Minimal information for Chemosensitivity assays
Chemosensitivity assays (drug sensitivity screens) have been increasingly used for preclinical drug discovery and clinical trial optimization. However, typical drug sensitivity assays are lack of sufficient annotation and standardization to make the data FAIR (Findable, Accessible, Interoperable and Reusable), resulting in a poor replicability as well as limited impact on drug discovery. To address these issues, we have recently launched MICHA (Minimal information for Chemosensitivity Assays), a web server at https://micha-protocol.org/ for the annotation of drug sensitivity screens for cell lines and patient-derived samples, including 1) compounds 2) specimens 3) assay protocols and 4) quality control and data processing methods.
MICHA is a user-driven project that allows the drug discovery research community to adopt advanced data standardization tools. We will first develop FAIR-compliant data resources by delivering identifier standards, ontologies and ontology services as well as content standards. The project will ensure drug sensitivity data are FAIR to support the downstream analysis and ultimately clinical translation.
The aim is to determine the ‘minimal’ information that:
MICHA is not to standardize the protocols among different labs; rather, it allows the annotation of these versatile protocols FAIR (Findable, Accessible, Interoperable and Reusable).
MICHA provides a webserver to automatically extracts compounds, cell line information from public databases, and generate complete reports. Target users are biologists, chemists, translational researchers, assay developers, data scientists, and pharmaceutical companies.
MICHA consists from the following components:
We are part of EATRIS (European Infrastructure for Translation Medicine), whose aim is to support researchers in developing their biomedical discoveries into novel translational tools and interventions for better health outcomes for society. Together with EATRIS, we are also involved in EOSC-Life project, whose aim is to populate EOSC with the scientific data resources and computational tools and drive usage by 1.7M researchers from Europe.