Terry Hermiston, Ph.D.
Vice President, US Biologics Research Site Head, US Innovation Center Bayer Healthcare, USA
ColoAd1 – An oncolytic adenovirus derived by directed evolution
Attempts at developing oncolytic viruses have been primarily based on rational design. However, this approach has been met with limited success. An alternative approach employs directed evolution as a means of producing highly selective and potent anticancer viruses. In this method, viruses are grown under conditions that enrich and maximize viral diversity and then passaged under conditions meant to mimic those encountered in the human cancer microenvironment. Using the “Directed Evolution” methodology, we have generated ColoAd1, a novel chimeric oncolytic adenovirus. In vitro, this virus demonstrated a >2 log increase in both potency and selectivity when compared to ONYX-015 on colon cancer cells. These results were further supported by in vivo and ex vivo studies. Importantly, these results have validated this methodology as a new general approach for deriving clinically-relevant, highly potent anti-cancer virotherapies. This virus is currently in clinical trials as a novel treatment for cancer.
Rajgopal Srinivasan, Ph.D.
Principal Scientist & Head Bio IT R&D, TCS Innovation Labs, India
Interpretation of Genomic Variation – Identifying Rare Variations Leading to Disease
Genome sequencing technologies are generating an abundance of data on human genetic variations. A big challenge lies in interpreting the functional relevance of such variations, especially in clinical settings. A first step in understanding the clinical relevance of genetic variations is to annotate the variants for region of occurrence, degree of conservation both within and across species, pattern of variation across related individuals, novelty of the variation and know effects of related variations. Several tools already exist for this purpose. However, these tools have their strengths and weaknesses. A second issue is the development of algorithms, which, given a rich annotation of variants are able to prioritize the variants as being relevant to the phenotype under investigation.
In my talk I will detail work that has been done in our labs to address both of the above problems. I will also illustrate the application of these tools that helped identify a rare mutation in the ATM gene leading to a diagnosis of AT in two infants.