More than half of all clinical trials fail due to safety issues. Discovering drugs that show therapeutic potential is difficult, time-consuming, and expensive. But of those found, it is harder still to find those drugs which do not also have severe side effects and can pass through clinical trials.
Most of these drugs are shelved and never reach patients. Safety issues are tough to fix without weakening the therapeutic effect, involving a mix of chemistry, biology, and knowledge of how humans will respond.
Our proprietary AI model, SAFEPATH©, applies deep learning to our combined bioinformatics and cheminformatics datasets to solve drug safety issues. SAFEPATH© utilises the latest deep learning approaches to identify the mechanism of toxicity, predict its effects on the human body, and balance that with therapeutic effectiveness.
We are building at speed a robust pipeline of matured assets. We look at historically failed clinical trials to identify the most promising targets as well as internal projects that were abandoned. By focusing on safety problems that occur in Preclinical, Phase 1, or Phase 2 trials, we are able to identify the most promising drugs therapeutically, turn them around quickly, and get them to patients faster than starting drug discovery from scratch.
Our mission is to bring more treatments to patients, faster. Thousands of life-changing drugs fall at the last hurdle and never reach patients. We’re here to change that.
