Avallano’s AI-powered protocol assistant aims to streamline clinical research
Avallano, a clinical trial solutions company, has launched ProtocolCopilot™, an artificial intelligence-driven tool designed to assist biopharmaceutical companies and clinical research sites in managing complex trial protocols. The product aims to address the challenges faced by research professionals in navigating lengthy protocol documents.
How it works
ProtocolCopilot utilises advanced AI technology to process and interpret clinical trial protocols, offering a chatbot interface for users to access critical information. The system is designed to ingest protocol data and respond to specific queries, eliminating the need for manual searches through extensive documentation.
Key features of the platform include:
1. AI-powered information retrieval
2. Enhanced usability through direct question-answering
3. Quick reference capabilities for protocol procedures
4. User-friendly learning interface
5. Compliance support for proper procedures and inclusion/exclusion criteria
6. Mobile accessibility for on-the-go reference
7. Customisable outputs in various languages and reading levels
8. ”Correct AI” assurance for factual, protocol-based responses.
The development of ProtocolCopilot comes as a response to the increasing complexity of clinical trial protocols and the cognitive demands placed on research professionals. Site staff, in particular, often struggle to manage multiple studies simultaneously, leading to potential inefficiencies and compliance risks.
Paul Della Maggiora, CEO of Avallano, commented on the launch: “We are excited to bring ProtocolCopilot to the market, offering a cutting-edge solution that not only enhances efficiency but also supports compliance and accuracy in clinical research. By leveraging the power of AI, we are ad-
dressing a significant pain point in the industry and empowering research professionals with a tool that understands their needs.”
Potential implications for clinical trial conduct
The introduction of AI-assisted protocol management tools like ProtocolCopilot could have significant implications for the conduct of clinical trials. By streamlining access to protocol information, such tools may:
1. Reduce protocol deviations resulting from misunderstandings or oversight
2. Improve site staff efficiency, allowing more focus on patient care and critical tasks
3. Enhance protocol adherence, particularly for complex study designs
4. Facilitate better understanding of inclusion/exclusion criteria, potentially improving participant selection
5. Support more consistent application of study procedures across sites
While the potential benefits of AI-assisted protocol management are evident, several considerations must be addressed:
Data security and privacy: As with any tool handling sensitive clinical trial information, robust data security measures will be crucial to protect confidential protocol details and maintain regulatory compliance.
AI accuracy and validation: The concept of “Correct AI” introduced by Avallano suggests a focus on ensuring factual, protocol-based responses. However, the medical community will likely require transparent validation processes to trust AI-generated protocol interpretations fully.
Integration with existing systems: For maximum utility, tools like ProtocolCopilot will need to integrate seamlessly with existing clinical trial management systems and electronic data capture platforms.
User adoption and training: Despite the promise of enhanced usability, successful implementation will depend on effective training programmes and user acceptance among clinical research professionals.
Avallano is currently seeking early partners for testing and deployment of ProtocolCopilot.
For more information, visit: www.avallano.com
Digital issue: Please click here for more information
