The Global AI In Biotechnology Market is projected to reach USD 7.75 billion by 2029 from USD 3.23 billion in 2024, at a high CAGR of 19.1% during the forecast period. Increasing cross-industry collaborations and partnerships that foster innovation and resource sharing are the main reasons for the growth of this market. High penetration of AI-powered biomarker discovery for complex diseases, rising utilization of AI in digital twins for drug discovery, and AI and CRISPR-Cas9 synergy in genetic drug discovery are some of the other factors propelling market growth. However, several factors will likely restrain market growth such as fragmented global regulations for AI, lack of sufficient AI infrastructure in developing economies, and difficulties in applying ai-generated knowledge to clinical settings are some factors contributing to challenges in the market growth.
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Based on deployment mode, the AI in biotechnology market is categorized into cloud-based and on-premises. The cloud-based segment accounted for the largest share of AI in biotechnology market in 2023. Each deployment type offers distinct advantages and is chosen based on factors like data sensitivity, scalability, cost considerations, and operational flexibility. cloud-based solutions offer scalability, ease of access, and reduced upfront costs, allowing companies to rapidly expand their AI capabilities without heavy investment in hardware. In contrast, on-premises deployments provide greater control over data security and infrastructure, making them ideal for organizations handling sensitive research and patient information.
Based on end user, the research institutes and labs segment are expected to register the fastest growth in the AI in biotechnology market. A significant share of this segment is attributed to the growing need to analyse enormous amounts of data and uncover meaningful patterns and insights that exceed human capacity, as human analysts often struggle to keep up with the volume and complexity. Also, AI enables researchers to create virtual models of complex biological processes that are difficult to replicate in real-life lab settings. This capability helps scientists explore different experimental conditions and predict outcomes without the need for physical experiments and the integration of AI can help researchers to be more effective and make informed decisions, saving time and resources.
North America holds the largest share of the AI in biotechnology market in 2023 followed by Europe and the Asia Pacific, by region. Drivers include substantial funding for AI-based startups and research projects for the development and deployment of AI solutions within the biotechnology sector, and the growing need to find causes of problems in diagnostic research also, wide range of sectors integrating AI into their solutions and operations, which is increasing overall market demand.
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Prominent players in the AI in the biotechnology market include NVIDIA Corporation (US), Illumina, Inc. (US), Exscientia plc (UK), Schrödinger, Inc. (US), Recursion Pharmaceuticals, Inc. (US), SOPHiA GENETICS (Switzerland), Predictive Oncology. (US), Deep Genomics. (Canada), Data4Cure, Inc. (US), Genoox (US), BenevolentAI (US), DNAnexus, Inc. (US), Tempus (US), NuMedii, Inc. (US), XtalPi Inc. (US), Lifebit Biotech Ltd (England), BPGbio, Inc. (US), Valo Health (US), VeriSIM Life. (US), Iktos. (France), Insilico Medicine (US), Eurofins Discovery. (US), Logica. (US), American Chemical Society (US), Aganitha AI Inc. (India).
These companies adopted strategies such as partnerships, collaborations, acquisitions, expansion, agreements, investment, and product launches to strengthen their market presence in the AI in Biotechnology market.
NVIDIA Corporation engages in the design and manufacture of computer graphics processors, chipsets, and related multimedia software. It operates through the following segments: Graphics Processing Unit (GPU) and Compute & Networking. Initially, the firm was primarily operating in graphics hardware for gaming, but through time, over the recent years, NVIDIA has been more focused towards applications of AI, machine learning, deep learning, and data science in a wide array of industries as well as into healthcare, for example. The company's GPUs have been known to provide better performance in AI computing; it thus formed the core of moving research that is driven by AI, including applications in medical imaging and digital pathology. NVIDIA is making deep inroads in the healthcare sector by furthering the development of AI innovations using its NVIDIA Clara platform as an AI engine that offers AI tools and frameworks for medical imaging, genomics, and drug discovery. At the level of digital pathology, NVIDIA is utilizing GPUs and AI frameworks to facilitate accelerated image analysis and faster and more accurate diagnosis from pathology slides. The company operates in North America, South America, Asia Pacific, and Europe.
Illumina, Inc. is one of the leading providers of genomic solutions. The company delivers array-based life sciences technology and DNA sequencing to facilitate personalized health and advanced research & discovery. It offers products related to infectious diseases, genetics, reproductive health oncology, and others. Illumina has collaborated with several global payers such as AstraZeneca, Janssen, PRECISE, Bristol-Myers Squibb, Kura Oncology, Myriad Genetics, Merck, and others to expand their product portfolio and strengthen their position in the global market.
Exscientia plc is a drug design firm that effectively develops medications for illnesses with substantial unmet patient needs by utilizing artificial intelligence (AI) and innovative technologies. The company aims to improve the probability of successful medication development by identifying and addressing potential causes of failure in the drug design process. Exscientia's technological platform includes several innovative methods, including generative Al, active learning, machine learning, and physics-based systems.
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