While this new year might not mark the moment when the first drugs are discovered via molecular dynamics simulations running on a full-scale quantum, there are several signs that a number of important collaborations between the few quantum vendors and major biotech companies are announced.
This means more internal labs dedicated to refining relevant algorithms, which could spur the industry ahead in the quantum computing space. It also incentivizes the quantum hardware vendors to understand how potential high-value users will want to interact with their devices in terms of programmatic stack, on-prem, and via cloud interfaces.
This is all coming at an important time because so far, commercial use of quantum computing has been limited. The use cases there are for the most part are interesting but if put into production, would rarely justify the operational cost of a quantum computer. If the life sciences industry gets serious about quantum, the game is really on.
There have been a growing number of academic papers on the algorithmic sides of molecular dynamics and related algorithms and applications relevant to biotech, but the actual enterprise mission from the large pharma companies has been scant, lumping quantum in with other broad initiatives like AI integration, for example. In 2021 and ahead, however, the impetus and funding are in place, especially with COVID in the picture, for more forward-looking technologies that emphasize time to result—something that quantum computing has going, if it can be proven at reasonable scale and accuracy.
The interest in quantum for drug discovery is not just about hype, there are real potential solutions to some future problems traditional simulations might run into in the future, including scalability and computing capacity. While MD codes have impressive scalability on the world’s largest supercomputers, with quantum, there is (in theory) to the number of molecules that can be run through in a single simulation via quantum methods. Not only will the results be far delivered faster (nearly instant/wall clock time, the development of such algorithms has its own timescale) the limits of computational capacity would no longer be a constraint.
Just today, Boehringer Ingelheim, a large European research and drug discovery company (€19 billion revenue) became the first pharma company to partner with Google for quantum computing efforts. The drug discovery giant also created an internal lab to collaborate on how AI and quantum will integrate with their current pharma R&D plans.
“Extremely accurate modelling of molecular systems is widely anticipated as among the most natural and potentially transformative applications of quantum computing,” says Ryan Babbush, Head of Quantum Algorithms at Google. Therefore, Google is excited to partner with Boehringer Ingelheim to explore use cases and methods for quantum simulations of chemistry. Boehringer Ingelheim brings both an impressive quantum computing team and deep expertise in real world applications of these capabilities in the pharmaceuticals space,”
“Quantum computing has the potential to significantly accelerate and enhance R&D processes in our industry. Quantum computing is still very much an emerging technology. However, we are convinced that this technology could help us to provide even more humans and animals with innovative and groundbreaking medicines in the future,” Michael Schmelmer, Member of the Board of Managing Directors of Boehringer Ingelheim says. He adds that Boehringer Ingelheim is significantly increasing its investment in a broad range of digital technologies, encompassing key areas such as Artificial Intelligence (AI), machine learning, and data science to better understand diseases, their drivers and biomarkers, and digital therapeutics.
Early experiments are important for the burgeoning quantum industry but molecular dynamics simulations running on traditional high performance computing systems are set to be the norm for the next several years at the very least. The performance of these applications have increased dramatically with GPU and other accelerators, along with the scalability and efficiency.
Further, the results can be validated. If quantum is another “black box” with big promise but no reproducibility, its integration into MD/drug discovery workflows might only be relegated to finding a molecular needle in a haystack and passing the heavy lifting with reproducibility onto the supercomputers.
Still, time to market is everything in drug discovery. If there was a silver bullet for at least starting the search in the right spot, there’s nothing to be lost in exploring a new area like quantum.
Boehringer Ingelheim is in front of a trend we expect to begin this year. For now, however, most pharma companies include quantum as one of several emerging trends they’re paying attention to. Roche has a general article about quantum on its website. Novartis CEO lists quantum along with other tech trends like telemedicine and counts it is off on the horizon. Others have been quiet entirely on the subject.
So, in the spirit of a new year, we predict that we will see stake-in-the-ground quantum computing in-house quantum labs at Pfizer, Johnson & Johnson, Novartis, and Merck, among others. More specifically, these will be separate from AI focused R&D labs. While Google took the lead on Boehringer Ingelheim’s quantum collaboration, we expect to see IBM take a significant role in other commercial pharma collaborations.
Quantum computing has had quite a bit of credence in research and academia but the enterprise use cases have been relatively slim with questionable real-world application value and ROI—at least currently. If pharma comes out as the early adopter expect the entire quantum hardware market to explode sooner than anyone would have expected.
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