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Depression
is the leading cause of disability worldwide. With an estimated 350 million
people suffering from the disorder, it is a major contributor to the overall
global burden of disease. Depression is a treatable illness and there are effective treatments, however, finding the
right medication can be a process of trial and error. There is still little way
to know which treatment will work, and many need to try two or three drugs or
drug combinations before experiencing relief. A process that can take several years.
The New
York-based startup Spring is determined to end the trial and error process of
early depression treatment. They have developed a machine-learning model, based
on peer-reviewed and published research, that help doctors make the best
treatment decisions. The online assessment tool is a 10-minute test, consisting
of 25 questions, which helps analyze the patient’s specific symptom profile and
help understand which drugs might be most effective. Their algorithm can
identify 66% of patients who will not recover from a specific drug, performing
significantly better than a psychiatrist.
The
technology is based on research by Adam Chekroud, who
published a paper in the medical journal The Lancet Psychiatry on the model. April Koh
read the paper and found it compelling after having friends and family go through the trial and error process, and decided to reach out. Together with
Abhishek Chandra they founded Spring, and have now developed an entire platform
where physicians can administer digital screenings of patients, a simple 10
question survey, and track patient progress to make better treatment decisions.
The
innovative, yet simple digital tool could help match patients with
effective drugs. Currently, less than one-third of people treated for
depression find relief from their first antidepressant, which is not only
frustrating but can have serious consequences. Although Spring and their
technology cannot replace physicians, it can play a major role in influencing
decisions, potentially giving millions of patients their life back. The
platform could even increase accuracy of assessment, reducing numbers of
misdiagnosis. The digital nature of the solution also mean that it could increase
access to care, potentially helping reduce the social stigma associated with
mental disorders.
Several
hundred patients have so far used Spring since its launch, and the startup is
working with a network of psychiatrists around the US. It has been well
received by both patients and physicians, and their feedback help guide the
startup’s development and refine their product. They are also looking to develop additional tests for other behavioral health conditions and drugs.
Spring has
previously participated in the YEI Fellowship, an 8-week boot camp for
accelerating ventures run by the Yale Entrepreneurial Institute, and won the
$25,000 Thorne Prize for Social Innovation in Health or Education from
InnovateHealth Yale. They have also received a $30,000 Bioscience Pipeline
award, and been part of the New York Digital Health Accelerator. In 2017, Spring
is part of PULSE@MassChallenge, a startup program specifically designed to
bring digital health innovators and the clinical community together to drive
better and faster innovation.
