AI-Assisted Clinical Trial Site Selection
Using analytics to help clinical teams shortlist trial countries and sites more quickly from available data.
Representative scenario based on the kinds of projects AWZ handles. Client names and proof are private. Targets are agreed and measured per project — published figures are not audited outcomes.
Representative client profile
Life-sciences client
Understanding the Problem
A pharmaceutical organization found manual site selection slow. Historical trial data and country-specific requirements were difficult to compare in spreadsheets.
How We Solved It
We built analytics and data pipelines that consolidated historical trial data, requirements, and demographic indicators so teams could rank candidate sites for review.
What We Measure
These are the measures we would define and validate with the client. They are not published client results.
Site selection time
Analytics can shorten the review step; actual timelines depend on data quality and completeness.
Site activation cost
Cost reduction is case-specific and validated against the client's own data; not a fixed percentage.
Site qualification
Scoring improves when input data is clean and validated with subject-matter experts.
Regulatory context
Regulatory compliance is the client's responsibility; our role covers data tooling, not approval.
Technologies Used
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