The global artificial intelligence (AI) in the drug discovery market was valued at USD 571.1 million in 2020 and is growing at a CAGR of 28.3% during the forecast period. The growing need for decreasing the cost of drug discovery and its approval process requires a lot of human expertise and time, which could be eased out with the help of artificial intelligence.
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It is estimated that, the average cost of drug development and discovery costs around USD 2.6 billion. This is primarily due to the strong approval process for different disease indications, which eliminates the majority of drug candidates within pre-clinical and phase I trials. To counter failures, pharmaceutical giants across the globe are focusing on artificial intelligence tools for faster and cost-effective drug discovery.
The huge amount of data generated during small molecule screening and preclinical studies have led to the adoption of artificial intelligence (AI) in the drug discovery process. The reviewing of such market data for researchers through scientific literature is a monumental and time-consuming task. Under such constraints, artificial intelligence (AI) boosts up the screening process and reduces the time for identifying drug molecular interactions and cell mechanisms.
Another important aspect of the rising use of artificial intelligence (AI) in drug discovery is the wide availability of options to carry out data mining and a range of specific customization according to the need. Moreover, the advancements in artificial intelligence (AI) such as machine learning and artificial neural networks have enabled pharma companies to recognize the binding properties of drugs with the highest accuracy.
The preclinical process is one of the important areas, accounting for high revenue loss and low returns. Here, artificial intelligence (AI)-based models are used for accurate analysis as compared with the standard animal models. These models help researchers in eliminating experiment costs and help in the prediction of differences in cross-species.
The market is primarily segmented on the basis of application, by therapeutic area, and geographic region.
By Therapeutic Area
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On the basis of type, the global artificial intelligence in the drug discovery market is bifurcated as drug optimization and repurposing, preclinical testing, and others. In 2020, the drug optimization and repurposing market segment accounted for the largest revenue share. This high share is attributed to the ability of artificial intelligence (AI) tools in providing an effective way to analyze the side effects of drugs and their adverse events on the human body.
Moreover, such artificial intelligence (AI) platforms are also being used in deducing alternative applications for the existing drugs, which will enable pharma firms in diversifying the portfolio of their offerings and assist in devising alternate therapies to alteration in drug’s mechanism of action.
However, the pre-clinical testing market segment is projected to witness a lucrative artificial intelligence in the drug discovery market growth rate over the study period. This is attributed to their effectiveness in reducing experimental costs and other overheads.
For instance, artificial intelligence (AI)-based platforms BenchSci’s machine learning platform is designed to reduce errors and assistance for scientists in different sets of experiments. Similarly, another AI system “Euretos” enables scientists in designing experiments through in-silico tools, reducing experimental costs to a larger extent.
North America artificial intelligence in the drug discovery market accounted for the highest revenue share in 2020. Key regional factors contributing to the market growth include the high adoption of artificial intelligence (AI) platforms among several pharma firms in the U.S. and the presence of well-established clinical infrastructure with sound funding capacity. According to the survey done by RELX, the establishment of artificial intelligence (AI) in companies has increased to 73 percent in 2019.
This was primarily due to the positive perception of artificial intelligence (AI) platforms among drug discovery market companies. Asia Pacific market is expected to witness a lucrative artificial intelligence in the drug discovery market growth rate over the assessment period.
The growing adoption of artificial intelligence (AI) systems in both India and China for drug development and a strong focus on pharma companies in boosting their capacities have driven the artificial intelligence (AI) systems for drug discovery in the concerned region.
Some of the major players operating in the market for artificial intelligence (AI) in drug discovery include IBM Watson, Alphabet (DeepMind), Exscientia, GNS Healthcare, Insitro, BioSymetrics, Euretos, Berg Health, Benevolent AI, Atomwise, and Cyclica. Big pharmaceutical players in the industry are focusing on collaboration to stay competitive.
For instance, in January 2021, Bayer entered into a collaboration agreement with artificial intelligence (AI) drug discovery firm Exscientia to identify novel and drug candidates for cardiovascular and oncology disorders. This will potentially speed up the drug discovery process, its development, cost, and turnaround time. The partnership will focus on early-stage research via an AI-based algorithm.