The regions analyzed for the market include North America, Europe, South America, Asia Pacific, the Middle East, and Africa. North America emerged as the most significant global AI-driven drug discovery platforms market, with a 41% market revenue share in 2024.
This market is largely dominated by North America because it has well-developed healthcare sector, advanced technology and substantial capital and effort that is invested into research and development. The area gains from several top pharmaceutical and biotech companies as well as from AI startups working on advanced drug discovery methods. The generous financial support from the public and private players significantly augments the market’s growth. There are strong and evolving safety rules in the region, headed by the FDA, to help AI technology gain clearance and approval. Because of this regulation, companies no longer worry so much and are more willing to use AI-based systems. Highly skilled experts in AI, machine learning and biomedical fields are available in North America which helps in developing AI tools for drug discovery a much easier and speedier process. Besides, AI’s impressive data-handling and prediction skills are useful for the North American market’s shift towards personalized treatments. Because of these advantages—strong innovation, financial support, friendly rules, good talent and healthcare focus—North America is at the forefront of the AI-driven drug discovery market worldwide.
North America Region AI-Driven Drug Discovery Platforms Market Share in 2024 - 41%
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The component segment is divided into software, hardware and services. The software segment dominated the market, with a market share of around 40% in 2024. The main reason behind software’s dominance in the market is its support in many stages in drug discovery. AI applications in the drug development area rely on software solutions to supply the main algorithms, tools for data processing and computational models for fast and precise selection of potential drugs. Software platforms give pharmacies scalable, repeatable and customizable tools they can build right into their research routines making them highly sought after components in the market. A major reason for software’s success is that it can process and study large and complicated biological data far more productively than traditional methods which saves both money and time. All in all, the AI-driven drug discovery market relies heavily on software because it scales well, is efficient, can handle large data and drives both innovation and productivity in modern drug development.
The application segment is divided into target identification, drug design & optimization, preclinical testing and clinical trials support. The target identification segment dominated the market, with a market share of around 35% in 2024. Recognizing and confirming which proteins, genes or pathways play a role in disease is necessary for creating good drugs. With AI, it becomes possible to quickly and accurately scan much more information about biological, chemical and clinical data than standard methods can handle. AI is applied in platforms for target identification to find important information hidden in big datasets, including genomics, proteomics and transcriptomics. Researchers can detect targets and biomarkers connected to particular diseases which helps design medicines with improved results and lower risks. Companies in the pharmaceutical sector emphasize this step, since it supports every following drug development activity and is why they make up most of the market. The main reason for this is that target identification plays a crucial part in drug development, is greatly influenced by AI and is key to the development of precision medicine initiatives.
The technology segment is divided into machine learning, deep learning and natural language processing (NLP)). The machine learning segment dominated the market, with a market share of around 39% in 2024. The reason ML is most popular in the drug discovery platforms market is its flexibility, strong performance and versatile use throughout the drug development process. Much like other AI technologies, ML algorithms are great at handling huge amounts of data, making patterns that are hard to notice with normal statistics easier to find. Another advantage is that machine learning models need less processing power enabling them to be used in many places regardless of limited resources. As a result, small and mid-sized companies are picking up AI at a faster pace to save money. In addition, ML is able to process genomic, proteomic, chemical and health data from patients, giving a complete picture of both drug action and patient responses. By collecting detailed knowledge, it is possible to make better choices at every step in drug development. Overall, machine learning’s effectiveness is based on being flexible, efficient, scalable and reliable in generating usable insights which is why it is chosen to drive drug discovery and speed up pharmaceutical innovation.
The therapeutic area segment is divided into oncology, neurology, infectious diseases, cardiovascular diseases and others. The oncology segment dominated the market, with a share of around 37% in 2024. Among all therapeutic areas, oncology leads in the AI-driven drug discovery platforms market because of the various challenges, how common cancer is and how urgent the care requirements are. Cancer involves many kinds of genetic changes, different tumour surroundings and various patient responses making it extremely challenging to find effective drugs for cancer. AI used in oncology can look through many different types of data, from genetic records to clinical information, to discover new drug targets, estimate treatment results and customize care. The increase in oncology is largely due to a greater effort and more money devoted to developing cancer drugs. Many companies and research institutions are prioritizing oncology because of a large group of cancer patients, high cancer-related deaths and the big benefits of successful cancer treatments on the market. AI helps quickly detect important connections in how tumours act and in patients’ information which allows experts to develop better targeted therapies with fewer side effects. In addition, precision medicine which tests DNA and RNA to design treatments for specific patients, is developing rapidly in oncology. Through use of AI, this process becomes much easier. In addition, government entities now favour new oncology therapies which also augment’s the segment’s growth. The field of oncology commands the AI-driven drug discovery market mostly because cancer is complex to treat, there are big gaps in care, there is rapid rise in cancer patients and plenty of funding is provided for cancer research.
The end-user segment is divided into pharmaceutical & biotechnology companies, contract research organizations (CROs) and academic & research institutes. The pharmaceutical & biotechnology companies segment dominated the market, with a share of around 44% in 2024. Most of the AI-driven drug discovery platforms are used by pharmaceutical and biotechnology companies, who depend on them to stay ahead in the market with new drugs, medication, therapies and treatments. They can make use of AI technologies in drug discovery because they have enough resources, rich private data and competent staff. Since bringing a new drug to the market is both difficult and expensive, AI-based tools are being used by these companies to make the process more efficient, faster and successful. In addition, the need to innovate due to rising competition and the interest in providing specific treatments motivates these companies. Overall, the main companies in this market are pharmaceutical and biotechnology firms that lead with their major role in drug development, strong investments, focus on new ideas and direct advantages from applying AI to discovering drugs.
This study forecasts revenue at global, regional, and country levels from 2021 to 2034. The Brainy Insights has segmented the global AI-driven drug discovery platforms market based on below mentioned segments:
Global AI-Driven Drug Discovery Platforms Market by Component:
Global AI-Driven Drug Discovery Platforms Market by Application:
Global AI-Driven Drug Discovery Platforms Market by Technology:
Global AI-Driven Drug Discovery Platforms Market by Therapeutic Area:
Global AI-Driven Drug Discovery Platforms Market by End-User:
Global AI-Driven Drug Discovery Platforms Market by Region:
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