Pharmacogenomics.
Until now, truly predictive GxEs were elusive:
GxEs are complex. Tens, hundreds, even thousands of SNPs (Single Nucleotide Polymorphisms) can be significant in predicting each interaction.
Current methodologies, such as genome-wide associations (GWAS), miss so many SNPS that they cannot predict response for most GxEs.
Genteract’s new machine learning technology finds a much greater fraction of the SNPs in each GxE and generates accurate GxE predictions.
Conventional Analysis
Traditional techniques find no significant change in this population’s phenotype with increasing exposure to a drug or other environmental factor.
Genteract Analysis
Genteract’s novel unsupervised analytical systems biology methodology detects genetically-defined sub-groups within the population who respond differently to the drug or other environmental factor, and discovers all the SNPs that are significant in this difference.
Contact us for more information, including analysis capabilities and research results,
GxE Applications
Pharmacogenomics Applications,
Enabled by High Precision GxE Predictions
Drug Response Prediction
Deliver significant cost savings for payers by decreasing prescriptions for drugs that patients won’t respond to, and recommending drugs most likely to be beneficial.
Drug Repositioning
Identify genetically-defined patient subgroups who respond differently to drugs, opening up new indications for existing drugs
Drug Approvals
Identify genetically defined patient subgroups who are strong responders, enabling FDA approval of drugs that fail phase III due to lack of broad efficaciousness.
Cancer Treatment
Utilize tumor and patient genomes simultaneously to select therapeutic agents most likely to produce a strong response with minimal side effects.
Partner with Us
The clinical trial or EMR data you already have may have massive hidden value that Genteract Analysis can unlock.
Contact us now to discuss a no-obligation analysis of your data to create GxE predictions with cross-validation.