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GENOMICS


Predictor-intercept classification Rare diseases P


Gene therapies I


Teen mental health P Assess mental health I Adult major condition P Personalised plans I


Elderly multimorbidity P Review polypharmacy I Nutrient/pharma-omics P Lifelong targets I


Generative AI transparency in the real world with human phenotype ontology the primary care Address ethical and legal data use for ontology use case P I


Focus on design of proactive management by practitioner and citizen P I Coordinate multidisciplinary roles from development to adoption P I Semantic interoperability and traceability services for sector P I Integration knowhow of ecosystem data sources for HPO models P I Impact analysis of P


in relation to I is assessed for populace groups


Data driven decisions from PHM ecosystem to HPO models P I Risk stratification P


and segment disease groups I for effective PHM


Neighbourhood clinics engage and educate the public on outcomes P I Feedback loops, reinforcement learning and continuous improvement P I


Table 4. Real-world setting for predictors and intercept classifications. P – Predictors [Pre-eXams], I – Intercepts [eXams].


genomic testing pathway. (NHSE, 2025) www.england.nhs.uk/long-read/nhs- england-nice-genomic-testing-pathway/


10 Fuat A, Adlen E, Monane M, et al. A polygenic risk score added to a QRISK®2 cardiovascular disease risk calculator demonstrated robust clinical acceptance and clinical utility in the primary care setting. Eur J Prev Cardiol. 2024;31(6):716- 722. doi:10.1093/eurjpc/zwae004


11 Hayward J, Evans W, Miller E, Rafi I. Embedding genomics across the NHS: a primary care perspective. Future Healthc J. 2023;10(3):263-269. doi:10.7861/fhj.2023- 0116


12 Fischer RP, Volpert A, Antonino P, Ahrens TD. Digital patient twins for personalized therapeutics and pharmaceutical manufacturing. Front Digit Health. 2024;5:1302338. doi:10.3389/ fdgth.2023.1302338


13 Medicines and Healthcare products Regulatory Agency. Guidance: Software and artificial intelligence (AI) as a medical device. (MHRA, 2025) www.gov.uk/ government/publications/software-and- artificial-intelligence-ai-as-a-medical- device/software-and-artificial-intelligence- ai-as-a-medical-device


14 National Institute for Health and Care Excellence. Use of AI in evidence generation: NICE position statement. (NICE, 2024) www.nice.org.uk/position- statements/use-of-ai-in-evidence- generation-nice-position-statement


15 Shaw D, Lorenzini G, Arbelaez Ossa L, et al. When and what patients need to know about AI in clinical care. Swiss Med Wkly. 2025;155:4013. doi:10.57187/s.4013


16 Kasahara A, Mitchell J, Yang J, Cuomo RE, McMann TJ, Mackey TK. Digital technologies used in clinical trial recruitment and enrollment including application to trial diversity and inclusion: A systematic review. Digit Health. 2024;10:20552076241242390. doi:10.1177/20552076241242390


17 Lekadir K, Frangi AF, Porras AR, et al. FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare. BMJ. 2025;388:e081554. doi:10.1136/bmj-


52 2024-081554


18 Ogbeyemi A, Lin W, Odeyemi J, et al. Human factors in digital healthcare systems: a critical literature review. Enterprise Information Systems. 2025;19:7–8. doi:10.1080/17517575.202 5.2524847


19 NHS England. The future of NHS human resources and organisational development. (NHSE, 2020) www.england.nhs.uk/future- of-human-resources-and-organisational- development/


20 Mayeur C, Mertes H, Van Hoof W. Do genomic passports leave us more vulnerable or less vulnerable? Perspectives from an online citizen engagement. Humanit Soc Sci Commun. 2023;10(1):83. doi:10.1057/s41599-023- 01580-7


21 AI Security Institute. About: The AI Safety Institute. (AISI, 2025) www.aisi.gov.uk/ about


22 AI and Digital Regulations Service for health and social care. Understanding regulations of AI and digital technology in health and social care. (NHS, 2025) www.digitalregulations.innovation.nhs.uk


23 Life Sciences Hub Wales. AIDRS: New AI guidance for health and social care endorsed by The AI Commission. (LS Hub Wales, 2024) www.lshubwales.com/news/ aidrs-new-ai-guidance-health-and-social- care-endorsed-ai-commission


24 UK Research and Innovation. £300 million to launch first phase of new AI Research Resource. (UKRI, 2023) www.ukri.org/ news/300-million-to-launch-first-phase-of- new-ai-research-resource/


25 Karunanayake N. Next-generation agentic AI for transforming healthcare. Informatics and Health. 2025;2(2):73-83. doi:10.1016/j. infoh.2025.03.001


26 Panas A, Karlsson A. Accelerating Agentic AI: McKinsey Perspectives. (McKinsey, 2025)


27 Reddy Thamma S. Agentic AI for Clinical Decision Support: Real-Time Diagnosis, Triage, and Treatment Planning. Int J Sci Research in Sci Eng and Tech. 2025;12(3):428-422. doi:10.32628/ IJSRSET251265


28 Ringeval M, Etindele Sosso FA, SEPTEMBER 2025 WWW.PATHOLOGYINPRACTICE.COM


Cousineau M, Paré G. Advancing Health Care With Digital Twins: Meta-Review of Applications and Implementation Challenges. J Med Internet Res. 2025;27:e69544. doi:10.2196/69544


29 Alam A, Basilico J, Bertolini D, et al. Digital Twin Generators for Disease Modeling. (arkix.org, 2024) www.arxiv.org/ abs/2405.01488


30 Flöther FF, Blankenberg D, Demidik M, et al. How quantum computing can enhance biomarker discovery. Patterns (N Y). 2025;6(6):101236. doi:10.1016/j. patter.2025.101236


31 Gov.uk. The Life Sciences Innovative Manufacturing Fund (LSIMF). (Gov.uk, 2024) www.find-government-grants. service.gov.uk/grants/life-sciences- innovative-manufacturing-fund-lsimf-1


32 University of Cambridge. Dawn. (Univ. Cambridge, 2025) www.hpc.cam. ac.uk/d-w-n


33 AI Security Institute. The Alignment Project. (AISI, 2025) www.alignmentproject. aisi.gov.uk/


34 Gov.uk. Guidance: National AI Strategy. (Gov.uk, 2021) www.gov.uk/government/ publications/national-ai-strategy


James A Henry, MSc Mol Path Research, MSc Biomedical Sciences, PhD Candidate by Publication.


James was invited by the United Nations to submit a Scientific Policy Brief. His research, appropriated by the NHSE workflow lead in 2014, aligns with ISO 15189:2022 Annex A and supports the global Agentic AI vision for population health. This article, adapted from his seventh manuscript in population health, represents a decade of inquiry and iterative refinement, centred on an Ethical People Ontology Plan to deliver truth at the point of need for 50% of the population by 2035. To safeguard the originality and integrity of this foundational work, the manuscript is designated ‘no licence’ on the OSF framework [doi:10.31219/osf.io/cg84z_v1] pending engagement and funding to support his doctorate by publication.


James.henry19@outlook.com


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