Philadelphia-based healthcare technology incubator Dreamit Health has announced its third class of health tech startups. The selected startup teams will participate in a 16-week boot camp from from July to October 2015 to rapidly achieve key business milestones in building high-growth potential companies.
In exchange for 8% in equity, each team will receive:
– $50,000 in seed capital, plus up to $250K in follow-on funding from DreamIt Ventures.
– coaching/mentorship from successful tech entrepreneurs including legal advice and counsel
– curriculum at the intersection of health care, business, technology and design
– free workspace at the University Science Center’s Innovation Center
– access to people and resources across leading health care organizations, which are typically out of reach to startups.
The program will end with Demo Day scheduled for October 26th for startups to present their progress to date and plans for the future with an audience of several hundred investors, industry leaders, potential customers and the press.
Here is the latest class of DreamIt Health Philadelphia startups:
- CareCierge (Philadelphia, Pennsylvania) — Concierge services for those who find themselves taking care of an ill or aging loved one.
- dBaza Health (Pittsburgh, Pennsylvania) — Clinically validated patient onboarding platform for managing chronic diseases like diabetes
- GraphWear Technologies (Philadelphia, Pennsylvania) — Low-cost graphene-enhanced flexible sensors measuring blood sugar, dehydration, and fat burning.
- Gray Matter Technologies (Austin, Texas) — Impact-sensing sports mouthguard that identifies athletes at risk of concussion.
- Neutun Labs (Toronto, Canada) — Tracking software for epileptics utilizing sensors in smart watches and other wearables.
- Oncora Medical (Philadelphia, Pennsylvania) — Analytics software for radiation oncologists to compare patients against past cases.
- Pallas Medical (Boulder, Colorado) — Mobile, easy-to-use device to cool scalp during chemo and prevent hair loss.
- VisExcell (New York, New York) — Better computer-aided detection in mammograms and other imaging modalities through big data and advanced machine learning algorithms.
