Imagine a GPS for scientists that doesn't just tell them where to go, but explains exactly why it chose that route. Most AI acts like a black box, giving answers without reasons, which is dangerous when making medicine. This tool opens that box, showing the logic behind its predictions to help researchers find safe drugs faster.
Drug discovery is currently too expensive and risky, with costs reaching €2.5B per drug. Many candidates fail late in the process due to unforeseen toxicity because existing AI tools are 'black boxes' that don't explain their reasoning.
The 'Reason' platform, powered by QLattice AI, which provides explainable and transparent predictions for RNA therapeutics and drug design.
If you are a drug discovery firm dealing with high failure rates and unforeseen side effects — this project developed the Reason platform that uses explainable AI to predict toxicity and off-target effects. This increases the probability of success for drug candidates.
If you are an RNA therapeutics startup dealing with the complexity of designing new compounds — this project developed a specialized AI toolset that empowers non-coding scientists to design better compounds. This reduces the risk of expensive R&D failures.
If you are an R&D laboratory dealing with the €2.5B average cost per drug — this project developed the QLattice technology that provides transparent, scalable insights. This helps reverse the trend of steady R&D cost increases.
The project targets the trend of R&D costs increasing to approximately €2.5B per drug today. By de-risking the process and increasing the probability of success, it aims to improve ROI and productivity.
Yes, the QLattice technology is described as a scalable solution. Based on available project data, it has already been used in over 15 pharma pilots.
Based on available project data, the project focused on developing a commercially viable AI offering called 'Reason' to enable wider access to the technology.
The platform is designed as a 'responsible, trustworthy and transparent AI' specifically to meet the high-stakes requirements of the pharmaceutical sector where explainability is crucial.
The 'Reason' platform is specifically designed to be utilized by non-code savvy R&D scientists, suggesting a low barrier to integration for laboratory staff.
The project is lean and highly commercial, consisting of 2 SMEs from Denmark and Spain. With a 100% industry ratio and zero university or research partners, the focus is entirely on commercialization and market disruption rather than basic research.
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