Clinical Trials News: Latest developments in the world of clinical trials in cancer
ACGT aims to provide a Europe-wide infrastructure to support multi-centric, postgenomic clinical trials on cancer, and thus, enable the smooth and prompt transfer of laboratory findings to the clinical management and treatment of patients. ACGT is then a mean to facilitate bench-to-bed communication in Cancer Management. To achieve this communication aim, semantic integration of diverse biomedical databases is needed. Within the ACGT framework, Integration of data is achieved by means of a mediator system that is based on an ontology [1].
Ontologies are a major trend in IT systems. They provide a formalized scheme of reference for different data resources and different users. A basic objective of ontologies is to enable better semantic integration of data, not only between humans, but also facilitating human-machine communication. Thus, ontologies are one strategy within the huge field of Artificial Intelligence. It is important to note that with respect to different terms and languages used, ontologies are completely neutral. Since ontologies aim at providing a formal definition of a class within a specific domain, it is possible to build an ontology in a completely language-neutral way. There is no need to attach any natural language term to the classes. Nevertheless, it can be done, since naming the classes with natural terms facilitates the development of the ontology and fosters its transparency for users.
After reviewing existing terminologies and taxonomies a new ontology was hand-tailored for the specific use within the ACGT system. This representational artefact is called the ACGT Master Ontology, (ACGT MO).
The scope of the ACGT MO is cancer research and management. Its initial version consists of 1300 classes and is written in the Web Ontology Language, OWL. OWL was developed specifically to develop ontologies. Even if based on the RDF syntax it exceeds the expressiveness of the RDF schema by far. OWL exists in three sublanguages, one of which is OWL DL. The latter is the one completely computable among sublanguages of OWL. In effect, this means that all conclusions drawn from the ontology are guaranteed to be computable [2].
The ACGT MO does not only represent classes as linked via the basic taxonomical relation, the "is_a"-relation or subsumption, but connects them via other semantic relations. Many existing categorizations focus on the classes or types of things in a given domain, health care or cancer management for instance. These representations might give a hierarchy of those entities, which will basically look like a taxonomy, e.g. in biology. But it is obvious that only representing other relations between classes, e.g. "x is part of y", "z is adjacent to u", "a is prior to b", can lead to a comprehensive representation of the phenomena occurring in medicine.
Even though the decision was taken to create a new resource for ACGT, the development built highly on pre-existing material. The relations in the ACGT MO provide an excellent example, since we re-used relations already present in other ontologies or Knowledge Management Systems. For one, we imported an ontology of biomedical relations that exists within a collaborating group for ontology based engineering called Open Biomedical Ontologies (OBO) Foundry [3]. The OBO Foundry presents a library of interoperable biomedical ontologies, all subject to specified criteria. It is the aim of the consortium to make the ACGT MO a member of this initiative and thus, ensure the quality of the ontology development.
The ACGT MO is not only a representation of biomedical entities and processes. The scope of the ACGT project includes scientific observation by different well-established, standardized methods stemming both from clinical research and molecular biology. In order to cover these areas the ACGT MO relied on CIDOC Conceptual Reference Model (CRM) [4], a formal reference for cultural heritage documentation. The CIDOC CRM is official standard ISO 21127:2006.
As mentioned above the mediator system will exploit the MO to integrate pre-existing data into the semantic schema of the ACGT system. This process is basically part of well-established integration strategies. Besides this use of the ontology ACGT aims to provide a completely novel tool to collect data, which are already in accordance with the ontology.
In the past, the method of choice to bring data in accordance with terminology resources was to code it with expressions from the terminology in question. Coding, however, has proved to be a source of mistake to a huge extend. Therefore, ACGT aims at providing an Ontology-based Clinical Trial Management System (ObTiMA), which will annotate data with terms referring to the ontology the very moment the data are created. The huge number of relations given in the ACGT MO is necessary to provide a representation of clinical reality and thus, enable, for instance, the creation of forms necessary in conducting clinical trials [5].
Supporting the two strategies mentioned above the ACGT MO provides the necessary reference framework for all data that is handled in the system. The ontology-based approach ensures that data can be disseminated over the borders of different databases and different biomedical disciplines, even over the borders between different real-world languages.
Mathias Brochhausen, University of Saarland
[1] Tsiknakis M, Brochhausen M, Nabrzyski J, Pucaski L, Potamias G, Desmedt C, Kafetzopoulos D, "A semantic grid infrastructure enabling integrated access and analysis of multilevel biomedical data in support of post-genomic clinical trials on Cancer". IEEE Transactions on Information Technology in B i ome d i c i n e , (Special issue on Bio-Grids) March 2008, Vol. 12, No. 2, 205-217.
[2] www.w3.org/TR/owl-features
[3] www.obofoundry.org
[4] cidoc.ics.forth.gr
[5] Brochhausen M, Weiler G, Cocos C, Stenzhorn H, Graf, Doerr M, Tsiknakis M, "The ACGT Master Ontology on Cancer - a New Terminology Source for Oncological Practice". Proceedings of the 21st IEEE International Symposium on Computer-Based Medical Systems, Jyv?skyl?, Finland, June 17-19, 2008. 2008, 324-329..