New in vitro 12-cell line panel assay predicts anti-cancer drug activity

in vitro 12-cell Southern Research Institute today announced a new service offering - a novel in vitro 12-cell line panel assay designed to predict drug activity and improve the success rate of drugs tested in xenograft models. The assay was recently presented in a poster entitled, "A Quick and Cost Effective 12-Cell Line Panel Assay to Predict Drug Activity in Human Tumor Xenograft Models," at the 105^th Annual Meeting of the American Association for Cancer Research (AACR) in San Diego, California.

The presentation shows that Southern Research Institute has developed a cost effective in vitro model which will enable more compounds to be tested earlier in the drug development process, thereby increasing the success rate of potential therapeutics.  Additionally, this new approach harnesses the genetic diversity of all of Southern Research's cell line and xenograft models and several cancer histotypes to provide a more comprehensive screen and ultimately identify more potential drug candidates.

"We are pleased to report the availability of this encouraging assay.  The data used to assemble this assay has already been used in our continued progress in successfully advancing drug development through the efficient identification of drug candidates," said Andrew D. Penman, Ph.D., Vice President, Drug Development at Southern Research Institute.  "With this assay, we will be able to provide our clients with unique access and insights into data, expanding the potential of drugs to be utilized in other histotypes."

For the assay, genomic analysis was performed on 100 human tumor xenograft and cell line models from a large cross section of cancer histotypes. The genomic profiles obtained underwent Unsupervised Hierarchical Cluster Analysis resulting in 12 distinct clusters with similar genetic profiles. When a drug shows efficacy in one or more of these representative models, Southern can suggest additional in vitro and in vivo models with a similar genetic background, increasing the compounds chance of success in multiple models of varying histotypes. Success in multiple models and histotypes in turn increases the chance of success in the clinic.