurposing. AI algorithms use extensive datasets, including existing drug databases, clinical records, and scientific literature to conduct data integration, advanced data analysis, and pattern recognition thereby helping in acceleration of drug repurposing. Predictive models play a crucial role in identifying new therapeutic uses for existing drugs [15].

Thus, the integration of AI into precision medicine is transforming the landscape of healthcare, enabling more accurate diagnoses, personalized treatment plans, and efficient drug discovery and repurposing. By utilizing vast amounts of data and advanced algorithms, AI enhances the ability to tailor medical interventions to individual patients' unique genetic, environmental, and lifestyle factors. This not only improves patient outcomes but also reduces the time and cost associated with developing new therapies, ultimately paving the way for a more effective and personalized approach to healthcare [16].

Examining AI in Precision Medicine Through a Regulatory Lens

AI systems in precision medicine are unlikely to replace human clinicians extensively. Instead, will be set to enhance the abilities of healthcare providers. Over time, medical professionals will likely concentrate on tasks that make use of distinctly human skills, while AI will develop into a vital resource, boosting the teamwork of clinicians in their pursuit of excellent patient care by streamlining clinical workflows, assisting in diagnostics, and enabling personalized treatment. Nevertheless, the introduction of these cutting-edge solutions poses substantial challenges in clinical and care environments, such as integration with existing systems, data privacy concerns, and the need for clinician training, necessitating a thorough exploration of ethical, legal, and regulatory considerations [17].

A robust governance framework is imperative to foster the acceptance and successful implementation of AI in healthcare. Regulatory oversight is crucial to ensure the safety, accuracy, and effectiveness of AI-driven diagnostic and treatment tools. Considerations for adopting AI systems include standardized protocols that guarantee uniform functionality, training of clinicians in their use, securing financial support from public and private payer organizations, and undergoing iterative updates [17, 18, 19].

Furthermore, a regulatory perspective considers the interplay between AI, data governance, and patient rights. This involves establishing clear guidelines for data handling, informed consent processes, and the allocation of responsibility for AI-driven decisions. Additionally, the regulatory framework must address the potential for algorithmic bias in AI systems, promoting fairness in healthcare outcomes and ensuring equitable access to AI-driven innovations [17, 18, 19]. Several initiatives have been started by the regulatory agencies and organizations worldwide in the field of AI, healthcare and precision medicine:

European Union (EU):

·         European Union (EU) AI Act (enacted in August 2024): Enacted for the development and deployment of responsible, safe and trustworthy AI in the EU and lays down the harmonized rules on AI.

·         European Health Data Space Regulation (EHDS) (entered into force March 2025): Regulation with the aim to establish a common framework for the use and exchange of electronic health data across the EU. This will facilitate AI in medicine to access the diverse and high-quality health data to ensure accuracy, robustness, and fairness across different populations while also ensuring compliance with data protection and ethical standards. The EHDS will build on the following existing EU frameworks:

o   EU General Data Protection Regulation (GDPR)

o   Data Governance Act

o   Data Act

o   Network and Information Systems Directive

·         HealthData@EU Central Platform: A central online hub that brings together health datasets from across Europe, making it easier for researchers, policymakers, and public health authorities to find and access health data in a secure, ethical, and harmonized way. This is a major step forward in building the EHDS.

·         The Product Liability Directive (adopted in November 2024): Introduced to modernize the EU's product liability framework for the digital age, ensuring that consumers are better protected and can more easily claim compensation for damages caused by defective products, including digital and AI-driven product.

·         AICare@EU (launched in 2024): Several initiatives interconnected under this framework with a purpose to ensure effective and efficient implementation of AI tools and scale up their equitable and fair adoption in clinical practice, improving diagnostics, treatment personalization, and resource management.

·         EUropean Federation for CAncer IMages (EUCAIM) Project (started in January 2023): Is the cornerstone of the European Commission-initiated European Cancer Imaging Initiative, a flagship of Europe’s Beating Cancer Plan (EBCP), which aims to foster innovation and deployment of AI tools and digital technologies in cancer treatment and care to achieve more precise and faster clinical decision making, diagnostics, treatment and predictive medicine for cancer patients.

US FDA:

·         Draft Guidance: AI-Enabled Device Software Functions - Lifecycle Management and Marketing Submission Recommendations (released in January 2025): This draft guidance provides recommendations to support development and marketing of safe and effective AI-enabled devices throughout the device’s total product life cycle. It ensures that AI devices meet safety and effectiveness standards.

·         Draft Guidance: Considerations for the Use of Artificial Intelligence To Support Regulatory Decision-Making for Drug and Biological Products | FDA  (released in January 2025): This draft guidance provides a risk-based credibility assessment framework that may be used for establishing and evaluating the credibility of an AI model for a particular context of use.

·           Artificial Intelligence/Machine Learning-enabled Software as a Medical Device (SaMD): This US FDA webpage offers comprehensive guidance and resources from the US FDA to promote consistency and share insights relevant to the development and regulation of AI/Machine Learning (ML) in medical device products.

·         AI/ML-Enabled Medical Device List: This US FDA list identifies AI/ML-enabled medical devices that are authorized for marketing in the United States. It increases transparency and helps stakeholders understand the regulatory status of AI devices.

·         National Evaluation System for Health Technology (NEST): This system is a part of FDA initiative to collaborate with medical device stakeholders to enable performance and patient outcome tracking across traditional devices and SaMD. This system will assist with regulatory decision-making and helps ensure the safety and effectiveness of AI-enabled medical devices.

Canada:

·         Canadian Precision Health Initiative (Genome Canada) (launched in March 2025): Is an initiative that aims to harness AI and genomics to drive breakthroughs in precision medicine and healthcare across Canada. The AI-powered genome sequencing data holds the key to a future with more precise, preventative and cost-effective healthcare and to Canada’s competitive edge in health innovation.

·         Pan-Canadian Artificial Intelligence Strategy (launched in 2017): Led by the Canadian Institute for Advanced Research (CIFAR), this strategy was the first national AI strategy in the world. It includes initiatives like the Pan-Canadian AI for Health (AI4H) Guiding Principles, which aim to support the responsible and ethical adoption of AI technologies across Canada's health systems. These principles focus on improving health outcomes, modernizing health systems, and promoting equitable access to high-quality healthcare.

·         AI for Health Research: The Canadian Institute of Health Research (CIHR) funds various research projects that utilize AI to improve health outcomes. These projects focus on areas such as precision medicine, diagnostics, and health system management.

·         Implementing AI in Canadian Healthcare: Healthcare Excellence Canada (HEC) has developed guiding principles and strategies to support in AI implementation in Canada’s health sector. This includes guiding principles and practical tools to help integrate AI into healthcare systems effectively and ethically.

United Kingdom:

·         UK National Health Service AI Lab (launched in 2019): Focuses on accelerating the safe, ethical, and effective adoption of AI in the UK healthcare system. It supports the development and deployment of AI technologies to improve patient outcomes and operational efficiency.

·         AI Opportunities Action Plan (published in January 2025): Outlines the UK's strategy to ramp up AI adoption across various sectors, including healthcare. It aims to boost economic growth, create jobs, and improve public services by leveraging AI technologies.

World Health Organization (WHO):

·         The Global initiative on AI for Health (GI-AI4H) (launched in 2023): Is a dynamic resilient, long-term institutional platform established to provide answers to the pressing questions surrounding AI in healthcare, grounded in its mission to enable, facilitate, and implement AI in healthcare.

·         Guidance Document Ethics and Governance of AI for Health (updated in March 2025): Focuses on establishing ethical principles and governance frameworks for the use of large multi-modal AI models in healthcare aiming to ensure that AI technologies are used responsibly, transparently, and equitably to improve health outcomes.

·         Guidance Regulatory Considerations on Artificial Intelligence for Health (released in October 2023): Provides key frameworks and best practices for the development and regulation of AI systems in healthcare. It serves as a resource for stakeholders, including developers and regulators, to ensure safe and effective AI integration into the design of medical devices.

These initiatives highlight the global effort to integrate AI into healthcare responsibly and effectively, ensuring that AI technologies are used to improve health outcomes while addressing ethical, legal, and regulatory challenges by establishing robust frameworks, promoting ethical standards, and ensuring regulatory compliance.

Conclusion

The integration of AI into precision medicine represents a transformative shift in healthcare, promising to enhance diagnostic accuracy, optimize treatment plans, and accelerate drug discovery and development. AI's ability to analyze large quantities of genetic, clinical, and environmental data enables a more personalized approach to patient care, improving outcomes and reducing healthcare costs. However, the successful implementation of AI in precision medicine requires robust regulatory frameworks to ensure safety, efficacy, and ethical use.

Regulatory bodies worldwide, including the European Union, the United States, Canada, and the United Kingdom, have initiated various guidelines and frameworks to address the challenges posed by AI in healthcare. These initiatives aim to standardize AI applications, protect patient data, and promote fairness and transparency in AI-driven healthcare solutions. The collaboration between regulatory agencies, healthcare providers, and technology developers is crucial to harness the full potential of AI while safeguarding patient rights and ensuring equitable access to advanced medical technologies.

As AI continues to evolve, ongoing efforts to refine regulatory policies and address ethical considerations will be essential. By fostering a supportive regulatory environment, we can pave the way for AI to revolutionize precision medicine, ultimately leading to more effective, personalized, and accessible healthcare for all.

References:

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