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Artificial Intelligence in Drug Discovery Market by Offering (Software, Service), Application (Target Discovery, Lead Identification, Clinical Testing), Therapy Area (Oncology, Cardiology, Neurodegenerative), Deployment, End User—Global Forecast to 2030
Report ID: MRHC - 104745 Pages: 200 Jun-2024 Formats*: PDF Category: Healthcare Delivery: 24 to 72 Hours Download Free Sample ReportPharmaceutical companies face several challenges during drug development, including timelines, high investment in R&D, and regulatory challenges. The need for developing and manufacturing advanced therapies has increased, resulting in newer challenges such as the collection and analysis of large data, the need for qualified professionals, and data security. Artificial intelligence (AI) is the replication of human intelligence processes. The use of AI has been increasing in various sectors, especially in the pharmaceutical industry. AI is used in R&D, drug development, diagnosis, disease prevention, remote monitoring, and epidemic prediction in the pharmaceutical industry. The adoption of AI in pharmaceutical drug discovery has enabled better success rates, quicker & faster delivery processes, and access to new biology.
The growth of the AI in drug discovery market is attributed to the rising focus on reducing the turnaround time in drug discovery, growing applications of AI in drug discovery, the rising incidence of chronic diseases, and the high risk of emerging infectious diseases. The rising adoption of machine learning (ML) in drug discovery, the emergence of local and regional start-ups in AI in drug discovery, and rising investments in R&D are creating opportunities for the growth of this market.
The incidence of chronic diseases, including chronic obstructive pulmonary disease (COPD), diabetes, coronary artery disease, hepatitis, arthritis, and cancer, is rising. According to the Centers for Disease Control and Prevention (CDC) data published in December 2022, six in ten adults in the U.S. have a chronic disease. Furthermore, according to the European Commission, in 2021, over 35.2% of the people in the European Union were reported to have chronic diseases.
According to the International Diabetes Federation, in 2020, 502 million people worldwide were diagnosed with diabetes. By 2030, 23.4 million new cases of cancer are expected to develop annually. Among all cancer types, lung cancer is the most common form leading to mortality in Asia-Pacific. Apart from cancer, the prevalence of several additional diseases has also increased over the years. Thus, the high prevalence of chronic diseases is driving the development and manufacturing of advanced therapies, boosting the applications of AI in drug discovery.
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After significant advancements in AI, its applications in drug discovery are rising. This is indicated by the increasing investments and a rise in the number of collaborations between pharmaceutical industries and AI companies. According to Stanford University’s Institute for Human-Centered Artificial Intelligence’s (HAI) Artificial Intelligence Index, investments in AI in drug discovery reached USD 13.8 billion in 2020. In April 2021, Exscientia (U.K.), a clinical-stage pharma tech company using artificial intelligence (AI) to design patient-based drugs, completed USD 225 million Series D funding round to continue expanding its proprietary pipeline and end-to-end AI drug discovery capabilities.
In 2024, the software segment is expected to account for the largest share of the AI in drug discovery market. AI in drug discovery software is used for faster, efficient, and cost-effective drug discovery and enhanced clinical trials. Thus, the growing interest of pharmaceutical companies in developing novel therapies has increased the adoption of AI in drug discovery software.
The cloud-based segment is projected to register the highest CAGR over the forecast period. The demand for cloud-based and web-based platforms is growing due to the benefits of cloud-based models in terms of security and flexibility, high-capacity data storage, quick accessibility, and cost-effectiveness.
In 2024, the lead compound identification segment is expected to account for the largest share of the AI in drug discovery market. The large market share of this segment is attributed to the benefits and importance of lead compound identification in drug discovery. Lead compound identification is a crucial step in drug discovery which is likely to finalize the compounds in drug discovery to reach lead compound optimization and, ultimately, to the clinical candidate development phase. Additionally, the use of AI in lead compound identification helps minimize time and cost.
In 2024, the oncology segment is expected to account for the largest share of the AI in drug discovery market. Most drug discovery companies focus on oncology for the drug discovery process. The high prevalence of cancer and the availability of funding for oncology research are the factors contributing to the large market share of this segment. Furthermore, a large number of collaborations between pharmaceutical companies and AI companies is also contributing to this segment’s large market share.
Pharmaceutical and biopharmaceutical companies are employing AI to find new drugs. These companies focus on reducing operating costs associated with the production of drugs and accelerating the introduction of new treatments to the market. Pharmaceutical companies are under pressure to find new drugs due to the rising burden of chronic and infectious diseases. Thus, pharmaceutical and biopharmaceutical companies are integrating AI into drug research to speed up drug discovery while reducing costs and time to market.
The emerging infrastructure for AI and pharmaceutical research in countries such as China, India, Singapore, and South Korea, rising funding for cancer research, and growing investments in AI are driving the growth of the AI in drug discovery market in Asia-Paicifc. Furthermore, the growing number of AI-based drug discovery startups is also boosting the growth of this market.
Key Players
The report includes a competitive landscape based on an extensive assessment of the key strategic developments adopted by key market players over the past few years. The key players profiled in the global AI in drug discovery market report are Microsoft Corporation (U.S.), Exscientia plc (U.K.), NVIDIA Corporation (U.S.), Schrödinger, LLC (U.S.), Atomwise, Inc. (U.S.), BenevolentAI Limited (U.K.), Deep Genomics Incorporated (Canada), InSilico Medicine (U.S.), Cloud Pharmaceuticals, Inc. (U.S.), and Standigm Inc. (South Korea).
Scope of the Report
Key questions answered in the report:
This study offers a detailed assessment of the AI in drug discovery market and includes the market size & forecast for various segmentations such as offering, deployment mode, therapeutic area, application, and end user. The AI in drug discovery market study also involves the value analysis of various segments of the AI in drug discovery market at regional and country levels.
The global AI in drug discovery market is projected to reach $8.95 billion by 2030, at a CAGR of 27.2% during the forecast period.
Based on offering, in 2024, the software segment is expected to account for the largest share. Recurring revenue from the companies owing to the subscription-based or licensing models offered by the software companies are the factors attributed to the large market share of this segment.
Based on deployment mode, the cloud & web-based segment is projected to register the highest CAGR over the forecast period. Growing preference for cloud-based and web-based models owing to their advantages contribute to the growth of this market.
The growth of the AI in drug discovery market is attributed to the rising focus on reducing the turnaround time in drug discovery, growing applications of AI in drug discovery, the rising incidence of chronic diseases, and the high risk of emerging infectious diseases. The rising adoption of machine learning (ML) in drug discovery, the emergence of local and regional start-ups in AI in drug discovery, and increasing investments in R&D are also creating opportunities for market growth.
The key players profiled in the global AI in drug discovery market are Microsoft Corporation (U.S.), Exscientia plc (U.K.), NVIDIA Corporation (U.S.), Schrödinger, LLC (U.S.), Atomwise, Inc. (U.S.), BenevolentAI Limited. (U.K.), Deep Genomics Incorporated (Canada), InSilico Medicine (U.S.), Cloud Pharmaceuticals, Inc. (U.S.), and Standigm Inc. (South Korea).
Emerging economies like China and India are projected to offer significant growth opportunities to the market players due to the availability of infrastructure for drug discovery research, leading to the growing adoption of AI in drug discovery in these countries.
Published Date: Jun-2022
Published Date: Nov-2022
Published Date: Oct-2013
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