What is Genomics?

Genomics is the study of genes and their function. It can be used in healthcare to help predict a person’s risk of developing certain diseases, to choose the best treatment for them, and to monitor their disease progression. It can also be used in research to develop new drugs and therapies. In recent years, next-generation sequencing (NGS) technologies have made it possible to sequence an individual’s entire genome quickly and cheaply. This advancement has led to a surge in interest in genomics and its potential implications for healthcare.

A company called Genomic Health was one of the first to use genomics in healthcare. Genomic Health’s Oncotype DX test analyzes a person’s tumor to predict their risk of cancer recurrence and helps guide treatment decisions. The test has shown to be accurate and is now used routinely by oncologists around the world. Furthermore, the Human Genome Project has provided a map of the entire human genome, which has been used to identify thousands of genes associated with disease. In the United States, the Cancer Genome Atlas project is sequencing the genomes of cancer patients to better understand the disease. In fact, they have mapped key genomic changes in more than 30 types of cancer. On the other hand, genomics is being used in other industries as well. For example, it is used in agriculture to improve crop yields and to develop more nutritious foods.

Overall, genomics deals with large sets of data that are too vast for humans to find anomalies and notice trends. Therefore, artificial intelligence and machine learning are being used for analyzing large data sets to identify harmful genes and treat genetic diseases across the healthcare industry.

How is AI Being Used in Genomics?

The field of genomics is rapidly evolving, and artificial intelligence is playing an increasingly important role. By analyzing vast amounts of genetic data, AI can help to identify patterns and correlations that would be difficult for humans to spot. This information can then be used to develop new treatments for diseases, improve diagnostic accuracy, and personalize patient care. AI is also being used to create digital models of the human body, which can be used to test the safety and efficacy of potential new drugs. In the future, AI may even be used to design custom-made treatments based on a patient’s individual genetic profile. The potential applications of AI in genomics are virtually limitless, and it is already beginning to transform healthcare. As seen in the graph below, the amount of genomic data worldwide is vast and is still expected to grow over the next couple of years.

A company called Freenome is using AI to screen for cancer. Freenome’s technology analyzes a person’s blood sample to look for signs of cancer. The company has already raised $100 million from investors, and its test is being used by leading healthcare providers such as the Mayo Clinic. Therefore, the field of genomics is lucrative for the healthcare industry. Another company called Recursion Pharmaceuticals is using AI to develop new drugs. Recursion Pharmaceuticals uses machine learning to screen for potential new drugs. So far, the company has identified more than 1,000 potential new treatments for diseases such as cancer and Alzheimer’s disease.

The Benefits of AI in Genomics

There are many potential benefits of using AI in genomics. First, AI can help to speed up the process of drug development. By screening for potential new drugs faster, medicine can be brought to market sooner, which can save lives. Second, AI can help to improve diagnostic accuracy. By analyzing a person’s genetic data, AI can often identify diseases earlier, which can lead to better outcomes. A company called Gen is using AI to develop a blood test that can detect more than 50 types of cancer. The test is still in development, but it has the potential to revolutionize cancer detection.

Third, AI can help to personalize patient care. By creating digital models of the human body, AI can be used to tailor treatments to an individual’s specific needs. The leading company that provides digital models of the human body is Freenome. Freenome is being used by leading healthcare providers to personalize patient care through precise and accurate digital models. Finally, AI can help to reduce healthcare costs. By identifying potential new treatments for diseases sooner, AI can help to reduce the cost of healthcare for everyone. In fact, the graph below shows that the cost of genomic sequencing has decreased over the years. More genomes can be sequenced at a lower cost per genome.

The Profitability of Genomics in the Healthcare Industry

The healthcare industry is highly profitable. In 2018, the global healthcare market was worth $8.7 trillion. The North American market was worth $3.65 trillion, while the European market was worth $2.79 trillion. Genomics is a rapidly growing field within the healthcare industry, and it is expected to be worth $47.6 billion by 2025.

AI is playing an important role in the advancement of genomics. By helping to speed up the process of drug development, improve diagnostic accuracy, personalize patient care, and reduce healthcare costs, AI is making genomics more profitable for the healthcare industry. With AI, the overhead costs of sequencing genomes and finding patterns are lower. Furthermore, there is a lower churn rate for healthcare companies that use AI in genomics because patients receive accurate and timely results. Therefore, Genomics is a field that healthcare providers should be investing in.

Conclusion

In conclusion, AI is playing a significant role in the advancement of genomics. Genomics is a rapidly growing field within the healthcare industry, and it is expected to be worth $47.6 billion by 2025. With its ability to speed up the process of drug development, improve diagnostic accuracy, personalize patient care, and reduce healthcare costs, AI will make genomics even more profitable for the healthcare industry in the years to come. Healthcare providers who are not already using AI in their genomics research should consider doing so, as it could help them to stay ahead of the competition, reduce overhead costs, and reduce churn.

References

National Geographic

Genomsys

SeekingAlpha