Integration of technological tools that have proven their value in areas such as transcriptomics, metabolomics, single-cell sequencing (single-cell RNAseq), and whole-genome sequencing.
AI in the analysis of medical and pathological imaging.
Deep learning-assisted drug discovery models, capable of simulating molecular interactions and accelerating the identification of therapeutic candidates. This combination of technologies enables the generation of predictive biomarkers, mechanistic models, and clinical stratification algorithms.
Deep tech startup dedicated to drug discovery and advanced oncological diagnostics through artificial intelligence and data science.
We combine omics data (genomics, transcriptomics, proteomics) and medical imaging with predictive machine learning algorithms to identify biomarkers and generate new therapeutic candidates and personalized diagnostic panels.
Our mission is to drastically reduce the time and cost of precision oncology development.
Computational support for genomic analysis, molecular modeling, drug generation, and AI-based prediction.
Advanced analysis of DNA and RNA sequences
Structural modeling and molecular simulation
Machine Learning for structural biology and complex systems
Integration and analysis of large-scale omic data
Scalable computational platforms
Quality Management System
Clinical Trials Management System
eCRF