Chris Benko, co-founder and CEO of Koneksa Health, on VatorNews podcast

Koneksa Health is a company that is developing, testing, and validating digital biomarkers

Steven Loeb speaks with Chris Benko, co-founder and CEO of Koneksa Health, a company that is developing, testing, and validating digital biomarkers to help its clients understand the impact of their treatments on the patients who need them.

Our goal is to understand tech breakthroughs radically changing healthcare: the way we screen, diagnose and treat conditions and measure outcomes. And whether tech is helping or hurting our well-being physically and mentally.

Highlights from the interview:

• Benko spent his entire adult life, from undergraduate intern to corporate vice president, the global pharmaceutical company Merck, prior to starting Koneksa. Starting about 15 years ago, he had an opportunity to go work in Merck's research labs, with a focus on how they grew and implemented their traditional biomarker capabilities, which use genetic and molecular information, or really advanced imaging technologies, that could be used to help us understand how to accelerate the development of new medicines. He was then given the opportunity by Merck to start Koneksa, with a focus on how to use digital health data to have the same impact. 
• A biomarker is an indicator of something that's going on with the body biologically, something that's happening because of a disease, or the response to a treatment, such as a drug, a device, or a surgery. For example, blood pressure is a biomarker rather than an outcome measure, because we know blood pressure can be predictive of things like heart attacks and strokes, which are ultimately what we care about. Most of the time we can't feel our blood pressure, but blood pressure is a measure that allows us to understand if medicines are working, or if our body is progressing towards disease. 
• In very similar ways in which you might take large amounts of genetic data, process it and understand how it relates to somebody's experience on cancer treatment, Koneska is trying to do the same thing, except instead of collecting molecular and genetic information, it’s collecting digital health information. It has to filter through it and figure out what are the data points within that digital information that tell us how somebody's disease is going to progress or whether or not a drug is working for them. So, there's a lot of science and computing power that has to get layered on data that's collected in very controlled ways from human beings that participate in clinical research.
• Koneksa also has to invest in the scientific studies that prove that these digital measurement methods are better than the traditional methods, meaning it has to do its own clinical trials and generate its own data that convinces sponsors and regulators that they can rely on the data. It's a more than just a technology enablement layer, it's the data that convinces sponsors that they can rely on these assessments to be a good, of not better, than the assessments that they would have done by bringing somebody into a clinic and sitting them down in front of a nurse or a doctor.
• Koneksa looked at being able to measure lung function repeatedly in patients with asthma and it showed that it reduced the measurement error by half. That means, statistically, you need about a quarter of the number of subjects in a clinical study to get the same answer. So, instead of needing a minimum of 100 subjects in a clinical study, we might be able to measure in 25. In a pharma sponsored study, if they need 100 patients, they enroll 200, they might be able to enroll less than 50 and see the same thing. 
• Pharma is the most economically motivated to develop new measures. There's not a lot of incentive in the healthcare system today to figure out how to better diagnose or treat Parkinson's because there are very few tools to treat Parkinson's, so there's not a lot of reason for adoption for it today. But, in pharma, they care very much about coming up with the next generation of tools that could characterize disease modifying therapies that they're trying to develop. What we think will happen downstream is once those drugs get to market, there will be more calls for them to be managed effectively and cost effectively in the healthcare system. 
• COVID helped drive a lot of good experiences into the community and the FDA worked really aggressively to make sure there was very practical guidance for sponsors across all areas, not specific to COVID, for how to think about using digital and remote measures, providing a lot more flexibility or clarity around flexibility to sponsors that allowed them to keep trials going at a minimal risk to patients by not having them come into the clinic. So overall, COVID has been a lift to the field but there are certainly many places where people have also gone back to their traditional ways. And it underscores the fact that change management in pharma and drug development is hard and it takes a long time.

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