On Monday morning, I decided to talk to Pilar, the founder of the Biomarkers team. It was a team I resonated with personally, but its members came from very different professional areas:
- Angela Scott had been in the small team that turned Sci-Fi into reality by cloning the first mammal – the sheep Dolly;
- Frank Xinyue, “Biosensor Scientist” at the Missouri University;
- Pilar Zarate, Social Entrepreneur, and Marketing specialist with extensive experience in design;
- Carlos Javier, Product Manager who had worked in an e-waste recycling company;
- Djamila Yousef, psychologist, hypnosis therapist and student at Harvard Business School.
This intimidated me at first but then I pulled myself together and said to myself: “I may not know bio-engineering, but you guys don’t know digital either, so there goes nothing.” I spoke to Pilar and, on the second day of Bootcamp, at 7 AM I was part of a different team. It turned out that the mentor’s’ advice about choosing one’s team was very important and true.
During the second day we had to define the actual problem (that we were trying to solve), to describe it with as many details as possible and to validate it through interviews with people from our main target zone. The problem we first defined was: the difficulty in the diagnosis of mentally impaired children. We thought we could use a gadget that could detect symptoms in children early on and indicate if they could really suffer of mental illnesses or not. Djamila confirmed that this problem is real and that we could develop an algorithm that could help us solve it.
After a long series of interviews, we realized that our problem could have severe ramifications that we hadn’t thought of to begin with. We realized people would see a specialist at the first signs of illness and they wouldn’t purchase a gadget or app as an intermediary step. Moreover, there had been cases in which families refused to accept a diagnosis even when given by a specialist. If the problem seemed simple at the beginning, the interviews revealed that there were dozens of associated problems that we had to solve before a gadget, app or algorithm could come in handy. What actually buried the idea were the words of the mentor Bill Kirkley, who spoke about a misdiagnosis: “Guys, you can ruin families’ lives if you do this.” Who would have thought so far ahead?
In spite of the interviews and the conclusions, Djamila, the main supporter of the idea insisted that we went on. She had made a mistake that Marius always told us to avoid: “She fell in love with the solution, not the problem.” Again, the compatibility of the team members spoke loud. Djamila left our team to join another one with whom she worked much better. I couldn’t judge her, since I had done the same thing before and it turned out to be right. So we decided to move on. Where to? No one knew. We had a few sessions of discussions and brainstorms, then at 3 AM we finally reached a consensus. We were set to revolutionize the medical industry and wouldn’t back down until we did just that.
The second problem we tried to solve (after rephrasing it several times) was the following: Current methods for analyzing biomarkers in cell therapies are inefficient. Nowadays it takes from 6 hours to 5 days to interpret the test results or a cancer patient and one must follow 5 very complicated steps. We decided to explore this problem and see if it could be done in a shorter time. The solution we found would help interpret the data much easier, so that the patients would receive the correct treatment faster