Clinical Trial Follow-up

Semi-automating continuous follow-up of clinical trial participants with AI to capture complete data

Background and Challenges

Routine follow-up cannot capture all data, resulting in only partial sampling and making it impossible to obtain information on the opinions and perceptions of all subjects.

There are variations in the level of detail recorded by staff and physicians, resulting in a lack of data consistency.

AS-IS (Conventional)

• High-burden follow-up (phone / in person)

• Variations in documentation (person-dependent)

• Delayed follow-up

TO-BE (After Implementation)

• Reduced burden through asynchronous, smartphone-based responses

• Standardized by AI for consistency and structure

• Real-time immediate alerts

Operational Flow

1. Subjects respond periodically or as needed using their smartphones

2. AI probes symptoms in more detail based on the response content

3. If there is a possibility of an abnormality, an alert is issued immediately

4. Reports are generated as structured data

Information That Can Be Collected

• Time-series changes in symptoms and physical condition

• Medication adherence status (compliance)

Implementation Benefits (KPI)

• Data collection rate: Improved

• CRC workload: Reduced

• Follow-up lead time: Shortened