The global artificial intelligence in drug discovery market was worth USD 1.10 billion in 2023. The global market is predicted to reach USD 1.54 billion in 2024 and USD 22.99 billion by 2032, growing at a CAGR of 40.2% during the forecast period.
Artificial intelligence (AI) integrated with machine learning (ML) is being used significantly in discovering drugs with high efficiency in treating diseases. The gap between understanding the disease and identifying the potential treatment procedure is filled by using AI, which acts as a powerful catalyst. The challenges posed by the traditional way of discovering drugs are completely rolled out in medical history with the help of AI. A drug discovery procedure involves various matters like disease identification, target identification, and predicting drug toxicity, among others. AI is unfolding all these tasks with ease, and it is anticipated to launch or discover a new drug with minimal human effort in very little time.
In general, AI is playing an important role in easily identifying the compounds that can selectively interact with the disease-causing molecule. Identifying the disease-causing molecule is one of the toughest parts in the process of drug discovery, which is lucratively possible by using artificial intelligence. The prominence of reducing the burden of diseases by improving the existing treatment procedure along with finding new drugs is ascribed to bolstering the growth rate of the market.
Drug discovery is the prominent and highly innovative phase for researchers who are hugely involved in following scientific principles. Traditional drug discovery is associated with huge initial investments, whereas artificial intelligence helps in predicting drug development procedures and simultaneously reduces the overall cost, which is definitely a driving factor for the market's growth rate. Artificial intelligence helps researchers to analyze various factors like safety and pharmacokinetics that have the potential to reduce the potential risk factors to develop a drug in that particular way, thereby reducing overall cost. In general, a drug discovery may take 10-15 years with huge initial investments in the research activities, which is a huge burden for the investors if the project fails due to uncertainties. AI overcomes all these factors, such as predicting the output accurately in very little time by completely analyzing the vast data, thereby reducing the overall cost factor at the same time.
AI in drug discovery has a lot of positive factors, like modeling the overall process in simple steps that help researchers validate the overall data and find out the effective way to discover a drug in very little time. However, there are some factors that are degrading the growth rate of the market, such as difficulty in interpretability and explainability of AI models that change frequently. Frequently changing AI algorithms are highly difficult to understand, which is likely to hamper the growth rate of Artificial intelligence in the drug discovery market. The growing concern in protecting the data from cyber attackers is also to degrade the fastest growth rate of the market.
The launch of innovative technological developments in discovering a new drug that helps in finding new ways to treat chronic or any other diseases is anticipated to gear up huge opportunities for artificial intelligence in the drug discovery market. Top companies are coming up with different strategies to launch innovative techniques in finding new drugs or modifying existing drugs. For instance, in 2024, the Global Health Drug Discovery Institute (GHDDI) and Microsoft Research joined hands together to launch innovative treatment procedures by drug discovery for global infectious diseases. The joint team successfully used artificial intelligence (AI) to design several molecule inhibitors that can treat novel coronavirus and tuberculosis. This project is ascribed to involving AI technologies in drug discovery that results in the launch of innovative drugs in minimal time that help promote the healthy lifestyle of people globally.
Stringent rules and regulations by government authorities in accepting the new AI technologies in drug discovery due to rising ethical considerations will certainly pose huge challenges for the market's key players in the coming years. Difficulty in approaching the decision-making process more effectively than the human mind is absolutely a negative factor that is the declining growth rate of AI in the drug discovery market. Top companies are actively working on rectifying all the key challenges in developing technologies that can improve their methods in the coming years.
REPORT METRIC |
DETAILS |
Market Size Available |
2023 to 2032 |
Base Year |
2023 |
Forecast Period |
2024 to 2032 |
CAGR |
40.2% |
Segments Covered |
By Offering, Technology, Therapeutic Area, Process, Use Cases, End User, and Region |
Various Analyses Covered |
Global, Regional & Country Level Analysis, Segment-Level Analysis, DROC, PESTLE Analysis, Porter’s Five Forces Analysis, Competitive Landscape, Analyst Overview on Investment Opportunities |
Regions Covered |
North America, Europe, APAC, Latin America, Middle East & Africa |
Market Leaders Profiled |
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) |
The software segment is leading with the largest share of artificial intelligence in the drug discovery market. IT companies are working vigorously to launch new ideas to promote the best treatment procedures in the healthcare industry. The services segment is likely to have the highest CAGR by the end of 2029, owing to the increasing prominence of the development of various drugs for novel therapeutics.
The machine learning segment is gaining huge traction over the market share. Deep learning, which is a sub-segment of machine learning, is expected to have huge growth opportunities throughout the forecast period. Machine learning is a prominent tool that helps in finding out the related chemical and biological information that simultaneously enhances the progress of drug discovery, eventually leveling up the market's growth rate during the forecast period. The natural language processing segment is likely to have the highest growth rate in the future period.
The oncology segment is expected to lead the largest share of the market. The rising number of cancer patients and the demand for the launch of innovative drugs that can completely cure the disease are likely to promote the market's drug rate in this area. Cancer is becoming one of the most common diseases across the world. The need to modify the existing drugs that are causing side effects is substantial to elevate the market's growth rate. The infectious diseases and cardiovascular diseases segment is expected to have the most prominent growth rate during the forecast period. The prominence of delivering new drugs for highly infectious communicable diseases is solely fulfilled with the help of AI in research studies.
The target identification & selection segment is gearing up with huge growth opportunities during the forecast period. This is the first and most important step in the overall process of drug discovery, which is simplified using artificial intelligence. AI plays a vital role in overall drug discovery, and researchers used to take a lot of time to identify the target and select the best output. AI is simplifying the job much better than human minds, where the target identification and selection are done in very little time, along with the projections of the output. The lead optimization segment is gearing up with a significant growth rate in the coming years.
The understanding disease segment is projected to lead the highest market size during the forecast period, whereas the small molecule design and optimization segment is expected to promote the market share in the coming years. The prevalence of new infectious diseases and the prominence to discover a new drug with the advanced technologies where there is minimum knowledge of the disease is perfectly done with the AI from understanding the disease to optimizing the molecule design that is leveling up the growth rate of the market.
The pharmaceutical & biotechnology companies segment is leading with the largest share of the market. The companies have already adopted the use of computers and several mathematical models in designing new drugs in the past decade. Now, the development of generative AI models in drug discovery is stepping towards the invention of highly successful outcomes in overall history with approximately less time. Research centers and academic & government institutes segment is likely to level up the growth rate of the market in the coming years.
North America is leading with the largest share of the Artificial Intelligence in Drug Discovery market. The US is a hub for the topmost healthcare industries where the prominence for the invention of new drugs with highly advanced technologies is attributed to showcasing huge growth opportunities for the market. High investments in drug discovery by government institutions in developed countries like the US and Canada are ascribed to boosting the growth rate of the market. Over the past two decades, the prominence of the development of new drugs for various diseases using AI models has totally expanded with the growing support from various government organizations through investments, especially in the US. The government spending on discovering vaccines and therapeutics for COVID-19 was accelerated to 9.9% in 2023. The US government is taking several measures to ensure that every person receives proper and effective treatment procedures at affordable prices, which is enhancing the market's growth rate.
Europe is next to North America, holding a prominent share of AI in the drug discovery market. The rapid adoption of various technologies to promote smooth operations in research centers is ascribed to fueling the growth rate of the market. The increasing number of people's expenditure on healthcare and their demand for high-quality treatment procedures is attributed to launching new drugs with fewer or no side effects, which is surging the market's growth rate in this region.
Asia Pacific artificial intelligence in the drug discovery market is likely to hit the highest CAGR by the end of 2029. Emerging countries like India and China are attributed to contributing the highest share of the market. The rising population is one of the driving factors for the growth of the market in these countries. Eventually, the increasing population in these countries is raising the demand to escalate the development of new drugs. Elderly people are more likely to surge the growth rate of the market in India and China.
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)
By Offering
By Technology
By Therapeutic Area
By Process
By Use Cases
By End User
By Region
Frequently Asked Questions
Key growth drivers include increased adoption of AI technology to reduce time and costs associated with drug discovery, growing collaboration between pharmaceutical companies and AI startups, advancements in machine learning algorithms, and the need for personalized medicine. AI can also accelerate drug development in emerging therapeutic areas like oncology and neurology.
AI is used for several applications in drug discovery, including target identification, drug screening, de novo drug design, biomarker discovery, and optimizing clinical trials. It helps researchers identify new drug candidates, predict drug responses, and reduce failures in later stages of development.
AI is transforming the pharmaceutical industry by providing advanced data analytics and predictive modeling, enabling faster identification of potential drug compounds, and reducing the cost of clinical trials. AI-driven platforms also allow for the discovery of new drug mechanisms and combinations, which were previously unfeasible with traditional methods.
The future of AI in drug discovery looks promising, with continuous advancements in AI technologies such as deep learning, big data analytics, and quantum computing. Increasing collaboration between AI firms and pharmaceutical companies, along with supportive regulatory frameworks, will drive sustained growth. AI's potential to address unmet medical needs, like rare diseases, will further fuel market expansion globally.
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