查看购物车
  • Traditional Chinese
  • English
  • Japanese
封面
市场调查报告书
商品编码
1836386

2032 年人工智慧药物研发平台市场预测：按组件、治疗领域、药物类型、部署模式、最终用户和地区进行的全球分析

AI-Powered Drug Discovery Platforms Market Forecasts to 2032 - Global Analysis By Component (Solutions and Services), Therapeutic Area, Drug Type, Deployment Model, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的数据，全球 AI 药物研发平台市场规模预计在 2025 年达到 24.629 亿美元，到 2032 年将达到 157.059 亿美元，预测期内的复合年增长率为 30.3%。

AI药物研发平台是先进的运算系统，利用人工智慧加速和优化新药化合物的识别、设计和测试流程。这些平台分析海量生物医学资料集，包括基因组学、蛋白质组学和临床记录，以预测药物-标靶相互作用、评估毒性并模拟分子行为。将传统上耗时的任务自动化，可降低研发成本并缩短开发週期。机器学习演算法能够持续改进模型，提高准确性和成功率。 AI平台广泛应用于精准医疗、肿瘤学和罕见疾病研究，正在将药物研发转变为更快、数据主导、更有效率的过程。

缩短药物研发时间

加快药物开发进度是人工智慧药物发现平台的关键驱动力。这些系统简化了化合物筛检、标靶识别和毒性预测，显着缩短了临床前和临床阶段所需的时间。透过自动化数据分析和分子相互作用模拟，人工智慧能够加快决策速度并更早检验。这种效率对于製药公司至关重要，尤其是那些正在应对新兴疾病和竞争压力的公司，因为他们力求更快地将治疗方法推向市场。

数据品质和整合问题

数据品质和整合问题是人工智慧驱动的药物研发市场的主要限制因素。不一致、不完整或孤立的生物医学数据会降低模型的准确性和可靠性。整合基因组学、蛋白质组学和临床记录等多样化数据集需要先进的基础设施和标准化。如果没有清晰、可互通的数据，人工智慧演算法就难以产生有意义的洞察，从而限制了其有效性。应对这些挑战对于充分发挥人工智慧在药物研发领域的潜力至关重要。

製药业研发成本上升

製药业不断上涨的研发成本为人工智慧药物研发平台带来了巨大的机会。传统的药物研发成本高且耗时，通常需要数十亿美元的投资。人工智慧透过自动化早期研究、改进候选化合物的选择以及最大限度地减少试验失败来降低成本。随着企业寻求经济高效的解决方案以保持创新和盈利，人工智慧平台提供了一种可扩展的数据主导方法，可以简化整个药物研发生命週期的运作并提高生产力。

初期投资高

高昂的初始投资是人工智慧药物研发平台应用面临的一大挑战。建构强大的人工智慧基础设施需要大量资金用于数据采集、运算资源和技术人员。规模较小的公司可能无法承担此类技术，从而限制了其市场渗透。此外，漫长的开发週期和不明确的投资报酬率也阻碍了相关人员的参与。缺乏财务奖励或合作模式，领先成本障碍可能会减缓从传统方法转向人工智慧主导的药物研发的转变。

COVID-19的影响：

新冠疫情凸显了快速药物开发的迫切性，并加速了人们对人工智慧平台的兴趣。这些系统透过分析大量资料集并预测分子交互作用，支持了疫苗和治疗方法的研究。然而，供应链中断和资源重新分配暂时减缓了采用速度。疫情过后，该产业将数位转型和韧性放在了优先位置，而人工智慧在未来的应对中发挥核心作用。最终，这场疫情强化了人工智慧在实现更快、数据主导的医药创新方面的价值。

预计肿瘤学将成为预测期内最大的领域

由于癌症研究的复杂性和紧迫性，预计肿瘤学将在预测期内占据最大的市场份额。人工智慧平台有助于识别新标靶、预测药物反应并根据基因图谱制定个人化治疗方案。随着癌症发病率的上升和精准医疗需求的不断增长，製药公司正在大力投资人工智慧工具，以加速抗癌药物的研发。这些平台正在增强临床试验设计和生物标记发现，使肿瘤学成为最大、影响力最大的应用领域。

预计生技公司板块在预测期内将以最高的复合年增长率成长

生技公司预计将在预测期内实现最高成长率，因为这些敏捷、创新主导的公司正在迅速采用人工智慧来增强其药物发现管道并降低开发成本。凭藉最尖端科技和专业数据集，生物技术公司正在利用人工智慧进行靶点识别、分子设计和预测建模。它们的灵活性以及对利基疗法的专注是人工智慧药物发现市场成长的关键驱动力。

占比最大的地区：

在预测期内，由于製药业的扩张、人工智慧投资的增加以及政府的支持政策，预计亚太地区将占据最大的市场份额。中国、印度和日本等国家正在推动其数位医疗基础设施建设，并促进高科技和生物技术领域之间的合作。该地区庞大的患者群体和丰富的生物医学数据资源将进一步增强人工智慧模型的训练和部署。这些因素共同使亚太地区成为全球市场的主导力量。

复合年增长率最高的地区：

在预测期内，北美预计将凭藉其强大的研发能力、先进的人工智慧基础设施以及科技巨头与製药公司之间的战略伙伴关係，实现最高的复合年增长率。美国在人工智慧创新和监管支援方面处于领先地位，这促进了其在医疗保健和生物技术领域的快速应用。精准医疗需求的不断增长以及对人工智慧新兴企业的强劲投资正在推动这一成长。北美在数位转型和药物开发方面的领先地位，使其成为该市场成长最快的地区。

免费客製化服务

此报告的订阅者可以使用以下免费自订选项之一：

  • 公司简介
    • 对最多三家其他市场公司进行全面分析
    • 主要企业的SWOT分析（最多3家公司）
  • 区域细分
    • 根据客户兴趣对主要国家进行的市场估计、预测和复合年增长率（註：基于可行性检查）
  • 竞争基准化分析
    • 根据产品系列、地理分布和策略联盟对主要企业进行基准化分析

目录

第一章执行摘要

第二章 前言

  • 概述
  • 相关利益者
  • 调查范围
  • 调查方法
    • 资料探勘
    • 数据分析
    • 数据检验
    • 研究途径
  • 研究材料
    • 主要研究资料
    • 次级研究资讯来源
    • 先决条件

第三章市场走势分析

  • 驱动程式
  • 抑制因素
  • 机会
  • 威胁
  • 最终用户分析
  • 新兴市场
  • COVID-19的影响

第四章 波特五力分析

  • 供应商的议价能力
  • 买方的议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争对手之间的竞争

5. 全球人工智慧药物研发平台市场（按组件）

  • 软体
  • 服务

6. 全球人工智慧药物发现平台市场（按治疗领域）

  • 肿瘤学
  • 神经病学
  • 心血管疾病
  • 感染疾病
  • 免疫学和炎症
  • 代谢紊乱
  • 罕见疾病
  • 其他的

7. 全球人工智慧药物发现平台市场（按药物类型）

  • 小分子
  • 生物製药
    • 单株抗体
    • 胜肽和蛋白质
    • 基于RNA的疗法
  • 细胞和基因治疗候选药物

第八章全球人工智慧药物发现平台市场（按部署模式）

  • 云端基础的平台
  • 本地解决方案
  • 混合模式

第九章全球人工智慧药物发现平台市场（按最终用户）

  • 製药公司
  • 生技公司
  • 合约开发组织（CRO）
  • 学术研究机构
  • 医疗保健提供者

第 10 章全球 AI 药物发现平台市场（按地区）

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲国家
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 其他亚太地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十一章 重大进展

  • 协议、伙伴关係、合作和合资企业
  • 收购与合併
  • 新产品发布
  • 业务扩展
  • 其他关键策略

第 12 章：公司概况

  • Atomwise
  • BenevolentAI
  • Insilico Medicine
  • Recursion Pharmaceuticals
  • Schrodinger
  • Exscientia
  • Healx
  • Cyclica
  • LabGenius
  • Numerate
  • Owkin
  • Relay Therapeutics
  • Generate Biomedicines
  • Cloud Pharmaceuticals
  • NVIDIA Corporation
Product Code: SMRC31510

According to Stratistics MRC, the Global AI-Powered Drug Discovery Platforms Market is accounted for $2,462.9 million in 2025 and is expected to reach $15,705.9 million by 2032 growing at a CAGR of 30.3% during the forecast period. AI-powered drug discovery platforms are advanced computational systems that leverage artificial intelligence to accelerate and optimize the process of identifying, designing, and testing new pharmaceutical compounds. These platforms analyze vast biomedical datasets-including genomics, proteomics, and clinical records-to predict drug-target interactions, assess toxicity, and simulate molecular behavior. By automating traditionally time-consuming tasks, they reduce R&D costs and shorten development timelines. Machine learning algorithms enable continuous refinement of models, improving accuracy and success rates. Widely used in precision medicine, oncology, and rare disease research, AI-powered platforms are transforming drug discovery into a faster, data-driven, and more efficient process.

Market Dynamics:

Driver:

Accelerated Drug Development Timelines

Accelerated drug development timelines are a key driver for AI-powered drug discovery platforms. These systems streamline compound screening, target identification, and toxicity prediction, significantly reducing the time required for preclinical and clinical phases. By automating data analysis and simulating molecular interactions, AI enables faster decision-making and early-stage validation. This efficiency is crucial for pharmaceutical companies aiming to bring therapies to market quickly, especially in response to emerging diseases and competitive pressures.

Restraint:

Data Quality and Integration Issues

Data quality and integration issues pose a major restraint to the AI-powered drug discovery market. Inconsistent, incomplete, or siloed biomedical data can impair model accuracy and reliability. Integrating diverse datasets-such as genomics, proteomics, and clinical records-requires advanced infrastructure and standardization. Without clean, interoperable data, AI algorithms struggle to generate meaningful insights, limiting their effectiveness. Addressing these challenges is essential to unlock the full potential of AI in pharmaceutical research and development.

Opportunity:

Rising R&D Costs in Pharma

Rising R&D costs in the pharmaceutical industry present a significant opportunity for AI-powered drug discovery platforms. Traditional drug development is expensive and time-consuming, often requiring billions in investment. AI reduces costs by automating early-stage research, improving candidate selection, and minimizing trial failures. As companies seek cost-effective solutions to maintain innovation and profitability, AI platforms offer a scalable, data-driven approach to streamline operations and enhance productivity across the drug development lifecycle.

Threat:

High Initial Investment

High initial investment is a notable threat to the adoption of AI-powered drug discovery platforms. Building robust AI infrastructure requires substantial funding for data acquisition, computing resources, and skilled personnel. Smaller firms may struggle to afford these technologies, limiting market penetration. Additionally, long development cycles and uncertain ROI can deter stakeholders. Without financial incentives or collaborative models, the upfront cost barrier may slow the transition from traditional methods to AI-driven drug discovery.

Covid-19 Impact:

The COVID-19 pandemic highlighted the urgency of rapid drug development, accelerating interest in AI-powered platforms. These systems supported vaccine and therapeutic research by analyzing vast datasets and predicting molecular interactions. However, supply chain disruptions and resource reallocation temporarily slowed adoption. Post-pandemic, the industry is prioritizing digital transformation and resilience, with AI playing a central role in future preparedness. The pandemic ultimately reinforced the value of AI in enabling faster, data-driven pharmaceutical innovation.

The oncology segment is expected to be the largest during the forecast period

The oncology segment is expected to account for the largest market share during the forecast period due to the complexity and urgency of cancer research. AI-powered platforms help identify novel targets, predict drug responses, and personalize treatments based on genetic profiles. With rising cancer incidence and demand for precision medicine, pharmaceutical companies are investing heavily in AI tools to accelerate oncology drug development. These platforms enhance clinical trial design and biomarker discovery, making oncology the largest and most impactful application area.

The biotechnology firms segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the biotechnology firms segment is predicted to witness the highest growth rate because these agile, innovation-driven companies are rapidly adopting AI to enhance drug discovery pipelines and reduce development costs. With access to cutting-edge technologies and specialized datasets, biotech firms leverage AI for target identification, molecule design, and predictive modeling. Their flexibility and focus on niche therapies position them as key drivers of growth in the AI-powered drug discovery market.

Region with largest share:

During the forecast period, the Asia Pacific region is expected to hold the largest market share owing to its expanding pharmaceutical industry, growing investments in AI, and supportive government initiatives. Countries like China, India, and Japan are advancing digital healthcare infrastructure and fostering collaborations between tech and biotech sectors. The region's large patient population and rich biomedical data resources further enhance AI model training and deployment. These factors collectively position Asia Pacific as a dominant force in the global market.

Region with highest CAGR:

Over the forecast period, the North America region is anticipated to exhibit the highest CAGR due to strong R&D capabilities, advanced AI infrastructure, and strategic partnerships between tech giants and pharmaceutical companies. The U.S. leads in AI innovation and regulatory support, fostering rapid adoption across healthcare and biotech sectors. Increasing demand for precision medicine, coupled with robust investment in AI startups, is fueling growth. North America's leadership in digital transformation and drug development makes it the fastest-growing region in this market.

Key players in the market

Some of the key players in AI-Powered Drug Discovery Platforms Market include Atomwise, BenevolentAI, Insilico Medicine, Recursion Pharmaceuticals, Schrodinger, Exscientia, Healx, Cyclica, LabGenius, Numerate, Owkin, Relay Therapeutics, Generate Biomedicines, Cloud Pharmaceuticals and NVIDIA Corporation.

Key Developments:

In September 2025, NVIDIA and Intel have joined forces to co-develop custom AI infrastructure and personal computing products. This strategic partnership aims to seamlessly integrate NVIDIA's accelerated computing capabilities with Intel's leading CPU technologies, utilizing NVIDIA's NVLink to deliver cutting-edge solutions across hyperscale, enterprise, and consumer markets.

In September 2025, OpenAI and NVIDIA have embarked on a strategic partnership to deploy at least 10 gigawatts of NVIDIA systems, marking a significant leap in AI infrastructure development. This collaboration aims to establish a robust foundation for training and operating next-generation AI models, propelling both companies toward the realization of superintelligence.

Components Covered:

  • Software
  • Services

Therapeutic Areas Covered:

  • Oncology
  • Neurology
  • Cardiovascular Diseases
  • Infectious Diseases
  • Immunology & Inflammation
  • Metabolic Disorders
  • Rare & Orphan Diseases
  • Other Therapeutic Areas

Drug Types Covered:

  • Small Molecules
  • Biologics
  • Cell & Gene Therapy Candidates

Deployment Models Covered:

  • Cloud-Based Platforms
  • On-Premises Solutions
  • Hybrid Models

End Users Covered:

  • Pharmaceutical Companies
  • Biotechnology Firms
  • Contract Research Organizations (CROs)
  • Academic & Research Institutes
  • Healthcare Providers

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2022, 2023, 2024, 2026, and 2030
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 End User Analysis
  • 3.7 Emerging Markets
  • 3.8 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global AI-Powered Drug Discovery Platforms Market, By Component

  • 5.1 Introduction
  • 5.2 Software
  • 5.3 Services

6 Global AI-Powered Drug Discovery Platforms Market, By Therapeutic Area

  • 6.1 Introduction
  • 6.2 Oncology
  • 6.3 Neurology
  • 6.4 Cardiovascular Diseases
  • 6.5 Infectious Diseases
  • 6.6 Immunology & Inflammation
  • 6.7 Metabolic Disorders
  • 6.8 Rare & Orphan Diseases
  • 6.9 Other Therapeutic Areas

7 Global AI-Powered Drug Discovery Platforms Market, By Drug Type

  • 7.1 Introduction
  • 7.2 Small Molecules
  • 7.3 Biologics
    • 7.3.1 Monoclonal Antibodies
    • 7.3.2 Peptides & Proteins
    • 7.3.3 RNA-based Therapeutics
  • 7.4 Cell & Gene Therapy Candidates

8 Global AI-Powered Drug Discovery Platforms Market, By Deployment Model

  • 8.1 Introduction
  • 8.2 Cloud-Based Platforms
  • 8.3 On-Premises Solutions
  • 8.4 Hybrid Models

9 Global AI-Powered Drug Discovery Platforms Market, By End User

  • 9.1 Introduction
  • 9.2 Pharmaceutical Companies
  • 9.3 Biotechnology Firms
  • 9.4 Contract Research Organizations (CROs)
  • 9.5 Academic & Research Institutes
  • 9.6 Healthcare Providers

10 Global AI-Powered Drug Discovery Platforms Market, By Geography

  • 10.1 Introduction
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
    • 10.2.3 Mexico
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 Italy
    • 10.3.4 France
    • 10.3.5 Spain
    • 10.3.6 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 Japan
    • 10.4.2 China
    • 10.4.3 India
    • 10.4.4 Australia
    • 10.4.5 New Zealand
    • 10.4.6 South Korea
    • 10.4.7 Rest of Asia Pacific
  • 10.5 South America
    • 10.5.1 Argentina
    • 10.5.2 Brazil
    • 10.5.3 Chile
    • 10.5.4 Rest of South America
  • 10.6 Middle East & Africa
    • 10.6.1 Saudi Arabia
    • 10.6.2 UAE
    • 10.6.3 Qatar
    • 10.6.4 South Africa
    • 10.6.5 Rest of Middle East & Africa

11 Key Developments

  • 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 11.2 Acquisitions & Mergers
  • 11.3 New Product Launch
  • 11.4 Expansions
  • 11.5 Other Key Strategies

12 Company Profiling

  • 12.1 Atomwise
  • 12.2 BenevolentAI
  • 12.3 Insilico Medicine
  • 12.4 Recursion Pharmaceuticals
  • 12.5 Schrodinger
  • 12.6 Exscientia
  • 12.7 Healx
  • 12.8 Cyclica
  • 12.9 LabGenius
  • 12.10 Numerate
  • 12.11 Owkin
  • 12.12 Relay Therapeutics
  • 12.13 Generate Biomedicines
  • 12.14 Cloud Pharmaceuticals
  • 12.15 NVIDIA Corporation

List of Tables

  • Table 1 Global AI-Powered Drug Discovery Platforms Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global AI-Powered Drug Discovery Platforms Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global AI-Powered Drug Discovery Platforms Market Outlook, By Software (2024-2032) ($MN)
  • Table 4 Global AI-Powered Drug Discovery Platforms Market Outlook, By Services (2024-2032) ($MN)
  • Table 5 Global AI-Powered Drug Discovery Platforms Market Outlook, By Therapeutic Area (2024-2032) ($MN)
  • Table 6 Global AI-Powered Drug Discovery Platforms Market Outlook, By Oncology (2024-2032) ($MN)
  • Table 7 Global AI-Powered Drug Discovery Platforms Market Outlook, By Neurology (2024-2032) ($MN)
  • Table 8 Global AI-Powered Drug Discovery Platforms Market Outlook, By Cardiovascular Diseases (2024-2032) ($MN)
  • Table 9 Global AI-Powered Drug Discovery Platforms Market Outlook, By Infectious Diseases (2024-2032) ($MN)
  • Table 10 Global AI-Powered Drug Discovery Platforms Market Outlook, By Immunology & Inflammation (2024-2032) ($MN)
  • Table 11 Global AI-Powered Drug Discovery Platforms Market Outlook, By Metabolic Disorders (2024-2032) ($MN)
  • Table 12 Global AI-Powered Drug Discovery Platforms Market Outlook, By Rare & Orphan Diseases (2024-2032) ($MN)
  • Table 13 Global AI-Powered Drug Discovery Platforms Market Outlook, By Other Therapeutic Areas (2024-2032) ($MN)
  • Table 14 Global AI-Powered Drug Discovery Platforms Market Outlook, By Drug Type (2024-2032) ($MN)
  • Table 15 Global AI-Powered Drug Discovery Platforms Market Outlook, By Small Molecules (2024-2032) ($MN)
  • Table 16 Global AI-Powered Drug Discovery Platforms Market Outlook, By Biologics (2024-2032) ($MN)
  • Table 17 Global AI-Powered Drug Discovery Platforms Market Outlook, By Monoclonal Antibodies (2024-2032) ($MN)
  • Table 18 Global AI-Powered Drug Discovery Platforms Market Outlook, By Peptides & Proteins (2024-2032) ($MN)
  • Table 19 Global AI-Powered Drug Discovery Platforms Market Outlook, By RNA-based Therapeutics (2024-2032) ($MN)
  • Table 20 Global AI-Powered Drug Discovery Platforms Market Outlook, By Cell & Gene Therapy Candidates (2024-2032) ($MN)
  • Table 21 Global AI-Powered Drug Discovery Platforms Market Outlook, By Deployment Model (2024-2032) ($MN)
  • Table 22 Global AI-Powered Drug Discovery Platforms Market Outlook, By Cloud-Based Platforms (2024-2032) ($MN)
  • Table 23 Global AI-Powered Drug Discovery Platforms Market Outlook, By On-Premises Solutions (2024-2032) ($MN)
  • Table 24 Global AI-Powered Drug Discovery Platforms Market Outlook, By Hybrid Models (2024-2032) ($MN)
  • Table 25 Global AI-Powered Drug Discovery Platforms Market Outlook, By End User (2024-2032) ($MN)
  • Table 26 Global AI-Powered Drug Discovery Platforms Market Outlook, By Pharmaceutical Companies (2024-2032) ($MN)
  • Table 27 Global AI-Powered Drug Discovery Platforms Market Outlook, By Biotechnology Firms (2024-2032) ($MN)
  • Table 28 Global AI-Powered Drug Discovery Platforms Market Outlook, By Contract Research Organizations (CROs) (2024-2032) ($MN)
  • Table 29 Global AI-Powered Drug Discovery Platforms Market Outlook, By Academic & Research Institutes (2024-2032) ($MN)
  • Table 30 Global AI-Powered Drug Discovery Platforms Market Outlook, By Healthcare Providers (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.