Computational Medicine and Drug Discovery Software Market Projected To Grow At A CAGR Of 4.6% During The Forecast Period 2020 To 2025

Increasing advancements in bioinformatics and various drug discoveries owing to the increase in the number of diseases are anticipated to boost the Computational Medicine and Drug Discovery Software market during the forecast period 2020-2025. The Computational Medicine and Drug Discovery Software Market size are forecast to reach $965.27 million by 2025, growing at a CAGR of 4.6% during the forecast period 2020-2025.

The Computational Medicine and Drug Discovery Software market is growing at a significant rate as medical device manufacturers are making substantial improvements towards computational medicine and drug discovery software. Computational Medicine involves a combination of mathematics, engineering, and computer science. It is an emerging field that is devoted to developing for understanding the mechanisms, diagnosis, and treatment of human disease. The main aim of this field is to develop computational models for molecular biology, physiology, and anatomy of disease, and apply these models to improve patient care. Drug discovery includes various disciples such as biology, chemistry, and pharmacology which involves the identification of drug target, synthesis, characterization, screening, and assays for therapeutic efficacy.

Recent advancements in computational medicine and drug discovery software such as fluorescence polarization and bioinformatics have made it possible to integrate and analyze large datasets in developing better treatment for chronic diseases such as cancer and other genetic disorders. Medical technology advances such as a number of computational advances have had a significant impact on the field of computer-aided drug design over the last several years. These advances can be grouped into three basic areas: conformational modeling (of small molecules, macromolecules, and their complexes), property modeling (of physical, biological, and chemical properties), and molecular design (to optimize physical, biological, or chemical properties). Nvidia is strategically shifting its focus from the computer hardware industry to the healthcare industry and has partnered with companies like GE, Mayo Clinic, and Nuance healthcare to define the workflow by developing computational software that would aid to virtualize all the hospital work and all the different instruments. These computational approaches hold a promise to improve the image quality and help the doctor to predict the diseases which would otherwise take time and are also focused on developing deep learning in genomics and drug discovery and make way towards personalized medicine.

North America dominated the global market share of computational medicine and drug discovery software market in 2019 owing to the advancement in pharmaceutical industries and its increasing usage in disease monitoring and medical imaging and personalized medicine. Increasing advancement in bioinformatics and various drug discoveries owing to the increase in number of diseases is increasing the growth of the computational medicine and drug discovery software market. The growing trends towards innovations in drug discovery software are owing to the increasing better treatment for chronic diseases such as chronic diseases such as cancer and other genetic disorders. The drug discovery process covers a broad range of disciplines from genomics and target discovery to pre-clinical testing. Within this space there are a variety of hardware, software and biological technologies. Healthcare providers using the computational medicine and drug discovery software are going to be ready to deliver a superior patient experience.

Computational Medicine and Drug Discovery software are resistant to combination of mathematics, engineering and computer science that can be devoted to develop for understanding the mechanisms, diagnosis and treatment of human disease. Computational medicine and drug discovery software are used to understand the protein – protein interactions as well as protein – ligand interactions which makes it easier to find the drug target. Researchers from KAIST, Korea developed DeepDDI, a computational framework that accurately predicts and generates 86 types of drug-drug and drug-food interactions. These interactions can help us to predict unexpected pharmacological effects such as adverse drug events (ADEs) and other unknown mechanisms. However, the current prediction methods do not provide detailed drug interactions. Regulatory agencies such as the Food and Drug Administration (FDA), Clinical and Laboratory Standard Institutes (CLSI), and IEC Telecommunication enforce guidelines that ensure the computational medicine and drug discovery software are consistent in manufacture. All the factors are set to avail of new growth opportunities to the computational medicine and drug discovery software market in the region during 2020-2025.

In Computational medicine and drug discovery software, information technologies enhance the chemical structure prediction, heterogeneous database access, pattern discovery, and systems & molecular modeling that have evolved to become core components of the modern computational medicine and drug discovery software. Information technology helps in target identification that involves acquiring a molecular-level understanding of a specific disease state and includes analysis of gene sequences, protein structures, and metabolic pathways. The ultimate goal is to discover macromolecules that can become binding targets for lead compounds, each one a potential drug. Major investments in computational medicine and drug discovery software explore unique applications for drug discovery software. With increasing productivity, information technology has helped pharmaceutical companies to reduce the high failure rate in the drug discovery process and the high cost of the various phase of clinical trials acts as limiting factors for several drugs, which can be developed by pharmaceutical companies and hence information technology helps in selecting the compounds with the best chances for approval.

Biologics are highly specific to their target and have invoked high levels of media and investor interest due to their innovative techniques and potential to cure previously untreatable diseases. The majority of drugs discovered during the 20th century were chemically synthesized small molecules, which still make up 90 percent of drugs on the market today.4 The advantages of small molecules include simple manufacturing and administration routes, low specificity, and stable shelf life, meaning they are safe and effective for large groups of people. However, low specificity can also lead to side effects, reducing the chances of success in clinical trials.

The growing use of computational medicine and drug discovery software for disease monitoring and medical imaging and personalized medicine. Computational medicine and drug discovery software are used to understand the protein-protein interactions as well as protein-ligand interactions which makes it easier to find the drug target. Continued developments in drug discovery software have made the technology a viable commercial processing tool, with applications in R&D, prototyping, short-run or low-volume production, and high-volume, high-throughput manufacturing. This is set to give a boost in the computational medicine and drug discovery software market in upcoming years.

Fujitsu Laboratories Ltd. and Fujitsu Limited announced the development of molecular simulation technology for drug discovery. This development can accurately estimate binding affinity between the target protein and the chemical substance which helps to predict the drug’s efficiency. This technique also estimates the degree of torsion in a chemical substance as well as the impact of neighboring atoms and thus will help in the development of new targeted therapies.

In February 2018, Roche acquired oncology tech company Flatiron Health to implement the use of artificial intelligence as another tool to facilitate drug discovery and help the company progress. This acquisition with Flatiron Health provided the required technology and data analytics needed for Roche as well as oncology research and development across the industry. 

The major companies in the Computational Medicine and Drug Discovery Software market include Entelos Inc., Genedata Ag, Crown Bioscience Inc., Biognos Ab, Chemical Computing Group Inc., Leadscope Inc., Nimbus Therapeutics Inc., Rhenovia Pharma Limited, Schrodinger Llc, Compugen, and Dassault Systemes among others. In February 2018, Roche acquired oncology tech company Flatiron Health to implement the use of artificial intelligence as another tool to facilitate drug discovery and help the company progress. This acquisition with Flatiron Health provided the required technology and data analytics needed for Roche as well as oncology research and development across the industry.

Over the years, the major market players have focused on the development of computational medicine and drug discovery software that uses a combination of mathematics, engineering, and computer science. The launch of new market companies, adequate funding, and government-aided policies help in the development of the computational medicine and drug discovery software market. The continuous development in the computational medicine and drug discovery software market such as increasing funding amount of startups and research organizations and surge in the number of computational medicine and drug discovery software approvals by the Food and Drug Administration (FDA) are the major factors set to drive the Computational Medicine and Drug Discovery Software market during the forecast period 2020-2025.