Engineering challenges in clinical trials

TrialSpark is bringing new treatments to patients faster by building the infrastructure to run entire clinical trials.

Clinical trials are the biggest bottleneck in the advancement of medicine, often taking multiple years and costing tens of millions of dollars. They are immensely complex, from both an operations and technology standpoint. Engineering has a direct impact on improving their efficiency and lowering their cost, and is critical to achieving our mission.

Our problem space spans the entire engineering spectrum, from UI/UX to data engineering and infrastructure. Here are a couple of problems we’re actively tackling today:

• Patient/trial matching. For patients, learning about and finding the right trial for their condition is difficult. For doctors, finding the right patients for their trials is even harder. We’re breaking down this problem by structuring trial criteria and patient health data in order to ultimately match patients to trials. How do we structure machine-unreadable clinical trial eligibility criteria? How do we build an eligibility engine to match sick patients to the trials they’re looking for? What does the best patient experience joining a clinical trial look like?
• Clinical data collection. We’re collecting data through our network of doctors that literally informs whether a new treatment is effective or not. How do we design a single, structured data layer for hundreds of potential data sources, including wearables and patient diaries? How do we ensure data accuracy, consistency, and timeliness? How do we audit all data-generating activity so that we’re certain about the quality of the data?
• Payments. In a single clinical trial, thousands of tasks and payments are completed between patients, doctors, sponsors, and lab providers. We’re building a smart payments engine to facilitate this process. How do we accurately track and verify medical procedures across multiple services, partners, and locations? How do we pay our patients and doctors on time and error-free?
• Real-time biostatistics. We collect hundreds of thousands of data points in every trial. This data needs to be analyzed and returned in a human and FDA readable format. How do we conduct real time clinical data analysis? How do we support dynamic biostatistics in adaptive trials? How can we predict and flag safety issues early in a trial?
• Physical network logistics. The operational inputs and outputs of a clinical trial are tremendous. We have a growing network of doctors and research coordinators in multiple geographical locations that conduct hundreds of patient visits per trial. How do we support the operations of network expansion to a new geography? How do we standardize a single set of practices across all of our trial sites, including scheduling, equipment tracking, visit capacity, study feasibility, and staff performance?

We’re building a culture of smart, empathetic, and mission-driven engineers, PMs, and designers in NYC. We believe we’re working on one of the most impactful problems in the world — check out our existing job openings and join us!