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The Future of Precision Medicine: Potential Impacts for Health Technology Assessment
Open accessAbstract
OBJECTIVE: Precision medicine allows healthcare interventions to be tailored to groups of patients based on their disease susceptibility, diagnostic or prognostic information, or treatment response. We analysed what developments are expected in precision medicine over the next decade and considered the implications for health technology assessment (HTA) agencies. METHODS: We performed a pragmatic literature search to account for the large size and wide scope of the precision medicine literature. We refined and enriched these results with a series of expert interviews up to 1 h in length, including representatives from HTA agencies, research councils and researchers designed to cover a wide spectrum of precision medicine applications and research. RESULTS: We identified 31 relevant papers and interviewed 13 experts. We found that three types of precision medicine are expected to emerge in clinical practice: complex algorithms, digital health applications and 'omics'-based tests. These are expected to impact upon each stage of the HTA process, from scoping and modelling through to decision-making and review. The complex and uncertain treatment pathways associated with patient stratification and fast-paced technological innovation are central to these effects. DISCUSSION: Innovation in precision medicine promises substantial benefits but will change the way in which some health services are delivered and evaluated. The shelf life of guidance may decrease, structural uncertainty may increase and new equity considerations will emerge. As biomarker discovery accelerates and artificial intelligence-based technologies emerge, refinements to the methods and processes of evidence assessments will help to adapt and maintain the objective of investing in healthcare that is value for money.
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![Fig. 3 Challenges for health technology assessment agencies raised by precision medicine. Note: The first-tier categories (scoping to review) relate to the four principal stages of a typical health technology assessment appraisal, such as that used by National Institute for Health and Care Excellence (NICE) in England for traditional pharmaceutical technologies [32]](/paper-figures/9d25b41ea6854d1fb5515fed4a227dee/the-future-of-precision-medicine-potential-impacts-for-health-technology-figure-3.jpg)
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“In addition to genetic information, other biomarkers such as protein expression, gut microbiome, and metabolic profile are also employed with machine learning to enable personalized treatments [12].”
From The rise of artificial intelligence in healthcare applications (2020) · cites this paper as [12]
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“Omics-based tests: Genetic information from a population pool is used with machine learning algorithms to find correlations and predict treatment responses for the individual patient.”
From The rise of artificial intelligence in healthcare applications (2020) · cites this paper as [12]
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Metadata
- Authors
- Love-Koh, J., Peel, A., Rejon-Parrilla, J. C., Ennis, K., Lovett, R., Manca, A., Chalkidou, A., Wood, H., & Taylor, M.
- Affiliations
- University of York (GB)
- University of Liverpool (GB)
- National Institute for Health and Care Excellence (GB)
- Luxembourg Institute of Health (LU)
- Corresponding author
- Love-Koh, James
- Venue
- PharmacoEconomics
- Published
- 2018-07-13
- Volume
- 36
- Issue
- 12
- Pages
- 1439-1451
- ISSN
- 1170-7690 (ISSN-L)
- 1179-2027
- PMC
- PMC6244622
- OpenAlex
- W2884983901
- Cited by
- 131
- References
- 53
- Citations by year
- 2026: 8 · 2025: 11 · 2024: 17 · 2023: 25 · 2022: 16 · 2021: 28 · 2020: 15 · 2019: 11
- FWCI
- 20.46
- Type
- journal article
- Language
- en
- Update notices
- correction (2018-10-26)
- Open access
- hybrid
- doi.org
- Licence
- Locations
- PharmacoEconomics (publishedVersion, cc-by-nc)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Research Portal (King's College London) (submittedVersion, cc-by-nc)
- Funders
- National Institute for Health and Care Excellence
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Technology and Human Factors in Education and Health
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Pharmaceutical Economics and Policy
- Keywords
- precision medicine, health technology assessment, patient stratification, digital health applications, artificial intelligence in healthcare, structural uncertainty, health care equity, value for money, decision-making
- MeSH terms
- Artificial Intelligence, Decision Making, Humans, Technology Assessment, Biomedical, Biomarkers, Biomedical Technology, Uncertainty, Precision Medicine
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