The aim of the OBIND project is to develop a computerised system in the field of oncology that enables the aggregation and analysis of heterogeneous datasets, focusing on the study of interactions between different biological molecules that are altered in cancerous conditions, with a view to establishing a rational framework for the design of new therapies.

THE RESEARCH AND DEVELOPMENT PROJECT

The study of complex diseases, such as cancer, requires an integrated approach to data analysis. In addition to analysing the genes involved in the process of transforming normal cells into cancer cells (more than 500 have been identified), the study of tumour onset also requires the analysis of interactions between proteins, RNA and small molecules.

The pharmaceutical development of new specialised and personalised anti-cancer therapies is a highly complex process; the development of new chemical entities (NCEs), in fact, takes an average of 13 years at a cost of nearly one billion euros. Studying the behaviour of the entire network of molecular interactions allows us to predict the effects of a therapy on a broader scale than that of a single interaction. A prerequisite for such analysis is the consultation of specialised databases available online or at research institutions.

The challenges associated with analysing the data required for cancer research and the development of new drugs include the presence of vast quantities of biomedical data that are difficult to consult and manipulate, the fragmented nature of the data which prevents a comprehensive overview of the issues related to the disease of interest, and poor interoperability caused by a variety of formats or a lack of standardisation.

The research and development project aims to optimise:

• the selection of data useful for the study of the tumour pathologies of interest, through a semantic search engine linked to the main databases of proteomics, transcriptomics, interactomics, chemogenomics, structural biology and medicinal chemistry;
• the integrated analysis of different types of data, in order to identify biological interactions between small molecules, RNA and proteins that influence, or could influence, the onset, progression and/or regression of the cancer;
• the exploitation of new statistical and computational approaches involved in data processing and of models for the integrated analysis of multiple data sources;
• the extraction of structural information from patent-protected molecules (scaffolds) to be included in the design workflow for new therapies.

Partners

• Exprivia S.p.A. – lead partner
• University of Palermo
• Ri.MED Foundation
• Securproject
• OS2
• 2038 Innovation Company
• IRIB-CNR