Sarah HardingDecember 17, 2021
Tag: Quantum computing , impact pharma
The topic of quantum computing just keeps on cropping up. There doesn’t seem to be any sector that isn’t enthralled by the potential that the quantum revolution will bring – and pharma is no different. But what is quantum computing? Why is it so much better than ‘normal’ computing? And how is it going to impact pharma… really?
You might have heard of quantum mechanics. This relatively young branch of physics deals with the mathematical description of the physical properties and nature of atoms and subatomic particles. However, very strange things can happen at the subatomic level, so in order to simulate these properties, scientists needed to make calculations that can handle uncertainty.
Classic computers – even very large, co-called ‘super computers’ – are not very good at dealing with uncertainly. Classic computers use binary data – millions of bits in combinations of ones and zeroes or, to put it another way, in combinations of ons and offs. But the universe doesn’t work in terms of just being on or off. Our existence and our environment are fluid – uncertain – and classic computers are unable to hold, compare and analyze simultaneous complex, uncertain real-world problems.
Therefore, in 1980, US physicist Paul Benioff offered the first theoretical possibility of a quantum computer. Instead of bits, quantum computers would use qubits. That means that the combinations used could be more than just on or off. Qubits could also be in ‘superpositions’ where they are both on and off at the same time, or somewhere on a spectrum between the two.
Estimates suggest that quantum computers are about 100 million times faster than any classical computer available today. As well as solving problems faster, that means they would require significantly smaller physical and energy footprints than current super computers.
However, it’s about more than just speed. Thanks to their ability to deal with ‘uncertainty’, quantum computers can generate highly complex simulations that would not be possible with classical computers. They can simulate quantum properties in molecules, for example, or complicated molecular reactions. With qubits, quantum computers can create vast multidimensional spaces in which to represent very large problems. Algorithms are then used to find solutions in this space, and translate them back into forms we can use and understand.
To put it more simply, the best analogy I have found is this:1 if you asked a classical computer to find its way out of a maze, it will try every single branch in turn, ruling them all out individually until it finds the right one. A quantum computer can go down every path of the maze at once. It can hold uncertainty ‘in its head’ and find a faster, better solution by analyzing multiple uncertainties, all at the same time.
Quantum computers could be applied wherever a large, uncertain, complicated system needs to be simulated. That could be anything from predicting the financial markets, to improving weather forecasts, or modelling the behaviour of individual electrons.1 Quantum computing has the potential to disrupt entire industries, from finance to cybersecurity, to healthcare and beyond.
While quantum computing may benefit the entire pharma value chain, from discovery, through development, and across production and delivery, its primary value is expected to lie in R&D.2
As stated previously by Brian Martin, Head of Artificial Intelligence in R&D information Research at AbbVie,3 “For most problems in computational chemistry for drug development, classical computing is sufficient, but there are situations where there are limitations. What we haven’t been able to do [until] now as an industry is pinpoint among those computationally limited problems which ones are amenable to resolution by quantum computing.”
Given its focus on molecular formations, pharma as an industry is a natural candidate for quantum computing. Quantum computers are especially well suited to molecular simulations – all molecules are based on quantum mechanics, so quantum computing should be able to predict and simulate the structure, properties and behaviors of drug molecules. This should enable computational tools for drug design and discovery, and for providing a ‘tool set’ of molecules that might be best suited to solving a particular medical problem. This could involve the design and optimization of protein therapeutics, or predictive algorithms to generate human-relevant data. If you want to know more about quantum computing and its impact on pharma, Pharmasource would be your best choice. It a professional platform providing the lasted information on phama and pharma companies.
In summary, within pharma R&D, quantum computing could significantly enhance:2
· Disease understanding and hypothesis development
· Target finding
· Hit generation and identification
· Lead generation
· Optimization of candidate properties
· Pharmacokinetic and toxicity predictions
· Dosing and solubility optimization
· Patient identification and stratification
· Pharmacogenetic modelling
· Casualty analysis for side effects
· Data management.
Beyond R&D, quantum computing could bring further value in terms of improving production processes, with optimization of catalytic processes or product formulations, quality monitoring and predictive maintenance.2 Logistics and supply chains could be improved with better routes and networks, or dynamic inventories and procurement approaches. Quantum computing could even help with advanced forecasting for market demand, patient understanding, tailored or personalized care, patient engagement, and automatic treatment recommendations.
In summary, pharma is a perfect case for quantum computing. In particular, it will help researchers find the molecules most likely to succeed, dramatically reducing the current 90% fail rate of drugs reaching the clinical trial phase. Such is the promise of quantum computing in pharma, that in 2019 the heads of digital research technology at some of the world’s top drug companies formed QuPharm, the Pharma Quantum Computing Working Group, to share the risks and rewards of quantum computing in pharma.3
Despite all of the excitement, we still have a while to wait before quantum computers can do all the things they promise. Right now, the best quantum computers have about 50 qubits. That’s enough to make them incredibly powerful, but they are not yet reliable – they have extremely high error rates. Even once those reliability issues are resolved, it will take time to develop commercial quantum computers, and to apply the technology in commercially useful ways.
Any company that has undergone a digital transformation will know how painful and time-consuming such initiatives can be. While the effort is invariably worth the input, in terms of improved efficiencies, better productivity, enhanced connectivity and visibility, and so on, just consider – if a digital transformation using just classic computers can be challenging, how much more challenging could it be to transform from classic to quantum systems?
Michael Guilfoyle, Vice President – Consulting at the ARC Advisory Group4 is an expert in digital transformations. The move to quantum computing seems to me like the supreme digital transformation, so I asked him what he thought.
“Given that quantum computing is still neither well understood nor commercially viable, it’s worth taking a step back for a moment when thinking about practical applications and the timeline for achieving them,” he advised. “People always want to make digital transformation about data and technology, but it’s about neither, really. At its heart, successful digital transformation – whether it’s quantum computing or any other technology – relies on people that are very good at identifying business outcomes and then uncovering the problems that impede those outcomes. Once that is done, then the technology and data become important, as they are the keys to how those problems get solved and the outcomes ensured.”
He’s right, of course. The promise of quantum computing is astounding. However, before organizations lay the foundations for quantum-based systems, they need to first consider any changes they might need to make. A clear understanding of goals, and a pathway for how quantum computing will help reach those goals, is critical, as is a realistic appreciation of the impact the transition will have on people, products and processes.
If you’re dreaming of quantum pharma, odds are that one day, in the not too distant future, your dreams will start to come true. It will take a while before the first commercial quantum computers are widely available, and it will take longer still before the impact on pharma is seen. However, that gives you time to figure out exactly what you want quantum to do, and how to uncover the problems that stand in your way to achieving those goals. With that exercise complete, you’ll have a far better chance of being at the head of the line when it comes to finally realizing the value of quantum computing in pharma.
1. Katwala A. Wired UK, March 2020 (https://www.wired.co.uk/article/quantum-computing-explained).
2. Evers M, Heid A, Ostojic. McKinsey & Company, June 2021 (https://www.mckinsey.com/industries/life-sciences/our-insights/pharmas-digital-rx-quantum-computing-in-drug-research-and-development).
3. Mullin R. Chemical & Engineering News, September 2020 (https://cen.acs.org/business/informatics/Lets-talk-quantum-computing-drug/98/i35).
4. ARC Advisory Group: https://www.arcweb.com
Sarah Harding, PhD
Sarah Harding worked as a medical writer and consultant in the pharmaceutical industry for 15 years, for the last 10 years of which she owned and ran her own medical communications agency that provided a range of services to blue-chip Pharma companies. She subsequently began a new career in publishing as Editor of Speciality Chemicals Magazine, and then Editorial Director at Chemicals Knowledge. She now focusses on providing independent writing and consultancy services to the pharmaceutical and speciality chemicals industry.
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