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.
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Crown Bioscience Inc.; Chemical Computing Group Ulc; Nimbus Therapeutics; Schrödinger, Inc.; Dassault Systèmes; Genedata Ag; Biognos Ab; Compugen Ltd; Acellera ltd.; and Leadscope, Inc plc are among the prominent players operating in the drug modeling software market.
The market players are focused on organic strategies to sustain their position in the market. For instance, in March 2020, Crown Bioscience has launched two new liver fibrosis rodent models, which allows rapid and cost-effective evaluation of the preclinical effects of NASH and anti-fibrotic treatments on acute liver injury, advanced fibrosis, and/or fibrosis reversal.
Based on product type, the drug modeling software market is segmented into database, software, and others. In terms of product type, the software segment held the highest share of the drug modeling software market in 2019 and is estimated to register the highest CAGR of 8.4% in the market during the forecast period. The growth of the market is attributed to the growing demand for effective therapeutics and increasing number of drug discovery efforts of various biologics across a wide range of therapeutics. Additionally, strategic activities by service providers such as collaborations, product advancement, and product launch in order to expedite drug discovery timeline are further accelerating the growth of the market.
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.
By Product Type
- Drug Discovery and Development
- Computational Physiological Medicine
- Disease Modeling
- Medical Imaging
- Predictive Analysis of Drug Targets
- Simulation Software
- Cellular Simulation
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