Data: The central component of precision medicine

Data: The central component of precision medicine

Publication date: Sep 10, 2019

Realizing the full potential of precision medicine starts with finding better ways to collect, share and make decisions based on data.

There are a number of daunting challenges that must be overcome collection For each relevant subgroup, data must be collected from thousands of patients, a huge task in itself.

Data Incompatibility The data needed to support precision medicine is currently siloed in a large number of incompatible systems.

To protect privacy, patient consent is mandatory before medical records can be shared, making data collection even more cumbersome.

For example, one New York City hospital network now operates a clinic that provides patient care but also conducts data science initiatives for populations as well as individuals.

Given the data tools available, and the dedication of so many research teams within the larger medical ecosystem, it is inevitable that precision medicine will flourish over time.

Concepts Keywords
Biomarkers Healthcare industry
Data Central Genomics
Ecosystem City hospital network
Genetic
Genome
Healthcare Industry
Hospital Network
Insurance
Pharmaceutical Companies
Pharmaceutical Company
Physician
Privacy
Regulatory Compliance
Subgroup

Semantics

Type Source Name
gene UNIPROT MET
drug DRUGBANK Methionine
gene UNIPROT SLTM
gene UNIPROT ALG3
gene UNIPROT NR4A2
disease MESH privacy
gene UNIPROT LARGE1
gene UNIPROT KCNK3
disease MESH uncertainty
disease MESH diagnoses
drug DRUGBANK Tropicamide
disease DOID cancer
disease MESH cancer
gene UNIPROT IMPACT
disease MESH lifestyle

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