Pharmaceutical companies must walk their drugs through a four-phase approval process before they ever hit the market. It’s an incredibly lengthy undertaking (think six to 11 years) and can cost drug developers tens of millions of dollars in clinical trials. Even still, they will sometimes find out their drug has unfavorable side effects, forcing them back to square one.
That's why an Austin startup named Litmus Health is stepping in, using data and technology to help pharmaceutical businesses during the clinical process.
“The cost of bringing a drug to market is doubling, and the pharmaceutical companies are getting a lot of pressure from Wall Street to make it faster and more efficient — but they’re losing money because most of the stuff they work on doesn’t make it to market,” said Litmus Health co-founder Josh Jones-Dilworth. “This is a very lucrative market for technologists to come in and revolutionize the way we do clinical trials, the way scientists look for correlations, and how we find out what works and what doesn’t.”
Jones-Dilworth joins co-founder Samuel Volchenboum and CEO Daphne Kis in developing a data science platform that hopes to improve the early stages of a clinical trial.
Their focus is on the first two phases of the drug development process, where the company wants to help determine if drug developers should move on to the third phase — which requires the most capital out of all four phases. Jones-Dilworth said the leap from the second to the third phase — when the number of trial participants increases from 30 to 150 — can be a $300 million decision.
“Before Litmus Health, the pharma companies go to phase three regardless. We can give you hints before that,” said Jones-Dilworth.
By collecting trial patient data from wearable devices and home sensors, Jones-Dilworth said they can help guide the trial decision flow. They measure factors like quality of life, sleep habits, pain, daily activity, air quality and more. All of that collected data then runs through the Litmus Health app, which triggers questions like "How did you sleep last night?" to garner real-time responses from participants.
A machine-learning algorithm then searches through the data to identify correlations and patterns based on trial user behaviors and responses, both individually and population-wide.
“If I can tell that you are having asthmatic problems every time you’re in a certain neighborhood, or only in your home, or only certain rooms in your home, then our customers — the researchers — can help to understand if the drug is working all of the time, none of the time, or [if] the drug even works at all,” said Jones-Dilworth.
Current clinical trial processes often invite participants to an appointment twice a month to answer questions by clipboard. This outdated method of data entry can lead to untrustworthy data, because people don’t tell the truth or can't remember details from the past two weeks, Jones-Dilworth said.
“We’re getting trustworthy data,” said Jones-Dilworth. "These are people’s lives we’re talking about, the quality of the data really matters.”
To date, Litmus Health has raised about $265,000, with plans to secure more funding soon. He said their average contract costs about $450,000 — and they already have active clients.
“The nice thing about Litmus life is that every customer is a seed round,” Jones-Dilworth joked.
On March 11, the team will participate in the 9th Annual SXSW Accelerator Pitch Competition.
Image provided by social media and Litmus Health.
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