Kuano Raises £1.8M in Seed Funding to Accelerate Quantum Drug Discovery
• Led by Mercia Ventures, investors include ACF Investors, Ascension Ventures, o2h Ventures, Meltwind Advisory LLP and Angel investors
• Funds will enable further growth and validation of Kuano’s quantum simulation platform for enzyme targeted drug discovery
12 September 2023 -- Cambridge, UK -- Kuano, a drug discovery company combining quantum mechanics with AI to design the next generation of medicines, announced the close of its £1.8m seed funding round, led by Mercia Ventures and investors ACF Investors, Ascension Ventures, o2h Ventures, Meltwind Advisory LLP and other Angel investors. The investment will facilitate further validation of Kuano’s quantum simulation platform for the design of more effective drug candidates targeting enzymes, as well as continued company growth through strategic partnerships and recruitment.
Dysfunctional enzymes are implicated in many human diseases and are therefore a prevalent target in today’s drug market. However, until now, scientists have only been able to view enzymes in their ‘resting’ state and not in their fully functioning ‘dynamic’ states. As different enzymes may appear very similar in a resting state, drugs designed to target one may also affect others, potentially impacting drug safety and efficacy.
Kuano’s quantum simulation platform enables scientists to see and model enzymes in their dynamic state, opening new possibilities for more effective drug design. Combining these unique enzyme profiles with its suite of AI tools, Kuano can then predict the best structures with which to target them. Drug candidates designed this way are a precise match to the target enzyme, meaning that they are therefore likely to be more potent with fewer side effects. The platform has already been validated in three separate disease areas, including bowel cancer and lymphoma.
“Enzymes play a wide-ranging role in disease, but current technologies are unable to develop drugs to tackle most of them. Our team at Kuano recognised the need to overcome these limitations.” Vid Stojevic, co-founder and CEO, Kuano, said. “Our platform creates a ‘quantum lens’ that reveals the difference between enzymes and allows us to target each one individually, without affecting the others. This funding round will not only allow us to continue our laboratory work, but also to strengthen our management team and prepare the Company for scaling.”
Kuano was co-founded in 2020 by Drs Vid Stojevic, an expert in quantum physics and AI, David Wright, who specialises in molecular modelling and simulation, Parminder Ruprah, a highly experienced ‘drug hunter’, and Jarryl D’Oyley, an expert computational medicinal chemist. The latest seed funding brings the total investment raised by Kuano to date to £2.8m. In this round, Mercia was investing from its EIS funds, and Kuano was advised by venture capital advisory firm KPMG Acceleris.
Robert Hornby, venture capital investor, Mercia, added: “Fewer than 20% of enzymes have so far been targeted by drugs because of the difficulty in understanding their dynamic states. Kuano’s quantum simulation platform goes beyond existing AI models and means they can design drugs for previously ‘undruggable’ enzymes. The Company addresses a huge untapped market and has already attracted the attention of leading pharmaceutical companies. This investment will enable it to move to the next stage.”
Tim Mills, managing partner, ACF Investors: “We are excited to be working with Kuano as they go from strength to strength. Artificial intelligence and quantum computing will continue to have a staggering effect on the way the biotech industry operates and Kuano’s quantum capabilities will be a core part of this. We are truly excited to see what Kuano does next.”
Kuano is an artificial intelligence company using quantum simulations to create molecular design solutions to challenging enzyme targets. Enzymes represent the largest clinically and commercially validated class of drug targets. Over $40bn of pharmaceutical sales are attributable to small molecule inhibitors of enzymes and yet there is considerable demand for enzyme inhibitors with improved potency, selectivity or reduced susceptibility to resistance.