Deep Machine Learning + big data (medical & "omics") = precision medicine
This is how we clarify clinical choices.
allows for additional products development and necessary for future business growth
capture patient views of how side-effects impact their life, informing medical decisions
Protection of all clinical and genomic information meets current regulatory standards. We conduct continuous quality review for updating new regulations along with external threats to prevent unauthorized access (public website cannot access personal health or genomic information)
Comprehensive, state-of-the-art machine learning
Started with millions of SNPs per person along with clinical outcome of side effects.
Identified SNP networks have <100 SNPs/side effect
Each side effect per regimen has a unique, predictive SNP network with accuracy rates >90% in training set; validation set accuracy rates with small sample sizes yet still >70%
Mapping each SNP in the network for each side effect to its known genes & associated biologic pathways demonstrated biologic validity.
Proprietary code driving custom analytics
Allows incorporation of new machine learning methods (including deep learning techniques) into our models rather than waiting for new releases or updates of “off the shelf” computing solutions
Facilitates more rapid product cycle development
Analytic cloud platform
Tailored to Inform Genomics specific business needs