How AI Can Help To Revolutionise Drug R&D

By Richard Lord

The boss of not one but two biotech companies, Kingsley Leung is trying to make pharmaceutical development safer, faster and more efficient

Tatler Asia
Photo: Getty Images
Cover  Photo: Getty Images

The remarkable achievements of the scientists who discover, test and introduce new medications have been front of mind for many of us for the past couple of years. But the drug development process itself, which is famously very slow and very expensive, hasn’t really changed much in decades.

Kingsley Leung is trying to do something about that. The chairman of pharmaceutical R&D company Uni-Bio Science Group, he also heads Great Bay Bio, a company he launched in 2019 in order to introduce AI into the drug development mix, potentially halving the time it takes, as well as dramatically reducing the risks.

Leung was born in Canada but moved to Hong Kong as a young child when his parents, owners of a manufacturing business, set up operations in mainland China.

“That’s how I was exposed to business at an early age,” he says. “All my family talked about at the dinner table was business. I saw all the ups and downs, and how running a business is extremely stressful.”

He started his career as a banker focusing on the healthcare industry, for employers including Goldman Sachs and Merrill Lynch, and made the leap to actually working in the industry when his boss from Merrill established a biotech start-up in Singapore and asked him to join, given his understanding of both healthcare and finance. In 2014 he went to work for Uni-Bio, then owned by his uncle, and three years later took over the company. He then embarked on ambitious plans to reorganise it.

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Kingsley Leung. (Photo: Affa Chan)
Above  Kingsley Leung, co-founder and chairman of Great Bay Bio. (Photo: Affa Chan)

“We had an existing platform that didn’t fit the profile of Uni-Bio: it was an early-stage research centre, but everything it had developed had come to fruition, and it didn’t make sense any more within a listed company,” he says. “I said: why not privatise this and do something more fun with it? Some of the investors in Uni-Bio were very supportive. It was a chance to build something really innovative, and it would provide capital for us to fund later-stage products.”

That new company, finally launched two years later, was Great Bay Bio, and the innovation he mentions soon started to flow.

“We built it from scratch,” he says. “We started adding AI on top of a traditional biotech research centre. The idea is quite attractive, so we had a lot of new investors. It was a big gamble, but it’s starting to pay off.

“AI helps with a process called CMC: chemistry, manufacturing and controls. Essentially it’s the scale-up process. When you create a new drug, the first process is drug discovery. So you find something that, for example, stops cancer growth. Then you find a way of manufacturing it on a bigger scale, so you can take it to clinical trial.

“That’s not as easy as you think. If you’re making, say, toys, you can inspect what comes out, but how do you control the quality of something you can’t see? The idea of CMC is: if the inputs and processes are constant, the outputs will always be constant too.

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AI helps with a process called CMC: chemistry, manufacturing and controls. Essentially it’s the scale-up process
Kingsley Leung

“You know the inputs—they’re pretty standard—but the processes you have to slowly develop. It takes at least two years and it’s very expensive: $3 to 5 million traditionally. A lot of the work is just repetitive: which cells manufacture this protein the most? You have to screen 1-2,000 cells. AI creates a lot of certainty: using big data, you can create a model or algorithm that mitigates a lot of repetition and blind screening. With AI, we took pictures of cells and told it: the cells we want look like this, so there’s a higher certainty they’ll generate the protein at a higher rate.”

What all this results in is a CMC package that Great Bay Bio can sell to its customers, something they need in order to secure the regulatory approval needed to take a drug to the clinical trial stage. The AI element of it, he says, could have been very useful if it had been applied to Covid-19 vaccines.

“One of the big difficulties before vaccines could be rolled out was the manufacturing process: how do we scale up to treat the global population? Most of the vaccine scale-up was done through traditional means. When Covid-22 comes along, if we could use AI to scale up much faster than in the past, it would be a huge advantage and very disruptive of the industry.”

The biotech industry is a uniquely rewarding one to work in, though, even when it isn’t fighting imminent global threats, he adds. He gets to meet a lot of extremely smart people—but also, “being able to launch a product, even if it’s not a hot drug: the feeling is pretty cool”.


See more honourees from the Healthcare & Sciences category of the Gen.T List 2021.

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