Opyl’s technology research and development pipeline provides lifescience developers and healthcare providers with unprecedented insight and data optimisation opportunities.
Opyl has three key platforms in development that utilise artificial intelligence to analyse structured and unstructured data to deliver high value insights.
- Clinical trial prediction and protocol design tool (Trial Key)
- Clinical trial recruitment tool (Opin)
- Deep social media insights in healthcare
Our purpose is to improve operational efficiency in clinical trials and reduce risk. We deliver value in two ways; by using AI to inform clinical trial design giving drug and device candidates the possible chance of success, and in using social media and digital tools to accelerate recruitment.
Our flagship research focus is our Clinical Trial Prediction and Protocol Design Platform. Inspired by the current high failure rate of clinical trials due to poor design and inefficient implementation, the tool has two key applications: predicting the outcomes (completion and primary endpoints being met) at each phase which has value to sponsors and investors, as well as the ability to model the probability of success of a trial in the initial design stage.
The Clinical Trial Prediction and Protocol Design Platform, though not yet complete in terms of full deployment into an enterprise solution, is functional and being applied by a group of ‘pilot’ clients. Having trained the algorithm initially in early 2020 with 300,000 registered clinical trials stretching back to 2005, and then with a subsequent 475 COVID19 trial cohort in July 2020, the Opyl model delivers consistently strong model predictability of AUD 0.84, using standard statistical techniques (AUC, MEC, recall etc).
Following successful proof of concept and reliability testing in early-mid 2020, the Opyl model now moves into UX and UI development as well as a features enrichment stage to deliver a scalable enterprise solution ready for full cross-market deployment with biopharma and medtech clinical trial developers as well as into fund managers and sponsors as a portfolio analysis tool.