AI in Drug Discovery Market (Offering - Software, and Services; Technology - Machine Learning, Natural Language Processing (NLP), Computer Vision, and Others; Application - Target Identification, Molecule Screening, Drug Design and Drug Optimization, Preclinical and Clinical Testing, and Others; Therapeutic Area - Oncology, Neurodegenerative Diseases, Infectious Disease, and Others; End User - Pharmaceutical & Biotechnology Companies, Contract Research Organizations, and Academic & Government Research Institutes): Global Industry Analysis, Trends, Size, Share and Forecasts to 2030

A recent report published by Infinium Global Research on AI in drug discovery market provides in-depth analysis of segments and sub-segments in the global as well as regional AI in drug discovery market. The study also highlights the impact of drivers, restraints, and macro indicators on the global and regional AI in drug discovery market over the short term as well as long term. The report is a comprehensive presentation of trends, forecast and dollar values of global AI in drug discovery market.

Market Insight:

AI in drug discovery market was valued at USD 1360.81 million in 2022 and expected to reach USD 9107.49 million in 2030, with a CAGR of 23.54% during the forecast period 2023-2030.

Artificial intelligence in drug discovery refers to the use of artificial intelligence technologies, particularly machine learning algorithms, to expedite and enhance the process of identifying potential new drugs and treatments. This involves predicting molecular bioactivity, analyzing complex biological data, and optimizing drug designs to ensure efficacy and safety. Additionally, the scope of AI in this field is in the initial drug discovery phase, where predictive models can significantly reduce the time and resources spent on experiments by forecasting how different compounds might behave. Additionally, AI can analyze vast datasets, such as patient records or genomic sequences, to uncover patterns and correlations that human researchers might overlook. This has the potential to lead to more personalized medicine strategies. In essence, by harnessing the power of AI, the pharmaceutical industry hopes to cut down the traditionally long and costly drug development cycle, thereby bringing effective treatments to market more rapidly and efficiently.

Artificial intelligence ability to swiftly analyze and optimize drug candidates accelerates drug discovery, minimizing the lengthy and expensive research process. This efficiency attracts pharmaceutical companies, as it promises cost savings, faster drug development, and increased chances of identifying novel treatments, making AI a driving force in the pharmaceutical market. Additionally, the proliferation of biological and chemical data has propelled AI advancements in drug discovery. Harnessing vast datasets, AI algorithms can predict drug interactions and efficacy, expediting the research process. This data-rich environment fosters innovation, enabling more efficient and targeted drug development in the pharmaceutical industry. However, regulatory hurdles, such as compliance with strict pharmaceutical regulations, and data privacy concerns surrounding the use of sensitive patient information, pose significant challenges for AI adoption in drug discovery. Although, AI accelerates drug discovery through data-driven insights and predictive models, fostering faster, more effective, and personalized treatments. This offers opportunities for pharmaceutical companies to streamline R&D, reduce costs, and enhance patient outcomes, ultimately transforming the industry's efficiency and capacity for innovation.

The largest market share holder region in the artificial intelligence in drug discovery market is North America, particularly the United States. The United States is a global leader in pharmaceuticals and biotechnology, hosting numerous AI startups, research institutions, and established pharmaceutical companies. Its well-established infrastructure, substantial investment in AI research, and favorable regulatory environment contributed to its dominant position in this market. Moreover, the fastest-growing region in AI for drug discovery is Asia-Pacific. Countries such as China, Japan, and South Korea made significant strides in AI adoption for drug development. These nations have been investing heavily in AI research, fostering collaborations between academia and industry, and offering regulatory support to accelerate innovation. Additionally, the region's vast patient populations and growing healthcare needs make it a promising market for personalized medicine, where AI plays a crucial role.

Report Scope of the AI in Drug Discovery Market:

Segment Covered

The report on global AI in drug discovery market covers segments such as offering, technology, application, therapeutic area, and end user. On the basis of offering, the sub-markets include software, and services. On the basis of technology, the sub-markets include machine learning, natural language processing (NLP), computer vision, and others. On the basis of application, the sub-markets include target identification, molecule screening, drug design and drug optimization, preclinical and clinical testing, and others. On the basis of therapeutic area, the sub-markets include oncology, neurodegenerative diseases, infectious disease, and others. On the basis of end user, the sub-markets include pharmaceutical & biotechnology companies, contract research organizations, and academic & government research institutes.

Companies Profiled:

The report provides profiles of the companies in the market such as BenevolentAI, Atomwise Inc., Cyclica Inc., DEEP GENOMICS, Exscientia, IBM Corporation, NVIDIA Corporation, Biosymetrics, Cloud Pharmaceuticals, and Insilico Medicine.

Report Highlights:

The report provides deep insights into demand forecasts, market trends, and micro and macro indicators. In addition, this report provides insights into the factors that are driving and restraining the growth in this market. Moreover, The IGR-Growth Matrix analysis given in the report brings an insight into the investment areas that existing or new market players can consider. The report provides insights into the market using analytical tools such as Porter's five forces analysis and DRO analysis of the AI in drug discovery market. Moreover, the study highlights current market trends and provides forecasts from 2023-2030. We also have highlighted future trends in the market that will affect the demand during the forecast period. Moreover, the competitive analysis given in each regional market brings an insight into the market share of the leading players.