Focus on drug discovery, molecular modeling, chemical screening, regulation and decision making
DUBLIN, May 7, 2021 / PRNewswire / – The Quantitative Forecast of Structure-Activity Relationship Market to 2027 – COVID-19 Impact and Global Analysis by Application; industry and geography ” the report was added to ResearchAndMarkets.com offer.
The Quantitative Structure-Activity Relationship market for Drug Discovery segment is expected to grow at the highest CAGR during the period 2020-2027.
The Quantitative Structure-Activity Relationship (QSAR) market is expected to reach US $ 1,888.5 million in 2027 US $ 1,388.1 million in 2019, it is expected to grow at a CAGR of 4.0% from 2020 to 2027.
The growth of the market is mainly attributed to the increasing adoption rate of modeling tools in drug discovery and increased investment in drug discovery. However, the low rate of adoption of the technique in emerging countries is hampering the growth of the quantitative structure-activity relationship market.
On the basis of applications, the quantitative structure activity relationship market is segmented into drug discovery, molecular modeling, chemical screening, regulation and decision making, and other applications. In 2019, the drug discovery segment accounted for the largest share, and it is further expected to register the highest CAGR in the market during the forecast period.
The drug discovery process often involves the use of QSAR to identify chemical structures that might have good inhibitory effects on specific targets and have low toxicity (non-specific activity). According to Lipinski’s rule of five, predicting the log P partition coefficient is an important measure used to identify “drug similarity”. .
QSARs play an important role in predicting toxicity, designing drugs, and modeling the environmental fate of foods and beverages, chemicals, and pharmaceuticals. Additionally, predictive QSAR models are used by different regulatory agencies to estimate chemical, physical and biological parameters of chemicals using specific applications that accurately perform the tasks of decision contexts in safety assessment. chemical.
Ineffective drug targets are the main reason for the failure of various late stage clinical trials. With the introduction of artificial intelligence (AI) in healthcare, many pharmaceutical companies have invested in partnership agreements with software companies to develop better healthcare tools and technologies to avoid drug failures. .
For example, Pfizer uses IBM Watson, a machine learning system, to improve its research into immuno-oncology drugs. Sanofi has collaborated with the artificial intelligence (AI) platform of Exscientia, a UK-based start-up, to discover therapies to cure metabolic diseases. Genentech is improving its cancer treatment research using an AI-based system offered by GNS Healthcare. Therefore, most companies engaged in drug discovery use AI tools to screen for and identify compounds, calculate their potential, and minimize drug interactions that could cause problems later.
With the introduction of AI in the pharmaceutical and health sectors, companies in these sectors are investing in collaborations with AI actors for the development of improved and advanced health tools, which facilitates better identification of drug targets and assistance in the design of new drugs. candidates.
Thus, an increase in the number of partnerships between pharmaceutical industries and AI companies, and government organizations has been observed globally. For example, in 2019, the Royal Free London NHS Foundation Trust entered into a five-year partnership with DeepMind Technologies (Google), where the company is expected to help the NHS discover therapies for the management of acute kidney injury. The UK 100,000 Genome Project is a global project that uses data and AI from NHS patients with rare diseases. The project also has Roche, Merck and Biogen as partners.
The COVID-19 pandemic is causing massive disruption in supply chains, consumer markets and economies across the world. However, the high demand for promising tools for rapid and accurate drug and vaccine development has driven the demand for QSAR, thereby fueling the growth of the market.
Key industry dynamics
- Growing adoption of modeling tools in drug discovery
- Growing economic burden of drug discovery
- Less adoption in emerging countries
- Initiatives by market players
- Growing adoption of QSAR and artificial intelligence in drug discovery
- Protoqsar Sl.
- Intertek Plc Group
- Bibra Toxicology Advice And Consulting Ltd
- Covance inc. (Labcorp)
- Latham Biopharm Group
- NSF International
- Creative biolabs
- Qsar Lab Sp. ZO
- Dassault Systèmes
The report segments the Quantitative Structure-Activity Relationship market as follows:
- Drug discovery
- Molecular modeling
- Chemical screening
- Regulation and decision making
- Other applications
- Beauty products
- Food and drink
- North America
- Asia Pacific (APAC)
- South Korea
- Middle East and Africa (AEM)
- Saudi Arabia
- United Arab Emirates
- South Africa
- South and central America (SCAM)
For more information on this report, visit https://www.researchandmarkets.com/r/ndk9t4
Research and markets
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SOURCE Research and Markets