Why the way we define diseases prevents innovation and precision medicine

Noncommunicable diseases (NCDs) have become globally abundant, yet the therapeutics we use for them are imprecise. In parallel, identifying new treatments has become more costly than ever due to the ever-aggravating efficacy crisis drug discovery faces. What unites these failures is our ontological classification of diseases, primarily based on descriptive terms. To achieve precision diagnosis and precision therapy in clinical practice, NCDs need to be redefined and subdivided based on their causal molecular mechanisms. However, the inconsistency and incompatibility of the current disease classification systems hinder data integration and analysis towards the characterization of such mechanisms. Here, we explain flaws in the current disease definitions and the dispersion among existing ontologies with the aim of establishing a mechanism-based classification of diseases hence, precision medicine.

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Author and article information

Journal

Title: DrugRxiv

Publisher: REPO4EU

Publication date (Electronic preprint): 1 February 2023

Affiliations

[1 ] Department of Pharmacology & Personalised Medicine, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands ( https://ror.org/02jz4aj89)

[2 ] Department of Pharmacology & Toxicology, Faculty of Pharmacy, Zagazig University, Zagazig, Egypt ( https://ror.org/053g6we49)

[3 ] Interdisciplinary Computing and Complex BioSystems (ICOS) Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom ( https://ror.org/01kj2bm70)

[4 ] School of Life Sciences, University of Warwick, Coventry, United Kingdom ( https://ror.org/01a77tt86)

[5 ] Department of Pharmacology & Personalised Medicine, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands ( https://ror.org/02d9ce178)

[6 ] Centro de Tecnología Biomédica / ETS Ingenieros Informáticos. Universidad Politécnica de Madrid. Pozuelo de Alarcón, Madrid, Spain;

[7 ] Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, USA ( https://ror.org/04b6nzv94)

[8 ] Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Department of Neurology, University Hospital Essen, Essen, Germany ( https://ror.org/02na8dn90)

[9 ] STALICLA, Barcelona, Catalonia, Spain;

Author notes

[* ]Email: zmamdouh@ 123456ppmlab.net .

Author information

Zeinab M. Mamdouh https://orcid.org/0000-0002-4201-7973

Article

DOI: 10.14293/S2199-1006.1.SOR-.PPCFYDY.v1

SO-VID: 4bfe23d9-d2f6-4e69-b86e-c6965ff9639e

License:

This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .

History

Date received : 1 February 2023

Funding

Funded by: funder-id http://dx.doi.org/10.13039/100018696, HORIZON EUROPE Health;

Award ID: 101057619

Funded by: funder-id http://dx.doi.org/10.13039/501100007601, Horizon 2020;

Award ID: 777111

Funded by: funder-id http://dx.doi.org/10.13039/501100003008, Ministry of Higher Education, Egypt;

Award ID: 40463/2019

Funded by: funder-id http://dx.doi.org/10.13039/501100002347, Bundesministerium für Bildung und Forschung;

Award ID: 01EJ2205D

References

Sollie Annet, Sijmons Rolf H., Lindhout Dick, van der Ploeg Ans T., Rubio Gozalbo M. Estela, Smit G. Peter A., Verheijen Frans, Waterham Hans R., van Weely Sonja, Wijburg Frits A., Wijburg Rudolph, Visser Gepke. A New Coding System for Metabolic Disorders Demonstrates Gaps in the International Disease Classifications ICD-10 and SNOMED-CT, Which Can Be Barriers to Genotype-Phenotype Data Sharing. Human Mutation. Vol. 34(7):967–973. 2013. Hindawi Limited. [Cross Ref]

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[1] Sollie Annet, Sijmons Rolf H., Lindhout Dick, van der Ploeg Ans T., Rubio Gozalbo M. Estela, Smit G. Peter A., Verheijen Frans, Waterham Hans R., van Weely Sonja, Wijburg Frits A., Wijburg Rudolph, Visser Gepke. A New Coding System for Metabolic Disorders Demonstrates Gaps in the International Disease Classifications ICD-10 and SNOMED-CT, Which Can Be Barriers to Genotype-Phenotype Data Sharing. Human Mutation. Vol. 34(7):967–973. 2013. Hindawi Limited. [Cross Ref]