Ep. 58: Dr. Alexander Bilbily and 16Bit AI

Osteoporosis and stones might break your bones, but Dr. Bilbily and the 16Bit AI team hope to prevent that.

This week, we had the pleasure of chatting with Dr. Alexander Bilbily about the rollercoaster journey he and his cofounder and co-CEO Dr. Mark Cicero have embarked on while founding and scaling a leading AI company which aims to detect osteoporosis opportunistically.

From blueberry muffins and chihuahuas to regulatory considerations, join us on this week’s episode of Med Tech Talks as we unravel the story of Dr. Bilbily, who is helping shape the future of how physicians will work with AI.

To find more of our podcasts, you can go to howitsmed.com, https://plnk.to/howitsmed, or https://youtu.be/WqHhj2eGzw4

#medicine #medtech #healthtech #healthcare #AI #podcasts #videocasts #physician #founder #Canada

1:14 - 10:22 - Alex recalls why he chose medicine and specifically radiology - uniquely, his story was shaped by an early invention to track patients’ adherence to therapy, and a preference for the diagnostic over the therapeutic side of medicine

11:30 - 16:30 - A discussion on the current state of and this history of the interaction between medical practices and those backing the integration of novel computer science tools into radiology workflows.

17:21 - 30:28 - Alex and Mark’s path toward entrepreneurship in medicine through 16Bit - and the “rollercoaster” story of 16Bit

31:11 - 39:11 - To patent or not to patent? What is the level of validation you need to get an algorithm approved by the FDA? Alex answers the difficult questions associated with commercializing an algorithm in radiology. 

40:01 - 42:45 - No fundraising, no luck? Alex doesn’t think so - he describes why 16Bit hasn’t raised so far despite the significant amount of investment money looking for companies such as 16Bit.

43:28 - 50:30 - How Alex keeps himself grounded through clinical practice, and how his company stays grounded despite the presence of competitor AI-based radiology companies with significant edges in the amount of data available to them.