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药物发现市场中的人工智慧 - 2018-2028 年全球产业规模、份额、趋势、机会和预测，按组件类型、药物类型、按应用类型、治疗领域、地区和竞争细分

AI in Drug Discovery Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, 2018-2028 Segmented By Component Type, By Drug Type, By Application Type, By Therapeutic Area, By Region and Competition
出版日期: | 出版商: TechSci Research | 英文 183 Pages | 商品交期: 2-3个工作天内

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简介目录

2022 年，全球人工智慧药物发现市场价值为 7.5004 亿美元，预计在整个预测期内将出现大幅增长，预计复合年增长率 (CAGR) 为 10.18%，预计到 2028 年将达到 13.2765 亿美元。智慧（ AI）是电脑科学中的一门学科，专注于模拟智慧行为。它使电脑能够模拟人类和动物的思维和任务执行，同时从错误中学习。人工智慧主要采用旨在以最小错误高效完成任务的演算法。透过利用深度学习和机器学习演算法，人工智慧应用个人化知识来执行各种任务。人工智慧在药物发现中的应用具有巨大的意义，有助于疾病追踪、促进治疗方法的开发，甚至预测突变动物病毒的出现。人工智慧彻底改变了药物发现的研究和开发，在慢性病治疗方面取得了突破。

主要市场驱动因素

减少药物研究时间

市场概况
预测期 2024-2028
2022 年市场规模 75004万美元
2028 年市场规模 132765万美元
2023-2028 年复合年增长率 10.18%
成长最快的细分市场 肿瘤学
最大的市场 北美洲

加速药物发现过程的推动刺激了药物研究中对人工智慧（AI）的需求，从而推动了市场成长。传统方法通常需要数年时间来优化用于人类评估的化合物，而人工智慧驱动的新创公司可能在几天或几个月内完成相同的任务。医疗保健预算的增加和医疗保健基础设施的进步进一步促进了市场扩张。人工智慧与高效药物活性探索的整合也推动了药物开发领域的需求。人工智慧驱动的方法简化了药物发现阶段，最大限度地减少了成本和耗时的失败。人工智慧演算法能够快速分析化合物库、精确的候选物优先排序和准确的特性预测，最终加快有效的药物开发。

科技巨头与製药公司的合作

微软等科技巨头与诺华等製药公司之间的策略协议为人工智慧演算法融入製药领域铺平了道路。 Nvidia 与 Schrodinger 合作增强分子预测的预测能力等合作伙伴关係对药物发现市场中的人工智慧产生了重大影响。像 Exscientia 这样的新兴企业专注于基于人工智慧的方法，吸引了大量投资。 Recursion Pharmaceuticals 等公司正在开发工具，利用人工智慧加速识别潜在候选药物。此外，IBM、微软和谷歌等 IT 公司正在投资製药公司并与製药公司合作，以推动人工智慧在药物发现市场的进步。

慢性病增加

糖尿病、慢性阻塞性肺病、冠状动脉疾病、关节炎、气喘、肝炎和癌症等慢性疾病的盛行率在全球范围内激增。这是由于老年人口不断增长、生活方式不断变化和城市化。国际糖尿病联盟报告称，2021 年全球将有5.37 亿人受到糖尿病的影响。预计到2030 年，每年新增癌症病例约为6.43 亿。例如，中国的肺癌病例占亚太地区所有肺癌病例的50%以上。人工智慧正在透过患者资料整合改变个人化医疗，实现精准医疗保健并提高治疗效果。它彻底改变了疾病的诊断、监测和治疗，带来更有效、更有针对性的治疗介入。

技术进步

机器学习、深度学习、自然语言处理等人工智慧技术的进步，显着增强了人工智慧分析复杂生物资料的能力。这些进步使得基因组学、蛋白质组学和临床资料等不同资料源的整合成为可能，从而在药物发现中获得全面的见解和快速决策。生物资料（包括基因组序列、蛋白质结构和药物与标靶相互作用）的指数增长为人工智慧驱动的分析和建模提供了充足的机会。大规模资料集使人工智慧演算法能够识别模式、预测化合物特性并产生创新假设，从而在药物发现中做出明智的数据驱动决策。

主要市场挑战

数据品质和可用性

人工智慧很大程度上依赖高品质、多样化、全面的资料来进行模型开发。在药物发现中，资料隐私、智慧财产权和监管考虑是重大挑战。获得可靠、精心整理的资料集，尤其是代表不同患者群体和疾病类型的资料集，为人工智慧驱动的药物发现带来了障碍。解决人工智慧模型（尤其是深度学习模型）的不透明性所带来的透明度问题至关重要。监管机构、临床医生和患者寻求透明的决策，因此可解释性至关重要。验证人工智慧模型并确保合规性提出了挑战。人工智慧模型必须满足严格的标准并表现出强大的性能才能获得监管部门的批准。制定一个适应人工智慧在药物发现中独特考虑的监管框架对于广泛采用至关重要。

技术挑战

儘管人工智慧取得了重大进展，但资料品质仍然是使用人工智慧方法进行药物开发的重大障碍。解决与资料所有权和保密性相关的挑战势在必行。持续的努力旨在优化药物发现中的当前人工智慧技术。

主要市场趋势

研发扩张

研究和开发活动的增加，加上基于云端的服务的使用，推动了药物发现市场中人工智慧的成长。新兴经济体和生物技术的进步进一步加速了市场的发展。 COVID-19 大流行显着促进了人工智慧在药物开发中的使用，特别是在识别和筛选用于治疗 COVID-19 的现有药物方面。人工智慧在识别各种疾病的活性物质方面的有效性促进了其在大流行期间的增长。

个人化医疗和精准医疗

人工智慧对包括遗传和临床资讯在内的患者资料的整合有可能彻底改变个人化医疗。它可以预测个体对治疗的反应并优化治疗策略，从而实现更有效的疾病诊断、监测和治疗。

细分市场洞察

组件类型

就组件类型而言，服务预计将在 2022 年主导药物发现市场的人工智慧，并在 2028 年之前呈现出最高的复合年增长率。服务的成长是由其优势和最终用户的强劲需求推动的。软体也发挥着重要作用，新兴公司专注于深度学习解决方案和生成模型，促进创新分子设计。

治疗领域

由于人工智慧在发现癌症药物方面的采用以及製药公司和人工智慧提供者之间的合作，预计肿瘤学领域在预测期内将经历最高的复合年增长率。

区域洞察

北美洲

由于人工智慧的高采用率、先进的医疗基础设施以及人工智慧和药物发现方面积极的临床研究，北美将引领市场。值得注意的研究机构和关键进展进一步促进了该地区在人工智慧驱动的药物发现方面的主导地位。

目录

第 1 章：服务类型概述

第 2 章：研究方法

第 3 章：执行摘要

第 4 章：客户之声

第 5 章：全球人工智慧药物发现市场展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 依组件类型（软体和服务）
    • 依药物类型（小分子和大分子）
    • 按应用类型（临床前测试、药物优化和再利用、标靶识别、候选筛选等）
    • 依治疗领域（肿瘤、神经退化性疾病、心血管疾病、罕见疾病等）
    • 按地区
    • 按公司划分 (2022)
  • 市场地图

第 6 章：北美药物发现中的人工智慧市场展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 依组件类型
    • 依药物类型
    • 按应用类型
    • 按治疗领域
    • 按国家/地区
  • 北美：国家分析
    • 美国
    • 加拿大
    • 墨西哥

第 7 章：欧洲人工智慧在药物发现市场前景

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 依组件类型
    • 依药物类型
    • 按应用类型
    • 按治疗领域
  • 欧洲：国家分析
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙

第 8 章：亚太地区人工智慧在药物发现市场的展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 依组件类型
    • 依药物类型
    • 按应用类型
    • 按治疗领域
  • 亚太地区：国家分析
    • 中国
    • 印度
    • 日本
    • 韩国
    • 澳洲

第 9 章：南美洲人工智慧在药物发现市场前景

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 依组件类型
    • 依药物类型
    • 按应用类型
    • 按治疗领域
  • 南美洲：国家分析
    • 巴西
    • 阿根廷
    • 哥伦比亚

第 10 章：中东和非洲人工智慧在药物发现市场前景

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 依组件类型
    • 依药物类型
    • 按应用类型
    • 按治疗领域
  • MEA：国家分析
    • 南非 药物发现中的人工智慧
    • 沙乌地阿拉伯 人工智慧在药物发现的应用
    • 阿联酋人工智慧在药物发现的应用

第 11 章：市场动态

第 12 章：市场趋势与发展

第 13 章：药物发现市场中的全球人工智慧：SWOT 分析

第14章：竞争格局

  • 商业概览
  • 服务产品
  • 最近的发展
  • 主要人员
  • SWOT分析
    • GNS Healthcare
    • BioSymetrics
    • BPGbio, Inc.
    • Atomwise Inc.
    • Owkin Inc.
    • NVIDIA Corporation
    • IBM Corporation
    • Microsoft Corporation
    • Aria Pharmaceuticals, Inc.
    • Insilico Medicine Inc.

第 15 章：策略建议

第 16 章：关于我们与免责声明

简介目录
Product Code: 4622

The Global AI in Drug Discovery Market was valued at USD 750.04 Million in 2022 and is expected to experience substantial growth throughout the forecast period, projecting a Compound Annual Growth Rate (CAGR) of 10.18% and expected to reach USD 1327.65 Million through 2028. Artificial intelligence (AI), a discipline within computer science, is focused on emulating intelligent behavior. It empowers computers to simulate human and animal-like thinking and task execution, while learning from mistakes. AI predominantly employs algorithms designed for efficient task completion with minimal errors. By harnessing deep learning and machine learning algorithms, AI applies personalized knowledge to perform a wide array of tasks. The application of AI in drug discovery holds immense significance, contributing to disease tracking, facilitating the development of treatments, and even predicting the emergence of mutated animal viruses. AI has revolutionized research and development in drug discovery, leading to breakthroughs in treating chronic diseases.

Key Market Drivers

Reduced Time in Medication Research

Market Overview
Forecast Period2024-2028
Market Size 2022USD 750.04 Million
Market Size 2028USD 1327.65 Million
CAGR 2023-202810.18%
Fastest Growing SegmentOncology
Largest MarketNorth America

The drive to accelerate the drug discovery process has spurred demand for artificial intelligence (AI) in pharmaceutical research, consequently propelling market growth. Traditional methods often take years to optimize compounds for human evaluation, while AI-powered startups could potentially accomplish the same in a matter of days or months. Increased healthcare budgets and advancements in healthcare infrastructure further contribute to market expansion. The integration of AI for efficient drug activity exploration is also driving demand in the drug development sector. AI-driven approaches streamline drug discovery stages, minimizing costs and time-consuming failures. AI algorithms enable rapid analysis of compound libraries, precise candidate prioritization, and accurate property predictions, ultimately expediting effective drug development.

Collaboration between Tech Giants and Pharma

Strategic agreements between technology giants like Microsoft and pharmaceutical companies like Novartis have paved the way for AI algorithm integration into the pharmaceutical landscape. Partnerships such as Nvidia's collaboration with Schrodinger to enhance predictive capabilities in molecular forecasting have significantly influenced the AI in Drug Discovery Market. Emerging enterprises like Exscientia focus on AI-based methodologies, attracting substantial investments. Companies such as Recursion Pharmaceuticals are developing tools to accelerate the identification of potential drug candidates using AI. Moreover, IT firms like IBM, Microsoft, and Google are investing and partnering with pharmaceutical companies to propel the advancement of AI in Drug Discovery Market.

Rise in Chronic Diseases

The prevalence of chronic diseases like diabetes, COPD, coronary artery disease, arthritis, asthma, hepatitis, and cancer has surged globally. This is attributed to the growing geriatric population, evolving lifestyles, and urbanization. The International Diabetes Federation reports that diabetes affected 537 million individuals globally in 2021. Predictions estimate around 643 million new cancer cases annually by 2030. China, for instance, accounts for over 50% of all lung cancer cases in the Asia Pacific region. AI is transforming personalized medicine through patient data integration, enabling precision healthcare, and enhancing treatment outcomes. It revolutionizes disease diagnosis, monitoring, and treatment, leading to more effective and tailored therapeutic interventions.

Technological Advancements

Advancements in AI technologies such as machine learning, deep learning, and natural language processing have significantly enhanced AI's capabilities in analyzing complex biological data. These advancements enable the integration of diverse data sources, including genomics, proteomics, and clinical data, leading to comprehensive insights and rapid decision-making in drug discovery. The exponential growth of biological data, including genomic sequences, protein structures, and drug-target interactions, offers ample opportunities for AI-driven analysis and modeling. Large-scale datasets empower AI algorithms to identify patterns, predict compound properties, and generate innovative hypotheses, enabling informed and data-driven decisions in drug discovery.

Key Market Challenges

Data Quality and Availability

AI relies heavily on high-quality, diverse, and comprehensive data for model development. In drug discovery, data privacy, intellectual property, and regulatory considerations are significant challenges. Obtaining reliable, well-curated datasets, especially those representing diverse patient populations and disease types, poses obstacles for AI-driven drug discovery. Addressing transparency concerns due to the opacity of AI models, especially deep learning models, is crucial. Regulators, clinicians, and patients seek transparent decision-making, making interpretability essential. Validating AI models and ensuring regulatory compliance present challenges. AI models must meet stringent standards and demonstrate robust performance to gain regulatory approval. Developing a regulatory framework catering to AI's unique considerations in drug discovery is vital for widespread adoption.

Technical Challenges

Although AI has made significant progress, data quality remains a substantial obstacle in using AI methods for drug development. Addressing challenges related to data ownership and confidentiality is imperative. Ongoing efforts aim to optimize current AI technologies in drug discovery.

Key Market Trends

R&D Expansion

Increased research and development activities, coupled with the use of cloud-based services, fuel growth in the AI in Drug Discovery Market. Emerging economies and advancements in biotechnology further accelerate the market's development. The COVID-19 pandemic significantly boosted the use of AI in drug development, especially in identifying and screening existing drugs for COVID-19 treatment. AI's effectiveness in identifying active substances for various diseases contributed to its growth during the pandemic.

Personalized Medicine and Precision Healthcare

AI's integration of patient data, including genetic and clinical information, has the potential to revolutionize personalized medicine. It predicts individual responses to therapies and optimizes treatment strategies, leading to more effective disease diagnosis, monitoring, and treatment.

Segmental Insights

Component Types

In terms of component types, Services are expected to dominate the AI in Drug Discovery Market in 2022, exhibiting the highest CAGR until 2028. The growth of services is driven by their advantages and strong demand among end users. Software also plays a significant role, with emerging companies focusing on deep learning solutions and generative models, facilitating innovative molecule design.

Therapeutic Area

The oncology segment is projected to experience the highest CAGR during the forecast period due to AI's adoption in discovering cancer drugs and collaborations between pharmaceutical companies and AI providers.

Regional Insights

North America

North America is set to lead the market due to high AI adoption, advanced healthcare infrastructure, and active clinical research in AI and drug discovery. Noteworthy research institutions and key developments further contribute to the region's dominance in AI-driven drug discovery.

Key Market Players

  • GNS Healthcare
  • BioSymetrics
  • BPGbio, Inc.
  • Atomwise Inc.
  • Owkin Inc.
  • NVIDIA Corporation
  • IBM Corporation
  • Microsoft Corporation
  • Aria Pharmaceuticals, Inc.
  • Insilico Medicine Inc.

Report Scope:

In this report, the Global AI in Drug Discovery Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below.

AI in Drug Discovery Market, By Component Type:

  • Software
  • Services

AI in Drug Discovery Market, By Drug Type:

  • Small Molecule
  • Large Molecule

AI in Drug Discovery Market, By Application Type:

  • Preclinical Testing
  • Drug Optimization
  • Repurposing
  • Target Identification
  • Candidate Screening
  • Others

AI in Drug Discovery Market, By Therapeutic Area:

  • Oncology
  • Neurodegenerative Diseases
  • Cardiovascular Diseases
  • Rare Diseases
  • Others

AI in Drug Discovery Market, By Region:

  • North America
  • United States
  • Canada
  • Mexico
  • Europe
  • France
  • United Kingdom
  • Italy
  • Germany
  • Spain
  • Asia-Pacific
  • China
  • India
  • Japan
  • Australia
  • South Korea
  • South America
  • Brazil
  • Argentina
  • Colombia
  • Middle East & Africa
  • South Africa
  • Saudi Arabia
  • UAE
  • Kuwait
  • Turkey
  • Egypt

Competitive Landscape

  • Company Profiles: Detailed analysis of the major companies present in the Global AI in Drug Discovery Market.

Available Customizations:

  • Global AI in Drug Discovery market report with the given market data, Tech Sci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

  • Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Service Type Overview

2. Research Methodology

3. Executive Summary

4. Voice of Customer

5. Global AI in Drug Discovery Market Outlook

  • 5.1. Market Size & Forecast
    • 5.1.1. By Value
  • 5.2. Market Share & Forecast
    • 5.2.1. By Component Type (Software and Services)
    • 5.2.2. By Drug Type (Small Molecule and Large Molecule)
    • 5.2.3. By Application Type (Preclinical Testing, Drug Optimization, and Repurposing, Target Identification, Candidate Screening, and Others)
    • 5.2.4. By Therapeutic Area (Oncology, Neurodegenerative Diseases, Cardiovascular Diseases, Rare Diseases, and Others)
    • 5.2.5. By Region
    • 5.2.6. By Company (2022)
  • 5.3. Market Map

6. North America AI in Drug Discovery Market Outlook

  • 6.1. Market Size & Forecast
    • 6.1.1. By Value
  • 6.2. Market Share & Forecast
    • 6.2.1. By Component Type
    • 6.2.2. By Drug Type
    • 6.2.3. By Application Type
    • 6.2.4. By Therapeutic Area
    • 6.2.5. By Country
  • 6.3. North America: Country Analysis
    • 6.3.1. United States AI in Drug Discovery Market Outlook
      • 6.3.1.1. Market Size & Forecast
        • 6.3.1.1.1. By Value
      • 6.3.1.2. Market Share & Forecast
        • 6.3.1.2.1. By Component Type
        • 6.3.1.2.2. By Drug Type
        • 6.3.1.2.3. By Application Type
        • 6.3.1.2.4. By Therapeutic Area
    • 6.3.2. Canada AI in Drug Discovery Market Outlook
      • 6.3.2.1. Market Size & Forecast
        • 6.3.2.1.1. By Value
      • 6.3.2.2. Market Share & Forecast
        • 6.3.2.2.1. By Component Type
        • 6.3.2.2.2. By Drug Type
        • 6.3.2.2.3. By Application Type
        • 6.3.2.2.4. By Therapeutic Area
    • 6.3.3. Mexico AI in Drug Discovery Market Outlook
      • 6.3.3.1. Market Size & Forecast
        • 6.3.3.1.1. By Value
      • 6.3.3.2. Market Share & Forecast
        • 6.3.3.2.1. By Component Type
        • 6.3.3.2.2. By Drug Type
        • 6.3.3.2.3. By Application Type
        • 6.3.3.2.4. By Therapeutic Area

7. Europe AI in Drug Discovery Market Outlook

  • 7.1. Market Size & Forecast
    • 7.1.1. By Value
  • 7.2. Market Share & Forecast
    • 7.2.1. By Component Type
    • 7.2.2. By Drug Type
    • 7.2.3. By Application Type
    • 7.2.4. By Therapeutic Area
  • 7.3. Europe: Country Analysis
    • 7.3.1. Germany AI in Drug Discovery Market Outlook
      • 7.3.1.1. Market Size & Forecast
        • 7.3.1.1.1. By Value
      • 7.3.1.2. Market Share & Forecast
        • 7.3.1.2.1. By Component Type
        • 7.3.1.2.2. By Drug Type
        • 7.3.1.2.3. By Application Type
        • 7.3.1.2.4. By Therapeutic Area
    • 7.3.2. United Kingdom AI in Drug Discovery Market Outlook
      • 7.3.2.1. Market Size & Forecast
        • 7.3.2.1.1. By Value
      • 7.3.2.2. Market Share & Forecast
        • 7.3.2.2.1. By Component Type
        • 7.3.2.2.2. By Drug Type
        • 7.3.2.2.3. By Application Type
        • 7.3.2.2.4. By Therapeutic Area
    • 7.3.3. Italy AI in Drug Discovery Market Outlook
      • 7.3.3.1. Market Size & Forecast
        • 7.3.3.1.1. By Value
      • 7.3.3.2. Market Share & Forecasty
        • 7.3.3.2.1. By Component Type
        • 7.3.3.2.2. By Drug Type
        • 7.3.3.2.3. By Application Type
        • 7.3.3.2.4. By Therapeutic Area
    • 7.3.4. France AI in Drug Discovery Market Outlook
      • 7.3.4.1. Market Size & Forecast
        • 7.3.4.1.1. By Value
      • 7.3.4.2. Market Share & Forecast
        • 7.3.4.2.1. By Component Type
        • 7.3.4.2.2. By Drug Type
        • 7.3.4.2.3. By Application Type
        • 7.3.4.2.4. By Therapeutic Area
    • 7.3.5. Spain AI in Drug Discovery Market Outlook
      • 7.3.5.1. Market Size & Forecast
        • 7.3.5.1.1. By Value
      • 7.3.5.2. Market Share & Forecast
        • 7.3.5.2.1. By Component Type
        • 7.3.5.2.2. By Drug Type
        • 7.3.5.2.3. By Application Type
        • 7.3.5.2.4. By Therapeutic Area

8. Asia-Pacific AI in Drug Discovery Market Outlook

  • 8.1. Market Size & Forecast
    • 8.1.1. By Value
  • 8.2. Market Share & Forecast
    • 8.2.1. By Component Type
    • 8.2.2. By Drug Type
    • 8.2.3. By Application Type
    • 8.2.4. By Therapeutic Area
  • 8.3. Asia-Pacific: Country Analysis
    • 8.3.1. China AI in Drug Discovery Market Outlook
      • 8.3.1.1. Market Size & Forecast
        • 8.3.1.1.1. By Value
      • 8.3.1.2. Market Share & Forecast
        • 8.3.1.2.1. By Component Type
        • 8.3.1.2.2. By Drug Type
        • 8.3.1.2.3. By Application Type
        • 8.3.1.2.4. By Therapeutic Area
    • 8.3.2. India AI in Drug Discovery Market Outlook
      • 8.3.2.1. Market Size & Forecast
        • 8.3.2.1.1. By Value
      • 8.3.2.2. Market Share & Forecast
        • 8.3.2.2.1. By Component Type
        • 8.3.2.2.2. By Drug Type
        • 8.3.2.2.3. By Application Type
        • 8.3.2.2.4. By Therapeutic Area
    • 8.3.3. Japan AI in Drug Discovery Market Outlook
      • 8.3.3.1. Market Size & Forecast
        • 8.3.3.1.1. By Value
      • 8.3.3.2. Market Share & Forecast
        • 8.3.3.2.1. By Component Type
        • 8.3.3.2.2. By Drug Type
        • 8.3.3.2.3. By Application Type
        • 8.3.3.2.4. By Therapeutic Area
    • 8.3.4. South Korea AI in Drug Discovery Market Outlook
      • 8.3.4.1. Market Size & Forecast
        • 8.3.4.1.1. By Value
      • 8.3.4.2. Market Share & Forecast
        • 8.3.4.2.1. By Component Type
        • 8.3.4.2.2. By Drug Type
        • 8.3.4.2.3. By Application Type
        • 8.3.4.2.4. By Therapeutic Area
    • 8.3.5. Australia AI in Drug Discovery Market Outlook
      • 8.3.5.1. Market Size & Forecast
        • 8.3.5.1.1. By Value
      • 8.3.5.2. Market Share & Forecast
        • 8.3.5.2.1. By Component Type
        • 8.3.5.2.2. By Drug Type
        • 8.3.5.2.3. By Application Type
        • 8.3.5.2.4. By Therapeutic Area

9. South America AI in Drug Discovery Market Outlook

  • 9.1. Market Size & Forecast
    • 9.1.1. By Value
  • 9.2. Market Share & Forecast
    • 9.2.1. By Component Type
    • 9.2.2. By Drug Type
    • 9.2.3. By Application Type
    • 9.2.4. By Therapeutic Area
  • 9.3. South America: Country Analysis
    • 9.3.1. Brazil AI in Drug Discovery Market Outlook
      • 9.3.1.1. Market Size & Forecast
        • 9.3.1.1.1. By Value
      • 9.3.1.2. Market Share & Forecast
        • 9.3.1.2.1. By Component Type
        • 9.3.1.2.2. By Drug Type
        • 9.3.1.2.3. By Application Type
        • 9.3.1.2.4. By Therapeutic Area
    • 9.3.2. Argentina AI in Drug Discovery Market Outlook
      • 9.3.2.1. Market Size & Forecast
        • 9.3.2.1.1. By Value
      • 9.3.2.2. Market Share & Forecast
        • 9.3.2.2.1. By Component Type
        • 9.3.2.2.2. By Drug Type
        • 9.3.2.2.3. By Application Type
        • 9.3.2.2.4. By Therapeutic Area
    • 9.3.3. Colombia AI in Drug Discovery Market Outlook
      • 9.3.3.1. Market Size & Forecast
        • 9.3.3.1.1. By Value
      • 9.3.3.2. Market Share & Forecast
        • 9.3.3.2.1. By Component Type
        • 9.3.3.2.2. By Drug Type
        • 9.3.3.2.3. By Application Type
        • 9.3.3.2.4. By Therapeutic Area

10. Middle East and Africa AI in Drug Discovery Market Outlook

  • 10.1. Market Size & Forecast
    • 10.1.1. By Value
  • 10.2. Market Share & Forecast
    • 10.2.1. By Component Type
    • 10.2.2. By Drug Type
    • 10.2.3. By Application Type
    • 10.2.4. By Therapeutic Area
  • 10.3. MEA: Country Analysis
    • 10.3.1. South Africa AI in Drug Discovery Market Outlook
      • 10.3.1.1. Market Size & Forecast
        • 10.3.1.1.1. By Value
      • 10.3.1.2. Market Share & Forecast
        • 10.3.1.2.1. By Component Type
        • 10.3.1.2.2. By Drug Type
        • 10.3.1.2.3. By Application Type
        • 10.3.1.2.4. By Therapeutic Area
    • 10.3.2. Saudi Arabia AI in Drug Discovery Market Outlook
      • 10.3.2.1. Market Size & Forecast
        • 10.3.2.1.1. By Value
      • 10.3.2.2. Market Share & Forecast
        • 10.3.2.2.1. By Component Type
        • 10.3.2.2.2. By Drug Type
        • 10.3.2.2.3. By Application Type
        • 10.3.2.2.4. By Therapeutic Area
    • 10.3.3. UAE AI in Drug Discovery Market Outlook
      • 10.3.3.1. Market Size & Forecast
        • 10.3.3.1.1. By Value
      • 10.3.3.2. Market Share & Forecast
        • 10.3.3.2.1. By Component Type
        • 10.3.3.2.2. By Drug Type
        • 10.3.3.2.3. By Application Type
        • 10.3.3.2.4. By Therapeutic Area

11. Market Dynamics

12. Market Trends & Developments

13. Global AI in Drug Discovery Market: SWOT Analysis

14. Competitive Landscape

  • 14.1. Business Overview
  • 14.2. Services Offerings
  • 14.3. Recent Developments
  • 14.4. Key Personnel
  • 14.5. SWOT Analysis
    • 14.5.1. GNS Healthcare
    • 14.5.2. BioSymetrics
    • 14.5.3. BPGbio, Inc.
    • 14.5.4. Atomwise Inc.
    • 14.5.5. Owkin Inc.
    • 14.5.6. NVIDIA Corporation
    • 14.5.7. IBM Corporation
    • 14.5.8. Microsoft Corporation
    • 14.5.9. Aria Pharmaceuticals, Inc.
    • 14.5.10. Insilico Medicine Inc.

15. Strategic Recommendations

16. About Us & Disclaimer