Northbrook, IL 60062 -- (SBWIRE) -- 05/22/2023 -- The integration of artificial intelligence (AI) in the genomics industry is set to revolutionize the field in the near future. AI has the potential to unlock valuable insights from the vast amount of genomic data generated through high-throughput sequencing and other genomic technologies. By leveraging machine learning algorithms and deep learning models, AI can analyze complex genomic patterns, identify disease-associated genetic variations, and predict disease risks more accurately. AI-powered genomics platforms can accelerate genomic data interpretation, enabling researchers and healthcare professionals to make more informed decisions regarding disease diagnosis, treatment selection, and personalized medicine. Moreover, AI can assist in drug discovery and development by analyzing genomic data to identify potential therapeutic targets and predict drug responses. The synergy between AI and genomics holds immense promise in unraveling the complexities of human genetics and advancing precision medicine. As AI continues to evolve, the genomics industry will witness transformative advancements, leading to improved patient outcomes, targeted therapies, and a deeper understanding of human health and diseases.

Artificial Intelligence In Genomics Market in terms of revenue was estimated to be worth $0.5 billion in 2023 and is poised to reach $2.0 billion by 2028, growing at a CAGR of 32.3% from 2023 to 2028 according to a new report by MarketsandMarkets™. Factors such as need to accelerate processes and timeline and reduce drug development and discovery costs, increasing partnerships and collaborations among players and growing investments in AI in genomics primarily drive the growth of this market. Furthermore, rising adoption of AI in precision medicine, explosion in bioinformatics data and genomic datasets drive market growth.

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Software segment is expected to be the largest artificial intelligence (AI) in genomics market, by offering, during the forecast period

Based on offering, the market is segmented into software and services. The software segment accounted for the largest share of the global market in 2022. Software is needed to generate new insights from large-scale datasets and help understand genomic variations, thus enhancing the search for disease-causing variants and reducing clinical analysis times. The benefits offered by AI in genomics software are driving its adoption among end users.

The pharmaceutical & biotechnology companies' segment, by end user, is expected to be the largest and fastest growing artificial intelligence (AI) in genomics market during the forecast period
Based on the end user, the market is broadly segmented into pharmaceutical & biotechnology companies; healthcare providers; research centers, academic institutes, & government organizations; and other end users. Pharmaceutical & biotechnology companies accounted for the largest share of the global end-user market in 2022. Market growth can be attributed to the rising demand for solutions to cut the time and costs of drug development.

Asia Pacific is expected to be the fastest growing in artificial intelligence (AI) in genomics market in 2022
Based on region, the global market has been segmented into North America, Europe, Asia Pacific, and the Rest of the World. In 2022, Asia Pacific market is projected to register the highest CAGR during the forecast period. Emerging countries in the Asia Pacific, such as India and China, offer lucrative growth opportunities for market players, primarily due to the increasing public and private funding, improving IT infrastructure, the demand for affordable healthcare, favorable government norms, an increasing number of NGS-based research projects, growing awareness about precision medicine, and the high incidence of cancer and chronic diseases are expected to boost the adoption of AI in genomics in Asia Pacific.

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Artificial Intelligence in Genomics Market Dynamics:

Drivers:

1. Need to accelerate processes and timeline and reduce drug development & discovery costs
2. Increased partnerships and collaborations among players and growing investments in AI in genomics
3. Rising adoption of AI in precision medicine
4. Explosion in bioinformatics data and genomic datasets
5. Improving computing power and declining hardware cost

Restraints:

1. Lack of skilled AI workforce and ambiguous regulatory guidelines for medical software

Opportunities:

1. Focus on developing human-aware AI systems

Challenges:

1. Lack of curated genomic data
2. Data privacy concerns

Key Market Players:

Major players operating in the artificial intelligence (AI) in genomics market are NVIDIA Corporation (US), Microsoft Corporation (US), Google, Inc. (US), Intel Corporation (US), BenevolentAI (UK), FDNA, Inc. (US), DNAnexus (US), Engine Biosciences (US), Tempus Labs, Inc. (US), Congenica Ltd (England).

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Recent Developments:

- In December 2022, Intel Labs and the Perelman School of Medicine at the University of Pennsylvania (Penn Medicine) completed of a joint research study using distributed machine learning (ML) and artificial intelligence (AI) approaches to help international healthcare and research institutions identify malignant brain tumors.

- In September 20222, NVIDIA Corporation partnered with the Broad Institute of MIT and Harvard to accelerate Genome analysis workflows and help teams to co-develop large language models for the discovery and development of targeted therapies. The collaboration connects NVIDIA's AI expertise and healthcare computing platforms with the Broad Institute's researchers, scientists, and open platforms with a focus on Making NVIDIA Clara Parabricks available in the Terra platform, building large language models, and providing improved deep learning to Genome Analysis Toolkit (GATK).

- In August 2021, Illumina, Inc. acquired GRAIL to provide patients with access to a potentially life-saving multi-cancer early-detection test.

- In March 2021, SOPHiA GENETICS collaborated with Hitachi. This collaboration agreement offered clinical, genomic, and real-world insights to healthcare practitioners and pharmaceutical and biotechnology firms and to further democratize Data-Driven Precision Medicine internationally for the benefit of patients.

Artificial Intelligence In Genomics Market Advantages:

- Enhanced Data Analysis: AI algorithms can process and analyze large volumes of genomic data quickly and efficiently. This enables researchers and healthcare professionals to gain insights into complex genetic patterns, identify disease-associated variants, and understand the underlying mechanisms of diseases. AI can also detect subtle genetic variations that might otherwise be missed, leading to more accurate diagnoses and personalized treatment plans.

- Accelerated Drug Discovery: AI can significantly expedite the process of drug discovery by analyzing genomic data and identifying potential drug targets. Machine learning algorithms can analyze vast amounts of genomic and molecular data, enabling researchers to identify novel therapeutic targets and predict drug responses. This can streamline the drug development process, reduce costs, and increase the success rate of clinical trials.

- Precision Medicine: AI in genomics plays a crucial role in advancing precision medicine. By integrating genomic data with clinical and phenotypic information, AI algorithms can predict individual patient responses to specific treatments, optimize treatment plans, and identify patients at high risk for certain diseases. This enables healthcare providers to deliver personalized therapies tailored to each patient's genetic makeup, resulting in improved patient outcomes and reduced adverse effects.

- Early Disease Detection and Prevention: AI algorithms can analyze genomic data to identify patterns and markers associated with various diseases, enabling early detection and prevention. By identifying high-risk individuals or populations, AI can help implement proactive interventions and preventive strategies, leading to improved health outcomes and reduced healthcare costs.

- Decision Support Systems: AI-powered decision support systems can assist healthcare professionals in interpreting genomic data and making informed clinical decisions. By integrating AI algorithms into clinical workflows, healthcare providers can access real-time insights, evidence-based recommendations, and treatment guidelines, improving the accuracy and efficiency of diagnosis and treatment planning.

- Data Security and Privacy: AI in genomics also brings advancements in data security and privacy. With the growing concerns around patient data protection, AI can be employed to develop robust data anonymization techniques, secure data sharing protocols, and privacy-preserving machine learning algorithms, ensuring the confidentiality of genomic data while enabling collaboration and research.

The integration of artificial intelligence in genomics presents significant advantages, including enhanced data analysis, accelerated drug discovery, precision medicine, early disease detection, decision support systems, and improved data security and privacy. These advantages have the potential to transform the genomics market, revolutionize healthcare delivery, and improve patient outcomes.