The Convergence of AI and Genomics

The convergence of artificial intelligence and genomics marks the dawn of a revolutionary age in human health, agriculture, and our understanding of the natural world. Genomics, the study of an organism's DNA, holds the key to unlocking the fundamental processes of life. By applying AI to analyse vast amounts of genomic data, we can uncover patterns and insights that were once beyond human reach. The synergy between these two technologies is paving the way for ground-breaking discoveries, transforming healthcare, biotechnology, and the very fabric of life as we know it.

The Democratization and Expansion of Genomic Data

In 2001, the Human Genome Project completed the first reference human genome sequence, covering approximately 92% of the human genetic variation. The total cost of the project was?$2.7 billion .

In 2022, the Telomere to Telomere (T2T) consortium, with leadership from the? National Human Genome Research Institute (NHGRI) ,?the University of California, Santa Cruz , and the University of Washington, Seattle, successfully?sequenced the remaining 8% of the human genome. ?The now-complete human genome sequence provides a comprehensive view of our DNA blueprint and paves the way for a revolution in our understanding of human genomic variation, disease, and evolution.

The sequencing done as part of the Human Genome Project and the sequencing done today are fundamentally the same in the sense that they are both attempting to determine the order of the base pairs (adenine, thymine, guanine, and cytosine) in a DNA molecule. However, the techniques and technologies used have changed significantly. The Human Genome Project used a method called?Sanger sequencing , which was state-of-the-art at the time but is slow and expensive by today's standards.

To generate a second reference human genome sequence using the approaches and technologies available in 2001 would have cost approximately?$100,000,000 . Today, using next-generation sequencing (NGS) technologies , companies like Illumina ?can sequence a human genome for?$600 (a cost decrease of more than 99.9999%), with some predicting that the $100 genome is not far off. (These sequences typically cover about 92% of the genome, similar to the initial Human Genome Project. The remaining 8% (telomeres and centromeres) are more difficult to sequence due to their repetitive and complex nature).

The dramatic decrease in the cost of sequencing is outpacing Moore′s Law and democratising access to personal genomic information like never before.

But the cost is not the only thing that has changed.?While the Sanger method only sequences a single DNA fragment at a time,?NGS is massively parallel , and can sequence millions or billions of fragments of DNA at the same time.

“With Sanger sequencing, we saw a limited DNA snapshot… NGS and its massively parallel sequencing enable us to look at tens to hundreds of thousands of reads per sample.” Michael Bunce, PhD -?Head of TrEnD laboratory

The surge in high-throughput sequencing technologies has exponentially increased the volume of genomic data we can generate. Estimates predict that genomics research will generate between?2 and 40 exabytes ?of data within the next decade. We're not just sequencing genomes more cheaply; we're sequencing more of them.

Simultaneously, the development of AI technology, specifically deep learning, has empowered us to make sense of this enormous and complex data, uncovering patterns and insights that would be impossible for humans to find alone. By efficiently and effectively analysing vast genomic datasets, deep learning is propelling us into new frontiers of genomics and its numerous applications.

The Revolution in Healthcare

AI and genomics are at the forefront of a revolution in healthcare, leading us towards a future of personalised medicine. AI-driven genomic analysis promises to enable healthcare providers to tailor treatment plans to each individual's unique genetic makeup. This level of precision is poised to improve patient outcomes, decrease healthcare costs, and initiate a radical shift in medical care.? Tempus AI is?using AI to analyse clinical and molecular data , empowering physicians to make data-driven decisions for cancer patients.

Within the field of diagnostics, the application of AI in genomics is paving the way for the early detection of diseases, potentially saving millions of lives. For instance,? GRAIL has engineered an AI-driven liquid biopsy,?Galleri , designed to detect multiple cancer types through a single blood test.

Simulation of Gene-Edits Using Machine Learning

CRISPR-Cas9 , a gene-editing technique that allows for precise manipulation of genetic sequences within an organism's DNA, marked a monumental shift in the field of genomics. It has granted us unprecedented control over our genetic destiny. However, the process of physical gene-editing is fraught with ethical, safety, and regulatory concerns. To circumvent these issues, scientists are now utilising machine learning and artificial intelligence.

These AI algorithms, trained on extensive genomic data, can predict the potential effects of genetic mutations without the need to perform physical editing. Essentially, they model the consequences of CRISPR-style changes, leveraging the vast amounts of data available to draw robust conclusions. The synergy of CRISPR's transformative capacity with AI's predictive power is paving the way for safer and more efficient exploration of our genomic potential.

Innovations in Biotechnology

By applying AI to genomic data, scientists are creating novel organisms with specific traits, such as plastic-degrading bacteria. Berkeley Lab ?has engineered?bacteria capable of converting carbon dioxide into biofuels . Similarly,?the Salk Institute for Biological Studies has developed?plants that can capture more carbon dioxide , contributing to climate change mitigation efforts.

The Transformation of Agriculture

AI-powered genomics is set to overhaul agriculture, optimising crop yields, nutritional content, and resistance to pests and diseases. For example, Benson Hill , an agritech company, is leveraging AI and genomics to develop crop varieties with improved yield, nutritional content, and resilience. They have developed?ultra-high protein soybean varieties ?that can help meet the growing global demand for plant-based protein sources while reducing the environmental impact of agriculture.

The Potential to Extend Human Lifespans

AI's integration with genomics may lead to therapies that slow down or even reverse the ageing process, potentially extending human lifespans. Scientists from Genentech and the Salk Institute successfully?delayed or reversed certain consequences of ageing ?in mice by applying cellular reprogramming techniques. By introducing four genes that had been silenced in mature cells, they were able to erase genetic marks of stress associated with ageing. The reprogrammed cells exhibited signs of increased metabolism and reduced levels of damage, resembling younger cells. These findings suggest that AI-driven genomic analysis could play a pivotal role in the development of therapies to slow down or even reverse the ageing process, opening up new possibilities for regenerative medicine and the prevention or treatment of age-related diseases.

The Impact on Drug Discovery

The integration of AI and genomics is significantly accelerating the drug discovery process and reducing associated costs. AI algorithms can identify potential drug targets, predict drug efficacy and safety, and streamline the drug development process.

By combining genomic data and artificial intelligence, Insilico Medicine , a clinical-stage AI-driven drug discovery company, has significantly expedited its drug discovery process. Their end-to-end?Pharma.AI ?platform uses generative AI to quickly identify potential cancer drug targets within genomic data in order to engineer new therapeutic molecules.

Understanding Rare Genetic Diseases

The fusion of AI and genomics also holds the promise of unraveling the complexities of rare genetic diseases. By identifying and studying genetic variants associated with these diseases, scientists can design targeted therapies or create diagnostic tests. The capability of AI to sift through huge volumes of genomic data is making this process exponentially faster and more efficient.

Looking Ahead: The Future of AI and Genomics

While predicting the future of AI and genomics may be challenging due to the rapid pace of technological advances, a few trends are evident:

1. Personalised Medicine:?With improvements in the accuracy and efficiency of AI algorithms, the 'one-size-fits-all' approach in medicine will become increasingly obsolete. Personalised medicine, powered by AI and genomics, will become the new standard, leading to more effective, targeted treatments for a wide range of diseases.

2. Sustainable Agriculture:?AI-driven genomics will revolutionise the agricultural industry, enabling the development of crops that are more resistant to pests and diseases, more efficient at using water and nutrients, and more resilient to climate change. This will allow us to produce more food in a more sustainable way.

3. Advances in Longevity:?AI and genomics are already being used to identify genes and pathways involved in ageing. This could lead to therapies that slow down or even reverse the ageing process, creating a future where people live longer, healthier lives.

With the convergence of artificial intelligence and genomics, we stand at the precipice of a new era of discovery that has far-reaching implications for healthcare, agriculture, and our environment. The synergy of these two technologies could reshape our existence, ushering in unparalleled health breakthroughs and sustainable innovations.