The drug modeling software market was valued at US$ 6,205.22 million in 2019 and is projected to reach US$ 11,299.85 million by 2027; it is expected to grow at a CAGR of 8.1% from 2020 to 2027.
Drug modeling has become an essential tool in the drug design process. Software based drug discovery and development methods are playing a key role in the development of novel drugs. Software based methods such as molecular modeling, structure-based drug design, structure-based virtual screening, ligand interaction, and molecular dynamics are considered to be powerful tool for the investigation of pharmacokinetic and pharmacodynamic properties of drugs. These methods are fast, accurate, and provide valuable insights of experimental findings and mechanisms of action. Additionally, appropriate implementation of these techniques may help in reducing drug designing and development cost. Increasing cost of the drug development coupled with increasing drug failures is likely to drive the growth of the drug modeling software market during the forecast period. However, the market is likely to get negatively impacted by the less adoption of drug modeling software in emerging countries.
Lucrative Regions for Drug Modeling Software Market
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Market Insights
Increasing Adoption of Modeling Tools in Drug Discovery
The discovery and development of new drugs with potential therapeutic applications is a complex, expensive, and time-consuming venture. Considering these challenges, various novel technologies have been developed to increase the efficiency of the drug discovery process. Computational methodologies have become a crucial part of several drug discovery programs. From hit identification to lead optimization, techniques such as ligand or structure-based virtual screening are widely being used by many pharmaceutical companies. With the help of modeling, existing data can be leveraged to gain insights on product safety and effectiveness. Owing to the efficiency of computational methods, the FDA and EMA have included modeling to support efficient drug development. Nowadays, in-Silico design (computer-aided) is being utilized to expedite and facilitate hit identification, optimize the absorption, distribution, metabolism, and toxicity profile to avoid safety issues. Commonly used in-silico approaches include ligand-based drug design, structure-based drug design, and quantitative structure-activity.
These methods are faster and provide valuable insights to experimental findings and mechanisms of action. Moreover, various pharmaceutical companies have started adopting these techniques for better outcomes. For instance, in April 2020, Boehringer Ingelheim has partnered with Insilico Medicine to leverage artificial intelligence (AI) technology to identify potential therapeutic targets. These methods are highly beneficial in case of virus outbark and emergency development of drugs. For instance, in Aug 2020, Certara announced the development of a new biosimulation platform for COVID-19 vaccines. The company has partnered with pharmaceutical companies to speed up the drug discovery and development. Its QSP platforms have vast potential to improve biopharmaceutical research and development and inform decision-making. By creating virtual patients and virtual trials, this new vaccine platform will facilitate dosing strategies for a range of patients infected by COVID-19. Moreover, many research organizations have also started adopting drug modeling technologies for expediting the research process. For instance, Southwest Research Institute (SwRI) is expanding the capacity to virtually screen drug compounds for possible treatment of COVID-19 and other infectious diseases. Recently, SwRI increased the capacity of its Rhodium software to scan 250,000 drug compounds per day. Thus, above mentioned factors are expected to drive the growth of the drug modeling software market during the forecast period.
Product Type-Based Insights
Based on product type, the drug modeling software market is segmented into database, software, and others. The software segment held the largest share of the market in 2019. Successful drug discovery, development, and launch of a single new drug into the market, costs about one billion dollars, and it requires nearly 12 years for accomplishing. High cost, insufficient and lengthy-time duration, high level of risk, uncertainty in the results, and highly complex procedures are the main challenges in developing a new drug. To overcome these problems, there is a strong need to employ new and cost-effective drug discovery and designing methods, such as software and computer-aided drug design and molecular docking. For instance, the platform provided by Schrödinger has devoted decades to refining computational algorithms to accurately compute the essential properties of molecules. The company uses NVIDIA GPUs to generate and evaluate the petabytes of data to accelerate drug discovery, as an improvement over the traditional process of slow and expensive lab work.
Exploring software and model-based tools has become a vital way of drug discovery and development in the pharmaceutical industry, playing a crucial role in expanding new bio-active drugs across a range of therapeutic areas. Proper use of software and computer-based modern methods has reduced several hindrances in drug discovery and hastened new drug development.
Global Drug Modeling Software Market, by Product Type– 2019 & 2027
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Application-Based Insights
Based on application, the drug modeling software market is segmented into drug discovery and development, medical imaging, computational physiological medicine, predictive analysis of drug targets, disease modeling, simulation software, cellular simulation, and others. The drug discovery process is complex and includes an interdisciplinary effort to design practical and commercially feasible drugs. In pharmaceutical, medicinal, and other scientific research, a computer plays a significant role in the development of new compounds in the quest for better therapeutic agents.
Moreover, computational power along with advanced analytical techniques such as X-ray crystallography and NMR, have improved the application of CADD (Computer-Aided Drug Design) in the field of pharmaceutical industries like numerous of approved drugs that credited their discovery in large part to the tools of CADD, such as angiotensin-converting enzyme (ACE) inhibitor captopril for the treatment of hypertension, Carbonic anhydrase inhibitor dorzolamide for the treatment of cystoid macular edema, renin inhibitor aliskiren, which is used for essential hypertension, Human immunodeficiency virus (HIV) protease inhibitors saquinavir, ritonavir, and indinavir for the treatment of HIV. Moreover, the CADD and bioinformatics tools provide benefits such as cost-saving, time to market, in-sight knowledge of drug-receptor interactions, and speed up drug discovery and development. Such advantages offered by drug modeling software for drug discovery and drug development will drive the segmental growth during the forecast period.
Additionally, the development of new platforms will further offer lucrative opportunities. For instance, on March 16, 2020, Fujitsu has partnered with Polarisqb to pilot a ground-breaking new drug discovery platform designed to support pharmaceutical companies in bringing vital medication to market quickly and cost-effectively. The platform uses quantum-inspired technology, machine learning, hybrid quantum mechanics, and molecular mechanics simulations (QM/MM) to transform the process of drug discovery. On July 19, 2019, Pumas-AI, a new company established by the University of Maryland School of Pharmacy faculty members, announced its first cutting-edge software platform for pharmaceutical researchers and clinicians, known as Pharmaceutical Modeling and Simulation (Pumas). It is a comprehensive platform based on the Julia programming language that contains multiple modules designed to meet the needs of analysts in the pharmaceutical industry, while also working to advance therapeutic innovation in the clinic setting. In August 2019, London, UK-headquartered Evaluate, a company providing software services for researchers and drug developers, has released Product Specific PTRS (probability of technical and regulatory success), a platform that processes data to predict a drug’s likelihood of success. However, the predictive analysis of drug targets segment is anticipated to witness a significant growth rate during the forecast period.
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Drug Modeling Software Market: Strategic Insights
Market Size Value in US$ 6,205.22 Million in 2019 Market Size Value by US$ 11,299.85 Million by 2027 Growth rate CAGR of 8.1% from 2020-2027 Forecast Period 2020-2027 Base Year 2020
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Customize Research To Suit Your Requirement
We can optimize and tailor the analysis and scope which is unmet through our standard offerings. This flexibility will help you gain the exact information needed for your business planning and decision making.
Drug Modeling Software Market: Strategic Insights
Market Size Value in | US$ 6,205.22 Million in 2019 |
Market Size Value by | US$ 11,299.85 Million by 2027 |
Growth rate | CAGR of 8.1% from 2020-2027 |
Forecast Period | 2020-2027 |
Base Year | 2020 |
Akshay
Have a question?
Akshay will walk you through a 15-minute call to present the report’s content and answer all queries if you have any.
Speak to AnalystProduct launches and expansion strategies are commonly adopted by the companies to expand their footprint worldwide, meet the growing demand, and increase its product portfolio.
The key players operating in the drug modeling software market adopted the strategy of product innovation to cater to changing customer demand across the world, which also permits the players to maintain their brand name globally.
By Product Type
- Database
- Software
- Others
By Application
- Drug Discovery and Development
- Computational Physiological Medicine
- Disease Modeling
- Medical Imaging
- Predictive Analysis of Drug Targets
- Simulation Software
- Cellular Simulation
- Others
By Geography
- North America
- US
- Canada
- Mexico
- Europe
- France
- Germany
- Italy
- UK
- Spain
- Asia Pacific (APAC)
- China
- India
- South Korea
- Japan
- Australia
- Middle East & Africa (MEA)
- South Africa
- Saudi Arabia
- UAE
- South and Central America (SCAM)
- Brazil
- Argentina
Company Profiles
- Crown Bioscience Inc.
- Chemical Computing Group Ulc
- Nimbus Therapeutics
- Schrödinger, Inc.
- Dassault Systèmes
- Genedata Ag
- Biognos Ab
- Compugen Ltd
- Acellera ltd.
- Leadscope, Inc
Report Coverage
Revenue forecast, Company Analysis, Industry landscape, Growth factors, and Trends
Segment Covered
Product type ; Application , and Geography
Regional Scope
North America, Europe, Asia Pacific, Middle East & Africa, South & Central America
Country Scope
Argentina, Australia, Brazil, Canada, China, France, Germany, India, Italy, Japan, Mexico, RoAPAC, RoE, RoMEA, RoSCAM, Saudi Arabia, South Africa, South Korea, Spain, United Arab Emirates, United Kingdom, United States
The List of Companies - Drug Modeling Software Market
- Crown Bioscience Inc.
- Chemical Computing Group Ulc
- Nimbus Therapeutics
- Schrödinger, Inc.
- Dassault Systèmes
- Genedata Ag
- Biognos Ab
- Compugen Ltd
- Acellera ltd.
- Leadscope, Inc
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Once we receive the confirmation from primary research sources or primary respondents, we finalize the base year market estimation and forecast the data as per the macroeconomic and microeconomic factors assessed during data collection.
- Data Analysis:
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The “Table of Contents” is formulated by listing and analyzing more than 25 - 30 companies operating in the market ecosystem across geographies. However, we profile only 10 companies as a standard practice in our syndicate reports. These 10 companies comprise leading, emerging, and regional players. Nonetheless, our analysis is not restricted to the 10 listed companies, we also analyze other companies present in the market to develop a holistic view and understand the prevailing trends. The “Company Profiles” section in the report covers key facts, business description, products & services, financial information, SWOT analysis, and key developments. The financial information presented is extracted from the annual reports and official documents of the publicly listed companies. Upon collecting the information for the sections of respective companies, we verify them via various primary sources and then compile the data in respective company profiles. The company level information helps us in deriving the base number as well as in forecasting the market size.
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