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. The new research study consists of an industry trend analysis of the market. The new research study consists of industry trends, pricing analysis, patent analysis, conference and webinar materials, key stakeholders, and buying behaviour in the market. The need to control drug development and discovery costs and time, increasing public and private investments in AI in genomics, and the adoption of AI solutions in precision medicine are driving the growth of this market. The market growth is primarily driven by the need to accelerate processes and timeline and reduce drug development & discovery costs and increasing partnerships and collaborations among players and growing investments in AI in genomics. Additionally, factors such as improving computing power and declining hardware cost, rising adoption of AI in precision medicine, and explosion in bioinformatics data and genomic datasets are also contributing to the market growth.

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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).

Driver: Need to accelerate processes and timeline and reduce drug development and discovery costs

Drug discovery is an expensive and lengthy process, which creates a need for alternative tools to discover new drugs. Drug discovery and development are commonly conducted through in vivo and in vitro methods, which are costly and time-consuming. Furthermore, it takes ~10 years on average for a new drug to enter the market and costs ~USD 2.6 billion.

Only one out of 5,000-10,000 compounds is approved as a potential drug for a particular condition. Most drug candidates selected in the discovery phase fail in the late stages of development due to toxicity or other pharmacokinetic characteristics. Machine learning technology can help at this stage by predicting the outcome of a drug compound in the discovery phase and eliminating compounds without potential in the early discovery phase itself. This will significantly cut downtime and expenses in identifying potential drug candidates.

The potential for time and cost reductions in this process has drawn significant stakeholder attention and resulted in numerous investigative projects. For instance, in November 2020, Deep Genomics and BioMarin announced a collaboration to discover and develop oligonucleotide drug candidates for four rare diseases, combining BioMarin’s extensive rare disease expertise with Deep Genomics AI Workbench platform. With that, AI in genomics for drug discovery has the potential to significantly accelerate the drug development process, reduce costs, and improve patient outcomes by enabling the development of more targeted and effective drugs.

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

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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.

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