Case Studies
Transforming Science with AI

Developed comprehensive nanoinformatics models and tools for NanoSolveIT, CompSafeNano, SABYDOMA, and DIAGONAL projects. Advanced QSAR/nanoQSAR models combined with safe-by-design frameworks for nanomaterial risk assessment.

De novo drug design assisted by AI for TNF & RANKL inhibitors, ATX inhibitors for cancer and autoimmune diseases, COMT inhibitors for Parkinson's, and BACE inhibitors for neurodegenerative diseases. Multi-parameter molecular optimization.

AI-driven cheminformatics models for per- and polyfluoroalkyl substances (PFAS) through PROPLANET, CHIASMA, and SCENARIOS projects. Includes inhalation toxicity modeling, environmental fate prediction, and hazard categorization.

Machine learning integrated with nano-enabled agriculture applications through CHIASMA project. Predictive models for plant growth indicators and safe nano-agrichemical design. XGBoost implementation achieving 85% prediction accuracy.

Sophisticated computational models for micro/nanoplastics fate tracking and chemical contaminant behavior in environment. Includes SimpleBox4Planet implementation for environmental compartment modeling and bioaccumulation prediction.

Advanced bioinformatics for precision medicine including THALAMOSS project for beta-thalassemia, CyNephron for inherited kidney disorders, and stratified pharmacogenomics in psychiatry. Personalized treatment optimization based on genetic profiles.

Network-based target identification from multi-omics data and innovative drug repurposing strategies. ReDEx tool enabling rapid exploration of therapeutic space through knowledge graph integration and systems pharmacology analysis.

AI/ML systems for unmanned aerial vehicle detection and neutralization protocols to protect critical infrastructure. Advanced computer vision and signal processing for real-time threat detection and response automation.