Abstract: A method of detecting biomarkers using an artificial intelligence (AI) deep learning model for conversion data of nucleotide sequences and mutations of population genomes, the method including: collecting nucleotide sequences and mutations of population genomes; generating conversion data by reflecting mutations of diploid genomes in the collected nucleotide sequences; performing an artificial intelligence (AI) deep learning model with the generated conversion data; generating a fully connected network (FCN) by connecting the results obtained by the machine learning; and extracting biomarkers by the learned model.

Abstract: The present disclosure relates to methods of predicting treatment sensitivity or drug resistance, especially for epidermal growth factor receptor (EGFR) inhibitors using leucine proline-enriched proteoglycan 1 (LEPRE1) gene expression level before or during a treatment, methods of discovering companion diagnostic biomarkers using efficacies of EGFR inhibitors on the expression of genes, including genes involved with regulation of extracellular matrix environment, or metabolism of collagen, and methods of predicting treatment sensitivity or resistance of drugs using the companion diagnostic biomarkers thereof.

Abstract: Disclosed are a system and a method of predicting neoantigens and immune response induction. The system and the method may verify induction of immunity against neoantigens having high binding affinity by identifying neoantigen candidates through genomic mutations and then predicting the binding affinities of the neoantigen candidates for MHC through molecular dynamics. The method provides neoantigen immunotherapy information for identifying a neoantigen using artificial intelligence (AI)-based molecular dynamics big data, and includes steps of: (A) identifying neoantigen candidates through a genomic mutation; (B) filtering the specificities of the neoantigen candidates for tissue and disease; (C) predicting the in silico binding of the neoantigens to MHC; and (D) calculating and ranking TCR activity.

Abstract: Disclosed is a pharmaceutical composition for preventing or treating severe acute respiratory syndrome coronavirus 2 infection disease, the composition comprising a compound represented by a Chemical Formula 1, or a pharmaceutically acceptable salt thereof, as an active ingredient.