Solution

Quantiphi developed an AI-powered clinical study research assistant utilizing LLMs, revolutionizing the protocol authoring process. By seamlessly integrating with external sources like clinicaltrials.gov and PubMed, as well as internal documents such as historical protocols investigator brochures and design concept sheets, the solution streamlined the collection and summarization of pertinent information.
This approach addressed the client’s primary pain points of a time-consuming (more than 25 weeks) manual protocol authoring process by a team of 50+ members, variability in references, empowering users to generate concise, context-driven content for different protocol sections efficiently.
The solution’s competitive advantage lies in its ability to deliver comprehensive and tailored information swiftly, enhancing the overall efficiency and effectiveness of protocol authoring.

Results

The solution quickly assimilated information, streamlined content gathering, and facilitated efficient sharing through MS Word and CSV export compatibility.
Users reduced manual effort of protocol development by more than 10 weeks through contextual dialogue with the solution, obtaining desired responses promptly with specific inquiries.
Integration with internal docs and external authentication empowered client to seamlessly expand usage across various therapeutic areas.
Enhanced productivity, reduced turnaround time, and improved accuracy were observed, leading to a more streamlined and effective protocol authoring process which may potentially lead into saving more than $50M per trial