*We use the phrase 'data-driven health' as an umbrella term for any healthcare innovation where data is core. Innovations in TechBio, HealthTech, and BioTech can all fall under this category.
“We have more data on a single cell than ever before,” says Vishal Gulati.
Throughout his career, he has seen many once-impossible tasks become possible: determining all the base pairs of the human genome and predicting the 3D structure of proteins from their sequences were previously unfathomable. Crucially, Vishal has been a key player in translating these innovations into viable healthcare solutions, starting with his early contributions to the Human Genome Project and now investing in companies leveraging cutting-edge technologies like AlphaFold.
Vishal has been instrumental to KQ Labs since its inception and is now a valued member of our Steering Board. As co-founder of Recode Ventures, the world’s first specialist AI Healthcare VC firm investing in deep-tech healthcare solutions in the US and UK, he has significant insight into the evolving data-driven health innovation landscape globally.
Can you share a bit about your background and career journey?
From an early age, l was obsessed with being a physician. When I started practising medicine, I realised instead of just being the end user of science, I wanted to contribute to discovering and developing new treatments. To achieve this, I needed to get involved in research, so I pursued immunology, virology and genomics. Yet, even as a researcher, I felt that while I was creating new science, I wasn’t able to advance it through the entire pathway to becoming a new product.
I eventually transitioned from research to the Wellcome Trust, where I developed strategies for utilising data from the Human Genome Project, the initiative that mapped out all human DNA. While there, I realised the next stage of translation involved securing venture capital funding. Scientists generate thousands of ideas, but all ideas require capital to become commercially viable. In this way, my career has been a journey of following each step of the translational process.
It’s not easy to translate science: it’s a complex process, fraught with varying levels of risk at different stages and every time you move from one stage to next, you have to contend with a competence gap as well as a culture gap. Even after securing venture capital, many additional factors must align for success. As a venture capitalist, you have to accept that things won’t always go right. The best you can do is to learn from past failures and try to help people avoid making the same mistakes.
Can you elaborate on Recode Ventures and the innovation landscape at the intersection of deep-tech and health?
Recode Ventures encounters a range of fascinating companies, from in silico technologies developing new antibodies to generative AI innovations and targeted gene therapy.
In particular, we invest in two verticals: computational biology and cognitive automation. Most investments in computational biology enhance the pharmaceutical value chain by aiding drug development or enabling companies to develop drugs in-house.
Meanwhile, investments in cognitive automation technology reinforce the healthcare provision value chain, helping hospitals and clinics deliver care closer to patients more effectively. This means upskilling tasks, either performing jobs for people or making their work more efficient. A nurse could take on tasks typically done by a doctor, maximising the time doctors spend on more urgent matters. Similarly, a surgeon could be upskilled to perform surgeries more efficiently.
From a therapeutic perspective, oncology initially generated a lot of excitement in computational biology, attracting significant VC investment. Likewise, there is substantial opportunity in areas where the impact will be huge, such as autoimmune diseases, and in diseases with complex phenotypes and undefined target spaces. For instance, ALS and pulmonary fibrosis have poorly understood mechanisms, making target-based discovery challenging and opening the door for innovation.
Recode Ventures operates in both the US and the UK. How do the health innovation ecosystems in both regions compare?
Both the US and UK ecosystems are exciting and distinct. The US has a larger scale, with research funding around $400 billion, exceeding Europe's $350 billion. The UK, however, boasts strong university systems and a large enough population to benefit from them. Notably, two of the top ten pharmaceutical companies globally are UK-based, which helps the UK ecosystem perform better than expected. In contrast, the US pharmaceutical presence is larger but more concentrated in specific hubs. In the UK, from a smaller base, AI-based biology is more prominent, while in the US, much of the biotech funding is directed towards target-based discovery. Places like London have very strong convergence of AI and biology talent which is unique.
What challenges do startups face when trying to innovate in this space?
Start-ups in data-driven health face several challenges, with funding being a primary concern. There are always more great ideas than available capital, leading many excellent companies to struggle with raising funds and forcing them to evolve how they operate. Another challenge is that many TechBio companies must decide whether to remain platform-based or take their products or services directly to clinics. Maintaining platforms at scale and outperforming competitors is difficult, often causing companies to become target-based, which can limit their overall potential. Navigating this current landscape while staying forward-thinking is a tricky but critical task.
What is the future outlook for data-driven health?
Moore’s Law, coined by Intel founders upon noticing that the number of transistors on a chip doubled every 12 to 18 months, suggests that technological innovation grows exponentially rather than linearly. Although exponential growth in computing technology has been slow to influence biological innovation, we are now beginning to see its potential impact. Groundbreaking technologies like AlphaFold have accelerated numerous products. The tools at our disposal have significantly increased our cognitive awareness by providing unprecedented amounts of information. We have more data on a single cell than ever before, and this data-rich biology will enhance our understanding of biological complexity. In short, we are on the brink of exponential growth in this sector.
