June 2025
The global AI-powered drug formulation market is witnessing rapid growth as AI technologies enable pharmaceutical companies to design optimized drug formulations efficiently and accurately. The market growth is attributed to the increasing integration of advanced AI technologies in drug formulation processes, enabling faster development and reduced costs.
The drug formulation market is undergoing a transformative technological shift, driven by the need to develop drugs more quickly and adherence to regulatory requirements. Their solubility and pharmacokinetics. Notably, Insilico Medicine has developed generative chemistry platforms that can provide predictive formulation modeling, reducing experimental cycles and accelerating development timelines.
The other notable change is the merger of AI with continuous production and digital twins to produce drugs. Novartis or AstraZeneca, among others, are using AI-enabled digital twin models to recreate the formulation process. This enables adaptive production with a minimal percentage of waste and improved reproducibility. Additionally, AI enables real-time monitoring and optimization of formulation scale-up, allowing for enhanced yield and quality. These technological changes are making AI formulation a major force of innovation, efficiency, and competitiveness in the pharmaceutical sector.
The growing need to develop drugs more quickly, with greater precision and at lower costs, is propelling the AI-powered drug formulation market. The field of pharmaceutical R&D is undergoing a revolution with the integration of AI technologies, including machine learning, deep learning, and computational chemistry. This facilitates the rapid design of formulations, predicting drug behaviour, and optimising dosage forms. These features reduce trial cycles, enhance effectiveness, and lower overall development costs.
Stanford University announced that AI-based simulation models shortened formulation design cycles by almost 40% on biologics projects in 2024. Large biopharma firms, including Pfizer, Novartis, and AstraZeneca, have adopted AI-based platforms into their drug development pipeline to speed up the preclinical development process. Furthermore, the development of AI-based predictive analytics in this market is also aiding in such expansions, as it is now possible to simulate the interactions between molecules and then test them physically. (Source: https://med.stanford.edu)
| Report Coverage | Details |
| Dominating Region | North America |
| Fastest Growing Region | Asia Pacific |
| Base Year | 2024 |
| Forecast Period | 2025 to 2034 |
| Segments Covered | Component, Technology, Application / Use Case, Drug Type, Dosage Form, and Region |
| Regions Covered | North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa |
| Country / Region | Regulatory Body / Initiative | Key Regulations / Frameworks | Focus Areas | Notable Notes |
| United States | U.S. Food & Drug Administration (FDA) + NIH | FDA Digital Health Innovation Action Plan- 21st Century Cures Act (AI in clinical trials)- AI/ML Software as a Medical Device (SaMD) guidance | Regulatory validation of AI models, Data privacy compliance, Clinical trial automation | In 2024, the FDA launched the AI Drug Development Challenge to accelerate the development of AI-based formulation platforms. The NIH has funded over USD 250 million in AI-drug formulation projects. |
| European Union | European Medicines Agency (EMA) + Horizon Europe | EU AI Act (proposed)- Good Machine Learning Practice (GMLP)- MDR (Medical Device Regulation) | Ethical AI deployment, Transparency in AI-assisted trials, Data interoperability | Horizon Europe allocated €350 million in 2024 for AI-driven formulation research, with a focus on adaptive trial designs and formulation optimization. |
| China | National Medical Products Administration (NMPA) + Ministry of Science & Technology (MOST) | AI Drug Development Guidelines- Data Security Law- Pharmaceutical Data Standards (2023) | AI-driven formulation validation, Integration of AI in regulatory submissions, Standardised data pipelines | China announced a USD 1.2 billion AI-Pharma initiative in 2024 to build national AI formulation platforms, with strong integration with CAS research centers. |
| Japan | Pharmaceuticals and Medical Devices Agency (PMDA) + AMED | Digital Health Innovation Strategy- AI Verification Guidelines for Medical Devices | AI-assisted drug formulation evaluation, Regulatory sandbox for AI validation, Biologics formulation AI | In 2024, PMDA expanded the regulatory sandbox for AI formulation trials to reduce approval timelines. |
| India | Central Drugs Standard Control Organisation (CDSCO) + DBT + CSIR | Draft National AI Strategy for Healthcare- Bioinformatics & Computational Chemistry Standards- Clinical Trial Regulation Updates | AI model certification sharing for drug formulation, Ethical AI use in pharma | DBT funded over 50 AI-drug formulation projects in 2024, emphasizing dosage optimization for generics and complex biologics. |
| South Korea | Ministry of Food and Drug Safety (MFDS) + KRIBB | AI Based Drug Development Guidelines- Good Clinical Data Practice (GCDP)- AI model transparency requirements | AI-assisted biologics formulation, Clinical simulation platforms, Regulatory model certification | KAIST and POSTECH reported breakthroughs in AI formulation in 2024, reducing biologics formulation timelines. |
(Source: https://www.fda.gov)
(Source: https://digital-strategy.ec.europa.eu)
(Source: https://www.drugpatentwatch.com)
(Source: https://www.pmda.go.jp)
How is the growing demand for data-driven formulation design reshaping the AI-Powered Drug Formulation Market?
The increasing demand for data-driven formulation design is expected to drive market growth in the coming years. Researchers and formulation scientists increasingly use deep learning and other sophisticated analytics to refine chemical, biological, and clinical information. Predictive models applied in molecular screening, solubility prediction, and excipient compatibility enable developers to acquire a more accurate formulation with fewer laboratory experiments. (Source: https://jamanetwork.com)
Increasing evidence in the year 2024 indicates that the integration of smart discovery instruments can have a significant impact on formulation development. An article published in JAMA states that 164 AI-related platforms are in clinical development in 2024, compared to 19 in 2023. Furthermore, the growing emphasis on reducing formulation development time and costs is expected to drive demand for AI-integrated formulation solutions. (Source: https://www.iqvia.com)
High upfront costs for AI infrastructure, high-performance computing, and integration of digital laboratories are expected to restrain the market. This cost constraint reduces the rate of adoption of intelligent formulation systems by new entrants and smaller players. Additionally, the stringent regulations surrounding patient data and pharmaceutical research are projected to restrain market expansion.
How does rising investment in digital transformation drive innovation in the AI-Powered Drug Formulation Market?
Growing investment in digital transformation of pharmaceutical R&D is anticipated to create immense opportunities for the AI-powered drug formulation market. Incorporating AI learning infrastructures and digital labs, major manufacturing pharmaceutical firms and research institutions are investing significant budgets in these fields. These investments facilitate automated experimentation, testing using simulations, and high-level formulation optimisation models.
Digital R&D financial and strategic investments hasten product development streams and strengthen competitive differentiation in the pharmaceutical ecosystem. A 2024 R&D report by IQVIA stated that more than 40% of late-stage drug development programs currently use AI-based formulation and predictive modelling tools, compared to 27% in 2022. Furthermore, the increasing use of advanced simulation and modeling techniques is likely to enhance the integration of artificial intelligence in formulation science. (Source: https://www.iqvia.com)
How Are Software Platforms Driving the Core Transformation of the AI-Powered Drug Formulation Market?
The software segment dominated the AI-powered drug formulation market in 2024, as formulation development became a highly data-driven process. In 2024, the EFPIA reported a yearly increase in the use of AI-enabled software for creating drug formulations across Europe.
This resurgence is indicative of increasing penetration of artificial intelligence-based chemical simulation, process automation, and prediction capacity into formulation pipelines. Furthermore, the major providers of AI platform offerings, including IBM Watson Health and Google DeepMind, have begun to incorporate quantum computing techniques into their offerings, enabling them to make molecular predictions more quickly. (Source: https://efpia.eu)
The service segment is expected to grow at the fastest rate in the coming years, owing to the increasing industry trend of outsourcing the complexity of formulation. A 2024 report by the OHE indicates that more than 35% of mid-sized biopharma companies in North America and Europe. They have already undertaken AI-driven contract formulation projects to speed up time-to-market, thereby further boosting the market. (Source: https://www.biocon.com)
How Are Machine Learning and Predictive Modelling Technologies Powering Innovation Across the Market?
The machine learning and predictive modeling segment held the largest revenue share in the AI-powered drug formulation market in 2024, due to its ability to process large volumes of data and provide accurate predictions about the formulation. These technologies have played a key role in improving accuracy in formulation and accelerating development processes, further supporting their shift to become the predominant technology in the market.
The generative AI and hybrid AI strategies segment is expected to grow at the fastest rate in the coming years, as they can develop new formulations with more efficiency than ever before.
In 2024, research at the Francis Crick Institute and ETH Zurich emphasised how generative AI can cut the number of formulation design cycles. Furthermore, the hybrid AI, a type of AI that combines machine learning and deep learning, provides a more accurate model of complex molecules and biologics, with significantly greater predictive power. (Source: https://ethz.ch)
How Is AI Revolutionizing Formulation Design and Optimization Across Multiple Drug Delivery Platforms?
The formulation design and optimisation segment dominated the AI-powered drug formulation market in 2024, as drug development is becoming more complex and requires more efficient operations. Additionally, the use of AI in formulation design is likely to continue increasing as pharmaceutical companies strive to improve the efficiency and effectiveness of their drug development pipeline.
The personalized & advanced therapy formulations segment is expected to grow at the fastest CAGR in the coming years. Owing to the rising demand for treatments that would address the needs of a specific patient profile, such as genetic composition, disease nature, and environmental forces. Furthermore, the introduction of advanced smart nanotechnology and 3D printing is further propelling the personalized medicine sphere, resulting in superior and more precise treatments.
What Makes Small-Molecule Formulations the Cornerstone of the AI-Powered Drug Formulation Ecosystem?
The small molecules segment held the largest revenue share in the AI-powered drug formulation market in 2024, as it has a well-established position in therapeutic development and is embedded with AI technology to enhance its effectiveness and safety profiles. Additionally, such a concerted effort marks the industry's willingness to utilize AI to optimize the small molecule drug development process, thereby facilitating segment dominance in the market.
The nucleic acid-based drugs and cell/gene therapy payloads segment is expected to grow at the fastest rate in the coming years, owing to the rising number of genetic disorders and the development of new technology of gene-editing technologies. This provides a new opening in the treatment of diseases. Moreover, AI finds its application in the creation of cell and gene therapies, analyzing enormous amounts of genomic data to reveal potential therapeutic targets and predict patient-specific responses.
Why Do Oral Solid Dosage Formulations Continue to Lead AI-Powered Formulation Research and Development?
The oral solid dosage segment dominated the AI-powered drug formulation market in 2024, as it is relatively affordable, simple to administer, and widely accepted by patients. In 2024, the Office for Health Economics (OHE) conducted a study that reported a 27% increase in the efficiency of formulating oral solid dosage products through the use of AI predictive modeling.
The Schrodinger and BenevolentAI platforms, based on AI, have improved the design of oral solid dosages by predicting the best excipient mixtures and dissolution profiles, thereby reducing the number of trial experiments. Additionally, the combination of real-world and experimental data was enhanced by collaboration between AI developers (XtalPi) and pharmaceutical giants, which also contributes to the prevalence of oral solid dosage forms. (Source: https://bmcmedinformdecismak.biomedcentral.com)
The Advanced Delivery Systems segment is expected to grow at the fastest rate in the coming years, owing to its ability to enhance drug solubility, targeted delivery, and controlled release. LNPs, which are being used in mRNA vaccines, including those developed by Moderna and BioNTech, have shown a high clinical success rate, and further AI-led progress in this area is encouraged. Furthermore, the growth in this sub-segment is also supported by industry alliances, such as the partnership between Pfizer and Arzeda to design AI-enhanced LNP.
Why did North America Dominate the AI-powered drug formulation market?
North America led the AI-powered drug formulation market, capturing the largest revenue share in 2024, due to its robust infrastructure, substantial funding for research, and favorable regulatory systems. In 2024, the U.S. Department of Health and Human Services plans to expand its AI-for-Drug Development Program through multi-institutional projects, focusing on formulation efficiency and the development of drugs for rare diseases.
This was also accompanied by the efforts of the National Science Foundation and NIH to incorporate AI attributes into pharmaceutical research pipelines. Boston, San Francisco, and San Diego, which are the hubs, reported an influx of AI-driven projects. Furthermore, this form of innovation is redefining the way formulations are developed, tested, and commercialized in the region and establishing a leading role for North America. (Source: https://www.fda.gov)
The Asia Pacific is anticipated to grow at the fastest rate in the market during the forecast period, driven by substantial government efforts, increased biotech investments, and rapid adoption of AI. In 2024, the Ministry of Science and Technology in China introduced its AI Pharma Leap program to fund AI-based drug formulation, with a particular focus on biologics and treatments for rare diseases. (Source: https://www.navlindaily.com)
This involved collaboration with Tsinghua University, Peking University, and leading pharma companies to create proprietary AI platforms. In 2024, Seoul National University collaborated with Samsung Biologics to roll out next-generation AI formulation systems. This predicts stability data of complex biologics before physical testing, thus further facilitating the market growth in the coming years. (Source: https://samsungbiologics.com)
(Source: https://www.reuters.com)
(Source: https://manufacturingchemist.com)
(Source: https://www.prnewswire.com)
(Source: https://www.digitalhealthnews.com)
By Component
By Technology
By Application / Use Case
By Drug Type
By Dosage Form
By Region
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