Boolzi
Boolzi provides B2B AI and cheminformatics services to pharmaceutical companies, combining machine learning with human expertise to optimize drug discovery and development. The company repurposes shelved compounds for new therapeutic indications and applies AI to detect complex biomarkers and design clinical trials with improved recruitment and success rates. Its workflow spans data curation, algorithm training, prediction, and technical reporting.
- Drug Discovery & Therapeutics
- Artificial Intelligence
- Biotechnology
- Healthcare Technology
- Data & Analytics
Funding
Founders
Founder details are not available yet.
Product
Problem
Over the past 25 years, pharmaceutical investments have grown steadily, yet for every 10,000 molecules investigated, only one reaches the market as a new drug. The low productivity of the drug development pipeline, where most candidates fail during the process, slows innovation and imposes significant economic burdens that are ultimately passed on to patients through approved medications.
Solution
Boolzi offers B2B AI and cheminformatics services to the pharmaceutical sector, combining advanced machine learning algorithms with human expertise to optimize the drug discovery and development cycle. The company applies two general strategies: repurposing shelved compounds for new therapeutic indications to enhance the value of pharmaceutical companies' proprietary libraries, and using AI to detect complex biomarkers and design clinical trials with increased chances of success. With a hybridization of in-house machine learning and human intelligence, Boolzi trains algorithms adapted to each client's needs, from data curation and processing through algorithm training and validation, helping more medications reach patients at lower costs.
Target Audience
Primary customers are pharmaceutical companies seeking to lower drug development costs and improve the value of their proprietary compound libraries, as well as organizations needing biomarker detection and informed clinical trial design.
Features
- AI-driven drug repurposing of shelved compounds for new therapeutic indications
- Machine learning algorithms adapted to detect complex biomarkers
- AI-informed clinical trial design with improved recruitment and enhanced success rates
- Hybrid approach combining in-house machine learning with human intelligence
- Full pipeline support from data curation and processing through algorithm training and validation
- Post-service technical support and personalized advice beyond the initial report