Open AccessOpportunities and Challenges in Implementation of Multiparameter Single Cell Analysis Platforms for Clinical Translation
Author(s) -
Keating Susan M.,
Taylor D. Lansing,
Plant Anne L.,
Litwack E. David,
Kuhn Peter,
Greenspan Emily J.,
Hartshorn Christopher M.,
Sigman Caroline C.,
Kelloff Gary J.,
Chang David D.,
Friberg Gregory,
Lee Jerry S. H.,
Kuida Keisuke
Publication year - 2018
Publication title -
clinical and translational science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.303
H-Index - 44
eISSN - 1752-8062
pISSN - 1752-8054
DOI - 10.1111/cts.12536
Subject(s) - government (linguistics) , translation (biology) , computer science , characterization (materials science) , medicine , data science , medical physics , nanotechnology , biology , materials science , philosophy , linguistics , biochemistry , messenger rna , gene
The high‐content interrogation of single cells with platforms optimized for the multiparameter characterization of cells in liquid and solid biopsy samples can enable characterization of heterogeneous populations of cells ex vivo . Doing so will advance the diagnosis, prognosis, and treatment of cancer and other diseases. However, it is important to understand the unique issues in resolving heterogeneity and variability at the single cell level before navigating the validation and regulatory requirements in order for these technologies to impact patient care. Since 2013, leading experts representing industry, academia, and government have been brought together as part of the Foundation for the National Institutes of Health (FNIH) Biomarkers Consortium to foster the potential of high‐content data integration for clinical translation.