In this episode, we talk to Patrick Short, a Co-Founder and the CEO at Sano Genetics. Patrick holds his PhD in Mathematical Genomics and Medicine from the University of Cambridge.

Sano Genetics is a user-centric genetic data-sharing platform. The company raised £3M from Episode 1 Ventures, Seedcamp, Cambridge Enterprise, January Ventures, and others.

Patrick shares insights on building the company and reflects on his experience of transferring from academia to entrepreneurship.

The healthcare sector is changing. At the macro-level, there are active investments in population genomics, in the UK for example the aim is to sequence 5 million people genomes. Another powerful trend is personalised medicine. Right now available mostly to cancer patients, whose medicines are usually genetically targeted, in the next 10 years it may have a wider adoption.

Macro trends create opportunities for startups. One of these opportunities was spotted by Sano's team. Being researchers themselves, founders have seen how difficult it was to interface with massive genomic datasets, to engage with patients/participants whose data was there, to request additional data, etc.

Through seeing the problem from the research perspective, Sano came up with a platform that serves not only consumers, but biotech, pharmaceutical companies, and researchers.

Building a multisided platform is hard. Sano selected exactly these participants since their interests are aligned, and it's relatively clear who is a customer.

Patrick shares a simple but elegant framework for thinking about how to select a side to monetise your product through. Patrick also suggests how one may prioritise investments in data science/research and other sides of the product, e.g. scalability.

Some other takeaways from the talk:

  • A good signal that the market may want your product - potential customer who tried internally to build a rudimentary version of what you are building;
  • End every meeting with a potential customer with clear next steps, the next call, meeting, etc.;
  • Building a research-driven startup requires non-research expertise in product management, marketing, sales, etc.