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Clinical Features - Review

The three horizons model applied to medical science

ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon show all
Pages 776-783 | Received 08 Mar 2022, Accepted 18 Aug 2022, Published online: 14 Sep 2022
 

ABSTRACT

The three horizons model is a framework that helps manage an organization’s innovation strategy. This model considers three aspects (horizons) that should be present in the institution and guide the development of new systems. Applied to medical science, the horizons are considered as paradigms that set the guidelines for clinical knowledge. New technologies can influence this model by causing disruptive changes. Horizon 1 (evidence-based medicine) reflects the current paradigm and emphasizes the aspect of continuous improvement needed to strengthen it, such as with the introduction of the GRADE (Grades of Recommendation Assessment, Development, and Evaluation) methodology. Evidence-based medicine has made it possible to stop performing harmful interventions like autologous bone marrow or stem cell transplantation in cancer treatment for women with early poor prognosis breast cancer or to discontinue the erroneous belief that children should not sleep on their backs to prevent sudden infant death syndrome. Horizon 2 (real-world evidence) refers to a new model in which innovation has generated new capabilities. This change makes it possible to correct weaknesses of the previous paradigm, as in the case of pragmatic clinical trials. Real-world evidence has been used to show that drugs such as tofacitinib are effective without using methotrexate as background or to demonstrate the efficacy of chemotherapy in older patients with stage II colon cancer. Horizon 3 (precision medicine) involves a disruptive innovation, leading to the abandonment of the traditional mechanistic model of medical science and is made possible by the appearance of major advances such as artificial intelligence. Precision medicine has been used to assess the use of retigabine for the treatment of refractory epilepsy or to define a genome-adjusted radiation dose using a biological model to simulate the response to radiotherapy, facilitate dose adjustment and predict outcome in breast cancer.

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Juan M. Roman-Belmonte: Twitter account: @juanmaromanb

Declaration of funding

No funding was received in the production of this manuscript.

Disclosure of any financial/other conflicts of interest

The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

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