AI in Genomics Market Expected to Reach $9.9 Billion by 2031—Allied Market Research

According to a new report published by Allied Market Research, titled, “AI in Genomics Market" was valued at $346.3 million in 2021, and is projected to reach $9,859.7 million by 2031, registering a CAGR of 40.6% from 2022 to 2031.
Genomics is the branch of molecular biology that deals with the study of the entire genetic material of an organism, including its DNA sequence, gene structure, function, and organization. It involves the use of advanced technologies and computational tools to analyze and interpret genomic data. Artificial Intelligence (AI) is a branch of computer science that focuses on developing computer systems to perform tasks that typically require human intelligence, such as recognizing speech, making decisions, and learning from experience. AI systems are designed to mimic human cognitive functions such as perception, reasoning, and learning. 

Few AI in Genomics Market Trends and applications include gene sequencing, gene expression analysis, and drug discovery. For instance, AI algorithms are being used to improve the accuracy and speed of DNA sequencing. Deep learning algorithms can identify and correct errors in DNA sequences and predict missing parts of the genome. Furthermore, AI algorithms can analyze large-scale gene expression data to identify patterns and predict gene function. This can help researchers understand how genes are regulated and how they contribute to diseases thereby driving the AI in Genomics Market growth.  

Moreover, AI algorithms can be used to screen large databases of molecules and predict their potential for drug development. This can speed up the drug discovery process and reduce the cost of developing new drugs. Furthermore, AI can be used to identify new drug targets by analyzing large datasets of biological and chemical information. By predicting which proteins or other molecules are most likely to be involved in a specific disease, researchers can identify potential targets for drug development. In addition, AI algorithms can be used to predict the potential toxicity of new drugs by analyzing their chemical structures and comparing them to known toxic compounds. This can help researchers identify potential safety issues early in the drug development process. AI can also be used to design more efficient and effective clinical trials by predicting which patients are most likely to respond to a particular therapy. By identifying subpopulations of patients who are most likely to benefit from a treatment, researchers can improve the chances of success in clinical trials. 

In addition, AI is being increasingly used in disease diagnosis to improve accuracy and speed, particularly in areas such as radiology and pathology. AI algorithms can analyze medical images, such as X-rays, CT scans, and MRIs, to detect and diagnose diseases. For example, AI can be used to detect early signs of cancer or identify abnormalities in the brain. Furthermore, AI algorithms can analyze digital pathology images to detect and classify diseases, such as cancer. This can help pathologists make more accurate diagnoses and improve patient outcomes. In addition, AI algorithms can be used to help clinicians make more informed decisions by providing them with diagnostic or treatment recommendations based on patient data. This can help clinicians provide more personalized and effective care to their patients. Overall, AI has the potential to transform disease diagnosis by enabling faster and more accurate identification of diseases, improving patient outcomes, and reducing healthcare costs 

By offering, the Artificial Intelligence in Genomics Market is segmented into software, services and hardware. The software segment accounted for the largest share in 2021, owing to the use of software for analyzing genomic data, such as genome assembly software, variant calling software, gene expression analysis software, and others. However, the hardware segment is projected to register the highest CAGR during the forecast period. AI hardware includes specialized hardware and software platforms designed to support the training and inference of AI models used in genomics. The explosion of data and the need for real-time processing has led to a demand for high-performance AI hardware. With the advent of big data, AI systems need to process huge amounts of data at a very high speed.

By technology, the AI in Genomics Market Size is segmented into machine learning and computer vision. Machine learning occupied the highest share in 2021 and is expected to grow with a faster CAGR during the forecast period owing to its application in genomic data analysis, drug discovery, and precision medicine. By application, the market is segmented into drug discovery development, precision medicine, diagnostics, and others. Drug discovery and development occupied the highest share in 2021 owing to the reason that AI in genomics can help to streamline the drug discovery process by reducing the time and cost required to develop new drugs, while also improving the success rate. However, the diagnostics segment is projected to register the highest CAGR during the forecast period owing to the reason that application of AI in genomics has greatly enhanced the accuracy and speed of diagnostic tests.  

Based on end users, the AI in Genomics Market Share is segmented into pharmaceutical and biotech companies, healthcare providers, research centers, and others. Pharmaceutical and biotech companies occupied the highest share in 2021 owing to a rise in the use of AI in drug discovery and development. Additionally, the healthcare providers segment is projected to register the highest CAGR during the forecast period owing to the rise in the use of AI by researchers and healthcare professionals for diagnostic purposes and genetic analysis.  

Region-wise, North America is expected to witness the highest growth, in terms of revenue, owing to the strong presence of key market players and advanced healthcare infrastructure. The upsurge in healthcare expenditure in emerging economies is anticipated to offer lucrative opportunities for market expansion. However, Asia-Pacific is anticipated to witness notable growth, owing to an increase in investments for the development of AI, and an increase in the number of key players developing AI drives the growth of the market during the forecast period. 

KEY FINDINGS OF THE STUDY  

• By offering, the software segment was the highest contributor to the AI in Genomics Industry in 2021. However, the hardware segment is anticipated to grow at the highest CAGR during the forecast period. 
• By technology, the machine learning segment dominated the market in terms of revenue in 2021.  
• By applications, the drug discovery segment was the highest contributor to the market in 2021. However, the diagnostics segment is anticipated to grow at the highest CAGR during the forecast period. 
• By end user, the pharmaceutical and biotech companies' segment was the highest contributor to the market in 2021. However, the healthcare providers segment is anticipated to grow at the highest CAGR during the forecast period.  
• Region-wise, North America generated the largest revenue in 2021. However, Asia-Pacific is anticipated to grow at the highest CAGR during the forecast period.