by AI in omics studies refers to the application of artificial intelligence techniques in genomics, proteomics and metabolomics studies. AI helps analyze the huge amount of omics data generated through techniques like next generation sequencing, mass spectrometry etc. This helps researchers gain in depth insights into diseases, drug efficacy and development of precision medicine approaches. With huge genomic and molecular data being generated, traditional data analysis methods are unable to handle such enormous volumes. AI helps generate hypothesis, predict outcomes, identify patterns and biomarkers through techniques like machine learning, deep learning and natural language processing.
The Global AI in Omics Studies Market is estimated to be valued at US$ 639.8 Mn in 2024 and is expected to exhibit a CAGR of 32% over the forecast period 2024 To 2031.
Key Takeaways
Key players operating in the Global AI in Omics Studies are Thermo Fisher Scientific, Agilent Technologies, Illumina, BGI Genomics, Dassault Systèmes, Qiagen, Waters Corporation, GE Healthcare, Amazon Web Services, Inc., Bruker, Danaher. These players are focusing on development of AI applications tailored for omics data analysis.
The key opportunities in the market include potential for AI to accelerate precision medicine goals, drug discovery and development through analysis of huge molecular data sets. Growing investment from pharmaceutical and biotech firms is also fueling development of AI for omics applications.
Advancements in machine learning and deep learning algorithms is allowing development of more sophisticated AI tools for multi-omics data integration, biomarker identification, subtyping of diseases and population health management. Automation of sequencing workflows using AI In Omics Studies Market Size is also an upcoming opportunity.
Market drivers
Generating huge volumes of omics data through high throughput techniques is a key driver for adoption of AI. AI helps gain insights from this data faster than traditional methods. Growing demand for precision medicine and personalized healthcare is also propelling the AI in omics market as it helps develop individualized treatment strategies. Expanding applications of AI from genomics to proteomics, metabolomics and multi-omics is expected to boost the market growth over the forecast period.
Current Challenges in the Global AI in Omics Studies Market:
The global AI in omics studies market is still at a nascent stage. Lack of trained professionals, difficulties in data integration, and privacy & security issues are some of the major challenges restraining the market growth. Omics datasets are complex with thousands to millions of data points generated for a single experiment. Integration and interpretation of such huge datasets requires strong computational and analytical skills. However, there is a severe shortage of data scientists and AI experts with deep understanding of life sciences. Issues associated with data privacy and security also limit wider adoption of AI solutions in clinical settings.
SWOT Analysis
Strength: AI tools can analyze huge genomic and transcriptomic datasets faster than humans. They also help discover patterns and insights that may otherwise remain hidden.
Weakness: Reliance on large curated datasets for training can limit applications initially. Biological interpretations of computational results also require domain knowledge.
Opportunity: AI is promising to solve bottlenecks in biomarker discovery, drug repositioning, and precision medicine. It can accelerate genomic research and support clinical decision making.
Threats: Lack of regulations for clinical use of AI may undermine safety and efficacy. Competition fromalternatives like cloud-based genomic analysis solutions can also affect growth.
Geographical Regions
North America currently dominates the global AI in omics studies market, both in terms of value and volume. Significant investments by government agencies and private players in the US contribute to the region’s large share. presence of leading life science companies and AI technology providers along with growing R&D expenditure on omics-based research further support market growth.
Asia Pacific is expected to witness the fastest growth during the forecast period from 2024 to 2031. This can be attributed to rising healthcare expenditure, increasing disease burden, and growing focus on precision medicine in countries like China and India. Favorable regulatory environment and emerging tech-driven hubs also accelerate adoption of AI solutions for omics applications in the Asia Pacific region.
*Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it
