Selbyville, Delaware, Aug. 27, 2023 (GLOBE NEWSWIRE) --
Artificial Intelligence in Genomics Market size is expected to reach USD 12.5 billion in 2032. The industry expansion is driven by the increasing adoption of AI in genomics research for analysis and personalized medicine. With its ability to process and interpret vast amounts of genomic data quickly, AI enable researchers to uncover valuable insights into genetic variations, disease mechanisms, and drug responses.
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Machine learning algorithms enhance genomic data analysis, enabling the identification of patterns, biomarkers, and potential therapeutic targets. Moreover, AI-powered tools help in the development of precision medicine by predicting individual disease risks and optimizing treatment plans. Considering these factors, the industry is poised for remarkable progression, holding great promise for advancing healthcare and improving patient outcomes.
Improved capabilities of AI integrated hardware
Artificial intelligence in genomics market is divided into hardware, service, and software. The hardware segment is predicted to witness significant gains through 2032. AI-driven advancements in genomics hardware have accelerated the sequencing process, making it faster, more accurate, and cost-effective. High-throughput sequencers equipped with AI algorithms can handle massive amounts of genomic data, enabling researchers to analyze genomes more efficiently. Additionally, AI enhances the capabilities of microarray technologies, improving their sensitivity and specificity for gene expression analysis. The integration of AI algorithms in genomics hardware is pushing the boundaries of genomic research, ultimately paving the way for more precise diagnostics and personalized treatments.
Solution adoption in diagnostics application for personalized medicine
The artificial intelligence in genomics market is divided into diagnostics, precision medicines, drug discovery & development, and others. The artificial intelligence industry size from diagnostics segment is anticipated to expand by 2032. AI is playing a transformative role in diagnostics through its application in genomics. By analyzing genomic data, AI algorithms can identify genetic variations associated with diseases and provide valuable insights for accurate diagnoses.
Machine learning techniques enable the development of predictive models that can assess an individual's disease risk based on their genomic profile. AI-powered tools aid in the interpretation of complex genomic data, allowing clinicians to make informed decisions about treatment strategies. Early disease detection, in consort with preference for personalized medicine are boosting the use of AI in genomics for diagnostics, thus improving patient outcomes and revolutionizing the field of medicine.
Focus on integrating AI technology in medicine across APAC
Asia Pacific artificial intelligence in genomics market value is poised to surge during 2023 and 2032, owing to the increasing adoption of AI technologies and advancements in genomics research in countries like China, Japan, and India. The large population and rising healthcare needs have fueled the demand for personalized medicine and genomic diagnostics. Government initiatives, academic collaborations, and investments in genomics research. The development of innovative AI-driven solutions, including genomic data analysis platforms, AI-powered sequencing technologies, and predictive models for disease risk assessment are transforming healthcare field in the region.
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Competitive sphere
The leading players in the artificial Intelligence in genomics market are Illumina, Inc., DEEP GENOMICS, Data4Cure, Inc., SOPHiA GENETICS, Freenome Holdings, Inc., and Benevolent, among others.
Partial Table of Contents (ToC) of the report:
Chapter 3 Artificial Intelligence in Genomics Industry Insights
3.1 Industry ecosystem analysis
3.2 Industry impact forces
3.2.1 Growth drivers
3.2.1.1 Increasing adoption of AI in precision medicine
3.2.1.2 Rising focus on reducing turnaround time in drug discovery
3.2.1.3 Increasing application of AI in genomics and growing investment in genomics
3.2.2 Industry pitfalls & challenges
3.2.2.1 Lack of skilled professionals and stringent regulatory framework
3.3 Growth potential analysis
3.3.1 By component
3.3.2 By technology
3.3.3 By functionality
3.3.4 By application
3.3.5 By end-user
3.4 COVID- 19 impact analysis
3.5 Regulatory landscape
3.6 Porter's analysis
3.7 PESTEL analysis
Chapter 4 Competitive Landscape, 2022
4.1 Introduction
4.2 Company matrix analysis, 2022
4.3 Competitive analysis of major market players
4.4 Competitive positioning matrix
4.5 Strategy dashboardBrowse Our Reports Store - GMIPulse @ https://www.gminsights.com/gmipulse
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