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?
What is quantum computing?
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.
Why is it better than normal computing?
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.
How is this going to impact pharma?
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 s...
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