BIOMARKER COMPOSITION FOR DETERMINING CANCER DRUG REACTIVITY, METHOD FOR DETERMINING CANCER DRUG REACTIVITY USING BIOMARKER COMPOSITION, AND DIAGNOSTIC CHIP FOR DETECTING BIOMARKER COMPOSITION FOR DETERMINING CANCER DRUG REACTIVITY

摘要

The present invention relates to genetic biomarker labeling scan (GBLscan) which is a drug indication and reaction prediction system and method as a novel learning model, capable of reliably predicting drug reactivity by binding analysis of a drugs molecular profile after transforming specific genetic variation fingerprints related to diseases including cancer into a haplotype with functional information. The present invention comprises: a learning module that learns a reactivity correlation of constituent information constituting a drug to genetic information contained in a genome from collected learning information by linear regression and deep learning machine learning; a prediction module that receives analysis information and calculates a prediction result of drug reactivity to the genome included in the analysis information; and a storage module that stores a reactivity prediction algorithm learned by the learning module, wherein the learning information is drug reactivity information for in vitro cell line and in vivo clinical studies. According to the present invention, it is possible to predict the degree of drug reactivity with the genome whose pharmacological effect is unknown from the results of drug reactivity to the genome collected from clinical trials.;COPYRIGHT KIPO 2020