AutoDeclare's use with RCTs: AutoRCT

Case Study

A digital therapeutics (DTx) developer based in Manchester, and their USA investor, faced several critical challenges when implementing a RCT:

• Labour-intensive documentation processes that were new to the business
• Inconsistent reporting standards from local, regional and national gate-keepers
• Extended trial completion timelines because of the lack of availability of academic researchers
• Rising costs amidst market pressures as often researchers need to be recruited for individual trials

Solution

AutoDeclare: AI-powered automation methods. The research results, process and results is shown below for individual AutoRCTs.

Results

• Trial completion time shortened by 60%
• Documentation errors reduced by 90%
• Staff productivity increased by 75%
• Cumulative cost savings relative to a academic only RCT: £234,960 - Total time saved: 2,070 hours

Outcomes

• Reduced time-to-market by 60%
• Strengthened investor relations
• Enhanced regulatory compliance
• Improved trial data quality

Learning Points

• Initial regulator staff resistance to new technology
• Data migration complexities
• System integration hurdles
• Learning curve impact on productivity

Mitigations

• Phased implementation approach​
• Parallel systems operation
• Regular validation protocols

Time Analysis

Traditional Process

200 hours

Automated Process

27.5 hours

Time Saved

172.5 hours (86%)

Cost Analysis

Traditional Cost

$36,200

Automated Cost

$11,725

Cost Saved

$24,475 (67.6%)