Reimagining CRISPR Editing
Empowering scientists at the forefront of the gene
editing revolution with the insights needed to realize the full potential of CRISPR.
CRISPR QC was created to assist scientists in gene therapy and agtech companies to advance their science and bring products to market quicker by providing predictive insights and quality control metrics.
We recognize the limitations of older technologies in providing practical, effective, and timely information for optimizing and resolving issues in CRISPR editing.
To address this, we have developed our CRISPR Analytics Platform with the unique capabilities of CRISPR-Chip and through deliberate collaboration with CRISPR experts.
Case Study:
gRNA Selection
PROBLEM
Established In-silico models failed to accurately predict outcomes - costing the customer weeks of lost work.
DATA
Comparative analysis of gRNA activity to identify highest-performing candidates; gRNA#39 demonstrated a clear separation from control
CONCLUSION
In this study, gRNA#39 showed the strongest performance and should be selected as the primary gRNA candidate
CUSTOMER OUTCOME
CRISPR QC identified the highest-performing gRNAs using our unique data, enabling them to achieve their desired gene edit.
Case Study:
Environmental Comparison
PROBLEM
Customer noticed the gRNA selections as predicted by in-silico algorithms didn't lead to optimal editing outcomes. Sequencing data only told them that the edits didn't occur, but not why.
DATA
Performance of various gRNAs was ranked in relation to their activity in differing pH levels. These graphs compare RNP response of 8 different gRNAs at three different pH levels.
CONCLUSION
pH was determined to be a causal factor in their editing, something in-silico algorithms couldn't emulate.
CUSTOMER OUTCOME
Customer was able to use our in-vitro data to select effective gRNAs. This greatly reduced the amount of cell work needed to produce a repeatable edit.
Case Study:
Multiplex Editing
PROBLEM
Customer facing challenges getting desired multiplex editing result, and wanted to investigate the cause.
DATA
CRISPR-Chip analysis was used to characterize the binding kinetics of different gRNAs to Cas.
CONCLUSION
CRISPR QC determined how different gRNAs compete for Cas binding sites. In this study, gRNA #5 proved to be the fastest displacer.
CUSTOMER OUTCOME
Insight provided by CRISPR QC has given the customer new factors to optimize their multiplex editing.
Case Study:
Cas Vendor Comparison
PROBLEM
Customer wanted to vet Cas9 vendors ahead of setting up a CRISPR editing program.
DATA
CRISPR QC ran analysis on the activity between the chosen vendors and between batches from each.
CONCLUSION
Vendor 1 showed the most consistent performance and was recommended as the supplier for customer editing.
CUSTOMER OUTCOME
Customer has been able to reduce variability in their outcomes by integrating regular Cas activity QC into their editing workflow.
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