Presentation: Biological Data Integration and Application for Personalized Cancer Treatment

Biological Data Integration and Application for Personalized Cancer Treatment

Hyungyong Kim, Jaeyoung Shim

Audience level:: Intermediate
Category:: Industry Uses

Description

Personalized approach is important in the area of cancer treatment. We constructed a data-warehouse which integrates 3 ontologies and 4 clinical databases semantically using Django's ORM. For the clinical use, a mobile web application was developed so that patients can get their personal pharmaceutical information about cancer therapy.

Abstract

There is a plenty of public resources of biophysical, clinical, and pharmaceutical information about cancer and its therapy. It's a big challenge to integrate these effectively. Besides, for competent cancer treatment, personalized approach is getting more importance.  

Here, a linkage approach between the data warehouse and mobile application was implemented using light-weight web framework, Django, for personalized cancer diagnosis and therapeutics. We constructed a knowledge-based data model using Django's object-relation mapping (ORM) in which the cancer-related informations from 3 ontologies, i.e. Gene Ontology, Disease Ontology, and ChEBI, and 4 clinical databases, i.e. 1000 Genomes, Comparative Toxicogenomics Database, ClinicalTrials, and DrugBank were utilized and semantically related. Using our data model, the integrated information such as related genes, their mutations, single nucleotide polymorphisms, clinical trials, and related drugs for given cancer types can be retrieved.  

In addition, a mobile application was devised for personal use which communicate with our data warehouse to retrieve customized information for cancer and more feasible drugs according to one's cancer type by entering one's personal genomic/diagnostic records.