The quantitative structure-activity relationship (QSAR) market is expected to reach US$ 1,888.5 million by 2027 from US$ 1,388.1 million in 2019; it is estimated to grow at a CAGR of 4.0% during 2020-2027.

The market growth is mainly attributed to the increasing adoption rate of modeling tools in drug discovery and rising investments for drug discovery. However, low adoption rate of the technique in emerging countries is hindering the quantitative structure-activity relationship market growth.

A quantitative structure-activity relationship (QSAR) is a computational or mathematical modeling approach of studying connections between the biological activities and structural properties of chemical compounds. The QSAR models are beneficial in predicting the actions of untested chemicals, among other applications. It is an in silico methodology that helps narrow down the spectrum of candidate molecules for in vivo experiments by sorting them on the basis of the desired biological activities.

Traditional drug discovery and development methods face challenges such as high failure rates, capital-intensive, and time-consuming. The drug discovery process involves experimental screening of already existing libraries of drugs or molecules, followed by synthesizing many molecules. The traditional method of drug development, from the discovery of a lead molecule to its commercial launch, is observed to take around 10-16 years; moreover, it demands a large amount of investments. According to pharmaceutical research and manufacturers of America, a successful research and development of a drug compound costs ~US$ 2.6 billion on an average. Moreover, only a small proportion of leads selected for further investigation are translated into clinical research studies.. As a result, there has been a direct rise in R&D expenditure in the pharmaceutical sector. For instance, Pharmaceutical Research and Manufacturers of America stated that biopharmaceutical companies sponsored more than 4,500 clinical trials in the US in 2017, which accounted for ~US$ 43 billion ; similarly, they invested ~US$ 97 billion in R&D in that year. Hence, the pharmaceutical industry is under massive pressure to cope with rising capital requirements in drug discovery, research, and molecule failure.

In the last few years, several computational and modeling tools have been developed to identify, select, and optimize pharmacological lead drug candidates, which ultimately support the drug discovery process. The predictive capabilities of these tools have been proven to be advantageous, allowing researchers to bypass the screening of billion s of molecules. As a result, computational services, such as molecular modeling and quantitative structure-activity relationship (SAR), have become an integral part of the pharmaceuticals, cosmetics, and food & beverages industries, among others. As a result, pharmaceutical companies focused on developing large drug molecules are likely to continue outsourcing their respective drug discovery and development operations from drug modeling providers.

Based on application, the quantitative structure-activity relationship (QSAR) market is segmented into drug discovery, molecular modelling, chemical screening, regulatory and decision-making, and other applications. In 2019, the drug discovery accounted for the highest share and is expected register the highest CAGR during the forecast period. The drug discovery process often involves the use of QSAR to identify chemical structures that could have good inhibitory effects on specific targets and have low toxicity (non-specific activity). According to Lipinski's Rule of Five, the prediction of partition coefficient log P is an important measure used in identifying "drug likeness."

The COVID-19 pandemic is causing massive disruptions in supply chains, consumer markets, and economies across the world. However, the high demand for promising tools for rapid and accurate drugs and vaccine development has boosted the demand for QSAR, thereby fueling the market growth.

The Organization for Economic Co-operation and Development (OECD), World Health Organization (WHO), European Union (EU), International Trade Administration (ITA), European Federation of pharmaceutical Industries and Associations (EFPIA), and US Food and Drug Administration (FDA) are a few of the prime secondary sources referred to while preparing the report on the quantitative structure-activity relationship market.