ACGT Overview
Life sciences are currently at the center of an informational revolution. Dramatic changes are being registered as a consequence of the development of techniques and tools that allow the collection of biological information at an unprecedented level of detail and in extremely large quantities. Advanced technologies, such as high-throughput screening, genomics, proteomics and metabolomics, have resulted in data generation on a previously unknown scale.
The nature and amount of information now available open directions of research that were once in the realm of science fiction. Pharmacogenomics, diagnostics and drug target identification are just a few of the many areas that have the potential to use this information to change dramatically the scientific landscape in the life sciences.
During this informational revolution, the data gathering capabilities have greatly surpassed the data analysis techniques. If we were to imagine the Holy Grail of life sciences, we might envision a technology that would allow us to fully understand the data at the speed at which it is collected. Ideally, we would like knowledge manipulation to become tomorrow the way goods manufacturing is today: highly automated, producing more goods, of higher quality and in more cost effective manner than manual production. It is our belief that, in a sense, knowledge manipulation is now reaching its pre-industrial age. The explosive growth in the number of new and powerful technologies within proteomics and functional genomics can now produce massive amounts of data but using it to manufacture highly processed pieces of knowledge still requires elaborate involvement of skilled human experts to forge through small pieces of raw data one at a time. The ultimate challenge in coming years, we believe, will be to automate this knowledge discovery process.
The objective of the Advancing Clinico-Genomic Trials on Cancer (ACGT) project is to contribute to the resolution of these problems through the development of a unified technological infrastructure which will facilitate the seamless and secure access and analysis, of multi-level clinical and genomic data enriched with high-performing knowledge discovery operations and services in support of multi-centric, post-genomic clinical trials.
The project has conceived an overall architecture for an integrated biomedical sciences platform. The infrastructure being developed uses a common set of services and service registrations for the entire clinical trial on cancer community.
The project has set up cross-disciplinary task forces to propose guidelines concerning issues related to data sharing, for example legal, regulatory, ethical and intellectual property, and is developing enhanced standards for data protection in a web (grid) services environment.
In addition the project is developing:
- standards and models for exposing web services (semantics), scientific services, and the properties of data sources, datasets, scientific objects, and data elements;
- new, domain-specific ontologies, built on established theoretical foundations and taking into account current initiatives, existing standard data representation models, and reference ontologies;
- innovative and powerful data exploitation tools, for example multi-scale modelling and simulation, considering and integrating from the molecular to the systems biology level, and from the organ to the living organism level;
- standards for exposing the properties of local sources in a federated environment;
- a biomedical GRID infrastructure offering seamless mediation services for sharing data and data-processing methods and tools;
- advanced security tools including anonymisation and pseudonymisation of personal data according to European legal and ethical regulations;
- a Master Ontology on Cancer and use standard clinical and genomic ontologies and metadata for the semantic integration of heterogeneous databases;
- an ontology based Trial Builder for helping to easily set up new clinico-genomic trials, to collect clinical, research and administrative data, and to put researchers in the position to perform cross trial (meta) analysis;
- data-mining services in order to support and improve complex knowledge discovery processes;
- an easy to use workflow environment, so that biomedical researchers can easily design their "discovery workflows" and execute them securely on the grid.
A range of demonstrators, stemming from the user defined scenarios, together with these core set of components will enable us to both begin evaluation and gather additional and more concrete requirements from our users. We are currently focusing on the development of the core set of components up to a stage where they can effectively support in silico investigation. These will allow us to improve and refine the facilities of the ACGT services.
The information in this site will provide you with details on project activities, its workplan and its current activities. Please select the areas of interest to you, to obtain additional information.