Artificial Intelligence In Drug Discovery Market Size, Share & Trends Analysis Report By Therapeutic Space (Oncology, Neurodegenerative Diseases), By Application, By Region, And Segment Forecasts, 2024 - 2030

Market Size & Trends  

The global artificial intelligence in drug discovery market size was estimated at USD 1.5 billion in 2023, and is expected to expand at a CAGR of 29.7% from 2024 to 2030. The demand for AI-powered solutions in drug discovery is rising due to the need for novel drug therapies, increased manufacturing capacities in the life sciences industry, and technological advancements. AI technologies, such as machine learning and deep learning, are being applied to various stages of drug discovery, including initial compound screening and predicting success rates in clinical trials. Moreover, increasing investments, funding, and the rise of startups developing AI-powered solutions are expected to drive market growth. For instance, in April 2024, Xaira Therapeutics announced it received $1 million in funding for drug discovery development.

Furthermore, the adoption of AI solutions in the clinical trial process has revolutionized the field by addressing potential obstacles, enhancing productivity and accuracy, and reducing cycle times. This advanced approach is increasingly popular among stakeholders in the life sciences industry, reflecting a growing recognition of its benefits. Data from Clinical Trials Arena in 2021 indicate a significant rise in strategic collaborations and partnerships between AI-driven drug discovery firms and pharmaceutical companies, with these alliances increasing from 4 in 2015 to 27 in 2020. This trend highlights the expanding role of AI in streamlining drug discovery and development processes.

Digitalization in biomedical and clinical research is paving the way for implementing AI solutions. The vast array of datasets generated from drug discovery processes, such as molecule screening phases and preclinical studies, is boosting the adoption of AI-powered solutions. These monumental datasets make it challenging for researchers to analyze studies accurately. AI solutions can accelerate screening processes and reduce turnaround times.

The market growth is driven by the availability of myriad options, such as data mining and personalization capabilities, in adopting AI solutions in drug discovery processes. Enhanced accuracy is achieved through integrating deep learning and machine learning algorithms in AI platforms, which help identify the molecule binding properties of drugs. Moreover, incorporating advanced technologies such as electronic data capture (EDC) supports manufacturers in improving patient data management and reducing monitoring costs. Process errors can be minimized by integrating electronic Clinical Outcome Assessment (e-COA) in AI solutions. Recently, advanced analytics have been integrated into these AI solutions, aiding stakeholders in data mining, patient recruitment, and medical & clinical records management.

Among the different phases of a clinical trial study, preclinical testing accounts for the highest revenue loss with low returns. Adopting AI solutions can optimize the preclinical testing phase to minimize costs. AI-based models accurately analyze human physiological responses, eliminating experimental costs. Stringent regulations pertaining to clinical trial studies laid down by regulatory authorities worldwide are anticipated to drive the demand for AI solutions in drug discovery processes. On the other hand, government authorities in various developed and emerging economies are undertaking favorable initiatives to increase the penetration of AI solutions and the number of clinical trials.

Impact of COVID-19 on Artificial Intelligence In Drug Discovery Market

The COVID-19 pandemic significantly accelerated the adoption of AI in drug discovery, particularly from 2020 to 2022. AI technologies were crucial in expediting the development of treatments and vaccines, highlighting their potential in rapidly identifying therapeutic candidates and optimizing clinical trials. A notable milestone was achieved in 2021 by the UK-based firm Exscientia, which commenced the Phase I trial of its second AI-designed molecule, the world’s first for immuno-oncology. This success led to a $100 million Series C funding round in March 2021.

Key trends during this period include the integration of multi-omics data, AI-driven target selection, drug screening, and the establishment of AI innovation labs. AI's ability to quickly and accurately analyze vast datasets has been especially impactful in oncology, enhancing early disease detection and enabling personalized treatment approaches.

Industry Dynamics

The market is characterized by significant innovation, driven by the integration of sophisticated algorithms, machine learning, and data analytics. Innovations are focused on improving the efficiency and accuracy of drug discovery processes, from target identification to lead optimization and clinical trial design. These advancements are substantially reducing the time and cost associated with bringing new drugs to market, transforming the pharmaceutical industry. For instance, in December 2023, Merck launched ADDISON drug discovery software, the first software-as-a-service platform to integrate virtual molecule design with real-world manufacturability through the SynthiaTM retrosynthesis software application programming interface (API). The platform combines machine learning, generative AI, and computer-aided drug design to accelerate drug development.

"With millions of people waiting for the approval of new medicines, bringing a drug to market, still takes on average, more than 10 years and costs over 1.9 Million Euros1, Our platform enables any laboratory to count on generative AI to identify the most suitable drug-like candidates in a vast chemical space. This helps ensure the optimal chemical synthesis route for development of a target molecule in the most sustainable way possible."

           - Karen Madden, Chief Technology Officer, Life Science business sector of Merck.

The market is witnessing a notable increase in mergers and acquisitions (M&A) activity. Major pharmaceutical companies and technology giants are actively acquiring AI startups and smaller companies with specialized expertise. For example, in July 2023, BioNTech acquired InstaDeep, a global AI and machine learning technology company. This acquisition aligns with BioNTech's strategy to advance AI-driven drug discovery and develop next-generation immunotherapies and vaccines. InstaDeep will operate as a UK-based global subsidiary, providing services to clients worldwide. This consolidation is fostering collaboration, accelerating innovation, and leading to the development of more effective and efficient drug discovery solutions.

Regulations significantly impact the market. Regulatory bodies such as the FDA in the U.S. and the EMA in Europe are increasingly establishing guidelines to ensure the safe and ethical use of AI in healthcare. These regulations address critical issues such as data privacy, algorithmic transparency, and the validation and reproducibility of AI models. Compliance with these standards is essential for gaining market approval and maintaining public trust. While stringent regulations can pose challenges, it ensure that AI applications in drug discovery are safe, reliable, and beneficial to patients.

Regional expansion in the AI-driven healthcare sector varies from moderate to high, with companies strategically extending their global presence. This expansion aims to meet growing demand, tap into emerging healthcare markets, and promote AI adoption in the industry. For example, in November 2023, Brainomix, specializing in AI-powered software for precision medicine in stroke, lung fibrosis, and cancer, expanded into the U.S. market. Brainomix launched FDA-cleared modules on its Brainomix 360 platform, offering a comprehensive stroke imaging solution. This move highlights the trend of leveraging AI to improve healthcare outcomes and streamline medical processes.

Application Insights

Based on application, the drug optimization and repurposing segment accounted for the highest market share of 53.7% in 2023. This dominance is primarily due to the efficiency and cost-effectiveness associated with these processes. Drug optimization involves refining and improving existing drug candidates to enhance their efficacy and safety profiles, which accelerates the path to market and reduces the overall R&D costs. Repurposing existing drugs for new therapeutic uses leverages previously gathered data on safety and efficacy, significantly shortening development timelines and lowering financial risks. These strategies are increasingly appealing to pharmaceutical companies aiming to maximize their investment returns and address unmet medical needs swiftly. Consequently, the growing emphasis on optimizing and repurposing drugs has led this segment to lead the market.

Preclinical testing segment is another application of AI in drug development that is growing at the fastest pace. This rapid expansion is driven by AI's ability to enhance various aspects of preclinical testing, such as predicting drug toxicity, optimizing drug candidate selection, and modeling biological interactions. AI technologies can analyze vast datasets from preclinical experiments, identifying patterns and insights that might be missed by traditional methods. These capabilities significantly reduce the time and cost associated with preclinical testing. By quickly identifying promising drug candidates and eliminating those likely to fail in later stages, AI streamlines the development process and increases the overall efficiency of R&D efforts. As a result, pharmaceutical companies are increasingly adopting AI-driven approaches in preclinical testing, fueling the segment's rapid growth.

Therapeutic Area Insights

Oncology segment held the largest revenue share of 22.4% in 2023. This prominence is attributed to several factors. Cancer remains one of the most significant global health challenges, driving substantial investment in research and development for effective treatments. According to the estimates by WHO, in 2022, 20 million new cancer cases and 9.7 million deaths were reported globally. AI technologies offer considerable advantages in oncology, including the ability to analyze complex datasets, identify novel drug targets, and predict patient responses to therapies. The integration of AI in oncology has accelerated the discovery and development of new cancer treatments, personalized medicine approaches, and improved clinical trial designs.

The infectious disease segment is expected to grow at the fastest CAGR of 32.0% during the forecast period. AI and related platforms such as the Internet of Things (IoT) are currently being deployed to understand infectious diseases, their transmission, and infection mechanism, and also to improve vaccine design. These platforms use a network of connected devices like smartphones and other medical devices, data collected from these devices can be used for understanding lifestyle patterns and anomalies for studying diseases.

Regional Insights

North America artificial intelligence in drug discovery market held the largest market share of 57.7% in 2023, driven by significant investments in healthcare technology and strong collaborations between pharmaceutical companies and tech giants. The region's renowned research institutions and supportive regulatory environment further stimulate innovation. Companies are increasingly utilizing AI to streamline drug discovery processes, lower costs, and expedite the introduction of new therapies to market.

U.S. Artificial Intelligence In Drug Discovery Market Trends

Artificial Intelligence In Drug Discovery Market in the U.S. held the largest market share in 2023. The U.S. stands out as a global hub for AI in drug discovery, with major pharmaceutical companies and tech firms investing heavily in AI technologies. The FDA's progressive approach to regulatory guidelines for AI applications in healthcare fosters innovation while ensuring safety and efficacy. The U.S. market is characterized by a high level of M&A activity, with companies seeking to integrate AI capabilities to gain a competitive edge in drug development. For instance, in February 2024, Ginkgo Bioworks acquired Reverie Labs' AI/ML tools and infrastructure for large-scale AI foundation models, aiming to strengthen its AI/ML-driven discovery services and accelerate the development of next-generation biological foundation models.

Europe Artificial Intelligence In Drug Discovery Market Trends

Europe artificial intelligence in drug discovery market is expected to grow significantly over the forecast period. Europe is a key player in the AI in drug discovery market, with substantial contributions from countries like Germany and the UK. The region boasts a strong research infrastructure and favorable regulatory frameworks that support the integration of AI in healthcare. European companies are at the forefront of adopting AI for drug discovery, focusing on personalized medicine and advanced data analytics to enhance drug development processes. Collaborative efforts between academia, industry, and government agencies are driving significant advancements in this field.

Artificial intelligence in drug discovery market in UK is expected to grow significantly over the forecast period. UK is home to numerous AI-driven initiatives aimed at revolutionizing drug discovery. Government support, through initiatives like the Industrial Strategy Challenge Fund, and collaboration between industry and academia are key factors driving the adoption of AI technologies in the UK.

Asia Pacific Artificial Intelligence In Drug Discovery Market Trends

Asia Pacific artificial intelligence in drug discovery market is expected to grow at the fastest CAGR by the end of 2030. The region is witnessing rapid growth in the AI in drug discovery market, driven by countries like China and India. Companies in the Asia Pacific are developing AI technologies to accelerate drug discovery and development intended to improve clinical trial efficiency and address unmet medical needs. For instance, in October 2023, Fujitsuand RIKEN collaborated to develop AI-driven technology for drug discovery, leveraging generative AI to predict structural alterations in proteins. This innovation integrates AI algorithms with electron microscope imagery, aimed at accelerating drug development processes while optimizing costs.

Artificial intelligence in drug discovery market of Japan is emerging as a notable player with a focus on integrating. Japanese companies are investing in AI to enhance drug discovery processes and develop personalized therapies. The government's push towards digital health transformation and strong collaboration between industry and research institutions are fueling advancements in AI-driven drug discovery in Japan. Furthermore, the entry of other market players in the Japan are also expected to drive the market growth. For instance, in September 2021, anIsraeli startup CytoReason has entered Japan, the world's third-largest pharmaceutical market, through a collaboration with Summit Pharmaceuticals International, the drug research and development division of Sumitomo Corporation, a global trading firm.

China artificial intelligence in drug discovery market is at the forefront of AI adoption in the Asia-Pacific region, with significant investments in healthcare AI and biotechnology. Many pharmaceutical firms in China are increasingly partnering with AI-driven companies, aiming to accelerate drug development efforts. These collaborations seen as pivotal to enhancing China's pharmaceutical industry, which has faced slower growth rates. China's contract research organizations are already reaping the rewards of AI technologies, which are fostering global interest in novel molecules. According to an article published by The Economist Newspaper Limited on March 2024, China invested over USD 1.26 Million in AI-assisted drug discovery in 2021, highlighted its commitment to leveraging advanced technologies in healthcare innovation.

Key Artificial Intelligence Intelligence In Drug Discovery Company Insights

The need to develop better drugs and faster is driving the adoption of AI in the pharmaceutical sector for studying diseases and drug designing as a whole. Major tech giants are taking initiatives for acceleration in the field of drug discovery. The majority of the share in the global market is held by corporations like IBM, Microsoft, Atomwise Inc., Cloud pharmaceuticals, Benevolent AI, BIOAGE, etc. Collaborations between Tech companies and academic and research institutes are providing the necessary spurt to the expansion of the use of AI in the pharmaceutical industry as a whole. Better drugs can be formulated with minimum side effects and diseases can be studied in a much faster and much better way so as to find necessary cures with the help of AI and related platforms.

Recent Developments

• In July 2024, Exscientia announced an expanded collaboration with Amazon Web Services (AWS) to utilize AWS's AI and machine learning (ML) services to enhance its end-to-end drug discovery and automation platform.

“Extending our collaboration with AWS beyond our DesignStudio to include the robotic automation of synthesis and testing of our molecular designs was the logical next step for Exscientia. We were seeking a solution that had flexibility and scalability, combined with high performance and generative AI capabilities. We also wanted a collaborator that is creative and passionate about life sciences. AWS ticks all of these boxes.”

-Chief Technology Officer of Exscientia

• In May 2024, Google DeepMind released the third version of its AlphaFold AI-based model, aimed at advancing drug design and disease targeting. This latest iteration allows researchers at DeepMind and Isomorphic Labs to map the behavior of all molecules, including human DNA.

• In April 2024, Xaira Therapeutics, an AI-powered drug discovery and development company, raised over USD 1 Million in a joint funding round with ARCH Venture Partners and Foresite Labs. The company uses machine learning, data generation models, and therapeutic product development to target traditionally challenging drug targets

• In December 2023, MilliporeSigma, the life science division of Merck, introduced AIDDISON, an innovative drug discovery software. This tool aims to seamlessly connect the design of virtual molecules with practical manufacturability. It leverages the Synthia retrosynthesis software API to enhance the efficiency and feasibility of drug development processes

• In May 2023, Google introduced two new AI-powered solutions designed to assist biotech and pharmaceutical companies in expediting drug discovery and advancing precision medicine. These tools aim to streamline the lengthy and costly process of bringing new treatments to the U.S. market. Cerevel Therapeutics, Pfizer, and Colossal Biosciences are among the early adopters of these solutions.

Artificial Intelligence In Drug Discovery Market Report Scope

Global Artificial Intelligence In Drug Discovery Market Report Segmentation

This report forecasts revenue growth at country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2018 to 2030. For the purpose of this study, Grand View Research, Inc. has segmented the global artificial intelligence (AI) in drug discovery market report on the basis of application, therapeutic area, and region.

• Application Outlook (Revenue, USD Million, 2018 - 2030)

  • Drug optimization and repurposing

  • Preclinical testing

  • Others

• Therapeutic Area Outlook (Revenue, USD Million, 2018 - 2030)

  • Oncology

  • Neurodegenerative Diseases

  • Cardiovascular Disease

  • Metabolic Diseases

  • Infectious Disease

  • Others

• Geographic Area Outlook (Revenue, USD Million, 2018 - 2030)

  • North America

    • U.S.

    • Canada

    • Mexico

  • Europe

    • U.K.

    • Germany

    • France

    • Italy

    • Spain

    • Denmark

    • Sweden

    • Norway

  • Asia Pacific

    • Japan

    • China

    • India

    • South Korea

    • Australia

  • Latin America

    • Brazil

    • Argentina

  • MEA

    • South Africa

    • Saudi Arabia

    • UAE

    • Kuwait