Global Artificial Intelligence (AI) in Drug Discovery Market – Industry Trends and Forecast to 2031

Global Artificial Intelligence (AI) in Drug Discovery Market, By Application (Novel Drug Candidates, Drug Optimization and Repurposing Preclinical Testing and Approval, Drug Monitoring, Finding New Diseases Associated Targets and Pathways, Understanding Disease Mechanisms, Aggregating and Synthesizing Information, Formation and Qualification of Hypotheses, De Novo Drug Design, Finding Drug Targets of an Old Drug, and Others), Technology (Machine Learning, Deep Learning, Natural Language Processing, and Others), Drug Type (Small Molecule and Large Molecule), Offering (Software and Services), Indication (Immuno-Oncology, Neurodegenerative Diseases, Cardiovascular Diseases, Metabolic Diseases, Rare Diseases, Infectious Diseases and Others), End Use (Contract Research Organizations (CROs), Pharmaceutical and Biotechnology Companies, Research Centers and Academic Institutes, and Others) – Industry Trends and Forecast to 2031.

Artificial Intelligence (AI) in Drug Discovery Market Analysis and Size

AI is becoming an important tool in healthcare, particularly in drug manufacturing, where it addresses R&D gaps and enables targeted drug production. Biopharmaceutical companies are leveraging AI to bolster their market presence. In drug discovery, AI simulates human intelligence, tackling complex challenges and expediting development. Its adoption in clinical trials streamlines processes, cutting cycle times, enhancing productivity, and improving accuracy.  

Data Bridge Market Research analyses the global artificial intelligence (AI) in drug discovery market, which was USD 932.24 million in 2023, is expected to reach USD 1,409.14 million by 2031, at a CAGR of 5.30% during the forecast period 2024 to 2031. In addition to the insights on market scenarios such as market value, growth rate, segmentation, geographical coverage, and major players, the market reports curated by the Data Bridge Market Research also include depth expert analysis, patient epidemiology, pipeline analysis, pricing analysis, and regulatory framework.

Report Scope and Market Segmentation      

Market Definition

Artificial intelligence (AI) in drug discovery involves the use of advanced computational algorithms and machine learning models to analyze biological data, predict potential drug candidates, and accelerate the drug development process. AI enables the identification of novel drug targets, optimization of molecular structures, and analysis of large datasets, ultimately aiding researchers in discovering new and more effective therapeutic solutions.

Global Artificial Intelligence (AI) in Drug Discovery Market Dynamics

Drivers

• Technology Advancements Enhances Ability to Analyse Drug Discovery Processes

AI leverages cutting-edge technologies such as machine learning and deep learning to analyze vast datasets, identify potential drug candidates, and optimize drug development pathways. The integration of advanced computational tools enables researchers to navigate complex biological and chemical interactions more efficiently, leading to faster and more accurate drug discovery outcomes. As technology continues to evolve, the application of AI in drug discovery is poised to further grow the pharmaceutical industry by expediting innovation and reducing development timelines.

• Precision Medicine Enhances Treatment Efficacy

Precision medicine, driven by AI in drug discovery, enhances treatment efficacy by tailoring therapeutic approaches to individual patient characteristics. AI analyzes vast datasets encompassing genetic, molecular, and clinical information to identify specific patient profiles and predict optimal drug responses. This personalized approach improves treatment outcomes and minimizes adverse effects, contributing to the growing adoption of AI in drug discovery on a global scale. The ability to target treatments more precisely aligns with the overarching goal of developing safer and more effective drugs.

Opportunities

• Increasing Strategic Initiatives Fosters Development of AI-Driven Solutions

As pharmaceutical companies and research institutions increasingly recognize the potential of AI, there is a surge in collaborations, partnerships, and investments. These strategic initiatives foster the development of innovative AI-driven solutions, creating a collaborative ecosystem for accelerating drug discovery. Such partnerships can lead to the pooling of resources, expertise, and diverse datasets, thereby enhancing the effectiveness of AI algorithms in identifying potential drug candidates and optimizing the drug development process.

• Researchers Analyses Diverse Datasets Associated with Data-Driven Biomarker

With AI algorithms, researchers can sift through extensive biological and clinical data, identifying subtle patterns and correlations that may serve as crucial biomarkers for diseases. This capability accelerates the biomarker discovery process, aiding in precise disease diagnosis, prognosis, and treatment response prediction. The ability to comprehensively analyse diverse datasets enhances the understanding of complex biological systems, facilitating the development of targeted therapies and personalized medicine approaches.

Restraints/Challenges

• Lack of Standardized Protocols Across Diverse AI Platforms and Tools

This variability hampers seamless integration and collaboration between different technologies, hindering interoperability. The absence of universally accepted protocols complicates data sharing, consistency, and compatibility across various AI applications in drug discovery. This lack of standardization poses challenges for efficient communication and workflow and potentially limits the scalability and widespread adoption of AI solutions within the industry.

• Ethical Concerns Arising from Algorithmic Bias

As AI systems increasingly contribute to decision-making processes, biases embedded in algorithms can inadvertently perpetuate disparities in healthcare outcomes. In the context of drug discovery, biased algorithms may inadvertently favour specific demographic groups, leading to unequal representation and potential exclusion of certain populations.

This global artificial intelligence (AI) in drug discovery market report provides details of new recent developments, trade regulations, import-export analysis, production analysis, value chain optimization, market share, impact of domestic and localized market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographic expansions, technological innovations in the market. To gain more info on the global artificial intelligence (AI) in drug discovery market contact Data Bridge Market Research for an Analyst Brief, our team will help you take an informed market decision to achieve market growth.

Recent Developments

• In November 2022, Exscientia and the University of Texas MD Anderson Cancer Center initiated a strategic collaboration, combining Exscientia's AI technology with MD Anderson's capabilities for patient-centric small molecule drug discovery. This partnership is poised to significantly advance novel drug development by synergizing AI-driven insights with the specialized knowledge of MD Anderson, potentially contributing to a more targeted and efficient drug discovery process
• In August 2022, GNS Healthcare and LES LABORATOIRES SERVIER joined forces to propel drug discovery and development for managing multiple myeloma. This collaboration reflects a concerted effort between GNS Healthcare and the pharmaceutical manufacturer to enhance therapeutic solutions for this specific cancer. Leveraging AI in tandem with Servier's expertise, the collaboration aims to streamline the drug discovery pipeline, potentially leading to innovative and more effective treatments for multiple myeloma
• In March 2022, NVIDIA Corporation launched Clara Holoscan MGX, an expansion of the Clara Holoscan platform, designed to develop and deploy real-time AI applications in the medical device industry. With a focus on surgery, diagnostics, and drug discovery, Clara Holoscan MGX provides a medical-grade reference architecture, enhancing AI performance and supporting innovation in healthcare

Global Artificial Intelligence (AI) in Drug Discovery Market Scope

The global artificial intelligence (AI) in drug discovery market is segmented into application, technology, drug type, offering, indication and end use. The growth among segments helps you analyze niche pockets of growth and strategies to approach the market and determine your core application areas and the differences in your target markets.

Application

• Novel Drug Candidates
• Drug Optimization and Repurposing Preclinical Testing and Approval
• Drug Monitoring
• Finding New Diseases Associated Targets and Pathways
• Understanding Disease Mechanisms
• Aggregating and Synthesizing Information
• Formation and Qualification of Hypotheses
• De Novo Drug Design
• Finding Drug Targets of an Old Drug
• Others

Technology

• Machine Learning (ML)
  • Deep Learning (DL)
  • Supervised Learning
  • Reinforcement Learning
  • Unsupervised Learning
  • Other Machine Learning Technologies
• Natural Language Processing (NLP)
• Context Aware Processing
• Others

Drug Type

• Small Molecule
• Large Molecule

Offering

• Software
• Services

Indication

• Immuno-Oncology
• Neurodegenerative Diseases
• Cardiovascular Diseases
• Metabolic Diseases
• Rare Diseases
• Infectious Diseases
• Others

End Use

• Pharmaceutical and Biotechnology Companies
• Contract Research Organizations (CROs)
• Research Centres And Academic Institutes
• Others

Global Artificial Intelligence (AI) in Drug Discovery Market Regional Analysis/Insights

The global artificial intelligence (AI) in drug discovery market is analyzed, and market size information is provided by the application, technology, drug type, offering, indication and end use.

The countries covered in the global artificial intelligence (AI) in drug discovery market report are U.S., Canada, Mexico, Germany, France, U.K., Italy, Spain, Russia, Turkey, Belgium, Netherlands, Switzerland, rest of Europe, China, Japan, India, South Korea, Singapore, Thailand, Malaysia, Australia and New Zealand, Philippines, Indonesia, rest of Asia-Pacific, U.A.E, Israel, South Africa, Saudi Arabia, Egypt, Rest of Middle East and Africa, Brazil, Argentina and Rest of South America.

North America is expected to dominate the AI in drug discovery market, attributed to a surge in research and development investments and widespread adoption of AI technology in medicine development. The region's dominance is further fueled by the robust presence of key AI technology providers, including IBM, Google, Microsoft, among others. Their influence and technological contributions contribute significantly to the anticipated growth of the market in North America.

The Asia-Pacific is expected to witness rapid growth in the AI in drug discovery market. This surge is attributed to heightened investments in innovative research and development initiatives. Additionally, the ongoing development of healthcare infrastructure in the region is poised to accelerate the market's growth, reflecting the increasing prominence of Asia-Pacific in shaping the landscape of AI applications in drug discovery.

The country section of the report also provides individual market impacting factors and changes in regulation in the market domestically that impacts the current and future trends of the market. Data points such as down-stream and upstream value chain analysis, technical trends and porter's five forces analysis, case studies are some of the pointers used to forecast the market scenario for individual countries. Also, the presence and availability of global brands and their challenges faced due to large or scarce competition from local and domestic brands, impact of domestic tariffs and trade routes are considered while providing forecast analysis of the country data.

Healthcare Infrastructure Growth Installed base and New Technology Penetration

The global artificial intelligence (AI) in drug discovery market also provides you with detailed market analysis for every country growth in healthcare expenditure for capital equipment, installed base of different kind of products for global artificial intelligence (AI) in drug discovery market, impact of technology using life line curves and changes in healthcare regulatory scenarios and their impact on the global artificial intelligence (AI) in drug discovery market. The data is available for historic period 2016-2021.

Competitive Landscape and Global Artificial Intelligence (AI) in Drug Discovery Market Share Analysis

The global artificial intelligence (AI) in drug discovery market competitive landscape provides details by competitor. Details included are company overview, company financials, revenue generated, market potential, investment in R&D, new market initiatives, production sites and facilities, company strengths and weaknesses, product launch, product trials pipelines, product approvals, patents, product width and breath, application dominance, technology lifeline curve. The above data points provided are only related to the company’s focus on the global artificial intelligence (AI) in drug discovery market.   

Some of the major players operating in the global artificial intelligence (AI) in drug discovery market are:

• NVIDIA Corporation (U.S.)
• IBM (U.S.)
• Atomwise Inc. (U.S.)
• Microsoft (U.S.)
• Benevolent AI (U.K.)
• Aria Pharmaceuticals, Inc. (U.S.)
• DEEP GENOMICS (Canada)
• Exscientia (U.K.)
• Insilico Medicine (U.S.)
• Cyclica (Canada)
• NuMedii, Inc. (U.S.)
• Envisagenics (U.S.)
• Owkin Inc. (U.S.)
• BERG LLC (U.S.)
• Schrödinger, Inc. (U.S.)
• XtalPi Inc. (China)