Quantum Computing in Pharma: Current Developments

Disruptive technologies promise to make transformative impacts throughout the life sciences. Two of the largest current disruptors are Artificial Intelligence (AI) and Quantum Computing (QC). AI has seen applications from diagnostics, to drug discovery and data management and processing. QC, however, has had a slower impact – with the technology still in an earlier stage of its infancy, compared to AI. We explored its potential in drug discovery in a previous article; today, we will examine the moves that show that it is nevertheless here to stay in the wider research and development industry.

Accelerating Research

There are many ways through which quantum computing can massively speed up the pace of research for the life sciences. The most obvious one would be the huge computational leaps it could provide in screening virtual compound libraries, as well as enabling better modeling for drug-target interactions. Improvements in this area of drug discovery hold the potential to slash costs and development times, particularly through lowering the number of investigational products that make it through the first screening phases only to fail later on.

Another area with large transformative potential for QC is the area of in silico clinical trials. These would be clinical trials where the participants and treatments are essentially simulated. While in silico trials will not likely be replacing in vivo trials in the near future, they can provide a more cost-effective way to screen out compounds before pouring resources into in vivo trials for them. Additionally, they confer advantages in patient diversity and the elimination of other participant biases that are very challenging to balance with a traditional trial. The key bottlenecks in the design and implementation of in silico trials are the limitations of computational power and, consequently, the very high amount of highly specialized work that is needed to construct the models.

Quantum Partnerships

The other knock-on effect QC is expected to bring to the industry is one we have already observed with AI: the arrival of new actors to the field, who will bring considerable resources and expertise with them. These would be companies that specialize in the development of the technology – such as Google, Honeywell, and a host of QC startups – partnering with established pharma stakeholders to move the pace of research forward. We have already seen promising moves in this regard, which we will expand on here.

A particular example is the collaboration between Accenture and quantum firm 1QBit, through which the two companies developed multiple new frameworks for the evaluation of molecular structures. The resulting modeling algorithms were later put to the test with a partnership with Biogen, verifying that their QC-enabled platform for drug discovery was as good or better than existing methods for locating shared traits between compounds and predicting interactions. The developments are expected to deliver significant cost-savings for Biogen’s pipeline, which seeks to innovate novel treatments for a variety of neurological and neurodegenerative diseases.

POLARISqb has also made a name for itself in the quantum-driven drug discovery space. The company was one of the first to build their very own QC drug discovery platform, combining high-throughput quantum screening of chemical libraries with machine learning to fine-tune the remaining compounds. Their approach has taken off, with multiple recent high-profile partnerships across the industry. These include work with PhoreMOST for cancer therapies, as well as Allosteric Bioscience for products to prolong human longevity.  

Google also made headlines through its partnership with Boehringer Ingelheim, marking one of Google’s first forays into the pharmaceutical industry. The partnership seeks to investigate better applications for chemistry simulations, with Boehringer setting out clear strategies for the advancement of QC itself – including setting up its own Quantum Lab. Roche announced a similar partnership with Cambridge Quantum, for the improvement of quantum chemical simulations through Cambridge’s proprietary EUMEN platform, marking another high-powered collaboration in the field for reaching quantum advantage in pharma.

The Path to Quantum Supremacy

We have seen great growth in the adoption of the early technologies made possible through QC – yet it is important to remember that we have done little beyond scratching the surface of the possibilities that QC can provide. At present, our best QC tools consist of Noisy Intermediate Scale Quantum (NISQ) algorithms – which can work on as little as 50 to a few hundred qubits. In the future, as we build systems that can handle thousands of qubits, the computational power will rise exponentially. This will only come about with improvements in infrastructure – such as the super-cool facilities needed to house quantum computers, and advancements in computing hardware.

Additionally, the advent of QC also promises to solve other problems presented by the latest transformations in the life sciences. The gargantuan amount of data generated through novel Real World Evidence (RWE) technologies, multi-omics methods and smart technologies requires exceedingly smart experimental designs to fully use. QC could ease the interpretative burden by processing such vast volumes of data at much faster speeds. 

Another possibility, when considering smart and RWE-based technologies, is the possibility of predictive health using this data – the accurate estimation of a person’s future health and lifespan, which opens up multiple use-case scenarios (but also privacy concerns). Equally relevant is the possibility of QC to increase the security of data management through the use of quantum cryptography and key distribution. This is particularly important for patient records, but also manufacturing and supply chain data.

We see that the use cases for QC in the life sciences are nearly limitless. It is already starting to see a number of implementations in drug discovery-related partnerships, with multiple high-profile companies and startups making inroads to work with pharmaceutical companies. But the role of QC goes beyond drug discovery, with applications in data management, security and in silico trials also lying on the horizon. As the technology advances further and makes itself a more reliable presence in the IT space, we expect to see increased adoption in pharma – much as we did with AI. The combination of both AI and QC can also be highly synergistic, with each technology further enabling the other: the future of innovative computer technologies in the life sciences remains bright.

Join Proventa International’s Bioinformatics Strategy Meeting in Boston to hear more about the current progress of quantum computing in biopharma R&D, as well as participate in closed door roundtable discussions on the latest cutting-edge topics from throughout the field!