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July 2025
The AI and ML in drug development market is rapidly advancing on a global scale, with expectations of accumulating hundreds of millions in revenue between 2025 and 2034. Market forecasts suggest robust development fueled by increased investments, innovation, and rising demand across various industries.
The global AI and ML in drug development market is experiencing several applications in drug development, including target identification, analysis of vast datasets derived from different sectors like genomic, proteomics, and clinical trials. Also, AI and ML-powered tools have major advantages like reduced timelines and expenditure in drug discovery to develop novel drug candidates, biomarkers, and personalized therapies in different diseases. In the coming era, opportunities like innovation in drug delivery systems such as nanoparticles, development of customized medicines, and big data analysis to analyze and identify the potential drug candidates.
AI and ML have broad applications across various sectors, including drug development as well. The global AI and ML in drug development market is driven by escalating timelines, minimized expenses, and optimized precision in therapeutic design. Whereas, the AI and ML are transforming this sector, along with natural language processing, which is employed in different stages, primarily from the identification of the target to the design of the clinical trial process. In 2025, many ongoing developments by using AI and ML algorithms in advancements in virtual screening, de novo drug design, biomarker discovery, and patient stratification are enhancing AI in biomedical research activities and sorting challenges such as data quality and model interpretation in the respective market.
Reduced Timelines and Expenditure
Traditional drug discovery processes are time-consuming with highly expensive in nature, so these issues are resolved by the rising AI and ML adoption in minimizing the timelines and expenses in development by automating tasks, improving experiments, and enhancing prediction accuracy. Moreover, numerous complex pathways involved in various diseases are generating limitations in the detection of efficient drug targets, in which AI and ML-powered software help in the analysis of huge datasets of biological information to determine new targets and estimate drug efficacy levels.
Data Quality and Privacy Issues
As AI models are widely relied on vast datasets, having personal information regarding patients is creating a challenge about data privacy, security breaches, and unauthenticated access, resulting in restricted data sharing and creating a barrier in AI-powered drug discovery. Also, heterogeneity and limited accessibility of data from different sources, such as clinical trials and biological assays, can pose challenges in the development and validation of AI models.
Developments in Precision Therapeutics and Clinical Trials
AI and ML have several opportunities in drug development processes, including drug repurposing, in which AI supports to detection of novel pharmacological applications for existing drugs by studying their interactions with biological targets and disease pathways with rapid and effective results. As well as the global AI and ML in drug development market has opportunities, like the development of customized medicine by analyzing patient information and estimating individual responses to drugs. In clinical trials, AI and ML help to improve trial design, patient selection, and data analysis.
The drug discovery segment held the largest revenue share of 42% of the market in 2024. However, different factors like rising cases of chronic diseases, the need for novel therapies, and the adoption of AI and ML in the analysis of large datasets, along with anticipating molecular patterns and improving drug design, are driving the segment growth.
By phase of drug development, the clinical trials segment is expected to grow at a 29% CAGR during the forecast period. The segment expansion is propelled by the automation of tasks, including patient recruitment and data analysis, as well as the rising need for quick and robust drug development approaches, which lead to lessens trial timelines and expenses. Also, the growing applications of AI in personalized treatment regimens and optimized safety monitoring through real-time analysis are accelerating overall segment and market growth.
By technology type, the machine learning (Supervised/Unsupervised) segment was dominant due to holding 45% of the global AI and ML in drug development market. The segment is fueled by the raised adoption of ML techniques in various areas, including drug discovery processes with a rapid and cost-effective development process, and also in innovative and personalized medicine approaches.
Whereas, the generative AI & foundation models segment is estimated to expand at ~35% CAGR during 2025-2034. Majorly contributing factors in the segment growth are rising applications in de novo drug design, growing clinical trial designs, and outcomes by the use of generative AI. The most important driver is that the Large language models (LLMs) and other foundation models are becoming robust and highly effective, allowing more sophisticated AI applications in drug discovery.
By function/application, the target identification & validation segment held the biggest revenue share of 27% of the market. As AI and ML algorithms are widely assisting in high-throughput screening and data analysis, along with accelerating demand for more efficient and effective drug discovery processes, they are driving the segment growth and ultimate market expansion.
However, the drug repurposing segment is anticipated to expand at ~31% CAGR during the forecast period. The segment is experiencing growth by increasing the need for effective and inexpensive development processes as compared to conventional methods, along with boosting the usage of AI and ML in the identification of new therapeutic applications of existing drugs, and rising focus on personalization of medicine.
The cloud-based AI platforms segment dominated the global AI and ML in drug development market by accounting for a 58% share in 2024. Numerous advantages of this segment, including measurability, accessibility, and reduced spending, are driving the segment in both large pharmaceutical industries and small-scale biotech firms. Also, the accelerating adoption of cloud computing and AI/ML techniques in different pharmaceutical research is fueling demand for the drug discovery process.
Whereas, the hybrid solutions segment is estimated to grow at approximately 25% CAGR during 2025-2034. Significant factors, including growing prevalences of complex and chronic diseases, which fuel demand for rapid and highly efficient drug development with minimized cost and personalized medicine properties, are driving the segment expansion. As hybrid solutions allow all these benefits, with transformation in many stages of the drug discovery process.
By therapeutic area, the oncology segment dominated with a 36% revenue share in 2024. The most important factor contributing to this segment's growth is increasing cases of different cancer types, which are fueling demand for tailored cancer therapies, and the benefits of AI to enhance the drug discovery process. Also, the accelerating advancements in AI and ML-powered technologies used in oncology, increasing investments in oncology, are propelling the segment expansion.
The metabolic disorders segment is predicted to register the fastest with ~26% CAGR in the upcoming years. The escalating cases of metabolic conditions, including diabetes and obesity, along with the growing adoption of AI and ML in drug discovery approaches and the rising demand for personalized therapeutics, are boosting the segment growth.
By end user, the pharmaceutical & biotechnology companies segment led the global AI and ML in drug development market with 61% revenue share in 2024. Mainly, rising demand for customized treatments with increased efficiency and reduced expenses in the drug development process is driving the segment growth. Along with this, the growing huge healthcare data and optimized success rates by using AI and ML by researchers to focus on potential drug candidates, leading to a successful number of clinical trials, are fueling the demand for the pharmaceutical and biotechnology industries.
And the AI startups & platform providers segment is estimated to grow at ~22% CAGR in the projected period. Primarily, enhanced focus of AI startups on creating novel AI-driven platforms and tools for different stages of drug discovery is contributing to the segment expansion. Moreover, rising demand from pharmaceutical and biotechnology companies for AI-powered tools and platforms is driving the overall segment and market expansion.
North America dominated with the largest revenue share of 52% of the global AI and ML in drug development market in 2024. This region is fueled by the advancements in technologies, including AI-driven tools and platforms, rising demand for personalized medicines, and accelerating collaboration of pharmaceutical and biotechnology companies. Also, increasing investments and expenditure on the healthcare system to advance facilities are driving the market expansion in this region.
The US is experiencing major growth due to the growing focus of regulatory bodies on streamlining the clinical trials design, increased investments in the healthcare system, and developing more efficient and cost-effective drug discovery processes by using AI and ML-driven approaches.
For instance,
The market is fueling revolution due to Canadian biotech companies widely introducing the applications of AI and ML algorithms in target identification, novel candidate development. As well as widespread adoption of machine learning in the analysis of large datasets in various healthcare companies to predict drug-protein interactions, and identification of potential products with high accuracy and speed, are also boosting the overall market growth.
Asia Pacific is estimated to show growth with ~24–26% CAGR in the upcoming years. The global AI and ML in drug development market in ASAP is propelled by rising R&D funding, with the demand for tailored medicine and therapies used in growing cases of complex diseases. Also, the ASAP region is the main area that generates a large amount of healthcare data from EHRs, clinical trials, and genomic sequences are fueling demand for AI and ML technologies to simplify the datasets and processes involved in drug development.
China’s market is experiencing rapid growth due to the active participation of the Chinese government in the development and application of AI in different areas, such as healthcare and life sciences. Along with this, China is facing a generation of huge biomedical data from clinical trials, genomics research information, and real-world evidence, which creates a precious resource for training AI models.
In India, the increasing prevalence of diabetes, heart diseases, genetic disorders, and other rare diseases is boosting demand for precision treatments based on biological information, along with the rising adoption of AI and ML-driven tools by numerous pharmaceutical and biotechnology companies, which is driving the market growth.
For this market,
As Europe is facing significant market growth due to enhanced use of AI and ML in optimization of drug formulations and delivery systems, including nanoparticles and 3D-printed drug delivery systems. As well as Europe has been employing AI and ML in various sectors like genomics, proteomics, and clinical trials to analyze vast datasets and simplify the drug development processes. However, regulatory agencies in Europe are increasingly providing guidance and support to encourage the wide adoption of these technologies in drug development.
The market in Germany is fueled by a growing focus on the adoption of rapid and cost-effective technologies in drug development, with rising demand for customized medicines and robust healthcare infrastructure. Also, the government is supporting to raise the focus on advancements in oncology and the life sciences sector, which ultimately accelerates the market growth.
In the UK, the market is driven by regulatory considerations, which are ensuring the safe and ethical application of AI in drug development approaches. Also, various AI-powered platforms are enabling collaborations between researchers, institutions, and pharmaceutical companies, which is further fostering innovation.
For instance,
By Phase of Drug Development
By Technology Type
By Function/Application
By Deployment Type
By Therapeutic Area
By End User
By Region
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