Generative Artificial Intelligence (AI) in Drug Discovery Global Market Report 2024

The generative AI in drug discovery market size has grown exponentially in recent years. It will grow from $0.15 billion in 2023 to $0.19 billion in 2024 at a compound annual growth rate (CAGR) of 30.6%. The growth in the historic period can be attributed to several factors, including the rising prevalence of chronic diseases, the development of new drug discoveries and clinical trials, the support for AI integration into healthcare and drug development, the growth of biotech industries, and increasing governmental support.

The generative AI in drug discovery market size is expected to see exponential growth in the next few years. It will grow to $0.57 billion in 2028 at a compound annual growth rate (CAGR) of 30.7%. The growth in the forecast period can be attributed to several factors, including the demand for cost-effective drug discovery, which drives the adoption of generative AI, growing collaborations among market players, increasing computational power, integration of generative AI with other emerging technologies, and rapid drug development. Major trends in the forecast period include advancements in technologies, the integration of generative AI with experimental biology, high-throughput screening for accelerated drug discovery pipelines, the development of AI-driven platforms for drug repurposing, and the rising adoption of cloud-based AI solutions for collaborative drug discovery efforts.

The increasing number of clinical trials is anticipated to drive the expansion of generative AI in the drug discovery market. Clinical trials, involving human volunteers, aim to evaluate the safety and efficacy of new medical treatments or procedures, providing valuable scientific data for human use. Several factors contribute to the rise in clinical trials, including advancements in medical research, heightened disease burden, regulatory shifts, globalization of clinical research, patient advocacy, industry competition, technological progress, and funding availability. Clinical trial data serves as input for generative AI models, which accelerate drug discovery by predicting interactions and designing compounds. This collaboration enables personalized medicine, enhances treatment effectiveness, improves patient outcomes, and transforms the pharmaceutical landscape. For example, ClinicalTrials.gov reported a global registration of 477,234 clinical trials by the end of 2023, up from 437,512 trials in 2022, underscoring the pivotal role of clinical trials in driving generative AI adoption in drug discovery.

Key players in the generative AI drug discovery market are developing sophisticated AI-powered tools to expedite drug development processes. These tools leverage AI and machine learning to streamline drug discovery, design, and clinical trials through predictive analytics. They enhance efficiency in target identification, compound screening, preclinical development, regulatory compliance, and manufacturing. For instance, in May 2023, Google Cloud introduced two groundbreaking AI-driven solutions, the Target and Lead Identification Suite and the Multiomics Suite. These solutions empower biotech, pharmaceutical, and public sector organizations by improving drug discovery and precision medicine. The Target and Lead Identification Suite aids researchers in understanding amino acid functions and predicting protein structures, while the Multiomics Suite accelerates genomic data analysis, facilitating the development of personalized treatments.

In May 2023, Recursion Pharmaceuticals acquired Cyclica and Valence for $40 million and $47.5 million, respectively, bolstering its drug discovery capabilities through advanced technologies. These acquisitions position Recursion as a prominent hub for top-tier professionals in machine learning and AI, poised to innovate and shape the future of drug discovery. Cyclica Inc., based in Canada, specializes in data-driven drug discovery and artificial intelligence. Valence Labs, also based in Canada, focuses on advancing AI in drug discovery.

Major companies operating in the generative artificial intelligence (AI) in drug discovery market are Bayer AG, NVIDIA Corporation, Merck KGaA, IBM Research, Schrödinger Inc., Valo Health, BenevolentAI, XtalPi Inc., Insilico Medicine Inc., Recursion Pharmaceuticals Inc., Exscientia, Atomwise Inc., InveniAI LLC, Healx, Aitia, Cloud Pharmaceuticals Inc., Optibrium, Aiforia, BioSymetrics Inc., Collaborations Pharmaceuticals Inc., MAbSilico, Reverie Labs, Standigm Inc., DeepMatter Group Limited, Variational AI Inc.

North America was the largest region in the generative AI in drug discovery market in 2023. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the generative artificial intelligence (AI) in drug discovery market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

The countries covered in the generative artificial intelligence (AI) in drug discovery market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Generative AI in drug discovery utilizes advanced machine learning techniques, particularly generative models, to create and identify new pharmaceutical compounds. These AI systems analyze vast datasets encompassing chemical properties, biological activity, and existing drug information to predict and generate novel molecules with potential therapeutic benefits. The primary goal is to expedite the discovery of novel pharmaceutical compounds with therapeutic potential, streamlining the drug development process by leveraging extensive data to efficiently predict and generate new molecules.

The main types of generative artificial intelligence (AI) in drug discovery are small molecule and large molecule. Small molecules are chemically synthesized drugs with typically low molecular weights. Various technologies including deep learning, machine learning, reinforcement learning, molecular docking, and quantum computing are employed by a range of end-users, including pharmaceutical and biotechnology companies, academic and research institutions, contract research organizations (CROs), and others.

The generative artificial intelligence (AI) in drug discovery market research report is one of a series of new reports that provides generative artificial intelligence (AI) in drug discovery market statistics, including generative artificial intelligence (AI) in drug discovery industry global market size, regional shares, competitors with a generative artificial intelligence (AI) in drug discovery market share, detailed generative artificial intelligence (AI) in drug discovery market segments, market trends and opportunities, and any further data you may need to thrive in the generative artificial intelligence (AI) in drug discovery industry. This generative artificial intelligence (AI) in drug discovery market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The generative AI in drug discovery market includes revenues earned by entities by providing services such as molecule generation, optimization, virtual screening, predictive modeling, de novo drug design, and consulting support. The market value includes the value of related goods sold by the service provider or included within the service offering. The generative AI in drug discovery market also includes sales of quantum computers, high-performance computing (HPC) clusters, tensor processing units, graphics processing units, and preclinical development tools. Values in this market are ‘factory gate’ values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.


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