Generative AI in Drug Discovery Market Size to Reach USD 1,637.9 Million in 2032

Demand for cost effective drug discovery is the key factor driving market revenue growth. AI in drug discovery comprises creating new content, such as molecules, compounds, or medication candidates, based by predefined criteria. One of the obstacles of traditional drug discovery is the scarcity of high-quality data. Generative AI in medicine solves this issue by learning from current data while also producing new data points. This synthetic data can then be utilized to train algorithms and improve accuracy, resulting in better drug discovery outcomes.

Traditional drug discovery, prior to the incorporation of modern AI techniques, was costly due to extensive study, several lab testing, failed attempts, and other factors. However, since Gen AI joined the pharmaceutical sector, it has enabled researchers to evaluate molecular data and identify probable reactions by entering prompts. It has lowered the company's expenditure on physical continuous test processes for drug development.

In March 2024, NVIDIA announced the release of more than two dozen new microservices, allowing healthcare companies globally to benefit from the most recent developments in generative AI from any location and cloud. The new NVIDIA healthcare microservices package combines optimized NVIDIA NIM AI models and workflows with industry-standard APIs (application programming interfaces) that serve as building blocks for developing and deploying cloud-native applications.

However, there are certain hurdles to overcome. One significant challenge is the necessity for high-quality, diversified, and properly labeled data while training AI models. Ensuring data privacy and security is also an important consideration, especially when working with sensitive patient information. Furthermore, the interpretability and explainability of AI models remain critical challenges, as researchers must understand how these models make predictions and ensure they do not perpetuate biases.

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Segments market overview and growth Insights:
Based on the technology Generative AI in drug discovery market is segmented into Deep learning, Machine learning, Molecular docking, Quantum computing, and Reinforcement learning. Quantum computing segment is expected to register a fast revenue growth during the forecast period. Quantum computing offers enormous potential in personalized medicine. When there is insufficient clinical trial data, researchers are typically unable to reach conclusions.
On January 2025, Quantum Computing Inc., a pioneering company specializing in integrated photonics and quantum optics technology, has announced a partnership with Sanders Tri-Institutional Therapeutics Discovery Institute, Inc. (Sanders TDI) to advance research in computational biomedicine. As part of this collaboration, QCi will grant Sanders TDI access to its quantum computing technology and hardware, including the Dirac-3 Entropy Quantum Computing Machine, to aid the Institute's experimental efforts.

Regional market overview and growth insights:
North America held the largest market 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 June 2024, Eli Lilly and Company have announced a relationship with OpenAI, which will allow Lilly to use OpenAI's generative AI to develop innovative antimicrobials for drug-resistant diseases. Antimicrobial resistance (AMR) is a major danger to public health and development worldwide. This engagement with OpenAI complements Lilly's previous commitment to combating drug-resistant diseases through its Social Impact Venture Capital Portfolio.

Competitive Landscape and Key Competitors
The Generative AI in drug discovery market is characterized by a fragmented structure, with many competitors holding a significant share of the market. List of major players included in the Generative AI in drug discovery market report are:

o BioSymetrics
o Merck KGaA
o NVIDIA Corporation
o BenevolentAI
o Insilico Medicine
o Atomwise Inc.
o XtalPi Inc
o Cyclica Inc
o Variational AI Inc.
o Numerate Inc
o Absci Corp.
o BioStrand BV
o Innodata Inc.
o Recursion Pharmaceuticals, Inc

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Major strategic developments by leading competitors:

InveniAI LLC: On 13 January 2025, InveniAI LLC, a global leader in the use of artificial intelligence (AI), machine learning (ML), and generative AI tools to revolutionize drug discovery and development, today announced several transformative milestones as part of its ongoing commitment to revolutionizing the drug development process. To mark this next chapter of innovation, the company has established a wholly owned subsidiary, AlphaMeld Corporation, whose name reflects its mission of combining advanced artificial intelligence (AI), machine learning (ML), and generative AI with domain expertise to identify "alpha signals" of innovation for the development of impactful therapeutic solutions.

Absci Corporation: On 10 January 2025, Absci Corporation, a data-first generative AI drug creation company, and Owkin, a TechBio that uses agentic AI to unlock complex targets for drug discovery, development, and diagnostics, announced a collaboration that will bring together two leading AI platforms to rapidly discover and design novel therapies for patients. Absci and Owkin will collaborate to develop pharmaceutical candidates addressing novel targets in immuno-oncology and other diseases, including immunology and inflammation.

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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)
o North America
U.S.
Canada
Mexico
o Europe
Germany
France
U.K.
Italy
Spain
Benelux
Nordic Countries
Rest of Europe
o Asia Pacific
China
India
Japan
South Korea
Oceania
ASEAN Countries
Rest of APAC
o Latin America
Brazil
Rest of LATAM
o Middle East & Africa
GCC Countries
South Africa
Israel
Turkey
Rest of MEA

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