AstraZeneca - Precision Clinical Trial Matcher

The Challenge: Manual Labor in a Digital World

At the heart of AstraZeneca's pursuit for medical innovation was a surprisingly manual and labor-intensive process: scouring patient histories to match them with clinical trials. Picture a team, armed with nothing but their expertise and endless spreadsheets, trying to decode complex medical data and cross-reference it against a laundry list of trial criteria. It was meticulous, exhaustive work, done by dedicated professionals who understood the stakes but were bound by the limitations of human speed and the sheer volume of data.

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Our Approach: Transforming the Process with AI

Recognizing the unsustainable nature of this manual labor, our agency proposed a shift towards something more fitting for the 21st century. We saw an opportunity to take this painstaking task and streamline it using artificial intelligence. Our goal was to preserve the human touch where it mattered most—interpretation and decision-making—while offloading the data-heavy lifting to AI. This approach promised not just efficiency but a revolution in how patient-trial matches were made.

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The Solution: Precision Clinical Trial Matcher

Enter the Precision Clinical Trial Matcher: AstraZeneca's new digital workforce. This platform wasn't just another tool; it was a paradigm shift. By feeding it patient histories and trial criteria, the Matcher uses AI to quickly sift through data, identifying eligible participants with an accuracy that matched—if not surpassed—the manual efforts of its human predecessors. Of course, we did this while keeping privacy our main concern and never relating any of the patient's medical histories to the patient's identity.

Why It Marks a New Era:

• Speed and Efficiency: What once took hours, now takes minutes. The Matcher can process vast amounts of data at speeds no human team could achieve, freeing them to focus on more nuanced aspects of patient care and trial design.
• Reduced Costs: With AI taking on the brunt of the matching process, the need for extensive manual labor is greatly reduced, allowing AstraZeneca to allocate resources more effectively and potentially lower the overall costs of clinical trials.
• Improved Accuracy: The AI doesn't tire or overlook details. It ensures that every patient history is scrutinized with consistent precision, increasing the likelihood of finding the right match for every trial.

The Impact: A Leap Towards the Future

This has been one of the first projects we've worked on where we automate a business process that will improve many people's efficiency, and we're very proud!
The use of artificial intelligence for business processes is still in its very early days, but we have no doubt that this will be one of the main drivers of economic growth in the years to come.

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