Written by

Bernard Marr

Bernard Marr is a world-renowned futurist, influencer and thought leader in the fields of business and technology, with a passion for using technology for the good of humanity. He is a best-selling author of 20 books, writes a regular column for Forbes and advises and coaches many of the world’s best-known organisations. He has over 2 million social media followers, 1 million newsletter subscribers and was ranked by LinkedIn as one of the top 5 business influencers in the world and the No 1 influencer in the UK.

Bernard’s latest book is ‘Business Trends in Practice: The 25+ Trends That Are Redefining Organisations’

View Latest Book

Follow Me

Bernard Marr ist ein weltbekannter Futurist, Influencer und Vordenker in den Bereichen Wirtschaft und Technologie mit einer Leidenschaft für den Einsatz von Technologie zum Wohle der Menschheit. Er ist Bestsellerautor von 20 Büchern, schreibt eine regelmäßige Kolumne für Forbes und berät und coacht viele der weltweit bekanntesten Organisationen. Er hat über 2 Millionen Social-Media-Follower, 1 Million Newsletter-Abonnenten und wurde von LinkedIn als einer der Top-5-Business-Influencer der Welt und von Xing als Top Mind 2021 ausgezeichnet.

Bernards neueste Bücher sind ‘Künstliche Intelligenz im Unternehmen: Innovative Anwendungen in 50 Erfolgreichen Unternehmen’

View Latest Book

Follow Me

The Amazing Ways Artificial Intelligence Is Transforming Genomics and Gene Editing

2 July 2021

By 2021, consultant firm Frost & Sullivan expects that artificial intelligence (AI) systems will generate $6.7 billion in revenue from healthcare globally. One area that machine learning is significantly evolving is genomics—the study of the complete set of genes within an organism. While much attention has been paid to the implications for human health, genetic sequencing and analysis could also be ground-breaking for agriculture and animal husbandry. When researchers can sequence and analyse DNA, something that artificial intelligence systems make faster, cheaper and more accurate, they gain perspective on the particular genetic blueprint that orchestrates all activities of that organism. With this insight, they can make decisions about care, what an organism might be susceptible to in the future, what mutations might cause different diseases and how to prepare for the future.     

Genome Sequencing and Gene Editing

Since the illnesses an individual experiences in a lifetime are largely determined by their genetics, there has been significant interest to better understand our genetic makeup for years. Our progress was stalled by the complexity and enormity of the data that needed to be evaluated. With advances in artificial intelligence and machine learning applications, researchers are better able to interpret and act on genomic data through genome sequencing and gene editing.

A genome sequence is a specific order of DNA building blocks (A, T, C, G) in a living organism; the human genome is made up of 20,000 genes and more than 3 billion base pairs of these genetic letters. Sequencing the genome is a critical first step to understanding it. The latest technology called high-throughput sequencing (HTS) allows the sequencing of DNA to occur in one day—a process that once took a decade when it was first done.

When changes are made to DNA at a cellular level, it’s called gene editing.

Personalised medicine and life-saving therapies

One of the most exciting prospects about gene technology is the development of precision or personalised medicine. The field, which enables interventions specific to a patient or population of genetically similar individuals, is expected to reach $87 billion by 2023. Historically, cost and technology limited the implementation of personalised medicine, but machine learning techniques are helping to overcome these barriers. Machines help identify patterns within genetic data sets and then computer models can make predictions about an individual’s odds of developing a disease or responding to interventions.  

Google’s tool DeepVariant uses the latest AI techniques to turn high-throughput sequencing (HTS) into a more accurate picture of a full genome. While HTS was available since the 2000s, DeepVariant is able to distinguish small mutations from random errors. Deep learning was instrumental in effectively training DeepVariant.

While we can now read and sequence genes quickly, we have barely scratched the surface to make sense of what it’s telling us. The Canadian start-up Deep Genomics uses its AI platform to decode the meaning of the genome to determine the best drug therapies for an individual based on the DNA of the cell. The company’s learning software analyses mutations and uses what it’s seen in the hundreds of thousands of mutation examples it’s analysed to predict the impact of a mutation.

New cancer cases number millions annually, but chemotherapies and drugs have inconsistent success. Companies such as Sophia Genetics hope that by using artificial intelligence to identify genetic mutations, physicians will be able to prescribe the best drug treatment for each individual patient.

The potential and perils of editing genes

Some companies are working on technologies that support editing of genes by making changes to the DNA at the cellular level. CRISPR, a gene-editing technology, is a collaboration between computer scientists and biologists. There are positive outcomes for “editing out” genes that might cause disease or “editing in” genes that create high-yielding, drop-resistant crops, but it also introduces complex ethical, moral and legal implications. Most people can see the benefits of “optimising” health by editing mutated genes, but the issue is more complex when we begin to “optimise” the human race.

Another thing experts are working to resolve in the process of gene editing is how to prevent off-target effects—when the tools mistakenly work on the wrong gene because it looks similar to the target gene.

Artificial intelligence and machine learning help make gene editing initiatives more accurate, cheaper and easier.

The future for AI and gene technology is expected to include pharmacogenomics, genetic screening tools for newborns, enhancements to agriculture and more. While we can’t predict the future, one thing is for sure: AI and machine learning will accelerate our understanding of our own genetic makeup and those of other living organisms. 

Business Trends In Practice | Bernard Marr
Business Trends In Practice | Bernard Marr

Related Articles

The Top 10 Tech Trends In 2023 Everyone Must Be Ready For

As a futurist, it’s my job to look ahead — so every year, I cover the emerging tech trends that will be shaping our digital world in the next 12 months.[...]

The Top Five Cybersecurity Trends In 2023

Here, we look at the most important trends to watch out for in 2023, including the increased threats from connected IoT devices, hybrid working, and state-sponsored attacks.[...]

The Disruptive Economic Impact Of Artificial Intelligence

I firmly believe that artificial intelligence (AI) has the potential to be among the most disruptive technologies we will ever develop.[...]

Artificial Intelligence | Bernard Marr

The 5 Biggest Artificial Intelligence (AI) Trends In 2023

Over the last decade, Artificial intelligence (AI) has become embedded in every aspect of our society and lives.[...]

The Problem With Biased AIs (and How To Make AI Better)

AI has the potential to deliver enormous business value for organizations, and its adoption has been sped up by the data-related challenges of the pandemic.[...]

Is AI Really A Job Killer? These Experts Say No

If you believe all the doom and gloom in the news today, you might think automation and the deployment of AI-enabled systems at work will replace scores of jobs worldwide.[...]

Stay up-to-date

  • Get updates straight to your inbox
  • Join my 1 million newsletter subscribers
  • Never miss any new content

Social Media

0
Followers
0
Followers
0
Followers
0
Subscribers
0
Followers
0
Subscribers
0
Yearly Views
0
Readers

Podcasts

View Podcasts