The AI In Genomics by The Business Research Company provides market overview across 60+ geographies in the seven regions – Asia-Pacific, Western Europe, Eastern Europe, North America, South America, the Middle East, and Africa, encompassing 27 major global industries. The report presents a comprehensive analysis over a ten-year historic period (2010-2021) and extends its insights into a ten-year forecast period (2023-2033).
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According to The Business Research Company’s AI In Genomics, The ai in genomics market size has grown exponentially in recent years. It will grow from $0.75 billion in 2023 to $1.08 billion in 2024 at a compound annual growth rate (CAGR) of 43.9%. The growth in the historic period can be attributed to advancements in genomic sequencing, data handling challenges, personalized medicine demand, disease understanding and diagnosis, drug discovery and development..
The ai in genomics market size is expected to see exponential growth in the next few years. It will grow to $4.58 billion in 2028 at a compound annual growth rate (CAGR) of 43.4%. The growth in the forecast period can be attributed to expansion of genomic databases, enhanced genomic data security, ai-driven biomarker discovery, integration with other ‘omics’ data, patient empowerment and education.. Major trends in the forecast period include ai in cancer genomics, ai-enhanced genomic imaging, ai-driven biomarker discovery, genomic data integration across healthcare systems, ai in functional genomics research..
Growing adoption of AI is expected to propel the growth of the AI in genomics market going forward. Artificial intelligence (AI) is a field that uses computer science and large datasets to solve problems. It includes the subfields of machine learning and deep learning, commonly referenced in the context of artificial intelligence. AI in genomics assists in identifying genetic illnesses and the primary type of cancer, forecasting the progression of certain diseases in a patient, identifying disease-causing genomic variations, and improving the function of gene editing tools. Additionally, due to such benefits, there is an increased demand for artificial intelligence (AI) in genomics. For instance, in May 2022, according to a report published by International Business Machines Corporation (IBM), a US-based technology corporation, The global adoption rate of AI climbed dramatically to 35%, up four percent from the previous year. Additionally, a survey of 7,502 company decision-makers shows that 13% more enterprises are expected to utilize AI in 2021 than in 2020. 35% of organizations reported employing AI, 42% are contemplating AI adoption, and two-thirds (66%) are either executing or aiming to use AI to fulfil their sustainability goals. Therefore, the growing adoption of AI is driving the growth of the AI in genomics market.
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The ai in genomics market covered in this report is segmented –
1) By Component: Hardware, Software, Services
2) By Technology: Machine Learning, Computer Vision
3) By Functionality: Genome Sequencing, Gene Editing, Other Functionalities
4) By Application: Drug Discovery And Development, Precision Medicine, Diagnostics, Other Applications
5) By End-use: Pharmaceutical and Biotech Companies, Healthcare Providers, Research Centers, Other End-Users
Technological advancements are a key trend gaining popularity in the AI in genomics market. Major companies operating in the AI in genomics market are focused on developing innovative technological solutions to strengthen their position in the market. For instance, in March 2023, Genomic Vision, a France-based biotechnology company that specializes in the development of diagnostic solutions for genetic diseases and cancers, launched FiberSmart, an AI-powered software that enables the visualization and analysis of long DNA fibers at high resolution. has the potential to completely change the diagnosis and treatment of genetic illnesses. It was introduced to increase the precision and effectiveness of diagnosing and treating genetic diseases. Large amounts of data are analyzed using this technology to find patterns and insights that would be impossible for humans to find on their own.
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