In this article, we will take a brief look at what is Quantum computing and how superposition is used in Quantum computing. We will also discuss a few Quantum computing applications in the healthcare industry and finally, we will look at the diagnostics.
Technology, from the invention of the transistor, all the way through to the first computer processor, has significantly impacted our way of life, with healthcare being no exception.
As we move towards a more focused, personalised health service, using the power of the genome, healthcare system providers must focus on developing systems with the ability to process huge amounts of data, empowering healthcare professionals to make accurate diagnoses and informed, health related decisions.
“Just as the 19th century was called the Machine Age and the 20th century the Information Age, the 21st century promises to go down in history as the Quantum Age.”
What is Quantum Computing?
The computers we use today process information sequentially, with a single ‘bit’ of information being a 0 or 1. This is the positive or zero electrical charge held by one of millions of tiny transistors within the atomic structure of a silicon chip. The computer makes calculations and remembers things by changing these transistors from 1s to 0s and vice versa. However, in the quantum world, this same information processing is done very differently. To try and explain, let’s think of this in terms of probability, using a household dimmer switch to visualise the probabilities involved. If you imagine a classic light switch, it can either be on or off, well that is how each silicon transistor works, there are only 2 options. If you then think of a ‘qubit’ (the quantum equivalent of a bit), as a permanently revolving dimmer switch with a range of probable states that the qubit can be in at any given time, it can be on, and off, and everything in between. One of the quirks of Quantum Theory is that the state of a qubit or a spinning electron, or indeed our dimmer switch, is not determined until we look at it, and looking at it will always change its state. What all this means is that the quantum transistor can hold a huge range of probability values, which in turn means it can carry out many more tasks and store many more pieces of information, making it far more powerful than a conventional processor. The qubits ability to be both a ‘1’ and a ‘0’ at the same time, is called a superposition. Computer scientists build algorithms that can take advantage of this state to effectively harness the power of the superposition. If all of this seems difficult to grasp, you are not alone. Top scientific minds struggle with these concepts too, especially as much of Quantum Theory is still just that, theoretical.
How is the Superposition used in Quantum Computing?
Taking this a step further, if we think of an electron as a wave, the superposition of this electron wave is its ability to exist in two possible states simultaneously. Electrons have a natural ability to spin up or down. Imagine pushing the spin of an electron into a superposition so it is spinning both up and down, by the rules of observation in the quantum world, it will collapse its superposition into either spin up or spin down when we measure it. This natural phenomenon allows qubits to be coded with quantum information in both states simultaneously. This ability to compute and select a solution out of many potential alternative solutions, means the qubit can be all of those options, all at the same time using the superposition, and in exponentially less time than a classical computer.
Quantum Computing Applications in the Healthcare Industry
Radiotherapy
Radiotherapy is one of the principal techniques used in cancer treatment today. Targeted radiation is used to destroy cancer cells and stop them from re-growing. It requires a highly accurate application of radiation to minimize the damage to the surrounding cells. The development of a ‘radiation plan’ is a complicated process that involves the processing of many thousands of variables to arrive at an optimal therapy plan. A classical computer does the job today using a limited set of data points to generate the plan in a clinically feasible timeframe. However, quantum‐inspired algorithms will allow medical systems to run all possible permutations simultaneously, using many more data points and develop an optimal plan, faster.
Accelerating Drug Development and Material Science
With the development of pharmaceuticals requiring lengthy and costly clinical trials, scientists and pharma companies are experimenting with using alternative methods to speed up the process and make it more cost effective whilst ensuring safety and efficacy. Artificial intelligence, human Organ-On-Chip and ‘in-silico clinical trials’ have all been tested. Quantum computing may prove a game changer here.
Today’s most powerful supercomputers only have the processing power to simulate the simplest of molecules, limiting their calculations to a small number of compounds present. For more complex molecules, researchers currently predict behaviour and then must test behaviour in trials. This is costly and inefficient, with most drugs failing the trial at this stage.
In future, we could be running algorithms and searches on quantum computers with the ability to review drugs at a molecular level with unimaginable speed and run drug trials with every possible permutation of compounds tested against cell models, all in a rapid timeframe. This would revolutionise drug discovery, making radical new treatments for Cancer and Alzheimer’s, amongst others, a real possibility.
Diagnostics
Artificial Intelligence
There is a growing trend to apply machine learning to patient diagnostics. Much of machine learning is about “pattern recognition”, with algorithms crunching large datasets of patient information to find patterns in the noise, the goal being to leverage comparisons leading to a diagnosis. Quantum computing promises a processing order of magnitude we have only been able to dream of thus far, for our healthcare systems, with doctors able to compare vast amounts of complex data, in parallel, with endless permutations.
Genomic Medicine
Using quantum computers, we can more rapidly sequence DNA and solve other Big Data issues in healthcare. This opens up the possibility of personalised medicine based on an individuals’ unique genetic makeup.
Protein Folding
Proteins are the basic building blocks of life. Malfunction of a given protein is frequently due to its being wrongly folded. While the chemical composition of proteins is quite well known, their physical structure is much less understood. Obtaining more detailed knowledge of the way proteins are folded can lead to the development of new therapies and medicines.
A quantum computer will, in theory, be able to simultaneously test a huge number of possible protein fold structures and identify the most promising ones.
Making Patients the Focus of Care
Soon we will see the application of health sensors, wearables and tiny medical gadgets that will collect vast amounts of data about patients that will be stored in cloud-based data lakes. Just for comparison: in 2020 the amount of digital data collected was roughly 10 times higher than it was in 2013. Given the amount of data requiring processing and the number of variables required to make sense of these datasets, quantum computers will play the pivotal role in patient surveillance through connected sensory systems. This revolutionary technology will move us from a responsive to a predictive healthcare system.
It would be remiss of me not to point out that these applications are still in their infancy and largely theoretical. However, there is in existence an ophthalmology app that demonstrates how a patient’s vision would change with a cataract over 5 years if they maintained their current lifestyle. Extrapolating this idea and by applying the principles of quantum computing, given huge amounts of health parameters, genetic information, sensory data, and other personal health information, an accurate prediction about a given person’s future health could be easily generated, providing insights and advice for future wellbeing.
History
- 27th April, 2021: Initial version
