Imagine trying to find the perfect way to stack LEGO bricks so they don't fall apart; in medicine, molecules do this too, and the wrong stack can make a drug unsafe. Instead of spending years guessing through trial and error in a lab, this technology uses super-smart computers to predict the perfect stack instantly. It's like having a GPS for chemistry that tells scientists exactly where to look.
Pharmaceutical companies face massive financial risks and regulatory delays because drug molecules can form different crystal structures (polymorphs), which affect safety and efficacy. Current lab-based testing is slow, expensive, and has a success rate of less than 1%.
A cloud-based predictive technology combining AI and Quantum physics to determine the most stable crystal structures of drug compounds.
If you are a large pharma enterprise dealing with costly product recalls or regulatory delays due to polymorphism — this project developed a predictive CSP technology that reduces the time to find stable crystal structures from 3 months to 3 weeks.
If you are an emerging biotech startup dealing with limited lab resources and a need for fast R&D — this project developed a cloud-based solution that reduces candidate experiments from 400 to 40.
If you are a CRO dealing with long and painstaking experimentation cycles for clients — this project developed a quantum-AI tool that boosts success rates for determining the most stable polymorph of a drug compound.
It reduces wasted scarce resources by cutting the number of required polymorph screening experiments from 400 down to 40.
Yes, the technology is designed to be scalable as a cloud-based solution, making it accessible to both large companies and small biotechs.
The invention is protected under patent EP3948877A1.
By reducing the CSP cycle from 3 months to 3 weeks, it addresses a process that can otherwise add 2 years or more to the time it takes to bring a medicine to market.
Based on available project data, it acts as a predictive guide for lab scientists, telling them where to focus experimentation for a right-first-time result.
The project is led by a single Irish SME, Biosimulytics Limited. With a 100% industry ratio and no university or research partners, the project is lean and focused entirely on commercial application and rapid deployment of its patented technology.
Contact Biosimulytics Limited in Ireland
Contact us to explore licensing opportunities for this quantum-AI drug prediction tool.
