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TUESDAY, JUNE 9
7:00 am – 6:00 pm Registration Open
7:30- 8:15 am Breakfast Presentation
(Sponsorship Opportunity Available)
Sponsored by
12:30 pm Next-Generation siRNAs: Combining Support Vector Machine Learning With Novel Chemical Modifications for More Consistent siRNA Performance in High-Content Screens
Susan Magdaleno, Ph.D., Senior Manager, Scientists, Applied Biosystems
Current RNAi technologies often yield confusing results in siRNA screens due to inconsistent or incomplete knock-down of the intended mRNA target, knock-down of unintended mRNAs and/or siRNA toxicity. Our newest siRNA technology alleviates these problems by developing an innovative algorithm for greater predictability and by incorporating chemical modifications to enhance specific properties of the siRNAs on a genome-wide level. A classification strategy using support vector machine (SVM) was developed to improve the ability to predict the highest potency siRNAs. A second SVM classifier was developed to predict and eliminate 80% of the potentially toxic siRNA. This new algorithm can identify siRNAs that can produce maximum mRNA knock-down at 5-100x lower siRNA concentration than previous siRNAs technologies. The algorithm was used as a foundation for screening and identifying the optimal chemical modification to enhance siRNA specificity and performance in cell based assays. Greater than 20 siRNA modification patterns were screened with three different chemistries in two high-content microscopy-based cell assays. The optimal modification gave the most benefit by removing the off-target phenotypes from a previously identified collection of “problematic” siRNAs while maintaining the desired expected phentotype in the two cell-based assays. The new SVM algorithm combined with the chemical modifications was developed into a genome-wide collection of siRNAs called Silencer® Select. Using Silencer® Select, RNAi screens can be performed at lower concentrations while maintaining potency and the enhanced specificity will provide greater confidence in screening results.
1:00 pm Presentation 2 (Opportunity Available) or Lunch on Your Own
In this session the speakers will each present case studies to elaborate on the do’s and don’ts for testing and validating various RNAi delivery systems, specifically forin vitro applications.
Participants:
Paul Kassner, Ph.D., Principal Scientist, Amgen Inc.
Shane Marine, Ph.D., Automated Biotechnology, Merck & Co., Inc.
Namjin Chung, Ph.D., Senior Research Investigator, Applied Genomics, Bristol-Myers Squibb Co.
David Davis, Ph.D., Scientist, Molecular Biology, Genentech Inc.
9:50 Networking Coffee Break Poster and Exhibit Viewing
11:15 Panel Discussion: Criteria for Testing and Validating Systems for RNAi Delivery
12:15pm Close of Morning Session
1:30 Close of Tackling RNAi Delivery and RNAi for Functional Screens Conferences