Identifying and validating new targets in order to overcome resistance to oncology treatments
Artificial intelligence (AI) is not a goal in itself, but rather a powerful technology to make Drug Discovery faster and more reliable.
The OncoSNIPER technology module embodies the core scientific competence of the “Study” activity. It is designed to identify signatures enabling the stratification of patient populations resistant to anti-cancer treatments. These signatures are then translated into therapeutic targets.
The OncoSNIPER platform integrates public, private, and proprietary data sources (from projects such as IMODI, OncoSNIPE®, etc.) and uses various artificial intelligence technologies (machine learning, deep learning, computer vision, natural language processing, etc.).
OncoSNIPER also integrates the knowledge of our Drug Discovery experts into the algorithms themselves, enabling a hybrid AI approach that combines the advantages of purely data-driven and expert system approaches.
OncoSNIPER also benefits from Oncodesign Services’ experimental capabilities, allowing us to generate ad hoc data and validate any results identified in silico at the preclinical stage. OPM thus identifies and selects targets based on an in silico scoring process and experimentation.
OncoSNIPER allows us to develop partnerships to discover new targets and biomarkers and to conclude licensing agreements on pre-identified therapeutic targets with pharmaceutical and biotechnological companies.
Our powerful databases: IMODI® and OncoSNIPE®
IMODI®: the missing link between cells and patients
IMODI® is a precision medicine cluster that brought together scientific experts from 18 public and private organisations, with an initial plan for eight years and a private and public investment of €41 million.
Designed and coordinated by Oncodesign as part of a PIA2 PSPC [a French Government granted R&D program], the IMODI® cluster has collaborated in 4 areas of research:
- Developing new experimental cancer models based on fully characterised, complete tumour specimens (data on the patient, biology, genomics, pharmacology, biobanking, etc.) xenografted on mice and immunodeficient rats.
- Modelling human tumour microenvironments in humanised transgenic mice
- Demonstrating the predictability of models using bioinformatics tools (databases and data mining)
- Studying the role of the intestinal microbiota in cancer
IMODI® capitalizes on medical and research skills around 10 key cancers: prostate, colon, breast, pancreatic, ovarian, lung, and liver cancers, as well as lymphoma, acute myeloid leukemia, and myeloma.
OncoSNIPE®: guide your therapeutic solutions for patients refractory to cancer treatment
The OncoSNIPE® programme aims to stratify and characterise populations of patients refractory to cancer treatments.
Based on bioinformatics, artificial intelligence, statistical learning, and semantic enrichment approaches, OncoSNIPE® guides and predicts a patient’s potential to benefit from treatment, enables the discovery of new therapeutic targets, and reduces treatment failure rates.
OncoSNIPE® is an 8-year PIA3 PSPC program run in partnership with Acobiom, Coexya and Expert AI, 19 French hospitals (CLCCs, CHUs and CHs) and the Unicancer federation…
The OncoSNIPE® database is powered by the results of a clinical trial (NCT04548960) designed, managed and promoted by OPM.
Clinical, biological, multi-omics and imaging data are collected longitudinally from over 800 chemo-naive patients with breast, pancreatic and lung cancers, who are followed for two years for pancreatic and lung cancers, and five years for breast cancers, as part of their therapeutic management.
We are able to provide new, validated therapeutic targets to our precision medicine platform to support our own therapeutic research and that of our partners.