Solution

The promise of quantum in life sciences

In an industry dominated by experiment, the ability to simulate, optimize, and orchestrate processes or portions thereof within the drug discovery lifecycle has the power to cut timelines, lower costs, and reduce the rate of failures.

Quantum holds great promise within the life sciences industry, with potential applications for technologies such as quantum computing and quantum sensors. Research from the Capgemini Research Institute on behalf of Capgemini’s Quantum Lab identified that one in five energy, chemicals, and life sciences organizations are already implementers of quantum technologies – launching experiments and pilots, and achieving early results.

Quantum computing provides a way of solving problems requiring complex optimization, simulation, or machine learning. So, the more pharma companies can optimize the drug discovery and development process and use in silico techniques to augment or replace laboratory assays, the more quickly they can identify and optimize lead molecules and commit to strong drug candidates.

High-potential use cases for quantum computing, using quantum algorithms, include accurate simulation of drug molecules and their interaction with biological targets, optimizing the design and development of new candidates, and optimizing the manufacture and supply of new products. Improving the accuracy of output reduces computation costs and is faster.

Applications in diagnostics and security

Quantum sensors, providing unprecedented precision in measurement, are already being deployed in healthcare/diagnostics sectors in areas such as biomedical imaging and could, as the technology develops, advance the understanding of neurological diseases, such as dementia and Parkinson’s.

Quantum has great potential in another dimension: life sciences and research organizations require highly secure data transfer for operational, clinical, and trial data. For this reason, companies need to anticipate post-quantum encryption technologies and embed crypto-agility into the design of future processes and applications.

While quantum technology is still nascent, some pharma majors are pushing ahead, and, for example, exploring how quantum approaches would potentially scale in the future. The time is now for companies to develop a strategy that will allow them to harness the power of this technology as it matures.

Capgemini is well-placed to support life sciences organizations in their quantum journey. Our dedicated Quantum Lab is a global network of quantum experts, partners, and specialist research facilities, running research programs and developing capabilities aimed at the advancement of quantum technologies. We work with our life sciences colleagues and our long-term partner IBM, helping to equip life sciences companies with the technology, skills, and strategic capabilities they need to develop and deploy an early-stage quantum roadmap.

Click here for more information on Capgemini’s work in the life sciences sector.

What if … quantum could transform the drug discovery lifecycle?

Meet our experts

Andrew Alderman

Andrew Alderman

Director Life Sciences, Hybrid Intelligence, Capgemini Engineering
Andrew focuses on the connection between life sciences R&D, technology, data and innovation. He has worked with clients from across the life science industry for over 22 years, supporting them on their path to becoming more data driven.
Julian van Velzen

Julian van Velzen

Head of Capgemini’s Quantum Lab
As the central coordinator for quantum and quantum-safe technologies at Capgemini, Julian van Velzen also leads Capgemini’s Quantum Lab. This global network unites experts, partners, and facilities to drive forward quantum innovation. Julian directs the research agenda and oversees the successful delivery of client projects. With a foundation in condensed-matter physics, he actively contributes to the broader CTIO community.
Phalgun Lolur

Phalgun Lolur

Scientific Quantum Development Lead
Phalgun leads the Capgemini team on projects in the intersection of chemistry, physics, materials science, data science, and quantum computing. He is endorsed by the Royal Society for his background in theoretical and computational chemistry, quantum mechanics and quantum computing. He is particularly interested in integrating quantum computing solutions with existing methodologies and developing workflows to solve some of the biggest challenges faced by the life sciences sector. He has led and delivered several projects with partners across government, academia, and industries in the domains of quantum simulations, optimization, and machine learning over the past 15 years.

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