AI in Diagnostics: An Investor Perspective

9 Jul

By Rory McCann, Marketing Manager & Conference Producer, LSN

It’s commonly said in business that “riches are in the niches”, which translates to targeting a specific market for an outstanding performance. In diagnostics investment, there’s no better example of this than Greybird Ventures. We spoke with the founder and CEO, Tom Miller, on his unique approach that sets his company apart in the often-competitive healthcare investment arena.

Miller started Greybird Ventures in 2013. He added two partners, and they made their first investment in 2016. Regarding their investment theme, Miller says that Greybird is, “[a] focused, totally dedicated, and only investing-in-diagnostic-technologies venture firm – we are also the world’s smallest one of those things – because I believe we’re the only ones doing that.”

Greybird’s foundation has remained the small team of three – Tom Miller, as well as Michael Devlin and Scott Gazelle – and the diagnostics-centered portfolio companies that have since grown to five, three of which work with artificial intelligence (AI)-enabled diagnostics. While the numbers may seem small, it has been an intentional strategy by Miller, who says, “[Greybird] holds a chairmanship in every firm we invest in, and we tell our CEOs who are about to take our money, ‘If you want a passive investor, don’t touch us.’ We are very active. We get involved with business development. We will help them with clinical trials. We’ll help them recruit principal investigators, and we get deeply involved in the science… That said, money is not really our limitation for how many companies we’ll invest in, but rather our own bandwidth. You don’t get a junior person. You get one of us.”

Using oncology as an example, Miller described the necessity of AI and machine learning (ML) in diagnostics. The more doctors and scientists understand certain cancers, the more specific types there are, and the broader the diagnostic range will be. Miller says, “I think within the next decade, for certain medical disciplines, practicing medicine without computerized assistance will be malpractice because you simply can’t do it.”

While a big believer in the promise of AI, Miller is skeptical of every application in the medical field, specifically in prognoses based on patient records and its potential to blur the lines between correlation and causation. He instead works to promote technologies where AI fills in the gaps, in addition to human study and close observation. Applications such as AI-enabled radiology, locating biomarkers for human cancer detection, and motion predicters to determine drug efficacy in degenerative diseases, such as Parkinson’s or Multiple Sclerosis (MS).

Just as Greybird’s success has grown in a specific space within healthcare investment, Miller believes that AI is the best solution for well-defined, narrow problems.

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