Abstract |
A workshop on research gaps and opportunities for Precision Medicine in Pancreatic Disease was sponsored by the National Institute of Diabetes and Digestive Kidney Diseases on July 24, 2019, in Pittsburgh. The workshop included an overview lecture on precision medicine in cancer and 4 sessions: (1) general considerations for the application of bioinformatics and artificial intelligence; (2) omics, the combination of risk factors and biomarkers; (3) precision imaging; and (4) gaps, barriers, and needs to move from precision to personalized medicine for pancreatic disease. Current precision medicine approaches and tools were reviewed, and participants identified knowledge gaps and research needs that hinder bringing precision medicine to pancreatic diseases. Most critical were (a) multicenter efforts to collect large-scale patient data sets from multiple data streams in the context of environmental and social factors; (b) new information systems that can collect, annotate, and quantify data to inform disease mechanisms; (c) novel prospective clinical trial designs to test and improve therapies; and (d) a framework for measuring and assessing the value of proposed approaches to the health care system. With these advances, precision medicine can identify patients early in the course of their pancreatic disease and prevent progression to chronic or fatal illness.
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Authors | Mark E Lowe, Dana K Andersen, Richard M Caprioli, Jyoti Choudhary, Zobeida Cruz-Monserrate, Anil K Dasyam, Christopher E Forsmark, Fred S Gorelick, Joe W Gray, Mark Haupt, Kimberly A Kelly, Kenneth P Olive, Sylvia K Plevritis, Noa Rappaport, Holger R Roth, Hanno Steen, S Joshua Swamidass, Temel Tirkes, Aliye Uc, Kirill Veselkov, David C Whitcomb, Aida Habtezion |
Journal | Pancreas
(Pancreas)
2019 Nov/Dec
Vol. 48
Issue 10
Pg. 1250-1258
ISSN: 1536-4828 [Electronic] United States |
PMID | 31688587
(Publication Type: Journal Article, Research Support, N.I.H., Extramural)
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Chemical References |
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Topics |
- Biomarkers
- Biomedical Research
- Computational Biology
- Datasets as Topic
- Deep Learning
- Humans
- Metabolomics
- Pancreatic Diseases
(diagnosis, etiology, therapy)
- Precision Medicine
- Research
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