Artificial Intelligence (AI) in Drug Discovery Market Worth $8.95 Billion by 2030

According to a new market research report titled, ‘Artificial Intelligence in Drug Discovery Market by Offering (Software, Services), Application (Target Discovery, Lead Identification, Clinical Testing), Therapy Area (Oncology, Cardiology, Neurodegenerative), Deployment, and End User – Global Forecast to 2030,’ published by Meticulous Research^®, the AI in drug discovery market is projected to reach $8.95 billion by 2030, at a CAGR of 27.2% during the forecast period 2023–2030.

AI systems can perform various human intelligence-based functions such as reasoning, learning, and problem-solving skills in different disciplines such as healthcare, computer science, mathematics, and engineering. The integration of AI into the healthcare ecosystem offers benefits such as automating tasks and analyzing big patient data sets to deliver better care at lower costs.

Artificial intelligence (AI) for drug discovery is a technology that uses algorithms to solve complex problems in the drug development process. The use of AI solutions in clinical trial processes eliminates issues like drug failure, reduces the time it takes for a clinical trial to complete, and improves the efficiency and accuracy of the process. As a result, stakeholders in the biomedical research field are using AI solutions in drug discovery processes.

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Impact of COVID-19 on the AI in Drug Discovery Market

The COVID-19 pandemic became a global challenge due to the overburdening of healthcare systems, strict isolation and quarantine protocols, limitations on social activities, travel restrictions, the closing of borders, and the shutting down of businesses. However, the pandemic created significant opportunities for AI in drug discovery for the development of drugs and vaccines. Without drug discovery and AI advancements, it would have been extremely challenging for researchers to perform a comprehensive potency evaluation of drugs and vaccine candidates.

The use of AI for COVID-19-related vaccines and therapies increased during the pandemic. The AI techniques boosted the drug discovery process by reducing the time required to bring drugs to the market and speeding up lead discovery, virtual screening, and drug validation. The AI was also used to leverage drug repositioning studies by screening the properties of the preapproved or validated drugs. BenevolentAI (U.K.), an AI-based drug discovery company, used machine learning methods to accelerate the COVID-19 drug discovery program and identified baricitinib as a potential drug against COVID-19. Additionally, during the COVID-19 pandemic, pharmaceutical & biotechnology companies and research institutes collaborated with AI companies to develop COVID-19 therapeutics and vaccines. For instance, In June 2020, RepurposeAI (U.S.) collaborated with Scripps Research (U.S.) to develop COVID-19 therapeutics with a focus on drug repurposing.

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The global AI in drug discovery market study is segmented by offering (software and services), deployment mode (on-premises mode, cloud & web-based mode), application (target discovery & validation, lead compound identification, de novo design and drug optimization, preclinical & clinical testing), therapeutic area (immuno-oncology, neurodegenerative diseases, cardiovascular diseases, metabolic diseases, other applications ), end user (pharmaceutical & biopharmaceutical companies, contract research organizations (CROs), and academic & research institutes,), and geography. The study also evaluates industry competitors and analyzes their market shares at the global and regional levels.

Based on offering, in 2023, the software segment is expected to account for the largest share of the global AI in drug discovery market. The presence of a large number of AI companies providing algorithms for drug discovery and the high pricing of AI-based drug discovery software compared to the support services are the key factors contributing to the large market share of this segment.

Based on deployment mode, the cloud-based segment is projected to register the highest CAGR during the forecast period. The use of cloud-based and web-based models in AI drug discovery is growing due to their high security, scalability, and flexibility benefits. Using cloud-based models eliminates the need to invest in building and maintaining onboard computer systems. Additionally, the cloud-based models provide greater scalability to manage large sample data sets.

Based on therapeutic area, in 2023, the oncology segment is expected to account for the largest share of the global AI in drug discovery market. A large number of collaborations among drug discovery and AI companies is supporting the large market share of this segment. For instance, in November 2022, The University of Texas MD Anderson Cancer Center (U.S.) and Exscientia plc (U.K.) entered into a strategic collaboration to combine the drug discovery and development expertise of MD Anderson with the patient-centric artificial intelligence (AI) capabilities of Exscientia to boost the development of novel small-molecule oncology therapies. Additionally, in November 2021, Sanofi (France) announced an equity investment of USD 180 million in Owkin (U.S.), an AI and precision medicine company, to advance its oncology pipeline.

Based on application, in 2023, the lead compound identification segment is expected to account for the largest share of the global AI in drug discovery market. Lead compound identification is a complex step in drug discovery, during which many important properties, such as selectivity or the potency of the drugs, are identified before moving into clinical studies. The use of AI can reduce the time required for pre-clinical development, allowing resources to be channelized efficiently. Thus, the application of AI in this stage of drug discovery is the highest, which, in turn, supports the large market share of this segment.

Based on end user, in 2023, the pharmaceutical & biopharmaceutical companies segment is expected to account for the largest share of the global AI in drug discovery market. The high prevalence of chronic and infectious diseases and high pressure on the pharmaceutical and biotechnology companies to bring effective therapies early to the market, coupled with advantages offered by AI algorithms for smooth drug discovery, are the factors contributing to the large market share of this segment.

Based on geography, in 2023, North America is expected to account for the largest share of the AI in drug discovery market, followed by Europe and Asia-Pacific. In 2023, the U.S. is expected to account for the largest share of the AI in drug discovery market in North America. This market is primarily driven by increasing public and private investments in drug discovery and the high adoption of AI solutions in drug discovery. The presence of key AI companies and pharmaceutical companies such as Abbott Laboratories (U.S) and Pfizer Inc. (U.S) also support the large share of this market. However, Asia-Pacific is expected to witnesss a rapid growth during the forecast period. 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.

Some of the key players operating 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).

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Scope of the Report:

AI in Drug Discovery Market, by Offering