Towards a national strategy for digital pathology in Switzerland.

Janowczyk, Andrew; Baumhoer, Daniel; Dirnhofer, Stefan; Grobholz, Rainer; Kipar, Anja; de Leval, Laurence; Merkler, Doron; Michielin, Olivier; Moch, Holger; Perren, Aurel; Rottenberg, Sven; Rubbia-Brandt, Laura; Rubin, Mark A; Sempoux, Christine; Tolnay, Markus; Zlobec, Inti; Koelzer, Viktor Hendrik (2022). Towards a national strategy for digital pathology in Switzerland. Virchows Archiv, 481(4), pp. 647-652. Springer 10.1007/s00428-022-03345-0

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Precision medicine is entering a new era of digital diagnostics; the availability of integrated digital pathology (DP) and structured clinical datasets has the potential to become a key catalyst for biomedical research, education and business development. In Europe, national programs for sharing of this data will be crucial for the development, testing, and validation of machine learning-enabled tools supporting clinical decision-making. Here, the Swiss Digital Pathology Consortium (SDiPath) discusses the creation of a Swiss Digital Pathology Infrastructure (SDPI), which aims to develop a unified national DP network bringing together the Swiss Personalized Health Network (SPHN) with Swiss university hospitals and subsequent inclusion of cantonal and private institutions. This effort builds on existing developments for the national implementation of structured pathology reporting. Opening this national infrastructure and data to international researchers in a sequential rollout phase can enable the large-scale integration of health data and pooling of resources for research purposes and clinical trials. Therefore, the concept of a SDPI directly synergizes with the priorities of the European Commission communication on the digital transformation of healthcare on an international level, and with the aims of the Swiss State Secretariat for Economic Affairs (SECO) for advancing research and innovation in the digitalization domain. SDPI directly addresses the needs of existing national and international research programs in neoplastic and non-neoplastic diseases by providing unprecedented access to well-curated clinicopathological datasets for the development and implementation of novel integrative methods for analysis of clinical outcomes and treatment response. In conclusion, a SDPI would facilitate and strengthen inter-institutional collaboration in technology, clinical development, business and research at a national and international scale, promoting improved patient care via precision medicine.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > BioMedical Research (DBMR) > DBMR Forschung Mu35 > Forschungsgruppe Präzisionsonkologie
04 Faculty of Medicine > Pre-clinic Human Medicine > BioMedical Research (DBMR) > DBMR Forschung Mu35 > Forschungsgruppe Präzisionsonkologie

04 Faculty of Medicine > Service Sector > Institute of Pathology
05 Veterinary Medicine > Department of Infectious Diseases and Pathobiology (DIP) > Institute of Animal Pathology

UniBE Contributor:

Perren, Aurel, Rottenberg, Sven, Rubin, Mark Andrew, Zlobec, Inti

Subjects:

500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health
600 Technology > 630 Agriculture

ISSN:

0945-6317

Publisher:

Springer

Language:

English

Submitter:

Pubmed Import

Date Deposited:

30 May 2022 08:13

Last Modified:

05 Dec 2022 16:20

Publisher DOI:

10.1007/s00428-022-03345-0

PubMed ID:

35622144

Uncontrolled Keywords:

Artificial intelligence Biomedical research Image analysis Pathology Precision medicine

BORIS DOI:

10.48350/170305

URI:

https://boris.unibe.ch/id/eprint/170305

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