Northbrook, IL 60062 -- (SBWIRE) -- 12/15/2023 -- Artificial Intelligence in Drug Discovery Market in terms of revenue was estimated to be worth $0.9 billion in 2023 and is poised to reach $4.9 billion by 2028, growing at a CAGR of 40.2% from 2023 to 2028 according to a new report by MarketsandMarkets. The ascent of precision medicine, characterized by tailored treatments aligned with individual patient attributes, has become a pivotal trend. This paradigm shift has bestowed prominence upon the field. Leveraging AI algorithms, intricate genetic and molecular datasets can be deciphered, discerning patient subgroups that exhibit heightened potential for favorable responses to specific therapies. This, in turn, culminates in the formulation of treatments that are both targeted and notably efficacious, ultimately propelling the growth of the AI in drug discovery market. The introduction of novel AI-driven methodologies necessitates regulatory bodies to undergo adaptation, a process that could potentially engender delays or uncertainties. These dynamics, in turn, pose potential challenges and threats to the market landscape.

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"Services segment is expected to grow at the highest rate during the forecast period."

Based on offering, the AI in drug discovery market is bifurcated into software and services. In 2022, the services segment is poised to register the highest CAGR throughout the forecast period. The ascendancy of AI services is attributed to their instrumental role in conducting comprehensive analysis and interpretation of intricate biological and chemical data. Leveraging advanced machine learning algorithms, these services enable the extraction of meaningful insights from expansive datasets, thereby facilitating the identification of potential drug candidates and more precise prognostication of their behaviors. These determinants collectively propel the dynamic expansion of this market segment.

"Machine learning technology segment accounted for the largest share of the global AI in drug discovery market."

Based on technology, AI in drug discovery market is bifurcated into machine learning, natural language processing (NLP), context-aware processing or context-aware computing and other technologies. In 2022, the machine learning sector held the largest market share and is poised to achieve the highest CAGR throughout the projected timeframe. Within the machine learning technology sphere, there exists further segmentation, encompassing deep learning, supervised learning, reinforcement learning, unsupervised learning, and other machine learning technologies. Machine learning algorithms have consistently showcased exceptional adeptness in dissecting intricate and multifaceted datasets, spanning genomics, proteomics, chemical structures, and clinical data. Their capacity to identify latent patterns and correlations within the data, which might elude conventional methodologies, empowers researchers to predict potential drug interactions, efficacy profiles, and safety attributes with heightened precision.

"The neurology diseases therapeutic area segment is expected to grow at the highest CAGR of the AI in drug
discovery market in 2022."

Based on therapeutic area, the AI in drug discovery market encompasses neurodegenerative diseases, oncology, cardiovascular diseases, metabolic diseases, immunology, and other distinct therapeutic areas. Notably, the neurology segment is expected to grow at the highest CAGR during the forecast period. This projection stems from AI's pivotal role in resolving the intricacies associated with neurological drug development. Additionally, strategic partnerships between pharmaceutical entities and solution providers significantly contribute to the elevated growth rate observed within the neurodegenerative diseases segment.

"North America is expected to dominate the AI in drug discovery market in 2022"

In 2022, North America commanded the foremost position in the global AI in drug discovery market share and is poised to maintain this leadership with the highest anticipated CAGR during the forecast period. This commanding position is attributed to North America's robust technological underpinning, which serves as a fundamental bedrock for the seamless integration and implementation of AI technologies within the domain of drug discovery. Distinguished by its advanced IT infrastructure, North America adeptly manages the intricate handling, processing, and analysis of the voluminous and intricate datasets intrinsic to drug discovery procedures. Undeniably, this region has spearheaded the early adoption of AI technology in drug discovery and developmental pursuits. This leadership is underpinned by a nexus of crucial factors, including the presence of key industry players, a firmly established pharmaceutical and biotechnology sector, substantial investments in research and development, and a steadfast focus on advancing innovative solutions. The culmination of these elements decisively contributes to North America's commanding market presence and is indicative of the region's sustained and remarkable growth trajectory in the AI in drug discovery domain.

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Artificial Intelligence in Drug Discovery Market Dynamics:

Drivers:

1. Growing need to control drug discovery & development costs and reduce time involved in drug development

Restraints:

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

Opportunities:

1. Emerging Markets

Challenge:

1. Limited availability of data sets

Key Market Players of Artificial Intelligence in Drug Discovery Industry:

The prominent players in artificial intelligence (AI) in drug discovery market are NVIDIA Corporation (US), Exscientia (UK), BenevolentAI (UK), Recursion (US), Insilico Medicine (US), Schrödinger, Inc. (US), Microsoft Corporation (US), Google (US), Atomwise Inc. (US), Illumina, Inc. (US), NuMedii, Inc. (US), XtalPi Inc. (US), Iktos (France), Tempus Labs (US), Deep Genomics, Inc. (Canada), Verge Genomics (US), BenchSci (Canada), Insitro (US), Valo Health (US), BPGbio, Inc. (US), IQVIA Inc (US), Labcorp (US), Tencent Holdings Limited (China), Predictive Oncology, Inc. (US), Celsius Therapeutics (US), CytoReason (Israel), Owkin, Inc. (US), Cloud Pharmaceuticals (US), Evaxion Biotech (Denmark), Standigm (South Korea), BIOAGE (US), Envisagenics (US), and Aria Pharmaceuticals, Inc. (US). Players adopted organic as well as inorganic growth strategies such as product launches and enhancements, and investments, partnerships, collaborations, joint ventures, funding, acquisition, expansions, agreements, sales contracts, and alliances to increase their offerings, cater to the unmet needs of customers, increase their profitability, and expand their presence in the global market.

Breakdown of supply-side, demand side, primary interviews, by company type, designation, and region:

· By Supply Side: Tier 1 (31%), Tier 2 (28%), and Tier 3 (41%)
· By Demand Side: Purchase Managers (45%), Head of Artificial Intelligence, Machine Learning, Drug Discovery, and Computational Molecular Design (30%) and Research Scientists (25%).
· By Designation: C-level (31%), Director-level (25%), and Others (44%)
· By Region: North America (45%), Europe (20%), Asia Pacific (28%), South America (4%) and Middle East & Africa (3%).

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Recent Developments:

· In October 2023, Recursion, in collaboration with Roche and Genentech, achieved its first significant milestone by identifying and validating a hit series for a specific disease, triggering Roche's Small Molecule Validation Program Option. Recursion would lead the program's advancement using its Recursion OS and digital chemistry tools. This marked progress in their joint efforts to develop therapeutic programs based on Maps of Biology and Chemistry, with plans to expand to multiple CNS cell types for novel target hypotheses and partnerships in the future.
· In September 2023, Exscientia entered into a collaboration with Merck KGaA focused on the discovery of novel small molecule drug candidates across oncology, neuroinflammation and immunology. The multi-year collaboration will utilize Exscientia's AI-driven precision drug design and discovery capabilities while leveraging Merck KGaA's disease expertise in oncology and neuroinflammation, clinical development capabilities and global footprint.
· In May 2023, Google Cloud launched two new AI-powered solutions, the Target and Lead Identification Suite, and the Multiomics Suite, to accelerate drug discovery and precision medicine for biotech companies, pharmaceutical firms, and public sector organizations. The Target and Lead Identification Suite enables more efficient in silico drug design, predicting protein structures and accelerating lead optimization for drug discovery.
· In May 2023, 9xchange partnered with BenevolentAI. The partnership aimed to leverage BenevolentAI's AI-enabled technology to support decision-making related to indication expansion and drug repurposing for assets within the 9xchange platform. By combining BenevolentAI's proven AI-enabled engine with the 9xchange platform, the partnership aimed to uncover untapped potential in therapeutic portfolios, create new opportunities for drug discovery.
· In March 2023, NVIDIA launched the BioNeMo Cloud service, expanding its generative AI cloud offerings to aid drug discovery and research in genomics, chemistry, biology, and molecular dynamics. The BioNeMo Cloud service allows researchers to fine-tune AI applications on their proprietary data and run AI model inference in web browsers or through cloud APIs.

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