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Cytomics and drug discovery
Author(s) -
Van Osta Peter,
Donck Kris Ver,
Bols Luc,
Geysen Johan
Publication year - 2006
Publication title -
cytometry part a
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.316
H-Index - 90
eISSN - 1552-4930
pISSN - 1552-4922
DOI - 10.1002/cyto.a.20236
Subject(s) - drug discovery , drug , computational biology , data science , computer science , medicine , biology , bioinformatics , pharmacology
Pharmaceutical companies try to develop new drugs that have a high success rate of reaching the market. However, current disease models lack a strong correlation to clinical reality, because of the underestimation of the complexity and variability of clinical disease processes. This leads to high attrition rates late in drug development and soaring costs. Improvement of disease models is an important issue to reduce the high attrition rates in drug development. Using cell‐based disease models, which should take into account the molecular diversity of the human cytome, will improve the predictive value of drug discovery. © 2006 International Society for Analytical Cytology