AI-based Drug Discovery Market is expected to develop at a compound annual growth rate (CAGR) of 22.1% from 2023 to 2030

• The AI-based drug discovery market was valued at 1.8 billion USD globally in 2023, and a compound annual growth rate (CAGR) of 22.1% is anticipated throughout the course of the forecast period.
• The market is expanding due to rising interest in AI-driven technologies, the demand for novel treatments to treat chronic illnesses, and the expansion of healthcare data availability. The industry is expanding as a result of increased financing investments from government organizations and pharmaceutical corporations. Conventional drug development procedures are costly and time-consuming; they frequently cost billions of dollars and take ten to fifteen years.
• AI speeds up these procedures by finding possible medication candidates and improving lead compounds, which lowers expenses. Target identification, medication repurposing, and chemical interactions may all be accurately predicted with AI models like deep learning and neural networks. AI is being heavily invested in by biotechnology and pharmaceutical industries to improve their R&D pipelines.

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Growth Drivers

• AI is being heavily invested in by startups and major industrial organizations to improve their R&D pipelines. AI use to evaluate large datasets for targeted drug discovery has been fuelled by the growth of precision medicine programs and the demand for individualized medicines based on genetic, environmental, and lifestyle factors. A strong basis for AI algorithm training is provided by the availability of massive data from clinical trials, genomic databases, and electronic health records.
• The pandemic demonstrated the usefulness of AI in emergency settings by highlighting its potential for quick medication discovery and vaccine development. Companies are compelled to optimize their resources due to pricing pressures and patent expirations.
• AI lowers trial-and-error procedures, resulting in cost-effective solutions. increased emphasis on oncology indications, the need to manage drug discovery and development costs and shorten the overall time spent in this process, and the growing number of cross-industry collaborations and partnerships.

Segmentation

By Offering

·?????????Software

·?????????Services

By Technology

·?????????Machine Learning

·?????????Deep Learning

·?????????Natural Language Processing

·?????????Computer Vision

By Application

·?????????Drug Discovery

·?????????Preclinical Testing

·?????????Clinical Trail Design and Optimization

·?????????Drug Repurposing

·?????????Other Application

By Drug Type

·?????????Small Molecules

·?????????Biologics

By Deployment Mode

·?????????On-Premise

·?????????Cloud-Based

By End-User

·?????????Pharmaceutical and Biotechnology Company

·?????????Academic and Research Institutes

·?????????Contract Research Organizations

Regional Outlook

·?????????Asia Pacific

·?????????North America

·?????????Latin America

·?????????Middle East and Africa

·?????????Europe

Key Players

·?????????Microsoft

·?????????Recursion

·?????????Google

·?????????Nivida Corporation

·?????????Tempus

·?????????Owkin, Inc.

·?????????Valo Health

·?????????DEEP Genomics

·?????????Merck KGaA

·?????????Iktos

·?????????Tempus

·?????????Schrodinger, Inc.

·?????????Atomwise Inc.

·?????????Xtalpi Inc.

·?????????Other Players

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