Artificial Intelligence (AI) in Drug Discovery Market Analysis

AI in Drug Discovery Market Analysis

By component, the AI in drug discovery market is classified into software and services. The software segment accounted for 63% of the market share in 2022 and is projected to witness significant growth over the analysis timeframe. Increasing demand for advanced analytics and machine learning tools within the pharmaceutical industry is expected to propel the segmental growth. Furthermore, AI software tools enhance efficiency and automate multiple stages of the drug discovery workflow, resulting in reduced time and resource requirements, thereby fuelling the adoption of AI software in drug discovery. Moreover, advancements in cloud computing and high-performance computing infrastructure have played a pivotal role in driving the growth of AI software.
 

Based on technology, the AI in drug discovery market is segmented into machine learning and other technology. The machine learning segment is expected to surpass around USD 18 billion by 2032. The increasing availability and accessibility of vast amounts of data, including genomics, proteomics, and clinical records, have created opportunities for machine learning algorithms to extract valuable insights and patterns. By leveraging these data sets, machine learning algorithms can identify potential drug targets, predict drug efficacy, and optimize drug design, enabling more targeted and efficient drug discovery processes. Such aforementioned factor is expected to drive the market growth.
 

Based on application type, the AI in drug discovery market is segmented into molecular library screening, target identification, drug optimization and repurposing, de novo drug designing, and preclinical testing. The molecular library screening segment accounted for 40.1% of the market share in 2022 and is projected to witness considerable growth over the analysis timeframe. The availability of vast and constantly expanding libraries of molecular compounds will presents a tremendous opportunity for AI-driven screening, thereby fostering the market growth.  Furthermore, increasing demand for the discovery and development of novel drug therapies and growing manufacturing capacities of the life science industry are boosting the demand of artificial intelligence in drug discovery.
 

Based on therapeutic area, the AI in drug discovery market is segmented into oncology, neurodegenerative diseases, inflammatory, infectious diseases, metabolic diseases, rare diseases, cardiovascular diseases, and other therapeutic areas. The oncology segment accounted for 44.8% of the market share in 2022 and is projected to witness considerable growth over the analysis timeframe. The increasing prevalence of cancer worldwide will supplement the market growth. For instance, according to the National Institute of Health (NIH) report, in 2022, the estimated number of incident cases of cancer in India was found to be 1,461,427 (100.4 per 100,000). Thus, growing cases of cancer will drive the demand for more effective and targeted treatments, thereby escalating the market growth.
 

Based on end-use, the AI in drug discovery market is segmented into pharmaceutical and biotechnology companies, contract research organization (CROs), and other end-users. The pharmaceutical and biotechnology companies segment accounted for 53.1% of the market share in 2022 and is projected to witness considerable growth over the analysis timeframe. The adoption of AI technologies by pharmaceutical and biotechnology companies offers numerous advantages, including the discovery of new targets and indications, optimization of drug development pipelines, enhanced collaboration, and the ability to address unmet medical requirements.
 

North America AI in drug discovery market accounted for 51.9% market share in 2022 and is anticipated to grow at considerable growth rate during the forecast timeframe. North America has a robust ecosystem of research institutions, academic centers, and healthcare facilities, thereby driving the regional growth. Moreover, the availability of diverse and high-quality dataset enables the development and validation of AI algorithms for drug discovery applications. Furthermore, increasing prevalence of chronic diseases coupled with rising investment in research and development activities is expected to supplement the artificial intelligence (AI) in drug discovery industry.