Live COVID-19 Cases
  • World 595,494,252
    Confirmed: 595,494,252
    Active: 20,035,981
    Recovered: 569,002,970
    Death: 6,455,301
  • USA 94,691,741
    Confirmed: 94,691,741
    Active: 3,713,554
    Recovered: 89,915,838
    Death: 1,062,349
  • India 44,268,381
    Confirmed: 44,268,381
    Active: 117,508
    Recovered: 43,623,804
    Death: 527,069
  • France 34,234,005
    Confirmed: 34,234,005
    Active: 602,921
    Recovered: 33,477,955
    Death: 153,129
  • Brazil 34,171,644
    Confirmed: 34,171,644
    Active: 544,141
    Recovered: 32,945,953
    Death: 681,550
  • Germany 31,535,343
    Confirmed: 31,535,343
    Active: 1,171,945
    Recovered: 30,217,700
    Death: 145,698
  • UK 23,420,826
    Confirmed: 23,420,826
    Active: 211,052
    Recovered: 23,023,687
    Death: 186,087
  • Italy 21,509,424
    Confirmed: 21,509,424
    Active: 867,064
    Recovered: 20,468,258
    Death: 174,102
  • Russia 18,907,231
    Confirmed: 18,907,231
    Active: 372,566
    Recovered: 18,151,487
    Death: 383,178
  • Spain 13,294,139
    Confirmed: 13,294,139
    Active: 276,103
    Recovered: 12,906,369
    Death: 111,667
  • China 235,670
    Confirmed: 235,670
    Active: 5,873
    Recovered: 224,571
    Death: 5,226
Generic selectors
Exact matches only
Search in title
Search in content
Generic selectors
Exact matches only
Search in title
Search in content
covid free office

BY Shadine Taufik


Isomorphic Labs – Google’s Latest Biotech Venture

Google’s parent company Alphabet launches an AI-powered drug discovery firm. Isomorphic Labs reimagines the entire drug discovery process.

JANUARY 14  2022


Google’s parent company Alphabet has recently launched Isomorphic Labs, a venture utilising AI in its drug discovery practises.

The DeepMind AI system, which was developed by another subsidiary of Alphabet, will be used to power this discovery.

Announcing the plans in November of last year, Founder and CEO of both Isomorphic Labs and DeepMind, Demis Hassabis, published a blog post on the new company’s website. He wrote:

‘I’m thrilled to announce the creation of a new Alphabet company – Isomorphic Labs – a commercial venture with the mission to reimagine the entire drug discovery process from first principles with an AI-first approach and, ultimately, to model and understand some of the fundamental mechanisms of life.’

In the past, DeepMind has been used to rival the world’s champions in Go, an abstract strategy board game, with their AlphaGo machine. Their AlphaZero was also able to trump other powerful computers in chess, go, and shogi (Japanese chess) after playing itself for a few days, through AI reinforcement learning.

Unlike IBM Watson or DeepBlue, which were created for specific purposes, DeepMind is purportedly versatile and utilises its neural network to learn from experience, as opposed to being programmed.

Most recently, and perhaps most pertinent to Isomorphic Labs, was DeepMind’s AlphaFold2, which provided a solution for a 50-year long scientific challenge of protein folding. It enabled the prediction of the 3D structure of a protein through amino acid sequencing, down to atomic-level accuracy.

Likening natural systems to technology, Hassabis expounded:

‘At its most fundamental level, I think biology can be thought of as an information processing system, albeit an extraordinarily complex and dynamic one. Taking this perspective implies there may be a common underlying structure between biology and information science – an isomorphic mapping between the two – hence the name of the company’.

How does drug discovery currently work?

Drug discovery is currently an arduous, manual process. In the UK, it takes 10-15 years for a drug to get approved. Additionally, a mean of around £228,000 to £2 billion is required to discover and develop these new drugs. In the UK, only 1 or 2 of 10,000 compounds tested are cleared for commercial use.

In the UK, there are four main steps taken to introduce a new drug into the market.

Preclinical research occurs before testing, and biological knowledge of the illness being treated should be garnered, and extensive research is carried out. In the past, drugs were found by chance through the active ingredients in traditional medicines. However, with the current technology, scientists are able to pull from chemical libraries, and test compounds through reverse pharmacology – helped by the sequencing of human DNA. This compound is first tested on cells, then animals.

The first step, Phase I, tests the drug on a small group of healthy human volunteers, which will allow scientists to test for dosages and preliminary reactions.

Phase II consists of testing on subjects with the illness that can be treated with the drug. Lab studies may be done with placebos. This is done with a larger group of people, over the course of a few months, or even years.

If the prior stage is successful, Phase III involves testing on hundreds of participants worldwide, to ensure that results are seen in a diverse group of patients. This will take even longer, as it monitors how people react to the drug over time.

The last step is licensing, which is led by the regulatory body of the country. For England, Wales, and Scotland, this is the Medicines and Healthcare products Regulatory Agency (MHRA).

Although scientists have large libraries of genomic and chemical data to pull from when discovering and developing new drugs, the process of creating these combinations during the preclinical phase is time and resource-intensive. This is where AI comes in.

AI in drug discovery

AI is extremely adaptable and every year programmers are finding new ways to utilise it and optimise processes. Especially with neural networks such as DeepMind, the possibilities are endless – these digital ‘brains’ can interact with data from any field, and create effective strategies or fix any problems that arise. The computing power, unlimited information, and tirelessness are some of the main reasons why AI can be so effective. Menial, repetitive tasks can be done accurately and more swiftly than human workers. This technology is most useful in the preclinical stage.

In drug discovery, computers can scan libraries containing biological and chemical data, and suggest the most compatible compounds for testing – AI could completely automate idea formulation. Additionally, experiments can be digitally modelled for accuracy before being conducted in real life.

During experimentation, robots can be programmed to adhere to strict lab protocols, such as the stirring or shaking of chemicals a precise number of times.

Additionally, all manners of data can be captured without errors, such as temperature, humidity, quantities, and timing.

Each experiment can be analysed for efficacy – having a digital track record of experimentation makes the process much more manageable for researchers.

Isomorphic Labs is also planning on modelling more biological processes to better understand how these drugs affect patients.

Hassabis explained:

‘AI methods will increasingly be used not just for analysing data, but to also build powerful predictive and generative models of complex biological phenomena.’

Future promise

Accelerating drug discovery, Isomorphic Labs promises to aid in finding cures for some of mankind’s most devastating diseases. This marks a new era in man-machine modelling, new developments in AI provide a promise of better healthcare and further innovations in medicine. Although there is not much to be known yet about their future endeavours, the company will undoubtedly spur a paradigm shift within the industry.

As the Isomorphic Labs CEO concluded:

‘Biology is likely far too complex and messy to ever be encapsulated as a simple set of neat mathematical equations. But just as mathematics turned out to be the right description language for physics, biology may turn out to be the perfect type of regime for the application of AI.’



About the Author: Shadine Taufik

Shadine Taufik is a contributing Features writer with expertise in digital sociology and culture, philosophy of technology, and computational creativity.

Recommended for you

BAME Nurses Speak Out on Pandemic Racism

A new report and documentary expose the realities of racism experienced by BAME nurses with the hopes of building a more compassionate NHS.