AI-based biodesign to develop peptide therapeutics for pneumonia-causing pathogens with experimental validation
| Reference number | |
| Coordinator | Kungliga Tekniska Högskolan - Kungliga Tekniska Högskolan Skolan f kemi bioteknologi & hälsa |
| Funding from Vinnova | SEK 2 796 180 |
| Project duration | August 2024 - September 2027 |
| Status | Ongoing |
| Venture | Swedish-Indian cooperation within innovation in the area of health and AI |
| Call | Cooperation with India within Health focusing on AI-based Digitalisation, Biodesign or Circular Economy |
Purpose and goal
The project develops AI-driven peptide therapeutics for pneumonia to enable faster, cost-effective solutions against pathogens. Machine learning models will predict antimicrobial activity, allergenicity, and toxicity, while generative AI creates optimized peptides. In vitro and lung organoid assays will validate findings, bridging computational and experimental research to deepen understanding of pathogen-host interactions and therapeutic potential.
Expected effects and result
The project aims to generate AI-designed peptides with high antimicrobial activity, low allergenicity, and minimal toxicity for pneumonia. Validated models will predict these properties, creating novel peptides effective against pathogens. In vitro and lung organoid assays will confirm results, enhancing understanding of pathogen-host interactions and peptide efficacy. This approach aims to shorten drug discovery timelines, offering cost-effective therapies for respiratory infections.
Planned approach and implementation
The project consists 6 work packages. WP1 will collect data on antimicrobial peptides, guiding WP2 to develop AI/ML models predicting antimicrobial activity, allergenicity, and toxicity. In WP3, generative AI will design peptides for pneumonia pathogens. WP4 will analyze cell membrane interactions, and WP5 will focus on peptide synthesis and in vitro validation with lung organoids. Finally, WP6 will manage dissemination and patenting, ensuring transition from data collection to applications.