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Clinical Trial Search Engine

Project

Clinical Trial Search Engine is the first project that I took on after I joined Archetyp Mobility in my junior year at UC Irvine. The branding is not ready to be revealed to the public yet so I will refer to this project simply as Clinical Trial in this case study.

The goal of the project is to create an NLP-centric clinical trial search engine for cancer patients.

It goes beyond a redesign of clinicaltrials.gov. With Natural-Language-Processing, the application can extract essential information from thousands of words in a trial listing. The application then streamline the information in the back end with a state-of-the-art product that delivers an unmatched trial searching experience. Unlike our competitors, the team is approaching the problematic clinical trial searching system with a new, unconventional lens that focuses more on the information architecture and the power of NLP.

My mission as a designer is to create a product that uplifts and encourages cancer patients to allow Clinial Trial to assist them in finding clinical trials that best fit their medical history.

Competitor Analysis

There are thousands of clinical trials, but the market is still waiting for a breakthrough technology that transforms the way people search for trials. There are companies that try to tackle the market's needs, but they are still approaching the problem with a traditional healthcare methodology.

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The information structure is flawed and complicated. For example, in MolecularMatch, the filter column on the left is long and full of unnecessary fields. The title of the trial listing takes up half of the space in the card and we can all agree no one is going to enjoy reading NCT02511106 - AZD9291 Versus Placebo in Patients With Stage IB ... Moreover, assuming most of the patients do not have a high-level understanding of medical terms, people are going to struggle at learning why those attributes matter to them.

In CenterMatch, we can see an improved user experience for the process of searching for a trial. However, on the result page, the patients are still going to have a relatively tough time calculating if they are qualified for a trial.

Design

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Impact

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Reflection

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