Data Management System

Tender description

The Medicines Discovery Catapult is a new, national centre of applied Research and Development expertise to promote and support innovative, fast-to-patient drug discovery in the UK through collaborative projects across the community. Medicines Discovery Catapult works with biopharma companies of all sizes, translational researchers, technology experts, patient groups and the contract research and finance sectors to help transform great ideas into commercial products and services for the wider health and wealth of the country. By developing and validating new ways of discovering new medicines, and promoting key talent and expertise across sectors, Medicines Discovery Catapult can help the UK maintain its heritage position as a global leader in this key industry. The Medicines Discovery Catapult will work with industry, academic teams, technology experts, charities, regulators and others, to develop new approaches for the discovery and early development of new medicines helping to transform ideas into commercial products and services. The Medicines Discovery Catapult also provides expertise to support small and developing businesses, as well as working closely with larger biomedical companies and contract research organisations. This procurement is for a data management system required for the handling of laboratory data within the Medicines Discovery Catapult (MDC) Limited at multiple sites with collaborative partrners. The requirement is for a software-based laboratory data management system with features that support a modern laboratory's operations is required. MDC requires the system to be flexible and upgradeable to manage large sets of structured data from many types of laboratory instruments. The system will be used by multiple operators requiring data storage, visualisation, analysis and data comparisons working both internally and externally with a defined access level. Key features of the data management system include, but are not limited to: • Capture, storage and integration of raw and refined experimental data from many lab technologies and platforms • Analysis of the captured data, following association with sample identifiers, to derive statistically robust and biologically meaningful parameters eg. Potency • Visualization to show biological effects eg. Mechanism of action, gene expression change profiles • Analytics to quantitate biological response • Project sharing; • Data integration and exchange eg. A central MDC data warehouse. • Ease of deployment across multiple MDC sites and to collavorative partners; • Intuitive and easy to use • Expandable and upgradeable • Automatic data back up processes