In 2022, the drug discovery market was valued at US$ 55.46 billion, and by 2032, that figure is expected to be more than double at US$ 133.11 billion. This is a huge sum of money, however, after events like COVID-19, we now know that time is equally crucial in the drug discovery sector.
With the discovery of novel drugs taking up to a decade, and costs of development on the rise, quantum computing can have a significant impact in this space. In terms of quantum use cases, the development of broad spectrum antiviral medication will see direct benefits. The pharmaceutical industry is becoming increasingly digital, aiming to optimize and maintain processes throughout the development life cycle to cut down on time and resource costs, aligning with the advent of novel computational technologies.
What are the realistic quantum benefits for life sciences?
First, the discovery of drug compounds with quantum computers will take noticeably less time than on a classical business computer, compressing research to generate quality leads from years to a few months or weeks.
A core activity of pharmaceutical companies is the development of therapeutics that will treat or cure challenging diseases. Classical computers are limited in calculation power, and predicting accurate molecular behavior could take years to accurately compute. Quantum computing can significantly reduce early drug discovery and optimize the development cycle, reducing time to the clinic significantly.
Quantum computing is ideally suited to optimize this process, with the biggest advantage of quantum computing is an increase in the precision of calculations beyond that of any classical computer. Meaning the quality of compounds designed computationally will improve.
Additionally, in 2019, pharmaceutical companies spent over 15% of their revenue on R&D, with some even spending over 20%. The R&D process involves identifying specific molecules to be optimized, and screening thousands of molecules and then testing in controlled conditions, which can take years. Ensuring the input molecules are of better quality is therefore paramount.
Head of Strategic Alliances at Kvantify.
Drug discovery involves multiple stages, and the time and costs vary between each, but the average cost of bringing a new drug to market is $1.3bn. The potential to cut costs is huge. Yet, despite all this, only 10% of drugs eventually make it past the testing phase in the end.
Quantum will be able to significantly boost research and development in drug discovery, but optimization of clinical trials and minimizing the risk of costly failures will reap benefits too. During drug development, pharma companies sometimes take trial-and-error approaches because the speed of doing this outweighs the cost of waiting for current classical computing calculations to occur. Quantum computers are able to much more rapidly and accurately generate predictive data, reducing time, eliminating guesswork and thereby cutting costs.
What are the barriers?
Nevertheless, while quantum computers are on the rise, there are still a number of barriers that prevent companies from adopting quantum computers.
Firstly, integrating quantum computing with the existing IT infrastructure is a complex task. Despite being more advanced, quantum computers are developed separately from classical computers, which makes integration more difficult.
Secondly is the lack of talent. Many businesses do not have the expertise to integrate the technology into their workflows, making quantum adoption much more difficult. Talent is limited in the quantum space, and the supply chain is too narrow to meet demand. Once talent is on board, it may take years to develop an understanding of quantum on the business, making early adoption much more crucial.
Finally, quantum computing is currently in the development stage, and quantum hardware is subject to noise and error, making algorithms intractable for current and near future devices. The development of new methods and algorithms that account for current noise and error will help mitigate measurement overheads.
When to invest in quantum computing?
Quantum computers are still in their early stage and there are barriers and hurdles to business use, but that doesn’t stop companies from investing. Quantum is expected to see an operating income of up to $850 billion by 2050, and will be a large enabler for drug discovery, financial market pricing and AI and ML.
The life science sector is among the industries who will likely see early quantum impact and record investment. While attracting and training talent may take years, the long-term benefits stand to gain with top sectors potentially gaining $1.3 trillion in value by 2035.
Taking this into consideration, it is important for businesses to invest into quantum as early as possible. Getting past barriers such as recruiting relevant talent and integrating systems takes time. Taking action now will give early adopters a head start for tackling these complex problems.
Additionally, quantum research is constantly evolving and demonstrates many long-term benefits in the life science sector. For example, quantum algorithms such as Kvantify’s FAST-VQE, which is designed to perform complex chemistry and find the energy in a chemical system, are already being developed today and show great promise for the future.
Overall, it is important for companies to start investing into being quantum ready now so we don’t experience a gap between solutions being ready and businesses being unable to take advantage. Additionally, it’s worth noting there are quantum companies out there who are business-first, and can help businesses who lack the resources or talent.
Early investment in talent and infrastructure will see significant returns, including revenue gains/ savings and time saved, as quantum computing develops further, widening the gap between quantum adopters and classical computing companies. With investment on the rise, particularly in the life sciences and drug discovery sector, it is becoming more important than ever for companies to invest to prevent themselves from falling behind competition, or even to get ahead.
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This post originally appeared on TechToday.