GMV technology in eTRANSAFE’ s biomedical data platform

GMV is managing the technological biomedical data platform under eTRANSAFE, which will help to improve the development of new drugs and make them safer for patients
  • The objective of the project is to boost safety assessment in the development of new drugs by legacy data sharing
  • GMV is developing advanced data-integration infrastructure under open standards

GMV is managing the technological biomedical data platform under eTRANSAFE, which will help to improve the development of new drugs and make them safer for patients. The project kicked off in September 2017 and is due to run until August 2022; it is being financed by European funds (20 million euros) topped up by the European Federation of Pharmaceutical Industries and Associations to a total budget of nearly 40 million euros.

Drug safety assessment is a knowledge-intensive process that demands advancement in data handling methods and tools for facilitating data sharing, mining, analysis, and predictive modeling. This need is not restricted to any specific type of data and real advancement requires integrating information of different types and from different sources (e.g., publicly available biomedical knowledge, proprietary preclinical and clinical data, etc).

Up to now big Pharma has been loath to share their information on the toxicity of thousands of compounds as gleaned from animal testing. Most of this data remained backed up in private silos without any possibility of pooling it. As the project leaders explain “one of the objectives of eTRANSAFE is to carry out more efficient drug safety assessment tests, replacing part of the animal testing by the retrospective analysis of the evidence accumulated in the archives of the pharmaceutical industry”.

Adrián Rodrigo, GMV’s Business Solutions for Smart Health manager, points out that “working from data governance techniques the project is striving to organize and share all the available information of pharmaceutical firms to generate a critical mass of biomedical data that can then tap into big data technology and computational methods capable of drawing conclusions from all the information that would otherwise have gone unprocessed”. He goes on ”the idea is to make data combination possible for joint analysis, applying all data confidentiality methods within a secure platform”.

GMV is managing the technological biomedical data platform under eTRANSAFE, which will help to improve the development of new drugs and make them safer for patients

The project will develop in-silico tools for data mining, visualization, and prediction of potential toxicity, with specific attention to the assessment of the preclinical to clinical predictivity and the discovery of safety biomarkers.

A cutting-edge architecture and strategy for exchanging preclinical and clinical data from the diverse sources and for mining and integrating this data has been developed under the project. The structure is managed by a Knowledge Hub (eTRANSAFE-Hub), an online information platform that will centralize access to all these toxicological databases and sources. GMV will contribute to the development of this platform, acting as responsible technician of the system, seeing to the definition and coordination of the features to be included in each version, as will be seen in the final product, as well as documenting and delivering prioritized features to end users.

Benefits to pharmaceutical research

eTRANSAFE develops an integrative data infrastructure and innovative computational methods and tools that aim to drastically improve the feasibility and reliability of translational safety assessment during the drug development process. This infrastructure will be underpinned by development of open standards and robust policies widely accepted by stakeholders, including regulatory agencies and international organizations.

The direct project benefits will be more efficient trials, shorter research times and better toxicity results. Part of the project compares preclinical with clinical studies, in order to analyze how far the former can predict what will occur in humans. The conclusion drawn is that computational models or cells can provide a better forecast of what will happen in the human body. The project will therefore have a significant impact on how preclinical trials are conducted and how the industry designs them.

The project is driven by public-private participation of 8 academic institutions, 6 SMEs and 12 pharmaceutical firms. The industrial coordinators are the pharmaceutical companies Novartis and Bayer AG. GMV is in charge of developing an advanced data integration infrastructure, applying open standards and policies widely accepted by the parties, including regulatory agencies and international organizations.