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市場調查報告書
商品編碼
2030045

人工智慧在藥物發現市場的應用——全球產業規模、佔有率、趨勢、機會和預測：按組件類型、藥物類型、應用類型、治療領域、地區和競爭格局分類，2021-2031年

AI in Drug Discovery Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Component Type, By Drug Type, By Application Type, By Therapeutic Area, By Region & Competition, 2021-2031F
出版日期: | 出版商: TechSci Research | 英文 185 Pages | 商品交期: 2-3個工作天內

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簡介目錄

全球人工智慧藥物發現市場預計將從 2025 年的 11.3 億美元成長到 2031 年的 22.9 億美元，複合年成長率為 12.49%。

人工智慧利用機器學習和計算演算法來簡化藥物研發的關鍵階段，例如標靶識別、先導化合物最佳化和臨床前評估。這一市場成長的主要驅動力是迫切需要加速開發針對未解疾病的新治療方法，同時降低傳統研發的高昂成本。此外，生物數據的日益複雜化也需要更先進的計算工具來進行準確分析，這進一步推動了人工智慧平台的整合應用。

市場概覽
預測期 2027-2031
市場規模：2025年 11.3億美元
市場規模：2031年 22.9億美元
複合年成長率：2026-2031年 12.49%
成長最快的細分市場 腫瘤學
最大的市場 北美洲

根據Benchling發布的《2026年生物技術人工智慧報告》，到2025年積極採用人工智慧的生物技術公司中，有半數縮短了實現目標所需的時間，並在初期研發階段取得了顯著的生產力提升。儘管取得了這些突破性成就，但市場進一步成長的主要障礙仍然是缺乏具備在複雜的藥物研發環境中無縫整合和利用人工智慧工具所需專業知識的人工智慧專業人才。

市場促進因素

縮短研發週期和降低相關成本的迫切需求是人工智慧在藥物研發領域市場發展的主要驅動力。人工智慧系統透過自動化工作流程和提高預測準確性，最佳化了從標靶識別到先導化合物篩選的多個階段。例如，根據AIM Media House 2026年4月的報告，輝瑞公司利用人工智慧篩檢了數百萬種化合物，並在短短30天內成功識別出有前景的候選藥物，顯著縮短了研發週期。透過縮短這些早期研發階段，製藥公司可以更快地將新治療方法推向市場，應對迫在眉睫的健康危機，並透過減少對成本高昂的物理實驗的依賴來最大化收益。

另一個重要的驅動力是複雜生物醫學資訊的指數級成長，包括臨床數據、基因組數據、蛋白質組學數據和真實世界數據。這些資料集的龐大規模要求強大的計算技術才能進行有效的評估。在這一領域，人工智慧演算法擅長處理、學習和解釋大量訊息，從而發現新的治療標靶並實現個人化醫療。例如，Healthcare Brew 在 2025 年 12 月報道稱，默克公司和英偉達公司的小分子人工智慧模型「KERMT」已使用超過 1,100 萬個分子進行了訓練。透過將原始數據轉化為可操作的洞察，人工智慧能夠實現更智慧的決策，而這一趨勢顯然正在加速市場擴張。 Drug Target Review 在 2026 年 2 月預測，該領域的市場規模將從 2025 年的約 50 億至 70 億美元飆升至 2026 年的 80 億至 100 億美元。

市場挑戰

全球人工智慧市場在藥物研發領域面臨的一大障礙是，同時具備生命科學深厚專業知識的人工智慧專家普遍短缺。這種人才短缺嚴重限制了企業在複雜的藥物研發環境中正確實施和理解人工智慧系統的能力。驅動這些平台的先進機器學習模型既需要尖端的電腦科學技術，也需要對藥物研發中複雜的生物學和化學原理有深刻的理解。缺乏具備這種綜合知識的人才，使得企業無法充分發揮其人工智慧投資的價值，導致從標靶發現、化合物最佳化到臨床前試驗等各階段的執行力不足和效率降低。

此外，專業知識的匱乏使得檢驗和提升預測演算法的準確性變得困難。 2025 年皮斯托亞聯盟的一項調查凸顯了這個問題，調查發現，34% 的生命科學研發團隊認為人才短缺是人工智慧應用的最大障礙，高於前一年的 23%。日益嚴重的技能短缺將阻礙關鍵研究計畫的推進，妨礙人工智慧全面融入整個藥物研發流程，並最終阻礙藥物進入市場。將複雜的人工智慧生成數據轉化為可操作的治療方法開發步驟需要高度專業化的雙重技能，然而，製藥業仍然缺乏此類人才。

市場趨勢

生成式人工智慧在從頭分子設計中的應用，正在革新藥物研發的早期階段。它超越了對已知化合物庫的簡單最佳化和篩檢，實現了全新化學結構的發現。透過產生具有特定理想特性的獨特分子，這項技術顯著拓展了新型療法的潛在化學領域。例如，Generare公司宣布，到2025年，該公司將發現超過200種先前未知的分子，超過競爭對手的總和。這些進步使得研究人員能夠有系統地針對特定生物標的設計客製化化合物，從而有效地淘汰了傳統的緩慢的試驗誤法。

另一個值得關注的趨勢是策略合作的增加和更廣泛的人工智慧生態系統的發展。這顯示創新模式正向合作方向轉變，大型製藥公司擴大與專注於人工智慧的生物技術公司合作。這些合作使大型製藥公司能夠接觸到尖端的人工智慧網路和獨家研發管道，從而加速將數位洞察轉化為實際醫療方案的過程。為了凸顯這些合作的巨大價值， In Silico Medicine於2026年3月29日宣布與禮來公司達成藥物研發合作協議。該協議包含里程碑付款和特許權使用費，總價值近27.5億美元。這些協同合作關係對於在複雜的藥物研發生命週期中整合先進技術工具和深厚的產業知識至關重要。

目錄

第1章概述

第2章：調查方法

第3章執行摘要

第4章：客戶心聲

第5章：全球人工智慧藥物研發市場展望

  • 市場規模及預測
    • 按金額
  • 市佔率及預測
    • 依組件類型（軟體、服務）
    • 藥物類型（低分子量、高分子量）
    • 依應用領域（臨床前試驗、藥物最佳化、仿單標示外用藥、標靶辨識、候選化合物篩檢等）
    • 依治療領域（腫瘤科、神經退化性疾病、心血管疾病科、罕見疾病科、其他科）
    • 按地區
    • 按公司（2025 年）
  • 市場地圖

第6章：北美藥物發現領域人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 北美洲：國別分析
    • 美國
    • 加拿大
    • 墨西哥

第7章：歐洲人工智慧藥物研發市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 歐洲：國別分析
    • 德國
    • 法國
    • 英國
    • 義大利
    • 西班牙

第8章：亞太地區藥物研發人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 亞太地區：國別分析
    • 中國
    • 印度
    • 日本
    • 韓國
    • 澳洲

第9章：中東和非洲藥物研發人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 中東與非洲：國別分析
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 南非

第10章：人工智慧在南美藥物發現領域的市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 南美洲：國別分析
    • 巴西
    • 哥倫比亞
    • 阿根廷

第11章 市場動態

  • 促進因素
  • 任務

第12章 市場趨勢與發展

  • 併購
  • 產品發布
  • 近期趨勢

第13章：全球人工智慧藥物研發市場：SWOT分析

第14章：波特五力分析

  • 產業競爭
  • 新進入者的潛力
  • 供應商的議價能力
  • 顧客權力
  • 替代品的威脅

第15章 競爭格局

  • GNS Healthcare Inc
  • BioSymetrics, Inc.
  • Berg, LLC
  • Numerion Labs, Inc
  • Owkin Inc.
  • NVIDIA Corporation
  • IBM Corporation
  • Microsoft Corporation
  • Aria Pharmaceuticals, Inc.
  • Insilico Medicine Inc.

第16章 策略建議

第17章：關於研究公司及免責聲明

簡介目錄
Product Code: 4622

The Global AI in Drug Discovery Market is anticipated to expand from USD 1.13 billion in 2025 to USD 2.29 billion by 2031, reflecting a compound annual growth rate (CAGR) of 12.49%. By leveraging machine learning and computational algorithms, artificial intelligence streamlines critical phases of pharmaceutical development, including target identification, lead optimization, and preclinical evaluations. This market growth is primarily fueled by an urgent need to speed up the creation of new therapies for unaddressed medical conditions while cutting the steep expenses typical of conventional research and development. Additionally, the growing intricacy of biological data requires sophisticated computational tools for proper analysis, further propelling the integration of AI platforms.

Market Overview
Forecast Period2027-2031
Market Size 2025USD 1.13 Billion
Market Size 2031USD 2.29 Billion
CAGR 2026-203112.49%
Fastest Growing SegmentOncology
Largest MarketNorth America

Benchling's 2026 Biotech AI Report highlights that half of the biotech firms actively employing AI in 2025 experienced a quicker time-to-target, demonstrating tangible productivity improvements in preliminary research. Even with these breakthroughs, a major hurdle restricting broader market growth remains the shortage of specialized AI professionals who possess the domain expertise needed to seamlessly incorporate and decipher AI tools within the intricate landscape of pharmaceutical research.

Market Driver

The urgent need to shorten research timelines and lower associated expenses acts as a primary catalyst for the AI in drug discovery market. By automating workflows and boosting predictive precision, AI systems optimize multiple phases ranging from target identification to lead refinement. For example, a report from AIM Media House in April 2026 noted that Pfizer leveraged AI to scan millions of compounds and pinpoint viable drug candidates in just 30 days, drastically outperforming conventional timelines. Shrinking these initial development stages allows drug manufacturers to introduce new treatments much faster, tackling pressing health crises while maximizing returns by reducing the reliance on costly physical lab experiments.

A further significant driver is the exponential surge in complex biomedical information, including clinical, genomic, proteomic, and real-world data. The massive scale of these datasets demands powerful computational technologies for meaningful evaluation, an area where AI algorithms excel by processing, learning from, and interpreting vast amounts of information to uncover new therapeutic targets and create personalized medicines. Showcasing this scale, Healthcare Brew reported in December 2025 that KERMT, a small-molecule AI model by Merck and Nvidia, was trained on over 11 million molecules. By turning raw data into actionable insights, AI empowers smarter decision-making, a trend that is clearly accelerating market expansion; Drug Target Review noted in February 2026 that the sector's value is expected to jump from roughly $5-7 billion in 2025 to $8-10 billion by 2026.

Market Challenge

A major obstacle facing the Global AI in Drug Discovery Market is the widespread shortage of AI professionals who also possess deep life sciences expertise. This talent deficit severely limits the ability to properly deploy and understand artificial intelligence systems within complex pharmaceutical R&D settings. The sophisticated machine learning models driving these platforms necessitate an intricate understanding of both advanced computer science and the complex biological and chemical principles of drug creation. Lacking staff with this combined knowledge, companies often fail to fully leverage their AI investments, resulting in flawed executions and diminished productivity during target discovery, compound refinement, and preclinical trials.

This lack of specialized expertise also makes it difficult to validate and improve the accuracy of predictive algorithms. Highlighting this issue, a 2025 Pistoia Alliance survey revealed that 34% of life sciences R&D groups viewed the talent shortage as a primary roadblock to implementing AI, up from 23% the previous year. This expanding skills deficit stalls important research schedules and prevents the comprehensive integration of AI throughout the drug development process, ultimately stifling market advancement. Converting complex AI-generated data into practical steps for therapeutic development requires a highly specific dual skill set that continues to be rare within the pharmaceutical sector.

Market Trends

The use of generative AI for de novo molecular design is revolutionizing the early stages of pharmaceutical research by facilitating the invention of completely new chemical structures, moving beyond the simple optimization or screening of known libraries. By generating original molecules that possess specific desired traits, this technology vastly broadens the potential chemical landscape for new therapies. Illustrating this rapid progression, Generare announced in 2025 that it had discovered over 200 previously unknown molecules, outperforming the collective results of its competitors. Such advancements empower researchers to methodically engineer custom compounds for precise biological targets, effectively leaving behind slower, trial-and-error techniques.

Another defining trend is the rise of strategic partnerships and the growth of a broader AI ecosystem, marking a transition toward collaborative innovation as established drug makers frequently team up with niche AI biotech firms. These partnerships grant major pharmaceutical companies access to cutting-edge AI networks and exclusive research pipelines, hastening the conversion of digital insights into actual medical treatments. Highlighting the immense value of these ventures, Insilico Medicine revealed a discovery agreement with Eli Lilly on March 29, 2026, valued at nearly $2.75 billion when accounting for milestones and royalties. These synergistic relationships are vital for blending advanced technological tools with deep industry knowledge throughout the complicated lifecycle of drug development.

Key Market Players

  • GNS Healthcare Inc
  • BioSymetrics, Inc.
  • Berg, LLC
  • Numerion Labs, 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

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, TechSci 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. Product Overview

  • 1.1. Market Definition
  • 1.2. Scope of the Market
    • 1.2.1. Markets Covered
    • 1.2.2. Years Considered for Study
    • 1.2.3. Key Market Segmentations

2. Research Methodology

  • 2.1. Objective of the Study
  • 2.2. Baseline Methodology
  • 2.3. Key Industry Partners
  • 2.4. Major Association and Secondary Sources
  • 2.5. Forecasting Methodology
  • 2.6. Data Triangulation & Validation
  • 2.7. Assumptions and Limitations

3. Executive Summary

  • 3.1. Overview of the Market
  • 3.2. Overview of Key Market Segmentations
  • 3.3. Overview of Key Market Players
  • 3.4. Overview of Key Regions/Countries
  • 3.5. Overview of Market Drivers, Challenges, Trends

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, Services)
    • 5.2.2. By Drug Type (Small Molecule, Large Molecule)
    • 5.2.3. By Application Type (Preclinical Testing, Drug Optimization, Repurposing, Target Identification, Candidate Screening, Others)
    • 5.2.4. By Therapeutic Area (Oncology, Neurodegenerative Diseases, Cardiovascular Diseases, Rare Diseases, Others)
    • 5.2.5. By Region
    • 5.2.6. By Company (2025)
  • 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
    • 7.2.5. By Country
  • 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. France 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. United Kingdom 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 & Forecast
        • 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. Italy 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
    • 8.2.5. By Country
  • 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. Middle East & Africa 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
    • 9.2.5. By Country
  • 9.3. Middle East & Africa: Country Analysis
    • 9.3.1. Saudi Arabia 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. UAE 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. South Africa 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. South America 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
    • 10.2.5. By Country
  • 10.3. South America: Country Analysis
    • 10.3.1. Brazil 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. Colombia 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. Argentina 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

  • 11.1. Drivers
  • 11.2. Challenges

12. Market Trends & Developments

  • 12.1. Merger & Acquisition (If Any)
  • 12.2. Product Launches (If Any)
  • 12.3. Recent Developments

13. Global AI in Drug Discovery Market: SWOT Analysis

14. Porter's Five Forces Analysis

  • 14.1. Competition in the Industry
  • 14.2. Potential of New Entrants
  • 14.3. Power of Suppliers
  • 14.4. Power of Customers
  • 14.5. Threat of Substitute Products

15. Competitive Landscape

  • 15.1. GNS Healthcare Inc
    • 15.1.1. Business Overview
    • 15.1.2. Products & Services
    • 15.1.3. Recent Developments
    • 15.1.4. Key Personnel
    • 15.1.5. SWOT Analysis
  • 15.2. BioSymetrics, Inc.
  • 15.3. Berg, LLC
  • 15.4. Numerion Labs, Inc
  • 15.5. Owkin Inc.
  • 15.6. NVIDIA Corporation
  • 15.7. IBM Corporation
  • 15.8. Microsoft Corporation
  • 15.9. Aria Pharmaceuticals, Inc.
  • 15.10. Insilico Medicine Inc.

16. Strategic Recommendations

17. About Us & Disclaimer