• Articles
  • February 17, 2021
  • Gareth Morris

Genomics, AI & Data Science


According to the latest market research, the artificial intelligence (AI) healthcare market is expected to reach $27.6 billion by 2025. One area set to benefit from this growth of med-tech and AI significantly is genomics. 

Genomics explained

Genomics is the study of the body’s genes, including their structure, function, influence, how they act with each other, and how this affects our health. The more we understand about the body’s genes, the more we can revolutionise diagnosis, medicine, treatment and medical study. 

For example, genomics is helping medical science to find causes of rare genetic conditions, track and treat MRSA infection, understand why different cancers develop, and progress targeted therapies. Ultimately, genomics gives medical scientists the potential to predict and prevent disease. 

The UK leading the way

The UK is a recognised world leader in genomics. Last year, the UK-led 100,000 Genomes Project reached its goal of sequencing 100,000 whole genomes – a ground-breaking achievement that makes the UK the first nation to apply whole genome sequencing in direct healthcare. 

Technology had a tremendous role to play in this achievement. Up until now, genomics was timely, costly and hugely complex. The first draft of the whole human genome took 13 years and cost over £2 billion, due to the sheer size of the data involved.  

Now, AI and data science are being used to clean, standardise and analyse data to highlight patterns for clinicians to investigate. With this technology, the sequencing of a human genome can take a matter of days and cost under £1,000 – a considerable leap in the field. And, there’s even more being done. 

Recent developments

Recent technical developments in the field of genomics include:

Elevation by Microsoft

Elevation is a tool developed by Microsoft in collaboration with biologists. Elevation uses machine learning to improve the gene-editing results achieved using CRISPR technology. It does this by predicting where best to edit a DNA strand to minimise mistakes, reduce side effects and make the whole process quicker. This can be used to treat diseases, improve birth rates, or even reduce allergic reactions. 

Deep Variant by Google

Deep Variant is an open-source deep learning model that analyses genetic sequences to identify the differences that make organisms unique. This can be used to produce more accurate pictures of the full genome, and help to distinguish small mutations from random errors. 

Deep learning tools by Scripps Research Translational Institute and NVIDIA

Scripps Research Translational Institute and NVIDIA have partnered to develop deep learning tools and methods for analysing genomic data. These tools will be used for disease prevention, enhanced biomedical research, and health promotion.

The future

Late this summer, the UK Health Secretary announced a £250 million investment for an AI lab that will elevate the use of AI and genomic medicine. 

“The experts tell us that because of our NHS and our tech talent, the UK could be the world leader in these advances in healthcare, so I’m determined to give the NHS the chance to be the world leader in saving lives through artificial intelligence and genomics.”

The lab will bring technology companies, specialists and academics together to work on AI genomic projects that could lead to earlier cancer detection, new dementia treatments and more personalised care. 

Get in touch

Interested in getting involved? If you’re looking for the top talent, the technical vacancy or the opportunity to make a huge impact in the field of AI genomics, schedule a call with me today.

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