mRNA science has shown the power of using an operating system framework for drug discovery and development with the successful COVID vaccine developments from Pfizer and Moderna. Integrating technology into the drug design process introduces unparalleled speed and flexibility. Kuano is using AI, quantum chemistry, and medical science to focus on enzyme reactions, a key factor in drug development, to develop novel therapeutics. The company is able to model enzyme reactions with unprecedented specificity allowing the drug makers to acquire the building blocks for pharmaceuticals that will address some of our most pressing and challenging diseases.
London TechWatch caught up with Cofounder and CEO Vid Stojevic to learn more about how the Kuano changes the paradigm of drug development, the company’s strategic plans, recent round of funding, and much, much more.
Who were your investors and how much did you raise?
We have raised £1 million in seed funding. The investments come from ACF Investors, o2h Ventures, and a syndicate of Cambridge, London and UK-based angel investors. The lead investors and most of the angel investors are from a biotech background, but we also received support from investors with technical, AI, and quantum computing backgrounds.
Tell us about your product or service.
Our mission is to design better drugs by using advanced simulations of quantum chemistry alongside AI. We are building a hybrid biotech / AI company through a combination of internal and collaborative drug design projects.
The approach we are developing is to use state-of-the-art technologies to accelerate and refine an approach known as transition state analogue design. This approach is based on the concept that enzymes make use of incredibly tightly bound states to accelerate chemistry. These states are defined by subtle quantum chemistry and are known as Transition States. Every enzyme is shaped by its environment and evolution to use a unique Transition State. Most drugs targeting enzymes block their function by binding to the same site as the input chemicals meaning that this configuration can be used as a template for drugs with incredible strength and specificity (and hence lower toxicity). As 40% of all marketed drugs target enzymes, this is a highly attractive method to design new therapeutics. We use quantum simulations to model the enzyme reactions and AI approaches to generate stable chemicals that mimic the Transition State.
How is it different?
Standard AI-based drug design approaches rely upon large quantities of data with the standard approach is to take information from previous binding experiments.
What market you are targeting and how big is it?
Enzymes represent the largest class of drug targets, with over $40 billion of pharmaceutical sales attributable to small molecule inhibitors of enzymes each year.
What’s your business model?
Our aim is to develop pre-clinical drug candidates for challenging disease targets using our computational platform as well as domain expert input, and sell these to Pharma and Biotech companies.
How has COVID-19 impacted the business?
Kuano was founded in February 2020, just as the pandemic was starting, and we have been working virtually since then. We have also not met most of our investors in person yet. The journey would have been significantly different in a pre-pandemic world.
What was the funding process like?
COVID meant that the process was almost entirely virtual. The funding opportunities were favourable for the biotech sector overall but less favourable for very early-stage companies like ourselves, which was a challenge we had to overcome.
Our focus was on biotech investors, as we felt that this was the optimal way to accelerate our growth towards becoming a fully-fledged asset biotech company. Since our core USP is based around a technical proposition, we had to build confidence with biotech investors and demonstrate the potential that the tech has in the enzyme drug design space. Ultimately, I believe that it is a unique technical proposition supported by a strong core interdisciplinary team, together with a business plan focused towards a commercially attractive direction (small molecule enzyme inhibitor design), that was key to unlocking investment.
Since our core USP is based around a technical proposition, we had to build confidence with biotech investors and demonstrate the potential that the tech has in the enzyme drug design space. Ultimately, I believe that it is a unique technical proposition supported by a strong core interdisciplinary team, together with a business plan focused towards a commercially attractive direction (small molecule enzyme inhibitor design), that was key to unlocking investment.
What are the milestones you plan to achieve in the next six months?
Run two internal projects, and achieve early validation through a co-development deal with a Pharmaceutical or a biotech company.
What advice can you offer companies in London that do not have a fresh injection of capital in the bank?
London has a huge number of resources to help with the process: accelerators, incubators, investors, government agencies, university support, embassy agencies to help with expansion into other countries. Investigate what’s relevant for the sector, and tap into them.
What’s your favourite outdoor activity in London?
Exploring London parks and playgrounds with our 4-year-old (during lockdown).
