Blueprint for a Universal Artificial Intelligence-Driven Digital Platform in Healthcare and Life Sciences – From Vision to Implementation (Preprint)

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BACKGROUND Digital transformation in healthcare and life sciences has accelerated through data-driven innovations, Artificial Intelligence (AI), and automation. Despite progress, digital platforms remain fragmented, limiting care continuity, research integration, and operational efficiency. A universal AI-driven digital platform could offer transformative potential by unifying healthcare services, patient engagement tools, and research databases. It could help address key challenges such as data interoperability, digital maturity, and ethical compliance, while enabling real-time monitoring, prevention, personalized treatment, and cross-sector collaboration. However, current efforts lack a unified solution design, strategy, and framework aligned with both healthcare and AI ethics. OBJECTIVE Develop a comprehensive design and strategic roadmap for a universal AI-based platform in healthcare and life sciences, ensuring alignment with healthcare ethics, AI ethics, and technological advances. By addressing technological, regulatory, and ethical dimensions, we bridge existing gaps and enable a transformative, integrated approach that fosters innovation, efficiency, and collaboration across sectors. METHODS This research employed a mixed-methods design, combining a systematic literature review with insights from previously published stakeholder interviews and expert panels, utilising PRISMA 2020. Only published data were used, ensuring ethical compliance without the need for additional approvals. RESULTS We created the strategic design and core features of a universal AI-based platform aimed at transforming healthcare and life sciences. The design unifies fragmented services and their management, integrates ethical AI aligned with medical ethics, and supports research, education, crisis management, health monitoring and patient care. Key strengths include comprehensive integration, ethical alignment, real-time insights, and adaptability. The platform distinguishes itself from existing models by offering a holistic, scalable system that incorporates real-time crisis management, patient engagement, and culturally competent AI. It uniquely aligns healthcare and AI ethics to ensure fairness, transparency, and accountability. Ethical challenges — such as bias, consent, autonomy, and regulatory disparities — are addressed through targeted mitigation strategies. To overcome regulatory complexity, a six-step pathway is proposed, including the creation of regulatory consortiums and development of standardized protocols. The platform has broad implications for healthcare delivery, policy, and research, enabling real-time analytics, informed decision-making, and collaboration. CONCLUSIONS The universal AI-driven platform, along with the development and implementation strategies created in this work, is designed to transform healthcare and life sciences by integrating advanced technology with ethical, legal, and regulatory frameworks. Together, they promote collaboration, continuity of care, equitable health outcomes, ethical and regulatory alignment, responsible AI, and sustainable implementation. While national deployment is the immediate goal, the platform is architected to support future wider integration efforts where feasible. Future research should focus on the continued minimization of AI bias, refinement of governance, and evaluation of equity impacts.

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