Today, pharmaceutical companies largely rely on institutional memory, medical expertise, and intuition to design clinical trials. We would like to change this.
We envision an integrated technology platform - with pre-built data ingestion pipelines, AI models, and an intuitive user experience - all built on AWS services.
By making more informed decisions at the beginning of the clinical trial design and planning lifecycle, you can proactively help reduce the risk of costly delays and protocol amendments - ultimately accelerating time to market and bringing potentially life saving treatments to patients faster.
With text extraction and NLP pipelines, make historical clinical trial protocols machine readable
AI models help you see the predicted impact of your inclusion / exclusion criteria choices on screen failure rate, enrollment feasibility, and diversity
Predictive models help you understand the likely patient burden and cost of your trial and improve the schedule of activities accordingly, including activity virtualization recommendations
Optimization algorithms suggest a list of countries and sites for your trial, based on your prioritized metrics (e.g., enrollment speed, cost, quality risk, Predictive Site Health™, and diversity)
Revamp trial design to improve enrollment timelines and reduce likelihood of protocol amendments and delays
Improve schedule of activity design, country allocation, and site selection to reduce costs
Leverage insights from your trial archives and real world data to design trials that are hybrid or decentralized, explore master protocol usage and adaptive designs, and reach more diverse populations