canSAR is an integrated knowledge-base that brings together multidisciplinary data across biology, chemistry, pharmacology, structural biology, cellular networks and clinical annotations, and applies machine learning approaches to provide drug-discovery useful predictions.
canSAR’s goal is to enable cancer translational research and drug discovery through providing this knowledge to researchers from across different disciplines. It provides a single information portal to answer complex multi-disciplinary questions including - among many others: what is known about a protein, in which cancers is it expressed or mutated and what chemical tools and cell line models can be used to experimentally probe its activity? What is known about a drug, its cellular sensitivity profile and what proteins is it known to bind that may explain unusual bioactivity?
please contact the ICR media office on 0207 153 5380 if you have publicity or media related queries.
canSAR works on Firefox, Chrome and Safari. We do not support Internet Explorer as it is non-standards compliant.
To view statistics of canSAR data please refer to the Data Sources. Data Sources.
canSAR is funded through the Cancer Research UK core funding to the Cancer Research UK Cancer Therapeutics Unit at the Institute of Cancer Research, grant number C309/A11566 (previously C309/A8274).
Thanks to all our collaborators and data providers especially the following:
canSAR is developed by the Computational Biology and Chemogenomic team at the Cancer Research UK Cancer Therapeutics Unit. We thank other colleagues and team members, past and present, for their contributions, especially: Prof. Paul Workman, Parisa Razaz, Costas Mitsopoulos, Mishal Patel and Mark Halling-Brown.