Alexandros Sagkriotis

BACKGROUND: Healthcare systems increasingly generate large volumes of clinical, imaging, genomic, wearable and real-world healthcare data. However, fragmentation across healthcare infrastructures continues to limit interoperability, integrated evidence generation and coordinated patient management. OBJECTIVE: This commentary examines how Personal Health Data Spaces (PHDS) may support interoperable, patient-centred, and evidence-informed healthcare through the integration of governance, real-world evidence (RWE), artificial intelligence (AI) and health data infrastructures. APPROACH: Drawing on regulatory science, digital health policy, interoperability frameworks and RWE practice, this commentary proposes a conceptual framework for PHDS that distinguishes them from existing health data initiatives and presents an implementation-oriented roadmap for their adoption within learning healthcare systems. DISCUSSION: Personal Health Data Spaces may support continuity of care, multimodal evidence generation, regulatory science, AI-enabled analytics and personalised medicine across increasingly interconnected healthcare environments. However, their successful implementation depends on interoperable infrastructures, harmonised governance, methodological transparency, cybersecurity, workforce capability and meaningful multi-stakeholder collaboration to avoid reinforcing existing healthcare inequities and operational fragmentation. CONCLUSION: Personal Health Data Spaces represent a patient-centred operational framework for integrating healthcare data across clinical care, research, and regulatory decision-making, supporting the transition towards interoperable and continuously learning healthcare systems. Their long-term success will depend not only on technological capability, but also on trustworthy governance, scalable implementation strategies, and sustained public trust.

External control arms (ECAs) have emerged as important tools to provide benchmark evidence on comparator effectiveness and thereby support regulatory decision making in situations where randomized controlled trials are difficult to conduct. However, how key methodological elements for ECAs are documented and implemented in practice and how residual uncertainty is managed at the time of approval remain unclear. Regulatory approvals of new medical products in Japan between 2019 and 2024 were systematically screened to identify cases employing ECAs. Among 674 eligible approvals screened from 835 approvals identified, 23 cases using ECAs were included and evaluated using a structured framework of 20 key attributes derived from regulatory guidance and methodological recommendations across planning, selection, design, analysis, and reporting domains. The post‐marketing requirements associated with each approval were also analyzed to assess how residual uncertainty was addressed following approval. ECAs were predominantly used in settings characterized by rare diseases and small patient populations. Although attributes related to study planning and data‐source selection were relatively well described in public documentation, there was substantial heterogeneity in the documentation of design and analysis elements. In particular, explicit specifications of estimands and approaches to handling intercurrent events and missing data were inconsistently described. Residual uncertainty was frequently addressed through post‐marketing requirements, often involving studies of efficacy considerations and long‐term surveillance, supporting a lifecycle‐based approach to uncertainty management. These findings highlight opportunities to enhance transparency and consistency in the documentation of ECA‐based evidence and to further develop structured approaches to uncertainty management in regulatory practice.

Real-world data (RWD) and real-world evidence (RWE) are increasingly used to inform regulatory decisions, health technology assessment, and health system planning. However, patients whose data underpin these activities often experience limited transparency or benefit when their information is monetised. While regulatory and HTA frameworks emphasise methodological rigor and analytical transparency, they provide limited guidance on fairness, reciprocity, and legitimacy from a patient perspective. This Policy Brief examines this governance gap and argues that evidence integrity must extend beyond technical standards to include ethical stewardship and public trust. Drawing on policy contexts from UK, EU, and North America, it proposes five pragmatic safeguards to strengthen transparency, accountability, and patient-centred governance in secondary data use, supporting the sustainability and legitimacy of RWE infrastructures as data initiatives expand.

Purpose: Real-world evidence (RWE) and real-world data (RWD) have become integral to regulatory, clinical, and policy decision-making. Yet oncology registries—the most structured and disease-specific RWD sources—remain fragmented, inconsistently governed, and poorly integrated with AI-driven analytical systems. This conceptual perspective synthesizes regulatory guidance, best practices, and three decades of professional experience to propose a pragmatic roadmap for transforming oncology registries into scalable, interoperable RWE platforms. Methods: The approach integrates practice-based evidence, international regulatory frameworks (EMA, FDA, MHRA), and case analyses from established registries and digital infrastructures. A three-year phased roadmap is proposed, focusing on governance, interoperability, artificial intelligence (AI) readiness, and multi-stakeholder collaboration. Although not a systematic review, the manuscript draws on applied use-cases and policy frameworks to illustrate transferability across healthcare systems. Results: Three conceptual models are developed to describe: (1) the main RWD domains; (2) the bidirectional alignment between RWE and RWD strategies; and (3) a phased roadmap for data activation, hybrid platform development, and AI-ready evidence generation. Case studies from the UK, France, Italy, Germany, and Finland demonstrate how registry modernization can enhance completeness, quality, and regulatory utility. Conclusions: Oncology registries can evolve from static repositories into dynamic learning infrastructures that generate regulatory-grade RWE. Achieving this transformation requires transparent governance, federated data architectures, Findable, Accessible, Interoperable, and Reusable (FAIR)-compliant interoperability, and ethically grounded AI integration. The proposed roadmap offers actionable guidance for regulators, payers, clinicians, and data scientists committed to advancing trustworthy, AI-enabled evidence ecosystems.

The integration of clinical and real-world evidence represents one of the most critical transformations in modern drug development and health technology assessment (HTA). Despite increasing regulatory openness, however, clinical trial evidence and real-world data (RWD) still operate largely as parallel rather than fully complementary systems. This commentary argues that experimental and observational research are not competing paradigms but two interdependent components of a unified evidence ecosystem, each capturing distinct yet equally essential dimensions of patient reality. Randomized controlled trials (RCTs) typically enrol highly selected populations and are optimised for internal validity, whereas RWD reflect the heterogeneity, comorbidities, and lived experiences of patients in routine clinical practice. Integrating these two evidence streams is therefore fundamental for personalised medicine, where the objective is to generate evidence that is both scientifically rigorous and meaningfully reflective of individual patient needs. This narrative Policy & Practice Commentary synthesises regulatory guidance, methodological literature, and applied case examples to examine how leading regulatorsand HTA agencies, including the U.S. Food and Drug Administration (FDA), European Medicines Agency (EMA), Medicines and Healthcare products Regulatory Agency (MHRA), Pharmaceuticals and Medical Devices Agency (PMDA), and National Institute for Health and Care Excellence (NICE), are developing frameworks to support the use of RWD and real-world evidence (RWE) in regulatory approval and reimbursement decision-making. Areas of convergence and divergence are explored, with particular emphasis on methodological transparency, data provenance, causal inference, and reproducibility as shared quality anchors across jurisdictions. Illustrative case examples from oncology and ophthalmology are used to demonstrate both the opportunities and challenges of hybrid evidence generation. In oncology, RWD are increasingly applied in external and hybrid control arms, pragmatic designs, and post-authorisation safety and effectiveness studies. In ophthalmology, advances in artificial intelligence-enabled image analytics and disease registries illustrate how routinely collected clinical data and patient-reported outcomes can be integrated to inform real-world value assessment. The commentary concludes by proposing actionable policy and practice recommendations to operationalise integrated evidence models, focusing on harmonised governance and methodological standards, transparent reporting and cross-sector collaboration, systematic incorporation of patient-generated data, and incentives for early and lifecycle-oriented RWD generation. By aligning regulatory policy, analytical methodology, and patient-centred design, integrated RWE frameworks can support decisions that are both scientifically robust and genuinely reflective of real-world patient experience.

Real-world evidence (RWE) plays an increasingly important role in healthcare decision-making, yet most industry-sponsored RWE studies are not intended for regulatory or reimbursement submission. While many such studies are conducted rigorously, this non-submission evidence base often operates without consistent protocol pre-specification, analytical transparency, or structured oversight, creating variability in quality and credibility. This Policy Brief examines this governance blind spot and argues that the challenge is structural rather than individual or intentional. Drawing on regulatory pilots and harmonisation initiatives, it shows that tools to strengthen non-submission RWE already exist but are unevenly applied. A framework is proposed based on three pillars: protocol registration, analytical transparency, and proportionate internal governance, including accountability for patient-contributed data. Extending these safeguards beyond submission-grade studies would raise baseline RWE quality and strengthen trust in RWE.

Aim: Real-world evidence (RWE) – defined here as clinical evidence derived from the analysis of real-world data (RWD) on patient health status and healthcare delivery – has become a cornerstone of regulatory and health technology assessment (HTA) decision making. However, despite broad consensus on its value, policy frameworks governing RWE generation and evaluation remain heterogeneous across jurisdictions. Importantly, this heterogeneity partly reflects the distinct purposes for which RWE is used, including regulatory safety assessment, effectiveness evaluation, health-economic modeling and natural-history research. These functional differences are not inherently problematic; however, fragmented operational requirements can create duplication, inefficiency and delays in patient access. Materials & methods: This study employed a narrative comparative policy review of RWE guidance issued by twelve major regulatory and HTA agencies, including the Medicines and Healthcare products Regulatory Agency (MHRA), the EMA, the US FDA and the Canadian Agency for Drugs and Technologies in Health (CADTH). Frameworks were compared across four domains: data quality, statistical methods, registry governance and transparency. Harmonization is defined as alignment across these domains sufficient to enable consistent planning, analysis and interpretation of RWE across jurisdictions, rather than uniformity of decision making. Results: The analysis identified convergence in high-level principles but persistent divergence in operational expectations. The MHRA emphasizes flexibility and scientific dialogue; the EMA prioritizes consistency and structured governance; and the FDA provides comprehensive but resource-intensive guidance, reflecting detailed documentation requirements, prespecified analytic expectations and extensive methodological review. HTA bodies apply additional evidentiary criteria related to comparative effectiveness and value, sustaining functional fragmentation even within the same healthcare systems. Conclusion: RWE fragmentation reflects both legitimate functional differences and avoidable operational misalignment. Progress toward harmonization therefore requires shared minimum standards and transparency mechanisms rather than additional guidance documents. The UK’s post-Brexit autonomy positions it as a test environment for collaborative pilots with the European Medicines Agency, the International Council for Harmonization (ICH) and the International Coalition of Medicines Regulatory Authorities (ICMRA). Six strategic actions are proposed to support pragmatic alignment while preserving contextual flexibility.

Real-world data (RWD) and real-world evidence (RWE) are now central to healthcare decision-making, supporting regulatory submissions, health technology assessments (HTA), and scientific communication. Yet patients whose data fuel these processes rarely see transparency or benefit when their information is commercialised. Governance frameworks from the European Medicines Agency (EMA), U.S. Food and Drug Administration (FDA), and other bodies emphasise methodological rigour and transparency, but they do not directly adjudicate questions of fairness, reciprocity, or perceived legitimacy from a patient perspective, which largely fall outside their formal remits. For clarity of scope, this commentary focuses specifically on patient perceptions of fairness, reciprocity, and legitimacy in the monetisation of secondary-use health data; it does not examine urgency-of-use questions, direct clinical benefits, or broader societal goals of data-driven healthcare. This article is a normative commentary informed by published patient surveys, governance case studies, and regulatory experience. It does not present original patient research but synthesises recurring patient-relevant concerns regarding trust, fairness, and public value in the secondary use of health data. This commentary argues that evidence integrity must extend beyond technical standards to encompass ethical stewardship. Drawing on case examples from the UK, EU, and North America, it shows how opacity in consent processes, selective disclosure of data use, and the absence of benefit-sharing widen the trust gap. Patients contribute information under the assumption it will improve care, not simply generate commercial value or institutional advantage. To address this, five pragmatic safeguards are proposed: i. transparent, plain-language consent; ii. mandatory disclosure of monetisation models; iii. governance boards with patient representation; While many national and international data governance bodies now include patient or public representatives, the depth of their influence varies considerably. In several early national data initiatives, patient involvement was limited to advisory or consultative roles without formal voting rights, agenda-setting authority, or oversight of commercial access decisions. Such structures risk being perceived as symbolic rather than substantive participation, reinforcing concerns about tokenism when representation is not matched by real decision power. iv. reinvestment of commercial gains into patient support, public health, and digital tools; Benefit sharing should not be interpreted as direct financial remuneration to individual patients, which is neither feasible nor desirable in most regulatory and research contexts. Rather, it refers to structured reinvestment of value generated from secondary data use into patient-relevant public goods, such as disease registries, patient organisations (including umbrella and European-level federations for rare diseases), digital infrastructure, education, and support services. In this way, reciprocity is achieved at community and system level, even when data originate from multiple countries and fragmented patient populations. v. mandatory registration of non-interventional studies in public registries. Together, these measures extend evidence integrity to include fairness, reciprocity, and legitimacy. Together, these measures extend evidence integrity to include fairness, reciprocity, and legitimacy. The future of RWE depends not only on scientific validity but also on whether patients trust that their data are handled responsibly and ethically. Perhaps it is time to move beyond passive consent and towards a new call for accountability—captured in a simple but powerful reminder: _“That is MY DATA.”_ This commentary is informed by principles of relational ethics and the _social responsibility of science_, framing data monetisation as both a technical and moral question of reciprocity and legitimacy. These safeguards are grounded in emerging international experience with data transparency and patient governance, though practical challenges and alternative frameworks are discussed.

Leadership in the pharmaceutical industry shapes not only organisational culture but also the pace of innovation and, ultimately, patient outcomes. This commentary synthesises insights from leadership theory and over three decades of industry experience to examine three recurring leadership archetypes: the Directive Strategist, the Enforcer, and the Corporate Diplomat. While each persona brings strengths—strategic vision, accountability, and external influence—they share common vulnerabilities: an overemphasis on ambition, external image, and personal growth, often at the expense of trust, psychological safety, and integrity. This commentary extends leadership literature by linking established constructs such as authoritarian leadership, abusive supervision, and impression management to pharmaceutical industry contexts, highlighting how these personas persist despite growing calls for patient-centred leadership. The analysis further integrates interdisciplinary perspectives from healthcare ethics, behavioural economics, and organisational psychology to situate leadership behaviours within broader systems of governance, incentives, and accountability. Across personas, integrity is frequently applied selectively—what may be termed “convenient integrity”—thereby eroding fairness and organisational resilience. These dynamics manifest in burnout, attrition, and innovation loss, all of which reduce the benefit delivered to patients. A key contribution is the introduction of the “PATIENT SCORE”—a conceptual and potentially empirical framework aligning leadership behaviours with measurable outcomes such as trial efficiency, pharmacovigilance reporting, staff retention, and patient access milestones. However, the commentary recognises that the “patient score” remains conceptual until empirically tested. Although conceptual, the model invites empirical testing through mixed-methods approaches integrating leadership-behaviour surveys, organisational performance data, and patient-outcome metrics. Future work should outline measurable indicators and validation strategies to evaluate its real-world applicability and strengthen its practical utility across leadership and patient-outcome settings. The commentary argues that sustainable pharmaceutical leadership requires authentic integrity, capability building, and team complementarity. RED-dominant leaders, for instance, are more effective when supported by BLUE (detail-focused) and GREEN (empathic) associates, balancing ambition with precision and harmony. Practical implications now include the development of Integrity Councils and Patient-Centred Dashboards to embed ethical oversight and patient alignment in leadership evaluation systems. Finally, the paper calls for mixed-methods research—combining qualitative interviews, network analysis, and quantitative performance metrics—to test the “patient score” construct empirically and its relationship to organisational trust and innovation. By combining conceptual reflection with future empirical pathways, the paper bridges theory and practice, reframing leadership success around a single guiding question: do our behaviours increase or decrease the score for patients?

Real-World Evidence (RWE) is a critical enabler of personalized medicine (PM), offering granular insights into how interventions perform across diverse, real-life populations. This manuscript, grounded in over 30 years of health data science and regulatory experience, explores the evolving role of RWE in transforming healthcare delivery—from regulatory frameworks and policy alignment to artificial intelligence (AI)-enabled patient stratification. Through real-world case examples in oncology, ophthalmology, and dermatology, the article illustrates how digital tools and data integration can enhance patient-centred care. Each vignette concludes with an “adoption path” outlining data requirements, minimal IT changes, training, and payer-relevant endpoints. The discussion critically examines risks—such as bias, opacity in algorithms, and lack of harmonization—and translates them into a pre-deployment audit checklist and an equity checklist for subgroup performance and representativeness audits. To guide global regulatory practice, a “regulatory pragmatics” checklist is proposed, covering data quality, traceability, validation, transparency, and patient voice, including patient-generated health data (PGHD). Building on the Healthcare 5.0 vision, the manuscript aligns RWE with human-centric, sustainable, and resilient pillars, highlighting IoT wearables, environmental sensors, and continuous lifestyle data streams. Policy and implementation recommendations, together with a global convergence roadmap, position RWE as a strategic tool for regulators, payers, and clinicians. The paper concludes with a call for systemic accountability: industry must innovate responsibly, regulators must approve with foresight, payers must assess tools beyond medications, and health systems must bridge infrastructure gaps. Over the next 12–24 months, measurable commitments are required across all stakeholders to ensure that PM becomes everyday care. PM must serve patients—not just science, policy, or business—and that demands leadership grounded in scientific integrity and human empathy.