InsightAce Analytic Pvt. Ltd. has announced the publication of a market research report titled “Global Artificial Intelligence in Genomics Market by (Application (Diagnostics, Drug Discovery & Development, Precision Medicine, Agriculture & animal Research, Other Applications), Technology ( Machine Learning (Deep Learning, Supervised Learning, Reinforcement Learning, Unsupervised Learning, Other Machine Learning Technologies) and Other Technologies), Functionality (Genome Sequencing, Gene Editing, Clinical Workflows, and Predictive Genetic Testing & Preventive Medicine),  End-user (Pharmaceutical & Biotech Companies, Healthcare Providers, Research Centers, Academic Institutes & Government Organizations, and Other End-users))  – Market Outlook and Industry Analysis 2030”

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Artificial intelligence (AI) approaches hold tremendous promise for genomic medical advancement. The science of genomics is continuing to increase its use of computational methodologies such as artificial intelligence and machine learning to aid in the discovery of hidden patterns in large and complex genomes data sets generated by fundamental and clinical research initiatives. Artificial intelligence, most especially machine learning and, more recently, deep learning, enables novel computational ways to solve critical challenges in genetic medicine. Machine learning and deep learning have impacted nearly every component of genetic analysis in a certain way. These approaches are being developed and utilized across several elements of the genomic data pipeline and throughout a broad range of analysis, from a single cell to large population studies.

AI is advancing clinical genomics analysis significantly, including phenotyping in uncommon illnesses and cancer, as well as variant analysis and interpretation. Diagnostics in clinical practice, particularly imaging-based diagnostics. The availability of big training datasets, such as vast collections of annotated medical pictures or massive functional genomics datasets, in conjunction with advancements in AI algorithms and the GPU systems needed to train them, is fueling this productivity increase. At the moment, the most potential uses of AI in clinical genomics appear to be the AI extraction of deep phenotypic information from pictures, electronic health records, and other medical equipment to aid in downstream genetic research. However, deep-learning algorithms have demonstrated enormous potential in various clinical genomics tasks, including variation identification, genome annotation, and functional effect prediction.

Market Dynamics:

Artificial Intelligence has yet to significantly impact genomic medical results, as genetic datasets remain primarily unexploited. The ability of genomics to prevent, manage, and treat illness has been scientifically demonstrated. Genomic applications are essential in the field of personalized medicine. Genomic data is becoming increasingly important as a source of innovative methodologies and drug-discovery processes, which is fueling the market’s growth. There has been an increase in government financing for genomics projects, an increase in clinical research activities, and an increase in personalization and treatment routines. The COVID-19 pandemic boosted the AI in genomics market. The industry saw rapid expansion as a result of the many genomic products employed in COVID-19 research to gain a better understanding of the coronavirus. Drug discovery and development are moving rapidly as genetic therapies advance under the increasing number of biotech companies. Deep Genomics announced the discovery of its first AI-discovered medication, an experimental therapy for Wilson disease, in 2019.  This uncommon hereditary condition is caused by a genetic mutation that impairs the liver’s capacity to eliminate excess copper.

The AI in the genomics market was dominated by North America in 2021, followed by Europe. This market growth is attributed to Precision medicine financing and government initiatives in the region and a well-developed healthcare system in the area account for a significant portion.

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The following key companies are engaged in the Artificial Intelligence in Genomics market:

AI Therapeutics, Inc., Ares Genetics GmbH, BenevolentAI, BioSymetrics, Cambridge Cancer Genomics (UK), Clover Therapeutics, Congenica Ltd, Coral Genomics, CureMatch, Inc., Cyclica Inc., Data4Cure, Inc, Deep Genomics, Desktop Genetics Ltd., Diploid (Belgium), DNAnexus, Emedgene, Empiric Logic, Engine Biosciences Pte. Ltd., Fabric Genomics, Inc., FDNA Inc. (US), Freenome Holdings, Inc., Genoox, Ltd., IBM (US), LifebitAI, Microsoft (Project Hanover), MolecularMatch Inc. (US), NVIDIA Corporation (US), PrecisionLife Ltd, Predictive Oncology, SOPHiA GENETICS, Inc., Trace Genomics, Verge Genomics, WhiteLab Genomics, WuXi Nextcode Genomics among others.

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