nForming AI in genomics market smart book

The AI in genomics market smart books by nForming provide historical and projected revenue, sales volume, prices, and more for each segment covered at the regional and country levels. The smart book also includes information on the main suppliers and their market share in the AI in genomics industry. The qualitative data consists of the AI in genomics market include comprehensive growth drivers, opportunities, and barriers.

Rapidly Growing Bioinformatics Data

The raw data generated by sequencing an individual’s entire genome is approximately 100 terabytes. After the genome is sequenced using complicated techniques and applications such as deep learning and natural language processing, this more than doubles.

As the cost of sequencing a human genome continues to fall, so does the volume of sequencing data. By 2025, it is projected that 40 exabytes will be required to store all human genomic data. As a comparison, that’s 8 times the storage required to store every word spoken in history.

Many genome analysis systems are having difficulty keeping up with the massive amounts of raw data being created. More due to exponential growth in the size of human genomic data, it is difficult to estimate its size by 2030 and beyond. This challenge can serve as the great opportunity for the supplier of AI in genomics products and services.

AI in genomics Market Drivers

The demand of AI in genomics seems to be gradually expanding in recent years and is projected to continue in the future. The following are some of the important factors fueling the demand growth for AI in genomics:

• Increasing Genomic Data Volume: Advances in genome sequencing technologies have resulted in a huge rise in the amount of genetic data produced. Artificial intelligence algorithms are critical for managing, analyzing, and deriving valuable insights from this massive volume of data. It is expected that storing the data created by analyzing human genome sequences will require approximately 40 exabytes of storage space.
• Precision Health Care and Personalized Healthcare: Artificial intelligence (AI) has the potential to transform precision medicine by allowing the analysis of human genomes for determining disease risks, anticipate therapy responses, and customise medical interventions. The increased interest in personalized healthcare techniques is driving demand for AI in genomics.
• Enhanced Diagnostic Capabilities: artificial intelligence algorithms can help with genetic data interpretation for diagnostic purposes. They are capable of detecting illness-causing mutations, detecting genetic predispositions, and providing information on disease prognosis. The need for quicker and more precise diagnosis and risk assessment drives the demand for artificial intelligence-driven diagnostics in genomics.
• Artificial intelligence can automate and optimize numerous genomics research tasks, including variation calling, the genome annotation, and analysis of pathways. AI allows professionals to focus on more advanced analysis and interpretation by decreasing the manual work required for these tasks. This increases research efficiency.
• Integration with Multi-Omics Data: To get a comprehensive understanding of biological systems, genomic data is frequently coupled with other data related to omics, such as transcriptomics, proteomics, and metabolomics. These multi-omics datasets may be integrated and analyzed using AI approaches, providing a comprehensive view and generating demand for AI in genomics research.
• AI Algorithms, Machine Learning Tools and Computational Resources: Continuous developments in AI algorithms, machine learning tools, and computational capabilities have made AI more accessible and powerful. The availability of intuitive AI platforms and tools has increased the demand of AI in genomics.

Overall, demand for AI in genomics is being driven by the need to handle and understand massive genomic datasets, enable precision medicine, speed drug discovery, improve diagnostics, increase research efficiency, and integrate multi-omics data. As the area of genomics advances, the demand for AI is expected to rise, shaping the future of genomics research and healthcare.

AI in Genomics Market Trends

• Based on components, the software segment expected to dominate the market with a revenue share of 45% in 2023 owing to the rapid adoption of software solutions in genomics driven by the increasing availability of genomic data, the rise of personalized medicine, the need for cost-effective solutions
• Based on end users, the pharmaceutical and biotech companies’ segment will command more than 30% of the AI in genomics market share in 2023 as the AI algorithms are used by these companies to analyze large amounts of genomic and chemical data to identify new drug targets and predict the efficacy and safety of potential drugs
• Based on application, the drug discovery and development segment to hold a majority of the AI in genomics market share of 30% in 2023 as AI solutions help to manage and analyze big data, enabling researchers to uncover new insights and knowledge that can be used to advance drug discovery and development
• Based on functionality, genomic sequencing expects to achieve majority share of the AI in genomics market with a revenue share of around 52% in 2023. AI-powered software solutions can help to automate many of the manual tasks involved in genomic sequencing, reducing the need for human labor and making the process more cost-effective
• Based on the technology, the machine learning segment to hold the largest AI in genomics market share in 2023 pertaining to the growing demand for machine learning in genomics as it provides new insights, improves accuracy, and enables the development of personalized medicine
• North America may hold the largest AI in genomics market share of around 44.0% in 2023 owing to the rising demand for AI in genomics driven by several factors such as technology advancements, a large amount of genomic data, a growing focus on personalized medicine, and significant investments in research and development

AI in genomics Market Challenge

Ethical Concerns and Regulatory and Legal compliance: As the adoption of AI in genomics grows, ethical concerns and compliance with regulations become increasingly important. To ensure ethical and accountable implementation of AI in genomics, discussions about data privacy, informed authorization, and ethical artificial intelligence practices are required.

AI in Genomics Market’s Key Suppliers

• IBM
• Microsoft Corporation
• NVIDIA Corporation
• Deep Genomics Incorporated
• Fabric Genomics, Inc.
• Data4cure, Inc.
• Predictive Oncology Inc.
• Emedgene Technologies Ltd
• Congenica Ltd.
• Sophia Genetics SA
• Illumina Inc.
• BenevolentAI limited.
• Freenome Holdings, Inc.
• Verge Genomics

AI in Genomics Market Segmentation: