Artificial Intelligence (AI) In Genomics Is Estimated To Witness High Growth Owing To Increasing Investments In Genomics Research
Genomics is the study of genomes, which involves analyzing the complete set of DNA within a single cell of an organism. Advances in genomic technologies have enabled high-throughput sequencing of entire genomes at relatively low costs. Genome sequencing has applications across various domains including precision medicine, drug discovery, agriculture, and more. Artificial intelligence is playing a key role in extracting clinically relevant insights from the growing volumes of complex genomic data by detecting patterns, making predictions, and discovering new biological insights. AI tools are being utilized for genome assembly, variant calling, phenotypic predictions, and more.
The global artificial intelligence (AI) in genomics market is estimated to be valued at US$ 481.2 Mn in 2023 and is expected to exhibit a CAGR of 6.1% over the forecast period 2023 to 2030, as highlighted in a new report published by Coherent Market Insights.
The global artificial intelligence (AI) in genomics market is driven primarily by increasing investments in genomics research and rising adoption of AI-based tools and systems across various application areas such as diagnostics, drug discovery, precision medicine, and agriculture. AI algorithms are helping analyze genomic sequences faster, identify sequence variations effectively, and discover novel associations between genetic variations and diseases. This is enabling genomics researchers to gain deeper clinical insights at an accelerated pace. Furthermore, growing collaborations between genomics and AI companies to develop advanced tools is also fueling market growth.
Market Dynamics:
The primary driver incorporated in the heading is increasing investments in genomics research. Global public and private funding for genomics research has grown substantially over the past decade. For instance, the U.S. National Institutes of Health's budget for the Human Genome Project increased from around US$ 200 million in 1991 to over US$ 2.7 billion by 2003. More recently in 2022, Ginkgo Bioworks raised over $1.6 billion in its initial public offering, indicating strong investor interest in synthetic biology and genomics. Such significant investments are enabling wider adoption of AI-based solutions for handling and analyzing large genomic datasets.
SWOT Analysis
Strength: Artificial intelligence in genomics has the potential to accelerate genomic research and discovery. AI-powered tools enable researchers to analyze vast amounts of genomic and biomedical data at speeds far greater than manual review. This allows researchers to identify patterns and glean insights that would be difficult or impossible via traditional human review alone. AI also minimizes human biases that can unintentionally influence research outcomes.
Weakness: Genomic datasets are often incomplete or inconsistent which poses challenges for AI model training and performance. Lack of high-quality labeled training data can limit the capabilities of machine learning in this field. Additionally, as with any new technology, initial AI solutions for genomics may be imperfect and require additional research and development to reach their full potential.
Opportunity: AI can help drive new discovery and innovation in personalized medicine. Analyzing an individual's whole genome using AI-powered insights into genetic correlations with diseases or drug responses could one day enable truly personalized treatment plans. AI may also accelerate drug discovery by aiding in target identification, predictive toxicology, and clinical trial optimization. This presents vast opportunities for improving human health worldwide.
Threats: Regulatory uncertainty regarding the use of genetic and biomedical data for AI training or commercial purpose poses risks. Privacy and ethical concerns related to genomic data access and ownership also threaten adoption without adequate guidelines. Overall, genomics is a complex domain requiring multidisciplinary expertise to ensure AI systems are developed and applied responsibly and for the benefit of improving human lives.
Key Takeaways
The global Artificial Intelligence (AI) in Genomics Market scope is expected to witness high growth over the forecast period of 2023 to 2030. The regional analysis indicates The global artificial intelligence (AI) in genomics market is estimated to be valued at US$ 481.2 Mn in 2023 and is expected to exhibit a CAGR of 6.1% over the forecast period 2023 to 2030.
North America currently dominates due to concentrated presence of leading AI and genomic companies as well as supportive government funding for precision medicine initiatives and research. However, Asia-Pacific is emerging as the fastest growing region with China and India establishing major AI hubs and investing heavily in applications across healthcare including genomics.
Key players operating in the Artificial Intelligence (AI) in Genomics Market are Intel Corporation, International Business Machines Corporation (IBM), Microsoft Corporation, BenevolentAI, Anthropic, Fabric Genomics, MolecularMatch, Pathway Genomics, Lifebit Biotechnology, and Freenome Holdings. These companies are developing advanced AI tools, platforms, and cloud-based solutions focused on accelerating genomic research, improving diagnostic yields, powering drug discovery initiatives, and enabling personalized medicine programs. They apply techniques including deep learning, neural networks, and natural language processing to large genomic datasets.
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