Biosimulation Market By Offering (Software {Physiologically Based Pharmacokinetic, Quantitative Systems Pharmacology, PK & PD Models, Systems Biology & Disease Progression Models, AI-based Tools}, Services {Model Development & Validation, Data Analysis & Interpretation, Virtual Clinical Trial Design, Regulatory Consulting & Submissions, Training & Technical Support}), By Modeling Approach (Mechanistic Models, Population-based Models, Data-driven Models, Engineering Models), By Therapeutic Area (Oncology, Neurology & CNS Disorders, Cardiovascular Diseases, Metabolic & Endocrine Disorders, Respiratory Disorders, Immunology & Autoimmune Diseases, Others), By Deployment Mode (On-premise Solutions, Cloud-based, Hybrid Models), By Application (Drug Discovery & Development, Preclinical Testing & Toxicology Studies, Clinical Trial Optimization, Dose Selection & Regimen Optimization, Safety & Risk Assessment, Regulatory Approval & Label Expansion, Others), By End User (Pharmaceutical & Biotechnology Companies, Contract Research Organizations (CROs), Academic & Research Institutes, Regulatory Authorities, Others), Global Market Size, Segmental Analysis, Regional Overview, Company Share Analysis, Leading Company Profiles And Market Forecast, 2025 – 2035.

---

What trends will shape the Biosimulation Market in the coming years?

The Biosimulation Market accounted for USD 4.01 Billion in 2024 and USD 4.70 Billion in 2025 is expected to reach USD 23.11 Billion by 2035, growing at a CAGR of around 17.26% between 2025 and 2035. The growth of AI and machine learning in predictive modeling, the use of virtual clinical trials that aim to lower the cost of R&D, and the increased usage of PBPK and QSP models in dose optimization and safety determination are likely to shape the biosimulation market.

Growing pressure on high-quality customized therapies and rare disease treatments will enhance more advanced simulation tools. Intelligent technologies will improve the accuracy of the models and decision-making since they will integrate real-world data (RWD) with digital health technologies. Also, cloud/SaaS-based platforms will increase access and collaboration, and also, regulatory agencies are now starting to understand the importance of model-informed drug development (MIDD), which can increase the credibility and market access of such a platform across the globe.

What do industry experts say about the Biosimulation market trends?

“In 2025, we will continue to invest in software and AI, strengthening our end-to-end biosimulation offering that spans from drug discovery through the clinic.”

• William F. Feehery, CEO of Certara.

“Our software revenue continued to perform well, increasing 6%, mainly driven by our ADMET Predictor® software and modest growth in our GastroPlus® and MonolixSuiteTM software, partially offset by a decline in our QSP/QST biosimulations software.”

• Shawn O’Connor, Chief Executive Officer of Simulations Plus.

Which segments and geographies does the report analyze?

What are the key drivers and challenges shaping the Biosimulation market?

What factors are accelerating the adoption of AI-integrated software in global drug development pipelines?

The Global Biosimulation Market has several key drivers and has been seeing a faster advancement of AI-based software in its drug development pipeline. The power of AI to examine intricate information regarding various biological and clinical results enables scientists to find probable drug candidates, thus saving time and money that is normally required in the case of drug discovery. It can reliably anticipate molecular interactions, design the best possible drugs, and model how drugs behave with humans, which in turn results in safer and more effective therapies. The personalization of medicine with the help of AI promotes the treatment of patients according to their genetic characteristics, which will allow enhancing patient health and may close a gap in clinical trials.

Target identification, preclinical testing, and clinical trial design are simplified by automation through AI that reduces human error and makes the process more productive. Availability of high volumes of biological and genomic data continues to increase, and this makes training and validation of robust AI models possible. The model-informed drug development can be increasingly adopted by regulatory agencies, spurring the use of AI. Pharma corporations are investing a great portion of their resources in AI so that they can avoid becoming extinct, keep pace, and boost innovation. Internet-based platforms also add to accessibility and help in cross-border cooperation across research teams. In total, AI incorporation is disrupting the field of pharmaceuticals and is turning drug development into a quicker, more cost-efficient process with a high level of precision.

How is the rising demand for predictive modeling improving the efficiency of clinical trial outcomes?

The Global Biosimulation Market is gracefully witnessing a better efficiency of clinical trials because of the increased predictive modeling demand. Machine learning can be utilized in predictive modelling, which performs advanced analyses on large clinical and biological data sets, enabling the researcher to learn their patient responses to predict future ones and to optimize trials. Such an ability can allow finding possible risks at the early stage, choosing the appropriate patient groups, and forecasting the results, minimizing the risk of expensive late-stage trial failures.

Regulatory bodies such as the FDA have recognized the promise of using the current capabilities of AI predictive modeling and counterfactual modeling as ways to make trials safer and more effective. Adaptive designs can be spawned using predictive models to monitor trial data in real-time and adapt a study depending on interim data to pursue more flexible designs. Predictive analytics is also integrative in relation to personalized medicine, which enhances the effectiveness of therapies by adapting them to the patient profiles. It saves the amount of time and financial expenditure of the trials and increases the accuracy and reliability of the data. In the quest to make drug development efficient and maintain a competitive advantage, drug companies are putting a lot of money into making use of predictive modeling applications. Predictive modeling is turning into the standard in the new world of clinical research since the regulations started showing their fondness for it. Altogether, the tendency is turning clinical trials into more streamlined, data- and patient-focused.

What challenges do high software development costs create for small-scale pharmaceutical companies worldwide?

The comparatively high price of the development of the software poses significant difficulties to the small scale of the pharmaceutical industry worldwide in the introduction of the newest biosimulation technology. Licensing of AI-integrated modeling platforms and cloud and computational software can be a hefty burden to account for with a small budget, and limit access to innovative technologies. The costliness of such solutions may force small-sized firms to rely on poor or obsolete devices, and this reduces accuracy and efficiency in research.

Maintenance and the revision of the complex software would incur an additional expenditure and technical liability. No less, smaller organizations may also experience the issue of having unqualified persons to work on the advanced platforms of simulations or the issue of training promising people. These barriers to costs may cause a drag on the timeline of drug discovery and the ability to compete with larger pharmaceutical competitors. There can be scarce resources prohibiting engagement in the joint projects or using real-time data, which also affects innovation. Limited finances may limit the scope to scale simulations to large datasets or expansive therapeutic areas. After all, the costs of software may serve as a bottleneck to R&D productivity, decreasing overall efficiency and hampering growth potential within the global pharmaceutical environment.

How can the integration of cloud-based platforms expand the accessibility of biosimulation software globally?

The Global Biosimulation Market is rising in international markets, facilitated by the involvement of cloud-based platforms, which greatly increase accessibility and cooperation in the development of drugs. Cloud computing delivers on-demand computational resources in a scalable manner and so allows researchers to conduct complex simulations without the large upfront capital investment in physical resources. The method democratizes access for smaller pharmaceutical firms, biotech start-ups, and academic institutions to greater access to state-of-the-art biosimulation technologies and the ability to compete with larger firms. Such efforts as the NIH STRIDES Initiative demonstrate how researchers can be enabled to use large volumes of biomedical data and complex computational models by making cloud resources affordable.

Cloud systems are also able to aid smooth teamwork across distances through geographically remote teams that enhance the real-time communication and data transfer processes. These platforms also minimize the cost of maintenance and ease updates, as software and information are centralized, and so all the users are always exposed to the updated tools. Cloud solutions can be integrated and speed up the process of simulating clinical trials, thus stimulating the decision-making process and optimizing trial designs. It can also assist in personalizing medicine because it makes it possible to simulate different patient groups. Moreover, the availability of clouds facilitates compliance levels of regulations due to the availability of secure and auditable cloud storage of data. To summarize, cloud-based platforms are driving evolution in the biosimulation market in terms of providing the latest technologies at a wide scale, affordability, and collaboration of biosimulation across all businesses and research.

What role does AI-driven automation play in reducing time and cost in research?

AI-driven automation constitutes a massive revolution that is impacting the Global Biosimulation Market, as it saves much time and money on the investment during research and development. Such AI technologies as machine learning and natural language processing automate complicated data analysis processes and enable researchers to interpret huge amounts of biological and clinical data and effectively process them. This increased speed allows the opportunity to discover potential drug candidates and biomarkers in less time, and total drug development timelines are reduced. It also reduces human error and error/variance in data interpretation, which enhances the validity and reliability of research findings.

Experimental designs and clinical trial protocols can be optimized with the help of AI-driven tools that result in the optimization of resource allocation and operational cost reductions. As an example, the U.S. Department of Energy at the Argonne National Laboratory has used AI-driven automated processes to simplify research processes, significantly saving time and cost since the process was used on several research projects. Biosimulation places are in a position to enhance predictive modeling, simulation, and decision-making using AI as a possible addition. The introduction of AI technologies in the biosimulation industry solidly establishes the fact that it is possible and necessary to apply them in the field to accelerate the development of drugs by becoming more precise, secure, and cost-effective. Additional benefits of cloud-based and collaborative platforms also exist, helping to provide global access and integration of research in real time. Therefore, in general, automation with AI will play a significant role in accelerating the innovation, efficiency, and transformation of the sphere of biosimulation worldwide.

What are the key market segments in the Biosimulation industry?

Based on the product type, the Biosimulation Market is classified into software and services, with both categories of offering being key to drug development and personalized medicine. Software-based solutions to pharmacokinetics/pharmacodynamics (PK/PD) modeling, systems biology, and ADMET prediction platforms allow users to model complicated biological processes with high fidelity. The services provided include consulting, model development, and validation to enable pharmaceutical companies to optimize experimental designs and decrease clinical trial failure.

Advances in both AI and computational biology are rapidly driving adoption of the software segment, and to a lesser degree, the services segment is being used to access highly specific knowledge and regulated expertise. The two solutions are complementary and allow them to support decision-making, both preclinical and clinical. The increasing demand for predictive modeling, customized therapy development, and cost-effective drug development are the factors that propel the growth of the market. Comprehensively, software and services synergy has been dominating the development of biosimulation solutions in the world.

Based on the application, the Biosimulation Market is classified into oncology, neurology & CNS disorders, cardiovascular diseases, metabolic & endocrine disorders, respiratory disorders, immunology & autoimmune diseases, and others, to show the versatility in the different drug treatment areas where modeling and simulation can and are being used in drug development. Oncology prevails because cancer treatment is complex, and virtual models of tumors have to extrapolate the treatment effects. The cardiovascular and CNS sections enjoy simulations that increase dose optimization, decrease adverse events, and shorten clinical trials.

Infectious diseases and diseases that involve metabolic disorders are catching up since the biosimulation is useful in disease development and the effectiveness of their treatment. Simulation tools are also experiencing greater adoption to help overcome the challenge of small volumes of patient data in emerging areas like rare diseases. Drug development. The expansion in therapeutic areas involves precision medicine efforts and the need to develop cost-effective drugs. In general, such an approach as therapeutic-specific biosimulation is conducive to more focused, quicker, and safer generation of innovative therapies.

Which regions are leading the Biosimulation market, and why?

The North American Biosimulation Market is leading due to the high level of healthcare infrastructure, the presence of pharmaceutical and biotechnological market leaders, and a high level of investment in research and development activities in the region. The U.S., in particular, fuels such growth by extensive use of computational models, platforms integrating artificial intelligence, and policies to support regulatory model-based drug development. Canada has a role in analysis and partnership research projects and a greater concentration on individualized medication.

The area is characterized by the existence of market leaders in terms of Certara, Simulations Plus, and Schrödinger, which are constantly innovating software and services. Biosimulation adoption is being accelerated by high recognition of cost reduction, accelerated drug development, and predictive modeling. Market penetration is also backed up by government financing, favorable regulatory laws, and cooperation with educational establishments. North America is also the location of clinical trial simulations and biomarker-oriented studies. Overall, the region, in technological terms and planned investments, places itself strategically as one of the major stimulators of the growth of the global biosimulation market.

The Asia Pacific Biosimulation Market is growing due to the booming pharmaceutical and biotechnology industries and the proliferation of high-powered computational resources. Drug discovery, clinical trials, and personalized medicine are heavily invested in in China, India, and especially Japan, and their need for biosimulation solutions is growing. Increasing attention to cost-efficient drug development and predictive modeling is motivating pharmaceutical organizations to use software and consulting services.

The alliance of the local biotech companies with the world market competitors is speeding up the usage of the technology and the advancement of skills. Model-informed drug development is gaining ground with regulatory agencies and further stimulates market growth. The increase in awareness of precision medicine and the necessity of maximizing the outcomes of clinical trials are some of the adoption drivers. Also, there is the ease of access to qualified talent and government-supported projects, which are also boosting the market ecosystem. Altogether, the joint effect of the growing healthcare infrastructure and cost benefits, along with strategic ties, makes Asia-Pacific the most promising biosimulation market on a global scale.

What does the competitive landscape of the Biosimulation market look like?

The Biosimulation Market is gaining considerable momentum, and the trend is set to continue as there is an increasing demand to use predictive modeling and simulation in drug discovery/development. The major industry players include Certara, Simulations PLUS, Schrödinger, and Genedata, who are dominating the competitive trend with a wide portfolio of software products together with services that streamline clinical trial design, pharmacokinetic/pharmacodynamic, and systems biology modeling. Such efforts by Certara have lately seen the company announce the imminent launch of a next-generation quantitative systems pharmacology (QSP) software, CertaraIQ, which is aimed at augmenting the efficacy and safety of drugs. Simulations Plus keeps extending its line by introducing such tools as ADMET Predictor® and GastroPlus® as the demand for correct and qualified predictions of absorption and metabolism is increasing.

Schrödinger employs the use of physics-based simulations enhanced with machine learning, and Genedata is aimed at the improvement of data analytics platforms with the aim of supporting personalized medicine projects. The market is also gaining more strength due to regulatory support and the inclusion of artificial intelligence and advanced computational technologies. In addition, there are increased collaborations and strategic partnerships that have been introduced into the industry to enable faster R&D and the provision of new therapies at a faster pace. Companies are investing enormous sums of money into the development of software, cloud computing, and more sophisticated modeling systems to stay up there. The launch of CertaraIQ is estimated to occur in the last year of 2025, and this will contribute to the market share of Certara in the sense that it will provide a cutting-edge system of biosimulation tools and will serve as a primary drive toward an increased revenue flow. Overall, the competitive nature can be described as the realm of unceasing innovation, strategic expansion, and maniacal focus on offering predictions and efficient responses in modern drug development.

Biosimulation Market, Company Shares Analysis, 2024

To explore in-depth analysis in this report - Request Sample Report

Which recent mergers, acquisitions, or product launches are shaping the Biosimulation industry?

• In July 2025, Certara launched CertaraIQ, a new QSP (Quantitative Systems Pharmacology) software designed to improve drug efficacy and safety assessments. This launch is strategically positioned to enhance Certara's standing in the drug development market by providing advanced tools, potentially boosting software revenue and customer loyalty, according to financial news and analysis sites. 
• In June 2025, Simulations Plus acquired Pro-ficiency, a company specializing in simulation-enabled performance and intelligence solutions for clinical and commercial drug development. This acquisition expands Simulations Plus' offerings across the drug development continuum, providing a comprehensive platform for pharmaceutical and biotech companies.

Report Coverage:

By Offering

• Software
  • Physiologically Based Pharmacokinetic
  • Quantitative Systems Pharmacology
  • PK & PD Models
  • Systems Biology & Disease Progression Models
  • AI-based Tools
• Services
  • Model Development & Validation
  • Data Analysis & Interpretation
  • Virtual Clinical Trial Design
  • Regulatory Consulting & Submissions
  • Training & Technical Support

By Modeling Approach

• Mechanistic Models
• Population-based Models
• Data-driven Models
• Engineering Models

By Therapeutic Area

• Oncology
• Neurology & CNS Disorders
• Cardiovascular Diseases
• Metabolic & Endocrine Disorders
• Respiratory Disorders
• Immunology & Autoimmune Diseases
• Others

By Deployment Mode

• On-premise Solutions
• Cloud-based
• Hybrid Models

By Application

• Drug Discovery & Development
• Preclinical Testing & Toxicology Studies
• Clinical Trial Optimization
• Dose Selection & Regimen Optimization
• Safety & Risk Assessment
• Regulatory Approval & Label Expansion
• Others

By End User

• Pharmaceutical & Biotechnology Companies
• Contract Research Organizations (CROs)
• Academic & Research Institutes
• Regulatory Authorities
• Others

By Region

North America

• U.S.
• Canada

Europe

• U.K.
• France
• Germany
• Italy
• Spain
• Rest of Europe

Asia Pacific

• China
• Japan
• India
• Australia
• South Korea
• Singapore
• Rest of Asia Pacific

Latin America

• Brazil
• Argentina
• Mexico
• Rest of Latin America

Middle East & Africa

• GCC Countries
• South Africa
• Rest of the Middle East & Africa

List of Companies:

• Certara, L.P.
• Dassault Systèmes SE
• Simulations Plus, Inc.
• Schrödinger, Inc.
• Genedata AG
• Chemical Computing Group ULC (CCG)
• Physiomics Plc
• In Silico Biosciences, Inc.
• Applied BioMath, LLC
• VeriSIM Life, Inc.
• Medidata Solutions, Inc.
• BIOVIA
• Entelos, Inc.
• Arzeda Corporation
• Simulations Plus GmbH

Frequently Asked Questions (FAQs)