by The Global Artificial Intelligence In Digital Genome Market is estimated to be valued at US$ 269.8 million in 2023 and is expected to exhibit a CAGR of 44.8% over the forecast period, 2023-2028, as highlighted in a new report published by Coherent Market Insights.
Market Overview:
The Artificial Intelligence In Digital Genome market involves the application of artificial intelligence algorithms and techniques to analyze complex genetic and genomic data. AI has the potential to revolutionize genomic research and medicine by speeding up analysis, discovering patterns, and enabling predictive analysis. By using machine learning on vast amounts of genomic and medical data, AI systems can learn relationships between genes, biomarkers and diseases. This helps researchers gain novel insights that would be impossible through human analysis alone. AI tools also assist in analyzing genomes at an individual level to deliver personalized risk assessments and treatment recommendations tailored to a person’s unique genetic profile.
Market key trends:
One of the major trends in the AI in digital genome market is the growing adoption of AI and machine learning for drug discovery and development. Pharmaceutical companies are increasingly relying on AI to speed up the drug discovery process and reduce costs. AI helps analyze huge amounts of genomic and other biomedical data to identify potential drug targets, biomarkers, and gain insights into disease mechanisms. It also aids in virtual screening of chemical libraries to predictively design new molecules with desired properties. This is helping streamline the drug design process and bring new therapies to market more quickly. Another key trend is the increasing integration of AI into precision medicine. As genomic databases grow larger, AI is playing a critical role in analyzing complex patient omics data and clinical information. This enables more targeted disease screening, diagnosis and treatment recommendations on an individual level.
Porter’s Analysis:
Threat of new entrants: Low barriers to entry due to advanced technologies making AI solutions more accessible. However, established players have significant resources and customer base.
Bargaining power of buyers: Buyers have high bargaining power due to availability of substitutes and less customer switching costs.
Bargaining power of suppliers: A few big specialized suppliers exist with significant differentiation in algorithms and capabilities. This gives them higher bargaining power.
Threat of new substitutes: Threat of new substitutes is high as adjacencies like precision medicine and alternative diagnostics offer competitive solutions.
Competitive rivalry: Intense competition exists among global technology giants as well as small niche players. Price wars and new product innovation further increase rivalry.
Key Takeaways:
The Global Artificial Intelligence In Digital Genome Market is expected to witness high growth, exhibiting CAGR of 44.8% over the forecast period 2023-2028, due to increasing adoption driven by benefits like improved disease therapeutics outcomes, optimized research and development processes, and reduced costs.
The North American region currently dominates the market due to high technological adoption, significant investments in genomics by key players, and growing focus on precision medicine in the US. Europe and Asia Pacific are also attractive markets expected to grow at a high pace owing to increasing healthcare expenditure, supportive government initiatives, and growing geriatric population with chronic diseases.
Key players operating in the artificial intelligence in digital genome market incorporate NVIDIA Corporation, IBM, Microsoft, Fabric Genomics Inc., Verge Genomics, MolecularMatch Inc., SOPHiA GENETICS, PrecisionLife Ltd, BenevolentAI, and Deep Genomics. Players are focusing on strategic collaborations, product launches, and technology advancement to gain market share in the competitive landscape.
*Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it
