Drug Modeling Softwares

Drug Modeling Softwares Market Outlook

The global drug modeling software market is expected to reach approximately USD 6.8 billion by 2035, growing at a robust CAGR of 12.4% during the forecast period of 2025 to 2035. This considerable growth is driven by the increasing demand for advanced computational tools in drug discovery and development processes, which enable researchers to better predict the efficacy and safety of drug compounds. Additionally, the integration of artificial intelligence and machine learning techniques in drug modeling software is further enhancing the accuracy and efficiency of drug design. As pharmaceutical companies focus on reducing time and costs associated with drug development, the adoption of modeling software is expected to surge. Furthermore, the rising prevalence of chronic diseases and the need for personalized medicine are expected to bolster the demand for such innovative solutions in the pharmaceutical sector.

Growth Factor of the Market

Several factors are contributing to the growth of the drug modeling software market. Firstly, the escalating investment in R&D activities by pharmaceutical and biotechnology companies is driving the adoption of sophisticated software tools that facilitate efficient drug design and optimization. Secondly, the shift towards precision medicine is creating a need for more personalized drug solutions, which can be developed through advanced modeling techniques. Thirdly, the increasing complexity of drug interactions necessitates robust simulation tools that can accurately predict pharmacokinetics and pharmacodynamics. Furthermore, the rise in regulatory compliance requirements is pushing companies to adopt software that can streamline the drug development process while ensuring adherence to guidelines. Finally, the growing trend of outsourcing drug discovery processes to contract research organizations (CROs) is also contributing to the demand for modeling software, as these organizations seek to enhance their capabilities.

Key Highlights of the Market

• The drug modeling software market is projected to grow significantly, driven by increased R&D investments.
• Technological advancements, including AI and machine learning integration, are set to enhance software functionalities.
• The rising focus on personalized medicine is creating new opportunities for drug modeling applications.
• Regulatory compliance is fostering the demand for software that ensures best practices in drug development.
• Outsourcing of drug discovery processes to CROs is driving demand for advanced modeling solutions.

By Product Type

Molecular Modeling Software:

Molecular modeling software plays a critical role in drug design and development by allowing scientists to create and manipulate representations of molecular structures. These tools enable researchers to visualize complex molecular interactions, analyze conformational changes, and predict the behavior of molecules in various environments. The molecular modeling segment has witnessed significant advancements, particularly with the integration of computational chemistry methods. This software is widely utilized for lead optimization and virtual screening processes, making it an essential component in pharmaceutical research. As the focus on structure-based drug design continues to grow, the demand for high-performance molecular modeling software is expected to rise accordingly.

Pharmacophore Modeling Software:

Pharmacophore modeling software is designed to identify and understand the essential features of molecules that interact with biological macromolecules, thereby aiding in the identification of new drug candidates. This type of software is crucial for virtual screening, as it helps researchers uncover compounds that meet the necessary pharmacophoric criteria. The increasing need for efficient drug discovery processes and cost-effective solutions is driving the growth of this segment. Moreover, as the pharmaceutical industry continues to explore novel therapeutic targets, pharmacophore modeling is becoming increasingly important in the design of selective and potent drug candidates.

QSAR/QSPR Modeling Software:

Quantitative Structure-Activity Relationship (QSAR) and Quantitative Structure-Property Relationship (QSPR) modeling software are essential tools used to predict the activity and properties of chemical compounds based on their molecular structure. The demand for this software is driven by its ability to reduce the time and cost associated with experimental testing by allowing researchers to perform in silico predictions. As regulatory agencies call for more predictive modeling to ensure the safety and efficacy of compounds, the QSAR/QSPR segment is experiencing substantial growth. The increasing availability of high-quality datasets and advancements in machine learning techniques are further enhancing the accuracy of these modeling tools.

Docking Software:

Docking software is a critical component of drug discovery, enabling scientists to predict the preferred orientation of a compound when it binds to a target protein. This software is instrumental in identifying potential lead compounds and optimizing their binding affinities. The growth of this segment is fueled by the rising number of structural biology studies and the increasing understanding of protein-ligand interactions. Moreover, the integration of artificial intelligence in docking algorithms is enhancing their effectiveness and accuracy. As researchers strive to develop more effective therapeutics, the demand for advanced docking software is expected to flourish in the coming years.

ADMET Prediction Software:

ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) prediction software is essential in understanding the pharmacokinetics of drug candidates. This software helps researchers evaluate the safety and efficacy profiles of compounds before proceeding to clinical trials, thereby minimizing the risk of failure. The increasing emphasis on drug safety and the stringent regulatory requirements are driving the demand for ADMET prediction tools. As pharmaceutical companies seek to accelerate their drug development pipelines while ensuring compliance with safety regulations, the ADMET prediction software market is poised for significant growth. Furthermore, advancements in computational methods and databases are enhancing the capabilities of these tools, making them indispensable in the drug development process.

By Application

Drug Discovery:

The drug discovery application segment is anticipated to witness substantial growth due to the increasing demand for innovative therapeutic solutions. Drug modeling software plays a vital role in streamlining the drug discovery process by facilitating the identification of potential drug candidates. As pharmaceutical companies strive to reduce the time and costs associated with traditional discovery methods, the reliance on computational modeling is expected to increase. The integration of artificial intelligence and machine learning algorithms in drug modeling tools is further enhancing their capabilities, allowing for more efficient screening of large compound libraries. This trend is expected to propel the growth of the drug discovery application segment as companies seek to innovate rapidly in a competitive market.

Drug Design:

Drug design involves the design and optimization of new drug candidates based on their molecular structures and biological targets. Modeling software is essential in this phase, enabling researchers to simulate molecular interactions and predict the efficacy of different compounds. The growing emphasis on personalized medicine is driving the demand for targeted drug design, which relies heavily on computational modeling techniques. Moreover, advancements in molecular dynamics simulations and structure-based drug design are further propelling the growth of this segment. As researchers strive to create more selective and potent drugs, the role of drug modeling software in drug design will continue to be significant.

Drug Development:

In the drug development phase, modeling software is utilized to evaluate the pharmacokinetics and pharmacodynamics of drug candidates. This application is crucial in ensuring the safety and efficacy of drugs before they enter clinical trials. The increasing focus on regulatory compliance and the need for thorough preclinical assessments are driving the growth of this segment. Drug modeling tools can help predict potential side effects and optimize drug formulations, thereby enhancing the chances of success in clinical development. As the pharmaceutical industry continues to prioritize safety and efficacy, the demand for drug development applications of modeling software is expected to rise significantly.

Pharmacokinetics/Pharmacodynamics Prediction:

Pharmacokinetics (PK) and pharmacodynamics (PD) prediction is a critical aspect of drug development, as it involves understanding how a drug behaves within the body and its effects on biological systems. Modeling software designed for PK/PD prediction enables researchers to simulate drug absorption, distribution, metabolism, and excretion processes. The increasing need for accurate predictions to reduce the risk of late-stage failures in clinical trials is driving the growth of this application segment. Moreover, advancements in computational modeling techniques are enabling more complex simulations, further enhancing the utility of PK/PD prediction tools in the drug development process. As a result, this segment is expected to experience significant growth in the coming years.

Virtual Screening:

Virtual screening is a powerful technique used in drug discovery to identify potential drug candidates from large compound libraries by simulating their interactions with biological targets. Drug modeling software is instrumental in this process, allowing researchers to quickly and efficiently screen thousands of compounds. The increasing complexity of drug discovery and the need for rapid identification of lead compounds are driving the growth of the virtual screening application segment. Furthermore, advancements in machine learning and data analytics are enhancing the accuracy and efficiency of virtual screening processes. As pharmaceutical companies seek to shorten their discovery timelines and increase their success rates, the demand for virtual screening tools is expected to rise dramatically.

By Distribution Channel

Online Platforms:

Online platforms have become a popular distribution channel for drug modeling software due to their accessibility and convenience. With the rise of cloud-based solutions, researchers can easily access powerful modeling tools from anywhere, facilitating collaboration and information sharing among global teams. The growing trend of subscription-based services is also contributing to the expansion of online distribution channels, as companies can offer flexible pricing models that cater to a wider range of customers. Additionally, the increasing availability of comprehensive online resources, including tutorials and community forums, is enhancing user experience and encouraging the adoption of drug modeling software via online platforms. This segment is expected to continue growing as companies increasingly recognize the benefits of online distribution.

Offline Platforms:

Offline platforms continue to play an essential role in the distribution of drug modeling software, particularly for organizations that require extensive computational resources or have concerns about data security. Many pharmaceutical companies and research institutions prefer offline solutions for their ability to handle large datasets and complex simulations without relying on internet connectivity. The offline platform segment is also characterized by the provision of comprehensive support and training services, as software vendors cater to the specific needs of their users. Although the trend is shifting towards cloud-based solutions, the offline platforms segment is expected to maintain a steady demand, especially among large organizations with established IT infrastructures.

Others:

This segment encompasses various distribution channels that do not fall under the online or offline categories. Examples include third-party vendors and integrators that provide customized software solutions tailored to the specific needs of pharmaceutical companies. These specialized distribution channels are often employed by organizations seeking unique integrations or bespoke software solutions that cater to their specialized research requirements. As the drug modeling software market continues to evolve, the demand for customized solutions is expected to increase, driving growth in this segment. Furthermore, partnerships with academic institutions and research organizations may also contribute to the expansion of alternative distribution channels, enhancing the overall market landscape.

By Software Type

Free Software:

Free software options are increasingly gaining traction in the drug modeling software market, particularly among academic institutions and small research organizations with limited budgets. These tools often provide essential features for molecular modeling and simulation, allowing users to perform critical analyses without incurring significant costs. The popularity of free software is partly due to the growing open-source community, which fosters collaboration and the sharing of knowledge among researchers. However, while free software can be a valuable resource, it may lack the advanced features and technical support provided by paid solutions, resulting in constraints on usability for complex projects. Nevertheless, the availability of free software is expected to encourage greater participation in drug modeling activities, especially in underfunded research sectors.

Paid Software:

Paid software solutions dominate the drug modeling software market due to their extensive features, technical support, and regular updates. These solutions typically offer advanced functionalities, including enhanced simulations and robust data analysis tools, making them indispensable for pharmaceutical companies engaged in drug discovery and development. The investment in paid software is often justified by the increased efficiency and accuracy it brings to research processes. As companies seek to maximize their return on investment in R&D, the demand for paid drug modeling software is expected to grow. Furthermore, as the complexity of drug interactions continues to rise, organizations are likely to prioritize the adoption of comprehensive paid solutions to maintain their competitive edge.

Open-Source Software:

Open-source software has emerged as a significant player in the drug modeling software landscape, providing researchers with a collaborative environment for innovation and development. These solutions allow users to modify and improve software features, fostering a sense of community and shared knowledge. The flexibility and cost-effectiveness of open-source software make it particularly appealing to academic institutions and startups looking to engage in drug modeling without incurring substantial expenses. The growing trend of open-source collaboration is facilitating the development of novel algorithms and methodologies, thereby expanding the functionality of drug modeling tools. As more researchers embrace the open-source philosophy, the demand for such solutions is expected to continue to rise.

Others:

The "Others" category encompasses various specialty software types that cater to specific needs within the drug modeling landscape. This may include tailor-made solutions designed for niche applications or integration with existing systems within pharmaceutical organizations. These customized software solutions can enhance research efficiency and provide unique functionalities that standard offerings may lack. As the drug modeling market evolves, the demand for these specialized software types is expected to grow, driven by the need for organizations to address specific challenges in drug discovery and development. Additionally, collaborations between software vendors and research organizations may lead to the creation of more specialized products, further enriching the landscape.

By Region

The drug modeling software market is experiencing varied growth across different regions, with North America holding the largest share. The North American market is projected to reach approximately USD 2.5 billion by 2035, driven by the presence of major pharmaceutical companies and extensive R&D activities in the region. The integration of advanced technologies, including artificial intelligence and big data analytics, is propelling the growth of drug modeling software in this region. Moreover, the increasing collaboration between academia and industry is facilitating innovation in drug discovery processes. With a CAGR of 13.1%, North America is expected to maintain its dominance in the drug modeling software market throughout the forecast period.

Europe is anticipated to follow closely, with a market size expected to reach approximately USD 2.0 billion by 2035, supported by strong government initiatives and funding for drug discovery research. The European market is characterized by a growing emphasis on regulatory compliance and the need for innovative solutions to streamline drug development processes. Additionally, the rising prevalence of chronic diseases in Europe is driving the demand for efficient drug modeling tools to expedite the discovery of novel therapeutics. As pharmaceutical companies prioritize the development of personalized medicine, the European drug modeling software market is expected to witness significant growth. The Asia Pacific region is also emerging as a key player, with a projected market size of USD 1.5 billion by 2035, spurred by the increasing investment in biotechnology and pharmaceutical research.

Opportunities

As the drug modeling software market continues to expand, numerous opportunities are presenting themselves for industry participants. One significant opportunity lies in the integration of artificial intelligence (AI) and machine learning (ML) technologies into drug modeling platforms. By utilizing AI and ML algorithms, researchers can enhance the predictive capabilities of modeling software, allowing for faster and more accurate identification of potential drug candidates. This integration can also facilitate the analysis of complex datasets generated during drug discovery processes, streamlining workflows and improving overall efficiency. As pharmaceutical companies increasingly seek to leverage these advanced technologies, software vendors can capitalize on this trend by developing innovative solutions that cater to this growing demand.

Another promising opportunity for growth exists in the emerging markets, where the pharmaceutical industry is rapidly evolving. Countries in the Asia Pacific and Latin America regions are witnessing increased investments in drug research and development, leading to a heightened demand for drug modeling software. As local pharmaceutical companies aim to enhance their research capabilities and compete on a global scale, the adoption of advanced modeling solutions is expected to grow. Furthermore, collaborations between software vendors and local research institutions can create tailored solutions that address the unique challenges faced by these markets. By expanding their presence in emerging regions and adapting their offerings to meet local needs, companies can tap into a wealth of new business opportunities in the drug modeling software market.

Threats

Despite the promising growth prospects, the drug modeling software market faces several threats that could impact its trajectory. One major concern is the rapid pace of technological advancements, which may render existing software solutions obsolete. As new modeling techniques and algorithms are developed at an increasing rate, companies must continually innovate to stay competitive. This constant need for updates and enhancements can strain resources and may lead to a situation where organizations struggle to keep pace with the evolving landscape. Additionally, the high cost associated with developing and maintaining advanced drug modeling software may deter smaller organizations from entering the market, limiting competition and innovation.

Another significant threat to the drug modeling software market is the increasing scrutiny from regulatory agencies. As the pharmaceutical industry faces growing demands for transparency and accountability in drug development processes, software solutions must comply with stringent regulations. This can pose challenges for software vendors, as they must ensure that their products meet regulatory standards while delivering the functionalities that researchers require. Failure to comply with these regulations could result in legal challenges, reputational damage, and financial losses. Consequently, companies operating in this space need to invest in compliance measures and stay informed about regulatory changes to mitigate these risks.

Competitor Outlook

• Schrödinger, Inc.
• Thermo Fisher Scientific Inc.
• Biovia Corporation (Dassault Systèmes)
• OpenEye Scientific Software, Inc.
• Agilent Technologies, Inc.
• Accelrys Software Corporation (Dassault Systèmes)
• ChemAxon Ltd.
• Simulations Plus, Inc.
• Bioinformatics Solutions Inc.
• Insilico Medicine, Inc.
• Advena Scientific
• Certara USA, Inc.
• IBM Watson
• ChemDiv, Inc.
• InSilico Research

The competitive landscape of the drug modeling software market is characterized by a diverse range of players, including established companies and innovative startups. Major software vendors such as Schrödinger, Inc., and Thermo Fisher Scientific Inc. are leading the market by offering comprehensive solutions that cater to various aspects of drug discovery and development. These companies invest significantly in research and development to enhance their software functionalities and maintain their competitive edge. The presence of well-established players not only fosters innovation but also sets high standards for product quality and customer support in the industry.

In addition to established companies, a growing number of startups and smaller firms are entering the drug modeling software market, offering niche solutions tailored to specific needs. These newcomers often focus on leveraging advanced technologies such as artificial intelligence and machine learning to differentiate their offerings and capture market share. This influx of innovative companies is driving competition and pushing established players to continuously improve their products. Collaborations and partnerships between software vendors and research organizations are also becoming increasingly common, as both parties seek to enhance their capabilities and deliver cutting-edge solutions to the market.

Companies such as Insilico Medicine, Inc., and Simulations Plus, Inc. are gaining recognition for their unique approaches to drug modeling, particularly in the areas of machine learning and predictive analytics. These firms are at the forefront of innovation, developing software solutions that can significantly accelerate the drug discovery process. As the industry evolves, it is expected that these companies will play a crucial role in shaping the future of drug modeling software, driving advancements that will benefit researchers and pharmaceutical companies alike. Furthermore, as market demand for personalized medicine and targeted therapies continues to grow, the focus on innovative drug modeling tools is likely to intensify, presenting lucrative opportunities for both established players and new entrants.

• 1 Appendix

  • 1.1 List of Tables
  • 1.2 List of Figures

• 2 Introduction

  • 2.1 Market Definition
  • 2.2 Scope of the Report
  • 2.3 Study Assumptions
  • 2.4 Base Currency & Forecast Periods

• 3 Market Dynamics

  • 3.1 Market Growth Factors
  • 3.2 Economic & Global Events
  • 3.3 Innovation Trends
  • 3.4 Supply Chain Analysis

• 4 Consumer Behavior

  • 4.1 Market Trends
  • 4.2 Pricing Analysis
  • 4.3 Buyer Insights

• 5 Key Player Profiles

  • 5.1 IBM Watson
    • 5.1.1 Business Overview
    • 5.1.2 Products & Services
    • 5.1.3 Financials
    • 5.1.4 Recent Developments
    • 5.1.5 SWOT Analysis
  • 5.2 ChemAxon Ltd.
    • 5.2.1 Business Overview
    • 5.2.2 Products & Services
    • 5.2.3 Financials
    • 5.2.4 Recent Developments
    • 5.2.5 SWOT Analysis
  • 5.3 ChemDiv, Inc.
    • 5.3.1 Business Overview
    • 5.3.2 Products & Services
    • 5.3.3 Financials
    • 5.3.4 Recent Developments
    • 5.3.5 SWOT Analysis
  • 5.4 Advena Scientific
    • 5.4.1 Business Overview
    • 5.4.2 Products & Services
    • 5.4.3 Financials
    • 5.4.4 Recent Developments
    • 5.4.5 SWOT Analysis
  • 5.5 Certara USA, Inc.
    • 5.5.1 Business Overview
    • 5.5.2 Products & Services
    • 5.5.3 Financials
    • 5.5.4 Recent Developments
    • 5.5.5 SWOT Analysis
  • 5.6 InSilico Research
    • 5.6.1 Business Overview
    • 5.6.2 Products & Services
    • 5.6.3 Financials
    • 5.6.4 Recent Developments
    • 5.6.5 SWOT Analysis
  • 5.7 Simulations Plus, Inc.
    • 5.7.1 Business Overview
    • 5.7.2 Products & Services
    • 5.7.3 Financials
    • 5.7.4 Recent Developments
    • 5.7.5 SWOT Analysis
  • 5.8 Insilico Medicine, Inc.
    • 5.8.1 Business Overview
    • 5.8.2 Products & Services
    • 5.8.3 Financials
    • 5.8.4 Recent Developments
    • 5.8.5 SWOT Analysis
  • 5.9 Schrödinger, Inc.
    • 5.9.1 Business Overview
    • 5.9.2 Products & Services
    • 5.9.3 Financials
    • 5.9.4 Recent Developments
    • 5.9.5 SWOT Analysis
  • 5.10 Agilent Technologies, Inc.
    • 5.10.1 Business Overview
    • 5.10.2 Products & Services
    • 5.10.3 Financials
    • 5.10.4 Recent Developments
    • 5.10.5 SWOT Analysis
  • 5.11 Bioinformatics Solutions Inc.
    • 5.11.1 Business Overview
    • 5.11.2 Products & Services
    • 5.11.3 Financials
    • 5.11.4 Recent Developments
    • 5.11.5 SWOT Analysis
  • 5.12 Thermo Fisher Scientific Inc.
    • 5.12.1 Business Overview
    • 5.12.2 Products & Services
    • 5.12.3 Financials
    • 5.12.4 Recent Developments
    • 5.12.5 SWOT Analysis
  • 5.13 OpenEye Scientific Software, Inc.
    • 5.13.1 Business Overview
    • 5.13.2 Products & Services
    • 5.13.3 Financials
    • 5.13.4 Recent Developments
    • 5.13.5 SWOT Analysis
  • 5.14 Biovia Corporation (Dassault Systèmes)
    • 5.14.1 Business Overview
    • 5.14.2 Products & Services
    • 5.14.3 Financials
    • 5.14.4 Recent Developments
    • 5.14.5 SWOT Analysis
  • 5.15 Accelrys Software Corporation (Dassault Systèmes)
    • 5.15.1 Business Overview
    • 5.15.2 Products & Services
    • 5.15.3 Financials
    • 5.15.4 Recent Developments
    • 5.15.5 SWOT Analysis

• 6 Market Segmentation

  • 6.1 Drug Modeling Softwares Market, By Application
    • 6.1.1 Drug Discovery
    • 6.1.2 Drug Design
    • 6.1.3 Drug Development
    • 6.1.4 Pharmacokinetics/Pharmacodynamics Prediction
    • 6.1.5 Virtual Screening
  • 6.2 Drug Modeling Softwares Market, By Product Type
    • 6.2.1 Molecular Modeling Software
    • 6.2.2 Pharmacophore Modeling Software
    • 6.2.3 QSAR/QSPR Modeling Software
    • 6.2.4 Docking Software
    • 6.2.5 ADMET Prediction Software
  • 6.3 Drug Modeling Softwares Market, By Software Type
    • 6.3.1 Free Software
    • 6.3.2 Paid Software
    • 6.3.3 Open-Source Software
    • 6.3.4 Others
  • 6.4 Drug Modeling Softwares Market, By Distribution Channel
    • 6.4.1 Online Platforms
    • 6.4.2 Offline Platforms
    • 6.4.3 Others

• 7 Competitive Analysis

  • 7.1 Key Player Comparison
  • 7.2 Market Share Analysis
  • 7.3 Investment Trends
  • 7.4 SWOT Analysis

• 8 Research Methodology

  • 8.1 Analysis Design
  • 8.2 Research Phases
  • 8.3 Study Timeline

• 9 Future Market Outlook

  • 9.1 Growth Forecast
  • 9.2 Market Evolution

• 10 Geographical Overview

  • 10.1 Europe - Market Analysis
    • 10.1.1 By Country
      • 10.1.1.1 UK
      • 10.1.1.2 France
      • 10.1.1.3 Germany
      • 10.1.1.4 Spain
      • 10.1.1.5 Italy
  • 10.2 Asia Pacific - Market Analysis
    • 10.2.1 By Country
      • 10.2.1.1 India
      • 10.2.1.2 China
      • 10.2.1.3 Japan
      • 10.2.1.4 South Korea
  • 10.3 Latin America - Market Analysis
    • 10.3.1 By Country
      • 10.3.1.1 Brazil
      • 10.3.1.2 Argentina
      • 10.3.1.3 Mexico
  • 10.4 North America - Market Analysis
    • 10.4.1 By Country
      • 10.4.1.1 USA
      • 10.4.1.2 Canada
  • 10.5 Middle East & Africa - Market Analysis
    • 10.5.1 By Country
      • 10.5.1.1 Middle East
      • 10.5.1.2 Africa
  • 10.6 Drug Modeling Softwares Market by Region

• 11 Global Economic Factors

  • 11.1 Inflation Impact
  • 11.2 Trade Policies

• 12 Technology & Innovation

  • 12.1 Emerging Technologies
  • 12.2 AI & Digital Trends
  • 12.3 Patent Research

• 13 Investment & Market Growth

  • 13.1 Funding Trends
  • 13.2 Future Market Projections

• 14 Market Overview & Key Insights

  • 14.1 Executive Summary
  • 14.2 Key Trends
  • 14.3 Market Challenges
  • 14.4 Regulatory Landscape

Segments Analyzed in the Report

The global Drug Modeling Softwares market is categorized based on

By Product Type

• Molecular Modeling Software
• Pharmacophore Modeling Software
• QSAR/QSPR Modeling Software
• Docking Software
• ADMET Prediction Software

By Application

• Drug Discovery
• Drug Design
• Drug Development
• Pharmacokinetics/Pharmacodynamics Prediction
• Virtual Screening

By Distribution Channel

• Online Platforms
• Offline Platforms
• Others

By Software Type

• Free Software
• Paid Software
• Open-Source Software
• Others

By Region

• North America
• Europe
• Asia Pacific
• Latin America
• Middle East & Africa

Key Players

• Schrödinger, Inc.
• Thermo Fisher Scientific Inc.
• Biovia Corporation (Dassault Systèmes)
• OpenEye Scientific Software, Inc.
• Agilent Technologies, Inc.
• Accelrys Software Corporation (Dassault Systèmes)
• ChemAxon Ltd.
• Simulations Plus, Inc.
• Bioinformatics Solutions Inc.
• Insilico Medicine, Inc.
• Advena Scientific
• Certara USA, Inc.
• IBM Watson
• ChemDiv, Inc.
• InSilico Research