Dr. Peter Ansell discusses the use of novel RNA-based gene expression profiling technologies for clinical and preclinical oncology research.
The ability to predict the cancer treatment for each individual patient is one of the most pivotal goals of oncology precision medicine. To accomplish this, scientists must gain an improved understanding of the biology driving each patient’s tumor. Differential gene expression can identify which molecular pathways are aberrantly regulated and thereby inform which treatment will be most effective.
Often such studies are limited due to sample size or quality issues, long turnaround times for lab processing, difficulty in deciphering the data, and insufficient reproducibility for an eventual companion diagnostic test.
In this talk, Dr. Peter Ansell from Abbvie discusses how he and his team overcame some of these challenges using novel technologies available on the market. He presents a case study to demonstrate the utility of such technologies and their benefits over traditional gene expression profiling methods. Lastly, he discusses the future of biomarker-based treatments for oncology patients and the impact HTG is making in the field.
Key Topics Include:
- Overview of advances in RNA-based gene expression profiling
- Introduction to ultra-efficient gene expression profiling (GEP) technology and its importance in maximizing reliable information while conserving precious samples
- Evaluation of the utility of ultra-efficient GEP in real-world applications, such as for clinical and preclinical oncology research
- Discussion about the benefits of novel profiling technologies compared to traditional methods
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Scientific Director and Research Fellow
Precision Medicine, Oncology
Senior Vice President
Research & Development