Generative AI in Drug Discovery Market Size to Reach USD 1,637.9 Million in 2032
The Generative AI in Drug Discovery Market size was USD 216.7 Million in 2024 and is expected to register a revenue CAGR of 28.7% during the forecast period
January 07, 2024 – The global Generative AI in Drug Discovery market size reached USD 216.7 Million in 2024 and is expected to register a revenue CAGR of 28.7% during the forecast period. Technological advancement of computational power is a key factor driving market revenue growth.
Generative AI enables pharmaceutical companies to improve efficiency, speed, and decision-making. They can utilize it to make several launches more productive by collecting data and learning from each one. Generative AI builds intelligence over time, preserving intellectual property and assisting to preserve knowledge while human intelligence is lost due to turnover. A speedier drug discovery process, for example, will help cure more diseases faster, freeing up resources that can then be directed to currently neglected areas. The ability to extract insights and patterns from massive amounts of health data will lead to more tailored treatments—and better patient outcomes. Gen AI tools could potentially improve patient care by minimizing variability in pharmaceutical manufacturing and distribution.
However, the revenue growth of generative AI in drug discovery market is hampered by validation and experimental confirmation. AI generated molecules often show promising results in silico but may fail during laboratory testing due to unforeseen biological complexities. Biological systems are highly intricate, and AI models may oversimplify certain variables, leading to predictions that are difficult to replicate experimentally. Lack of comprehensive datasets for benchmarking AI predictions against experimental results hinders robust validation.
Key Highlights:
- Quantum computing segment is expected to register the highest growth rate over the forecast period. Quantum computing has huge potential in customized medicine. Researchers are usually unable to draw conclusions when there is insufficient clinical trial data. Quantum machine learning has the potential to improve the interpretation of sparse clinical trial data, allowing researchers to extract useful insights that would otherwise be difficult to distinguish using classical computing. On February 2024, 1910 Genetics, the only biotechnology company using a multimodal AI platform driven by laboratory automation to advance small and large molecule drug discovery, announced a new five-year commercial agreement and go-to-market partnership with Microsoft. The goal of the partnership is to use next-generation, high-performance computing (HPC) and advanced artificial intelligence (AI) to reverse seven decades of declining pharmaceutical R&D productivity.
- Molecule design segment is expected to account for the largest revenue share over the forecast period. Advances in generative AI have had a significant impact on de novo drug design, which involves the development of novel drug-like compounds ab initio. The encoding and decoding procedures have been enhanced by innovations like DeepSMILES and SELFIES (Self-Referencing Embedded Strings), guaranteeing more validity and diversity of created molecules. These models are further enhanced by Reinforcement Learning (RL) techniques, such as Reinforcement Learning-Variational Autoencoder (RL-VAE), which optimize molecular attributes through iterative feedback processes.
- North America accounted for the largest revenue share in the generative AI in drug discovery market in 2024 driven by increase in prevalence of chronic disorders and technological advancements in the field of generative AI. On March 2024, Cadence Design Systems, Inc. announced the expansion of its multi-year cooperation with NVIDIA in EDA, system design and analysis, digital biology, and AI, with the introduction of two disruptive technologies to reimagine design through accelerated computing and generative AI. The Cadence Reality platform’s integration with NVIDIA Omniverse adds OpenUSD data interchange and physically based rendering to the digital twin solution, accelerating data center design and simulation operations by 30 times.
- Some major companies in the market report include BioSymetrics, Merck KGaA, NVIDIA Corporation, BenevolentAI, Insilico Medicine, Atomwise Inc., XtalPi Inc, Cyclica Inc, Variational AI Inc., Numerate Inc, Absci Corp., BioStrand BV, Innodata Inc., and Recursion Pharmaceuticals, Inc.
- On September 2024, XtalPi has announced the formal introduction of XFEP and XMolGen, two proprietary software applications aimed to speed and improve the efficiency of drug discovery. Upon introduction, XtalPi will provide commercial licenses with flexible terms for industry and academic scientists to use the software based on their research objectives. These platforms have user-friendly interfaces and are seamlessly integrated into a shared suite, allowing for streamlined drug discovery workflows. Scientists can use XMolGen’s generative and predictive AI modules to generate diverse compound libraries, which can then be assessed for potency using physics-based ligand binding affinity predictions with XFEP, paving the way for faster discovery of novel therapeutics by efficiently tapping into diverse, unexplored chemical space.
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Navistrat Analytics has segmented generative AI in drug discovery market based on technology, application, end-use, and region:
- Technology Outlook (Revenue, USD Million; 2022-2032)
- Deep learning
- Machine learning
- Molecular docking
- Quantum computing
- Reinforcement learning
- Application Outlook (Revenue, USD Million; 2022-2032)
- Molecule design
- Antibody design & development
- De novo drug design
- Precision drug discovery
- Toxicity Prediction
- Others
- End-Use Outlook (Revenue, USD Million; 2022-2032)
- Pharmaceutical & Biotechnology Companies
- Contract Research Organizations (CROs)
- Academic And Research Institutions
- Regional Outlook (Revenue, USD Million; 2022-2032)
- North America
- US.
- Canada
- Mexico
- Europe
- Germany
- France
- U.K.
- Italy
- Spain
- Benelux
- Nordic Countries
- Rest of Europe
- Asia Pacific
- China
- India
- Japan
- South Korea
- Oceania
- ASEAN Countries
- Rest of APAC
- Latin America
- Brazil
- Rest of LATAM
- Middle East & Africa
- GCC Countries
- South Africa
- Israel
- Turkey
- Rest of MEA
- North America