Prof Sabrina Maniscalco says quantum computing can solve real-world problems, but several challenges must be overcome first.
There has been a growing focus on emerging and deep-tech sectors such as AI and quantum computing. However, while they may be considered ‘emerging technologies’, they’re far from new.
Prof Sabrina Maniscalco has been working on quantum technology for more than 20 years. She is a professor of quantum information, computing and logic at the University of Helsinki and the co-founder and CEO of quantum computing start-up Algorithmiq.
The start-up aims to use quantum computers in drug development. It has a headquarters in Helsinki but it also now has an Irish subsidiary.
Algorithmiq is also one of several organisations that have been working with Trinity College Dublin (TCD) to form the Trinity Quantum Alliance, which was launched earlier this month to make quantum computing skills education more widely available.
Maniscalco was in Dublin for the launch of the Trinity Quantum Alliance and, before hopping on a plane, she spoke to SiliconRepublic.com about her work and how quantum computing can stand to benefit the life sciences and medical industries in particular.
‘We have models that are oversimplified to understand something which is very complex’
“My specialty is in handling, characterising and countering the imperfections arising from noise,” she said.
Noise refers to any unwanted disturbance or interference that affects the stability of quantum systems. It can come from interactions with the environment, such as stray electromagnetic fields, temperature fluctuations, material imperfections or other external interference.
“Because all quantum properties are very fragile and therefore, everything which is surrounding quantum devices is quickly destroyed by interaction with whatever is around it.”
Maniscalco now applies her knowledge to identify the most suitable use cases and best applications of quantum computing, one of which is simulating other quantum systems, for example molecules or materials to applications in chemistry, life sciences and material physics.
“So, what we will be able to do is to go beyond what is possible with any conventional computers by default in simulating these quantum systems because these systems are quantum by nature,” she said.
“It’s an interesting way of using computers … to simulate systems which are naturally quantum in a way.”
Quantum drug discovery
Once these naturally quantum-based systems can be simulated, the possibilities for applications can be revealed. Focusing specifically on the medicine and life sciences side of things, Maniscalco said her work is focused on drug discovery and development.
Bringing new drugs to market is believed to take anywhere between seven and 10 years – sometimes longer – and the cost for the pharma industry can be more than $1bn.
“But the number of new molecular entities that are brought to market as new drugs remains constant over the years, so clearly there is something that is stuck,” said Maniscalco.
“Many scientists from industry agree the real problem is the oversimplification of the cell biology. So, we have models that are oversimplified to understand something which is very complex.”
She said much of the process will still require more classical tools and technologies, including machine learning and AI. However, the “bottleneck” currently present in the drug-development process is really the calculations and simulation at the microscopic level.
“This is where quantum computers will be providing what is impossible to do classically and therefore will allow, for example to explore the chemical compounds space that is mostly undiscovered at the moment because it’s so vast,” she said. “It is estimated to contain a 10 to the 16th molecules at the moment. This is a number impossible to describe.”
Ongoing challenges
While the true power of quantum computing is still emerging, it faces many limitations and challenges, mainly from an engineering and software-development perspective.
“One of the major challenges is, what I called before, ‘the noise’,” she said. “This is because all function properties are very fragile. So they tend to be very easily destroyed unless the systems are in very high isolation.”
While there is software and algorithms that have been developed to mitigate errors and help to solve these problems, Maniscalco said development needs to be ongoing in order for these algorithms to be scalable and tackle larger problems.
This is accompanied by an engineering problem, she said, because engineers will need to create chips, quantum devices and the very building blocks of these devices in such a way that they will be less subject to these errors.
‘We still need highly specialised and very well-trained people to run the quantum computers’
Another major roadblock to quantum technology and perhaps all areas of emerging tech is the skills shortage, especially in niche areas that are still in their infancy.
“We still need highly specialised and very well-trained people to run the quantum computers and even to develop software and hardware design. You need really PhDs and master’s in quantum science and technology and it’s very multidisciplinary, so of course you need them to collaborate with many other highly skilled personnel and from other fields,” said Maniscalco.
She said that the industry already knows it doesn’t have enough workers in the field, and this is why master’s degrees in the area of quantum science and technology are so important.
She called out the work TCD has been doing in this area. In 2021, it teamed up with Microsoft to accelerate advances in quantum tech, with Microsoft agreeing to fund PhD researchers working in the area.
In September 2022, the university signed a memorandum of understanding with tech giant IBM to expand their existing collaboration on education and research activities in areas such as quantum, AI and security.
Maniscalco said her company Algorithmiq hired three interns who completed the master’s degree in quantum science and technology at TCD. Now, they are working towards an industrial PhD at the start-up.
“This is an example of how you can really in some way bring together academia and the start-up world.”
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