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| Data Timeline | Historical Data: 2022โ2025 | Base Year: 2025 | Forecast Period: 2026โ2034 |
|---|---|
| Offering Segment | Software, Services |
| By Deployment Mode Segment | Cloud, On-Premise, Hybrid |
| Process Segment | Target Identification & Selection, Target Validation, Hit Identification & Prioritization, Hit-to-Lead Identification /Lead Generation, Lead Optimization, , Candidate Selection & Validation |
|---|---|
| Drug Design Segment | Understanding Diseases, Small Molecule Design and Optimization, Vaccine Design and Optimization, Antibody & Other Biologics Design and Optimization, Safety and Toxicity |
| End-User Segment | Pharmaceuticals & Biotechnology Companies, , Contract Research Organizations, Research Centers, Academic & Government Institutes |
| Technology Segment | Machine Learning, Natural Language Processing, Context-Aware Processing, Other Technologies |
| By Tool Segment | CNN, GAN |
| By Organization Size Segment | SMEs, Large Enterprises |
| By Pricing Model Segment | Subscription (SaaS), License-based, Freemium |
| Regions & Countries |
|
Using AI in creating personalized medicine provides opportunity for players to establish themselves in the market
Availability of suitable data for AI algorithms restraining the market
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| Region / Country | 2021 (A) | 2025 (A) | 2033 (P) | CAGR |
|---|
A = Actual ยท E = Estimated ยท P = Projected ยท ๐ Locked values require full access. Click headers to sort.
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The AI in the drug discovery market is shaped by a dynamic set of players, each leveraging unique strengths to gain competitive advantage. NVIDIA Corporation stands out for its foundational role in supplying GPU hardware and AI computing platforms that power drug discovery pipelines across the ecosystem. In contrast, Exscientia differentiates itself through a deep focus on AI-driven precision drug design and has already delivered multiple AI-designed compounds into clinical trials, setting benchmarks in speed and efficiency. Google, through its DeepMind spin-off Isomorphic Labs, is applying its mastery of protein structure prediction (via AlphaFold) to reimagine drug development from a structural biology lens. Meanwhile, Insilico Medicine combines AI with a strong biomedical knowledge base, focusing on aging-related diseases and end-to-end drug development platforms. Recursion, distinctively, emphasizes high-throughput biological imaging and phenomics to create one of the largest proprietary datasets in the industry, enabling rich, data-driven drug discovery. This diversity reflects the evolving and specialized nature of AI integration in pharma.
References:https://www.nvidia.com/en-gb/industries/healthcare-life-sciences/drug-discovery/
https://www.exscientia.com/pipeline/
https://www.recursion.com/scientificmaterials
https://www.isomorphiclabs.com/articles/rational-drug-design-with-alphafold-3
https://insilico.com/blog/first_phase2
| Company | 2022 (A) | 2023 (A) | 2024 (A) | 2025 (A) |
|---|---|---|---|---|
| NVIDIA Corporation (US) | โขโขโข | โขโขโข | โขโขโข | โขโขโข |
| Exscientia (UK) | โขโขโข | โขโขโข | โขโขโข | โขโขโข |
| BenevolentAI (UK) | โขโขโข | โขโขโข | โขโขโข | โขโขโข |
| Recursion (US) | โขโขโข | โขโขโข | โขโขโข | โขโขโข |
| Insilico Medicine (US) | โขโขโข | โขโขโข | โขโขโข | โขโขโข |
| Schrรถdinger Inc. (US) | โขโขโข | โขโขโข | โขโขโข | โขโขโข |
| Microsoft Corporation (US) | โขโขโข | โขโขโข | โขโขโข | โขโขโข |
| Google (US) | โขโขโข | โขโขโข | โขโขโข | โขโขโข |
| Atomwise Inc. (US) | โขโขโข | โขโขโข | โขโขโข | โขโขโข |
| Celsius Therapeutics (US) | โขโขโข | โขโขโข | โขโขโข | โขโขโข |
| CytoReason (Israel) | โขโขโข | โขโขโข | โขโขโข | โขโขโข |
| Cloud Pharmaceuticals (US) | โขโขโข | โขโขโข | โขโขโข | โขโขโข |
| Evaxion Biotech (Denmark) | โขโขโข | โขโขโข | โขโขโข | โขโขโข |
| Standigm (South Korea) | โขโขโข | โขโขโข | โขโขโข | โขโขโข |
| Aria Pharmaceuticals Inc. (US) | โขโขโข | โขโขโข | โขโขโข | โขโขโข |
Revenue data requires full access. *2nd & 3rd tier companies available on enquiry.
Request company profile for validation โAccording to Cognitive Market Research, the global Artificial Intelligence / AI in Drug Discovery market size is USD 0.6 billion in 2024 and will expand at a compound annual growth rate (CAGR) of 40.00% from 2024 to 2031.
The Artificial intelligence (AI) in drug discovery employs sophisticated computational algorithms and machine learning models to analyze biological data, anticipate potential drug candidates, and hasten the drug development process. AI facilitates uncovering novel drug targets, refining molecular structures, and scrutinizing extensive datasets, thereby empowering researchers to uncover innovative and enhanced therapeutic options. One of the key drivers propelling the growth of the Artificial Intelligence / AI in Drug Discovery market is the widespread adoption of digital health solutions. These technologies offer remote patient monitoring, telemedicine services, and personalized healthcare delivery, improving patient outcomes and reducing costs. Integration of artificial intelligence (AI) and machine learning enhances data analytics, enabling healthcare providers to make informed decisions.
Our study will explain complete manufacturing process along with major raw materials required to manufacture end-product. This report helps to make effective decisions determining product position and will assist you to understand opportunities and threats around the globe.
The Global Artificial Intelligence Ai In Drug Discovery Market Analysis is witnessing significant growth in the near future.
In 2023, the Software segment accounted for a notable share of the Global Artificial Intelligence Ai In Drug Discovery Market Analysis.
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| Offering | Software, Services |
| By Deployment Mode | Cloud, On-Premise, Hybrid |
| Process | Target Identification & Selection, Target Validation, Hit Identification & Prioritization, Hit-to-Lead Identification /Lead Generation, Lead Optimization, , Candidate Selection & Validation |
| Drug Design | Understanding Diseases, Small Molecule Design and Optimization, Vaccine Design and Optimization, Antibody & Other Biologics Design and Optimization, Safety and Toxicity |
| End-User | Pharmaceuticals & Biotechnology Companies, , Contract Research Organizations, Research Centers, Academic & Government Institutes |
| Technology | Machine Learning, Natural Language Processing, Context-Aware Processing, Other Technologies |
| By Tool | CNN, GAN |
| By Organization Size | SMEs, Large Enterprises |
| By Pricing Model | Subscription (SaaS), License-based, Freemium |
| List of Competitors | NVIDIA Corporation (US), Exscientia (UK), BenevolentAI (UK), Recursion (US), Insilico Medicine (US), Schrรถdinger Inc. (US), Microsoft Corporation (US), Google (US), Atomwise Inc. (US), Celsius Therapeutics (US), CytoReason (Israel), Cloud Pharmaceuticals (US), Evaxion Biotech (Denmark), Standigm (South Korea), Aria Pharmaceuticals Inc. (US) |
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