Earlier this month we posited the idea that 2021 could be the year of quantum computing-led drug discovery and predicted that partnerships like those of Google and European pharma giant Boehringer Ingelheim would be more common with more quantum hardware makers tying the knot with drug manufacturers.
Today we saw another example of progress in quantum drug discovery with Roche partnering up with Cambridge Quantum Computing on next-generation quantum algorithms for early-stage drug discovery and development. This is not just a one-off partnership for good press; it’s a multi-year collaboration agreement based on further refinement and use of Cambridge Quantum’s EUMEN platform for quantum chemistry.
Cambridge Quantum has published widely in the area of quantum chemistry and has made a number of quantum chemistry hires, adding to its existing team of over 70 quantum computing and application area specialists. The company has backing (including a $45 million round from investors, including Honeywell Ventures and IBM Ventures, among others) to continue hiring and pushing for broader relationships in the pharma industry. From their hiring efforts it is clear they are in need of quantum chemistry PhD candidates for engineering positions.
While it is possible to plow through Cambridge’s published works for some insight on how their EUMEN platform for development actually works, details are scant, likely because each customer has code and workflow-specific requirements. They describe EUMEN as a “complete package to facilitate the design of pharmaceuticals, specialty chemicals, performance materials, and agrochemicals” but the research work is based on highly customized methods. Nonetheless, this may be what quantum algorithm will take for the years ahead—in other words, there’s no “easy path” to quantum code development, only the outsourcing of complexity.
Roche has been proactive about exploring quantum computing for its early drug discovery efforts. They have been collaborating with the University of Oxford on exploring the limits of quantum simulations and have a division called Roche Partnering that will allow them to look at possible partnerships with companies with hardware and software resources while in turn providing them with what they might not have; an in-depth understanding of applications, workloads, and main drivers for what they’ll need out of future quantum algorithms and systems.
Mariëlle van de Pol, Global Area Head, Technical Solution Delivery & Architecture, Pharma Research and Early Development at Roche says that quantum possibilities are part of a “big wave” coming for their industry.
“One of the most promising applications is the simulation of molecules and their chemical behavior, which would enable faster and more precise development of new medicines. Quantum technology could also be used for quantum-powered neural networks in machine learning, allowing us to solve optimization problems, for instance in protein folding. In biomedical image analysis, quantum computers could help detect topological changes that are caused by the disease. And there are many other applications beyond R&D, for instance in production, finance and IT.”
“We are scanning the horizon, waiting for the big wave, but we don’t know how big it is going to be, or when it will come. But if you see how much tech companies are investing in this topic, and how quickly the whole landscape is evolving, you realize that it will come and it will be a game-changer,” van de Pol adds.
As a side note, earlier in January when we discussed why 2021 would be a big year for quantum drug discovery, we emphasized the point that algorithms and software would be at the heart of important partnerships. At this early stage of quantum computing there appears to be “enough hardware” to choose from with roughly equivalent performance capabilities, despite a range of architectures, approaches, coherence times, and so on.
The real test is coming—can algorithms be developed efficiently enough to make the investment in hardware, cloud-based on on-prem, worth the trouble? That’s the question, and the value prop for companies like Cambridge Quantum, who can work across the quantum hardware aisles and choose the best architecture for their algorithms.
As yet another side note, for an in-depth analysis of where quantum computing might be first applied in pharma here is a peer-reviewed compendium of possibilities from a range of research leads at some of the world’s top drugmakers and biotech companies.
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