Sequence2Script is a web tool that helps clinicians learn about how drugs interact with their patient’s genetic differences.
People metabolize drugs differently, depending on their genetics, which means not all drugs are as effective for everyone. This is especially critical for things like mental health, where proper drug dosages are important. Sequence2Script draws on validated guidelines and recommendations from three different databases to create a single report that can guide them towards the best drug to prescribe for their patients.
The Problem and Existing Solution
The project was based on a specific problem posed by our challenge lead, who works with the University of Calgary’s pharmacogenetic consult service.
At the time, physicians had to contact the consult service with a patient’s genetic data. From there, the consultant (such as our challenge lead) would need to search through multiple databases to find the relevant information. Compiling these data into a single recommendation was both time-consuming and tedious.
The goal of Sequence2Script was to automate this process and aggregate all of the information from these databases into a single report for clinicians. This frees up time for the consultants and reduces a lot of inefficient searching through different services.
Neuro Nexus Prototype and Alpha Build
For the Neuro Nexus hackathon, I took the role of UI design lead and built wireframes in Figma based on specifications provided by our challenge lead. We decided to base our decisions on our challenge lead’s criteria because they were the one who would be using this tool first.
The first build of the software incorporated four genes, drawing information from two different databases to provide recommendations for antidepressant prescriptions. This minimum viable prototype was presented at the end of our eight-week challenge.
After the competition ended, we decided to expand the scope of the project to include more drugs, more genes, and more features. Many of the original team members moved on and we brought on a new developer to continue the project. This developer refactored the existing code into an alpha build.
Usability Testing Methods
We decided to conduct some usability testing on our alpha to provide direction for future development. I was tasked to lead the usability testing sessions and bring our findings back to the team to drive further development.
We ran two rounds of qualitative usability testing. For the first round, we conducted six user testing sessions with 10 participants between December 2019 and February 2020. The second round was conducted with 10 more participants from May to June 2020, done remotely over Zoom due to COVID-19 safety measures.
The participants tested came from a variety of backgrounds, including physicians, pharmacologists, lab technicians, industry professionals, and pharmacists. Many of these participants were contacts and colleagues of our challenge lead.
We prepared a number of tasks for participants, which we believed would be similar to their day-to-day work. For example, we would ask a doctor to prescribe a particular drug to a patient but we would ask a lab technician to do data entry and report generation.
During these sessions, we asked participants to complete these tasks with the alpha version of the software. Participants would verbalize their thoughts by “thinking aloud,” and I would only ask probing questions when users were quiet. Otherwise, I allowed them to use the software without our intervention.
After the tasks were completed, we interviewed the participants to hear their first impressions, their suggestions, and address any questions they had.
Key Findings from Usability Testing
These usability testing sessions revealed surprising insights into the users’ expectations about how this software worked. One crucial observation was that many users seemed willing to enter the information they want to see into the wrong fields “just in case,” rather than erring on the side of caution.
For example, we originally had an input field for drugs that a patient is currently taking, and we would show interactions in the resulting report. However, many participants were used to other drug interaction tools where they would input drugs they had considered prescribing and seeing how they would interact with each other.
These session revealed some major assumptions that we made about the users’ mental models of how this software worked. We were concerned that in its current state, a user might enter the wrong information, believe it was right, and prescribe patients the wrong drug. That was an unacceptable risk. We also quickly discovered in the second round of testing that adding additional written instructions did not completely eradicate this problem.
The testing sessions also gave us insights into how to better structure the form layout. The alpha version had fields in two columns, but we discovered that this did not have enough visual hierarchy to show what the workflow was for the user.
These results showed us that we needed to change the layout to improve usability.
Major Changes for Beta Launch
We made some major changes in the beta version based on the insights we gained from the usability testing.
For one, we adjusted the layout of the input form to be a single vertical column, separated into different steps with short, simple instructions on what kind of input is expected. We also restructured the output report into a single column for easier scrolling and printing.
We also created an additional step on the input form specifically for users to enter drugs they are considering. This is intended to show users that there is a difference between the two concepts. By creating two buckets for users to sort this information into, we hope that it will reduce input errors by allowing users to enter that information elsewhere.
With the Sequence2Script beta launch, I am hoping to continue conducting usability testing with early adopters and continue gaining insights on how we can improve the experience. I also intend to work with our developer to make the UI responsive for different screen sizes and explore interactions for viewing the data tables on mobile devices.