Integromics® has announced that it has entered into a partnership with the Celgene Institute for Translational Research Europe (CITRE) and the Centre of Studies and Technical Research (CEIT), for the execution of SANSCRIPT, a project that aims at the development of new data analysis methods applied in clinical genomics studies.
Based on the strength of its R&D work, the new partnership has been awarded a EUR two million grant from the Spanish Government for the development of algorithms and statistical tools to identify alternative splicing events significantly related with disease associated biomarkers or therapeutic targets using RNA sequencing (RNA-seq).
Current algorithms, due to their intrinsic characteristics, have major limitations in characterizing gene alterations, which are frequently related to drug resistance and other phenotypes.
Therefore, it is essential to adapt the present methods developed for the new massive sequencing technologies to extract all their potential for development of diagnostic and prognostic tests, and drug discovery in the clinical and pharmaceutical environment.
The SANSCRIPT collaboration, coordinated by Integromics, has been designed to address these issues through the synergy between the engineers at CEIT, scientists at CITRE and the bioinformaticians from Integromics, which will undoubtedly accelerate the development of solutions for personalized medicine.
The new solutions will be validated for personalized-drug development processes where gene expression is essential to understand the differing responses to treatment.
The SANSCRIPT project represents an ideal opportunity for Integromics to reinforce its commitment to the development of software solutions for personalized medicine in the context of clinical studies.
“This is the first time that we can effectively work hand in hand with both an advanced software engineering team from a first class Technical Center and a research group from a leading biopharmaceutical corporation to cooperatively address an important gap”, said Eduardo González Couto, Chief Strategy Officer, Integromics. “The SANSCRIPT grant provides key financial support for us to spearhead the usage of NGS for drug development and help us make personalized medicine a reality.”
“Automated next-gen sequencers have increased the speed and reduced the cost of sequencing, making it possible to offer genetic testing to consumers. Producing the genomic data is not a problem anymore, while the analysis and interpretation of this data has become the ‘new hurdle’ ”, continues Dr. Gonzalez Couto.
Dr. Couto continued, “In order to identify the gene expression changes associated to sensitivity to treatment, including the detailed characterization of transcription isoforms for clinical usage, bioinformatics tools are crucially needed to design novel algorithms from the very beginning to be compatible with long reads from upcoming NGS technologies.”
"For us it is a pleasure to work with both a leading Spanish biosoftware company and a Pharma industry. This collaboration will help us to focus on a specific problem and provide a solution: algorithms that identify gene aberrations related to drug resistance in cancer” said Prof. Angel Rubio, Principal Investigator of the CEIT.
Prof. Rubio continued, “We are quite excited in working to improve the health: even though we have had other projects related with human health, they were not so ambitious as this one” concluded Prof. Rubio.
As genome sequencing continues to take footholds in diagnosis, prognosis and treatment of diseases, it is expected that the findings of the SANSCRIPT project, in terms of software and new methodologies, will enhance the reliability and significance of the next generation sequencing (NGS) technology in the pipelines of drug development and clinical genomics studies.
The results of SANSCRIPT will be made available through new releases of the Integromics’ OmicsOffice® software suite.
This will give clinical drug discovery scientists an immediate access to the fruits of the SANSCRIPT project, allowing them to apply new data analysis methods to their own studies.