South Africa's Centre for Proteomic and Genomic Research has recently used Affymetrix arrays in a project with Malaysian pharmacogenomics form Simugen to try to predict human toxicity early in the drug-development process.
The project provided data that Kuala Lumpur-based Simugen used to design its pharmacogenomics software, HT-Stream, which it launched this month.
CPGR Managing Director Reinhard Hiller told BioArray News this week that the Cape Town, South Africa-based center is using its genomics resources, including its microarray platforms, to attract new partners that are interested in toxicogenomics screening.
"We are now aiming at positioning part of the organization as a specialist toxicogenomics service provider using a combination of in vitro cell culture models, our 'omics capabilities, and bio-computational solutions, including Simugen’s new HT-Stream software," he said.
Founded as a non-profit in 2006, CPGR is an integrated core-technology facility that offers a variety of array-based applications, including gene, microRNA, and protein-expression profiling, comparative genomic hybridization, and ChIP-on-chip. It also uses non-array technologies, such as real-time -PCR-based assays and mass spectrometry.
As part of its work with Simugen, CPGR performed a compound-screening study aimed at generating an RNA-signature algorithm to model drug toxicity of known compounds, and to predict toxicity in lead compounds more efficiently.
As part of the study, cDNA samples were processed on 63 Affymetrix GeneST arrays to determine compound-related RNA expression at the gene level. Additionally, more than 70,000 quantitative RT-PCR assays were carried out to study toxicology effects. The data was used to develop algorithms that were later built into HT-Stream.
Hiller said HT-Stream is meant to be used in conjunction with an in vitro cell culture model system that uses the hepaRG liver cell line for prioritizing lead compounds in drug development. CPGR used Affy GeneST arrays in the study because of their "convenient workflow and protocol with very low RNA input amount requirements" and "comparatively low costs" compared to other platforms, he said.