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製薬業界向け機械学習（ML）市場：コンポーネント別（ソリューション、サービス）、企業規模別（中小企業、大企業）、展開別（クラウド、オンプレミス）：世界の機会分析と産業予測、2021年～2031年

Machine Learning in Pharmaceutical Industry Market By Component (Solution, Services), By Enterprise Size (SMEs, Large Enterprises), By Deployment (Cloud, On-premise): Global Opportunity Analysis and Industry Forecast, 2021-2031
出版日: | 発行: Allied Market Research | ページ情報: 英文 280 Pages | 納期: 2～3営業日

価格
価格表記: USDを日本円(税抜)に換算
本日の銀行送金レート: 1USD=156.58円
製薬業界向け機械学習（ML）市場：コンポーネント別（ソリューション、サービス）、企業規模別（中小企業、大企業）、展開別（クラウド、オンプレミス）：世界の機会分析と産業予測、2021年～2031年
出版日: 2023年04月01日
発行: Allied Market Research
ページ情報: 英文 280 Pages
納期: 2～3営業日
  • 全表示
  • 概要
  • 図表
  • 目次
概要

製薬業界向け機械学習（ML）の世界市場は、2021年の12億米ドルから2022年から2031年までのCAGR 37.9%で成長し、2031年には262億米ドルに達すると予測されています。

Machine Learning in Pharmaceutical Industry Market-IMG1

製薬業界向け機械学習（ML）とは、アルゴリズムや統計モデルを使用してデータを分析し、医薬品開発、臨床試験、規制当局の承認、マーケティング、販売に関する予測や意思決定を行うことを指します。

機械学習は製薬業界、特に臨床試験の分野で重要性を増しています。機械学習アルゴリズムの助けを借りて、製薬会社は膨大な量のデータを分析し、パターンを特定することができます。これは臨床試験のデザインにおいて特に有用であり、機械学習は臨床試験デザインと患者選択を最適化するのに役立ち、コスト削減と開発プロセスの加速につながる可能性があります。例えば、機械学習アルゴリズムを使用して患者データを分析し、特定の薬剤が特定の疾患の治療に有効である可能性が高いかどうかを示すバイオマーカーを特定することができます。

規制上の制約は、製薬業界向け機械学習（ML）が直面する重大な課題のひとつです。機械学習アルゴリズムは新しい技術と考えられており、製薬用途で使用する前に厳しい規制要件を満たす必要があります。米国食品医薬品局（FDA）などの規制当局は、機械学習アルゴリズムの開発と検証に関する厳格なガイドラインを定めています。これらのガイドラインは、アルゴリズムを大規模かつ多様なデータセットで検証し、その正確性、信頼性、安全性を実証することを求めています。機械学習アルゴリズムの検証プロセスには時間とコストがかかり、企業がこれらの技術を採用する際の課題となっています。

機械学習は製薬業界、特に医薬品の安全性の分野で大きな可能性を秘めています。機械学習の助けを借りて、膨大な量のデータを分析し、潜在的な安全性の問題が発生する前に予測するために使用できるパターンを特定することが可能です。これにより、製薬会社は医薬品の副作用を未然に防ぐ対策を講じることができ、患者の安全性を向上させることができます。機械学習アルゴリズムは、電子カルテ、ソーシャルメディア、その他のソースを含む様々なデータソースを分析し、副作用を検出することができます。これらのアルゴリズムは、人間の分析者にはわからないようなパターンを特定することができるため、製薬会社は潜在的な安全性の問題が広まる前に検出することができます。

COVID-19の大流行は、革新的なソリューション、より迅速な医薬品開発プロセス、より効率的なサプライチェーン管理に対する需要の増加など、製薬業界に大きな変化をもたらしました。機械学習は、こうした課題に対処し、製薬業界に影響を与える上で重要な役割を果たしている技術のひとつです。MLアルゴリズムは、大量のデータを迅速かつ正確に分析し、疾患パターンに関する洞察を提供し、潜在的な創薬ターゲットを特定し、開発中の薬剤の有効性を予測することができます。MLは、パンデミック時のCOVID-19治療薬やワクチンの可能性の特定など、創薬や医薬品開発において幅広く使用されています。

目次

第1章 イントロダクション

第2章 エグゼクティブサマリー

第3章 市場概要

  • 市場の定義と範囲
  • 主な調査結果
    • 影響要因
    • 主な投資ポケット
  • ポーターのファイブフォース分析
  • 市場力学
    • 促進要因
    • 抑制要因
    • 機会
  • COVID-19市場への影響分析
  • 主要規制分析
  • 市場シェア分析
  • 特許情勢
  • 規制ガイドライン
  • バリューチェーン分析

第4章 製薬業界向け機械学習（ML）市場：コンポーネント別

  • 概要
    • 市場規模と予測
  • ソリューション
    • 主な市場動向、成長要因、機会
    • 市場規模・予測：地域別
    • 市場シェア分析：国別
  • サービス
    • 主な市場動向、成長要因、機会
    • 市場規模・予測：地域別
    • 市場シェア分析：国別

第5章 製薬業界向け機械学習（ML）市場：企業規模別

  • 概要
    • 市場規模と予測
  • 中小企業
    • 主な市場動向、成長要因、機会
    • 市場規模・予測：地域別
    • 市場シェア分析：国別
  • 大企業
    • 主な市場動向、成長要因、機会
    • 市場規模・予測：地域別
    • 市場シェア分析：国別

第6章 製薬業界向け機械学習（ML）市場：用途別

  • 概要
    • 市場規模と予測
  • クラウド
    • 主な市場動向、成長要因、機会
    • 市場規模・予測： 地域別
    • 市場シェア分析：国別
  • オンプレミス
    • 主な市場動向、成長要因、機会
    • 市場規模・予測：地域別
    • 市場シェア分析：国別

第7章 製薬業界向け機械学習（ML）市場：地域別

  • 概要
    • 市場規模・予測：地域別
  • 北米
    • 主要動向と機会
    • 市場規模・予測：コンポーネント別
    • 市場規模・予測：企業規模別
    • 市場規模・予測：展開別
    • 市場規模・予測：国別
      • 米国
      • 主な市場動向、成長要因、機会
      • 市場規模・予測：コンポーネント別
      • 市場規模・予測：企業規模別
      • 市場規模・予測：展開別
      • カナダ
      • 主な市場動向、成長要因、機会
      • 市場規模・予測：コンポーネント別
      • 市場規模・予測：企業規模別
      • 市場規模・予測：展開別
      • メキシコ
      • 主な市場動向、成長要因、機会
      • 市場規模・予測：コンポーネント別
      • 市場規模・予測：企業規模別
      • 市場規模・予測：展開別
  • 欧州
    • 主要動向と機会
    • 市場規模・予測：コンポーネント別
    • 市場規模・予測：企業規模別
    • 市場規模・予測：展開別
    • 市場規模・予測：国別
      • ドイツ
      • 主な市場動向、成長要因、機会
      • 市場規模・予測：コンポーネント別
      • 市場規模・予測：企業規模別
      • 市場規模・予測：展開別
      • 英国
      • 主な市場動向、成長要因、機会
      • 市場規模・予測：コンポーネント別
      • 市場規模・予測：企業規模別
      • 市場規模・予測：展開別
      • フランス
      • 主な市場動向、成長要因、機会
      • 市場規模・予測：コンポーネント別
      • 市場規模・予測：企業規模別
      • 市場規模・予測：展開別
      • スペイン
      • 主な市場動向、成長要因、機会
      • 市場規模・予測：コンポーネント別
      • 市場規模・予測：企業規模別
      • 市場規模・予測：展開別
      • イタリア
      • 主な市場動向、成長要因、機会
      • 市場規模・予測：コンポーネント別
      • 市場規模・予測：企業規模別
      • 市場規模・予測：展開別
      • その他欧州
      • 主な市場動向、成長要因、機会
      • 市場規模・予測：コンポーネント別
      • 市場規模・予測：企業規模別
      • 市場規模・予測：展開別
  • アジア太平洋地域
    • 主要動向と機会
    • 市場規模・予測：コンポーネント別
    • 市場規模・予測：企業規模別
    • 市場規模・予測：展開別
    • 市場規模・予測：国別
      • 中国
      • 主な市場動向、成長要因、機会
      • 市場規模・予測：コンポーネント別
      • 市場規模・予測：企業規模別
      • 市場規模・予測：展開別
      • 日本
      • 主な市場動向、成長要因、機会
      • 市場規模・予測：コンポーネント別
      • 市場規模・予測：企業規模別
      • 市場規模・予測：展開別
      • インド
      • 主な市場動向、成長要因、機会
      • 市場規模・予測：コンポーネント別
      • 市場規模・予測：企業規模別
      • 市場規模・予測：展開別
      • 韓国
      • 主な市場動向、成長要因、機会
      • 市場規模・予測：コンポーネント別
      • 市場規模・予測：企業規模別
      • 市場規模・予測：展開別
      • オーストラリア
      • 主な市場動向、成長要因、機会
      • 市場規模・予測：コンポーネント別
      • 市場規模・予測：企業規模別
      • 市場規模・予測：展開別
      • その他アジア太平洋地域
      • 主な市場動向、成長要因、機会
      • 市場規模・予測：コンポーネント別
      • 市場規模・予測：企業規模別
      • 市場規模・予測：展開別
  • ラテンアメリカ・中東・アフリカ
    • 主要動向と機会
    • 市場規模・予測：コンポーネント別
    • 市場規模・予測：企業規模別
    • 市場規模・予測：展開別
    • 市場規模・予測：国別
      • ブラジル
      • 主な市場動向、成長要因、機会
      • 市場規模・予測：コンポーネント別
      • 市場規模・予測：企業規模別
      • 市場規模・予測：展開別
      • サウジアラビア
      • 主な市場動向、成長要因、機会
      • 市場規模・予測：コンポーネント別
      • 市場規模・予測：企業規模別
      • 市場規模・予測：展開別
      • アラブ首長国連邦
      • 主な市場動向、成長要因、機会
      • 市場規模・予測：コンポーネント別
      • 市場規模・予測：企業規模別
      • 市場規模・予測：展開別
      • 南アフリカ
      • 主な市場動向、成長要因、機会
      • 市場規模・予測：コンポーネント別
      • 市場規模・予測：企業規模別
      • 市場規模・予測：展開別
      • その他の地域
      • 主な市場動向、成長要因、機会
      • 市場規模・予測：コンポーネント別
      • 市場規模・予測：企業規模別
      • 市場規模・予測：展開別

第8章 競合情勢

  • イントロダクション
  • 主要成功戦略
  • 主要10社の製品マッピング
  • 競合ダッシュボード
  • 競合ヒートマップ
  • トップ企業のポジショニング、2021年

第9章 企業プロファイル

  • cyclica inc.
  • BioSymetrics Inc.
  • Cloud Pharmaceuticals, Inc.
  • Deep Genomics
  • Atomwise Inc.
  • Alphabet Inc.
  • NVIDIA Corporation
  • International Business Machines Corporation
  • Microsoft Corporation
  • IBM
図表

LIST OF TABLES

  • TABLE 01. GLOBAL MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 02. MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET FOR SOLUTION, BY REGION, 2021-2031 ($MILLION)
  • TABLE 03. MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET FOR SERVICES, BY REGION, 2021-2031 ($MILLION)
  • TABLE 04. GLOBAL MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 05. MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET FOR SMES, BY REGION, 2021-2031 ($MILLION)
  • TABLE 06. MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET FOR LARGE ENTERPRISES, BY REGION, 2021-2031 ($MILLION)
  • TABLE 07. GLOBAL MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 08. MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET FOR CLOUD, BY REGION, 2021-2031 ($MILLION)
  • TABLE 09. MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET FOR ON-PREMISE, BY REGION, 2021-2031 ($MILLION)
  • TABLE 10. MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY REGION, 2021-2031 ($MILLION)
  • TABLE 11. NORTH AMERICA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 12. NORTH AMERICA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 13. NORTH AMERICA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 14. NORTH AMERICA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COUNTRY, 2021-2031 ($MILLION)
  • TABLE 15. U.S. MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 16. U.S. MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 17. U.S. MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 18. CANADA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 19. CANADA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 20. CANADA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 21. MEXICO MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 22. MEXICO MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 23. MEXICO MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 24. EUROPE MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 25. EUROPE MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 26. EUROPE MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 27. EUROPE MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COUNTRY, 2021-2031 ($MILLION)
  • TABLE 28. GERMANY MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 29. GERMANY MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 30. GERMANY MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 31. UK MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 32. UK MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 33. UK MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 34. FRANCE MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 35. FRANCE MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 36. FRANCE MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 37. SPAIN MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 38. SPAIN MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 39. SPAIN MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 40. ITALY MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 41. ITALY MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 42. ITALY MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 43. REST OF EUROPE MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 44. REST OF EUROPE MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 45. REST OF EUROPE MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 46. ASIA-PACIFIC MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 47. ASIA-PACIFIC MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 48. ASIA-PACIFIC MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 49. ASIA-PACIFIC MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COUNTRY, 2021-2031 ($MILLION)
  • TABLE 50. CHINA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 51. CHINA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 52. CHINA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 53. JAPAN MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 54. JAPAN MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 55. JAPAN MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 56. INDIA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 57. INDIA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 58. INDIA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 59. SOUTH KOREA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 60. SOUTH KOREA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 61. SOUTH KOREA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 62. AUSTRALIA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 63. AUSTRALIA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 64. AUSTRALIA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 65. REST OF ASIA-PACIFIC MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 66. REST OF ASIA-PACIFIC MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 67. REST OF ASIA-PACIFIC MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 68. LAMEA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 69. LAMEA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 70. LAMEA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 71. LAMEA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COUNTRY, 2021-2031 ($MILLION)
  • TABLE 72. BRAZIL MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 73. BRAZIL MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 74. BRAZIL MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 75. SAUDI ARABIA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 76. SAUDI ARABIA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 77. SAUDI ARABIA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 78. UNITED ARAB EMIRATES MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 79. UNITED ARAB EMIRATES MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 80. UNITED ARAB EMIRATES MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 81. SOUTH AFRICA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 82. SOUTH AFRICA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 83. SOUTH AFRICA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 84. REST OF LAMEA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021-2031 ($MILLION)
  • TABLE 85. REST OF LAMEA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021-2031 ($MILLION)
  • TABLE 86. REST OF LAMEA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021-2031 ($MILLION)
  • TABLE 87. CYCLICA INC.: KEY EXECUTIVES
  • TABLE 88. CYCLICA INC.: COMPANY SNAPSHOT
  • TABLE 89. BIOSYMETRICS INC.: KEY EXECUTIVES
  • TABLE 90. BIOSYMETRICS INC.: COMPANY SNAPSHOT
  • TABLE 91. CLOUD PHARMACEUTICALS, INC.: KEY EXECUTIVES
  • TABLE 92. CLOUD PHARMACEUTICALS, INC.: COMPANY SNAPSHOT
  • TABLE 93. DEEP GENOMICS: KEY EXECUTIVES
  • TABLE 94. DEEP GENOMICS: COMPANY SNAPSHOT
  • TABLE 95. ATOMWISE INC.: KEY EXECUTIVES
  • TABLE 96. ATOMWISE INC.: COMPANY SNAPSHOT
  • TABLE 97. ALPHABET INC.: KEY EXECUTIVES
  • TABLE 98. ALPHABET INC.: COMPANY SNAPSHOT
  • TABLE 99. NVIDIA CORPORATION: KEY EXECUTIVES
  • TABLE 100. NVIDIA CORPORATION: COMPANY SNAPSHOT
  • TABLE 101. INTERNATIONAL BUSINESS MACHINES CORPORATION: KEY EXECUTIVES
  • TABLE 102. INTERNATIONAL BUSINESS MACHINES CORPORATION: COMPANY SNAPSHOT
  • TABLE 103. MICROSOFT CORPORATION: KEY EXECUTIVES
  • TABLE 104. MICROSOFT CORPORATION: COMPANY SNAPSHOT
  • TABLE 105. IBM: KEY EXECUTIVES
  • TABLE 106. IBM: COMPANY SNAPSHOT

LIST OF FIGURES

  • FIGURE 01. MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, 2021-2031
  • FIGURE 02. SEGMENTATION OF MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, 2021-2031
  • FIGURE 03. TOP INVESTMENT POCKETS IN MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET (2022-2031)
  • FIGURE 04. PORTER FIVE-1
  • FIGURE 05. PORTER FIVE-2
  • FIGURE 06. PORTER FIVE-3
  • FIGURE 07. PORTER FIVE-4
  • FIGURE 08. PORTER FIVE-5
  • FIGURE 09. DRIVERS, RESTRAINTS AND OPPORTUNITIES: GLOBALMACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET
  • FIGURE 10. IMPACT OF KEY REGULATION: MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET
  • FIGURE 11. MARKET SHARE ANALYSIS: MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET
  • FIGURE 12. PATENT ANALYSIS BY COMPANY
  • FIGURE 13. PATENT ANALYSIS BY COUNTRY
  • FIGURE 14. REGULATORY GUIDELINES: MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET
  • FIGURE 15. VALUE CHAIN ANALYSIS: MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET
  • FIGURE 16. MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT, 2021(%)
  • FIGURE 17. COMPARATIVE SHARE ANALYSIS OF MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET FOR SOLUTION, BY COUNTRY 2021 AND 2031(%)
  • FIGURE 18. COMPARATIVE SHARE ANALYSIS OF MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET FOR SERVICES, BY COUNTRY 2021 AND 2031(%)
  • FIGURE 19. MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE, 2021(%)
  • FIGURE 20. COMPARATIVE SHARE ANALYSIS OF MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET FOR SMES, BY COUNTRY 2021 AND 2031(%)
  • FIGURE 21. COMPARATIVE SHARE ANALYSIS OF MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET FOR LARGE ENTERPRISES, BY COUNTRY 2021 AND 2031(%)
  • FIGURE 22. MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT, 2021(%)
  • FIGURE 23. COMPARATIVE SHARE ANALYSIS OF MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET FOR CLOUD, BY COUNTRY 2021 AND 2031(%)
  • FIGURE 24. COMPARATIVE SHARE ANALYSIS OF MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET FOR ON-PREMISE, BY COUNTRY 2021 AND 2031(%)
  • FIGURE 25. MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET BY REGION, 2021
  • FIGURE 26. U.S. MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, 2021-2031 ($MILLION)
  • FIGURE 27. CANADA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, 2021-2031 ($MILLION)
  • FIGURE 28. MEXICO MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, 2021-2031 ($MILLION)
  • FIGURE 29. GERMANY MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, 2021-2031 ($MILLION)
  • FIGURE 30. UK MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, 2021-2031 ($MILLION)
  • FIGURE 31. FRANCE MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, 2021-2031 ($MILLION)
  • FIGURE 32. SPAIN MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, 2021-2031 ($MILLION)
  • FIGURE 33. ITALY MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, 2021-2031 ($MILLION)
  • FIGURE 34. REST OF EUROPE MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, 2021-2031 ($MILLION)
  • FIGURE 35. CHINA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, 2021-2031 ($MILLION)
  • FIGURE 36. JAPAN MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, 2021-2031 ($MILLION)
  • FIGURE 37. INDIA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, 2021-2031 ($MILLION)
  • FIGURE 38. SOUTH KOREA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, 2021-2031 ($MILLION)
  • FIGURE 39. AUSTRALIA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, 2021-2031 ($MILLION)
  • FIGURE 40. REST OF ASIA-PACIFIC MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, 2021-2031 ($MILLION)
  • FIGURE 41. BRAZIL MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, 2021-2031 ($MILLION)
  • FIGURE 42. SAUDI ARABIA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, 2021-2031 ($MILLION)
  • FIGURE 43. UNITED ARAB EMIRATES MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, 2021-2031 ($MILLION)
  • FIGURE 44. SOUTH AFRICA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, 2021-2031 ($MILLION)
  • FIGURE 45. REST OF LAMEA MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, 2021-2031 ($MILLION)
  • FIGURE 46. TOP WINNING STRATEGIES, BY YEAR
  • FIGURE 47. TOP WINNING STRATEGIES, BY DEVELOPMENT
  • FIGURE 48. TOP WINNING STRATEGIES, BY COMPANY
  • FIGURE 49. PRODUCT MAPPING OF TOP 10 PLAYERS
  • FIGURE 50. COMPETITIVE DASHBOARD
  • FIGURE 51. COMPETITIVE HEATMAP: MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET
  • FIGURE 52. TOP PLAYER POSITIONING, 2021
目次
Product Code: A74504

The global machine learning in pharmaceutical industry market is anticipated to reach $26.2 billion by 2031, growing from $1.2 billion in 2021 at a CAGR of 37.9 % from 2022 to 2031.

Machine Learning in Pharmaceutical Industry Market - IMG1

Machine learning (ML) in the pharmaceutical industry refers to the use of algorithms and statistical models to analyze data and make predictions or decisions related to drug development, clinical trials, regulatory approval, marketing, and sales.

Machine learning has become increasingly important in the pharmaceutical industry, particularly in the area of clinical trials. With the help of machine learning algorithms, pharmaceutical companies can analyze vast amounts of data and identify patterns. This can be particularly useful in the design of clinical trials, where machine learning can help optimize trial design and patient selection, potentially reducing costs and accelerating the development process. For example, machine learning algorithms can be used to analyze patient data and identify biomarkers that may indicate whether a particular drug is likely to be effective in treating a particular disease.

The regulatory constraints are one of the significant challenges that machine learning faces in the pharmaceutical industry. Machine learning algorithms are considered to be a new technology, and they need to meet strict regulatory requirements before they can be used in pharmaceutical applications. The regulatory authorities, such as the U.S. Food and Drug Administration (FDA), have established strict guidelines for the development and validation of machine learning algorithms. These guidelines require that the algorithms be validated on large and diverse datasets and demonstrate their accuracy, reliability, and safety. The process of validating machine learning algorithms can be time-consuming and costly, making it a challenge for companies to adopt these technologies.

The machine learning has a significant potential in the pharmaceutical industry, particularly in the area of drug safety. With the help of machine learning, it is possible to analyze vast amounts of data and identify patterns that can be used to predict potential safety issues before they occur. This can help pharmaceutical companies to take proactive measures to prevent adverse drug reactions, thereby improving patient safety. Machine learning algorithms can analyze a variety of data sources, including electronic health records, social media, and other sources, to detect adverse drug reactions. These algorithms can identify patterns that might not be apparent to human analysts, allowing pharmaceutical companies to detect potential safety issues before they become widespread.

The COVID-19 pandemic brought about significant changes in the pharmaceutical industry, including an increase in demand for innovative solutions, faster drug development processes, and more efficient supply chain management. Machine learning (ML) is one technology that is playing a crucial role in addressing these challenges and impacting the pharmaceutical industry. ML algorithms can analyze large amounts of data quickly and accurately, providing insights into disease patterns, identifying potential drug targets, and predicting the efficacy of drugs in development. ML has been used extensively in drug discovery and development, including identifying potential COVID-19 treatments and vaccines during the pandemic.

The key players profiled in this report include: Cyclica Inc., BioSymetrics Inc., Cloud Pharmaceuticals, Inc., Deep Genomics, Atomwise Inc., Alphabet Inc., NVIDIA Corporation, International Business Machines Corporation, Microsoft Corporation, and IBM.

Key Benefits For Stakeholders

  • This report provides a quantitative analysis of the market segments, current trends, estimations, and dynamics of the machine learning in pharmaceutical industry market analysis from 2021 to 2031 to identify the prevailing machine learning in pharmaceutical industry market opportunities.
  • The market research is offered along with information related to key drivers, restraints, and opportunities.
  • Porter's five forces analysis highlights the potency of buyers and suppliers to enable stakeholders make profit-oriented business decisions and strengthen their supplier-buyer network.
  • In-depth analysis of the machine learning in pharmaceutical industry market segmentation assists to determine the prevailing market opportunities.
  • Major countries in each region are mapped according to their revenue contribution to the global market.
  • Market player positioning facilitates benchmarking and provides a clear understanding of the present position of the market players.
  • The report includes the analysis of the regional as well as global machine learning in pharmaceutical industry market trends, key players, market segments, application areas, and market growth strategies.

Key Market Segments

By Component

  • Solution
  • Services

By Enterprise Size

  • SMEs
  • Large Enterprises

By Deployment

  • Cloud
  • On-premise

By Region

  • North America
    • U.S.
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • France
    • Spain
    • Italy
    • Rest of Europe
  • Asia-Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Rest of Asia-Pacific
  • LAMEA
    • Brazil
    • Saudi Arabia
    • United Arab Emirates
    • South Africa
    • Rest of LAMEA

Key Market Players:

    • cyclica inc.
    • BioSymetrics Inc.
    • Cloud Pharmaceuticals, Inc.
    • Deep Genomics
    • Atomwise Inc.
    • Alphabet Inc.
    • NVIDIA Corporation
    • International Business Machines Corporation
    • Microsoft Corporation
    • IBM

TABLE OF CONTENTS

CHAPTER 1: INTRODUCTION

  • 1.1. Report description
  • 1.2. Key market segments
  • 1.3. Key benefits to the stakeholders
  • 1.4. Research Methodology
    • 1.4.1. Primary research
    • 1.4.2. Secondary research
    • 1.4.3. Analyst tools and models

CHAPTER 2: EXECUTIVE SUMMARY

  • 2.1. CXO Perspective

CHAPTER 3: MARKET OVERVIEW

  • 3.1. Market definition and scope
  • 3.2. Key findings
    • 3.2.1. Top impacting factors
    • 3.2.2. Top investment pockets
  • 3.3. Porter's five forces analysis
  • 3.4. Market dynamics
    • 3.4.1. Drivers
    • 3.4.2. Restraints
    • 3.4.3. Opportunities
  • 3.5. COVID-19 Impact Analysis on the market
  • 3.6. Key Regulation Analysis
  • 3.7. Market Share Analysis
  • 3.8. Patent Landscape
  • 3.9. Regulatory Guidelines
  • 3.10. Value Chain Analysis

CHAPTER 4: MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY COMPONENT

  • 4.1. Overview
    • 4.1.1. Market size and forecast
  • 4.2. Solution
    • 4.2.1. Key market trends, growth factors and opportunities
    • 4.2.2. Market size and forecast, by region
    • 4.2.3. Market share analysis by country
  • 4.3. Services
    • 4.3.1. Key market trends, growth factors and opportunities
    • 4.3.2. Market size and forecast, by region
    • 4.3.3. Market share analysis by country

CHAPTER 5: MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY ENTERPRISE SIZE

  • 5.1. Overview
    • 5.1.1. Market size and forecast
  • 5.2. SMEs
    • 5.2.1. Key market trends, growth factors and opportunities
    • 5.2.2. Market size and forecast, by region
    • 5.2.3. Market share analysis by country
  • 5.3. Large Enterprises
    • 5.3.1. Key market trends, growth factors and opportunities
    • 5.3.2. Market size and forecast, by region
    • 5.3.3. Market share analysis by country

CHAPTER 6: MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY DEPLOYMENT

  • 6.1. Overview
    • 6.1.1. Market size and forecast
  • 6.2. Cloud
    • 6.2.1. Key market trends, growth factors and opportunities
    • 6.2.2. Market size and forecast, by region
    • 6.2.3. Market share analysis by country
  • 6.3. On-premise
    • 6.3.1. Key market trends, growth factors and opportunities
    • 6.3.2. Market size and forecast, by region
    • 6.3.3. Market share analysis by country

CHAPTER 7: MACHINE LEARNING IN PHARMACEUTICAL INDUSTRY MARKET, BY REGION

  • 7.1. Overview
    • 7.1.1. Market size and forecast By Region
  • 7.2. North America
    • 7.2.1. Key trends and opportunities
    • 7.2.2. Market size and forecast, by Component
    • 7.2.3. Market size and forecast, by Enterprise Size
    • 7.2.4. Market size and forecast, by Deployment
    • 7.2.5. Market size and forecast, by country
      • 7.2.5.1. U.S.
      • 7.2.5.1.1. Key market trends, growth factors and opportunities
      • 7.2.5.1.2. Market size and forecast, by Component
      • 7.2.5.1.3. Market size and forecast, by Enterprise Size
      • 7.2.5.1.4. Market size and forecast, by Deployment
      • 7.2.5.2. Canada
      • 7.2.5.2.1. Key market trends, growth factors and opportunities
      • 7.2.5.2.2. Market size and forecast, by Component
      • 7.2.5.2.3. Market size and forecast, by Enterprise Size
      • 7.2.5.2.4. Market size and forecast, by Deployment
      • 7.2.5.3. Mexico
      • 7.2.5.3.1. Key market trends, growth factors and opportunities
      • 7.2.5.3.2. Market size and forecast, by Component
      • 7.2.5.3.3. Market size and forecast, by Enterprise Size
      • 7.2.5.3.4. Market size and forecast, by Deployment
  • 7.3. Europe
    • 7.3.1. Key trends and opportunities
    • 7.3.2. Market size and forecast, by Component
    • 7.3.3. Market size and forecast, by Enterprise Size
    • 7.3.4. Market size and forecast, by Deployment
    • 7.3.5. Market size and forecast, by country
      • 7.3.5.1. Germany
      • 7.3.5.1.1. Key market trends, growth factors and opportunities
      • 7.3.5.1.2. Market size and forecast, by Component
      • 7.3.5.1.3. Market size and forecast, by Enterprise Size
      • 7.3.5.1.4. Market size and forecast, by Deployment
      • 7.3.5.2. UK
      • 7.3.5.2.1. Key market trends, growth factors and opportunities
      • 7.3.5.2.2. Market size and forecast, by Component
      • 7.3.5.2.3. Market size and forecast, by Enterprise Size
      • 7.3.5.2.4. Market size and forecast, by Deployment
      • 7.3.5.3. France
      • 7.3.5.3.1. Key market trends, growth factors and opportunities
      • 7.3.5.3.2. Market size and forecast, by Component
      • 7.3.5.3.3. Market size and forecast, by Enterprise Size
      • 7.3.5.3.4. Market size and forecast, by Deployment
      • 7.3.5.4. Spain
      • 7.3.5.4.1. Key market trends, growth factors and opportunities
      • 7.3.5.4.2. Market size and forecast, by Component
      • 7.3.5.4.3. Market size and forecast, by Enterprise Size
      • 7.3.5.4.4. Market size and forecast, by Deployment
      • 7.3.5.5. Italy
      • 7.3.5.5.1. Key market trends, growth factors and opportunities
      • 7.3.5.5.2. Market size and forecast, by Component
      • 7.3.5.5.3. Market size and forecast, by Enterprise Size
      • 7.3.5.5.4. Market size and forecast, by Deployment
      • 7.3.5.6. Rest of Europe
      • 7.3.5.6.1. Key market trends, growth factors and opportunities
      • 7.3.5.6.2. Market size and forecast, by Component
      • 7.3.5.6.3. Market size and forecast, by Enterprise Size
      • 7.3.5.6.4. Market size and forecast, by Deployment
  • 7.4. Asia-Pacific
    • 7.4.1. Key trends and opportunities
    • 7.4.2. Market size and forecast, by Component
    • 7.4.3. Market size and forecast, by Enterprise Size
    • 7.4.4. Market size and forecast, by Deployment
    • 7.4.5. Market size and forecast, by country
      • 7.4.5.1. China
      • 7.4.5.1.1. Key market trends, growth factors and opportunities
      • 7.4.5.1.2. Market size and forecast, by Component
      • 7.4.5.1.3. Market size and forecast, by Enterprise Size
      • 7.4.5.1.4. Market size and forecast, by Deployment
      • 7.4.5.2. Japan
      • 7.4.5.2.1. Key market trends, growth factors and opportunities
      • 7.4.5.2.2. Market size and forecast, by Component
      • 7.4.5.2.3. Market size and forecast, by Enterprise Size
      • 7.4.5.2.4. Market size and forecast, by Deployment
      • 7.4.5.3. India
      • 7.4.5.3.1. Key market trends, growth factors and opportunities
      • 7.4.5.3.2. Market size and forecast, by Component
      • 7.4.5.3.3. Market size and forecast, by Enterprise Size
      • 7.4.5.3.4. Market size and forecast, by Deployment
      • 7.4.5.4. South Korea
      • 7.4.5.4.1. Key market trends, growth factors and opportunities
      • 7.4.5.4.2. Market size and forecast, by Component
      • 7.4.5.4.3. Market size and forecast, by Enterprise Size
      • 7.4.5.4.4. Market size and forecast, by Deployment
      • 7.4.5.5. Australia
      • 7.4.5.5.1. Key market trends, growth factors and opportunities
      • 7.4.5.5.2. Market size and forecast, by Component
      • 7.4.5.5.3. Market size and forecast, by Enterprise Size
      • 7.4.5.5.4. Market size and forecast, by Deployment
      • 7.4.5.6. Rest of Asia-Pacific
      • 7.4.5.6.1. Key market trends, growth factors and opportunities
      • 7.4.5.6.2. Market size and forecast, by Component
      • 7.4.5.6.3. Market size and forecast, by Enterprise Size
      • 7.4.5.6.4. Market size and forecast, by Deployment
  • 7.5. LAMEA
    • 7.5.1. Key trends and opportunities
    • 7.5.2. Market size and forecast, by Component
    • 7.5.3. Market size and forecast, by Enterprise Size
    • 7.5.4. Market size and forecast, by Deployment
    • 7.5.5. Market size and forecast, by country
      • 7.5.5.1. Brazil
      • 7.5.5.1.1. Key market trends, growth factors and opportunities
      • 7.5.5.1.2. Market size and forecast, by Component
      • 7.5.5.1.3. Market size and forecast, by Enterprise Size
      • 7.5.5.1.4. Market size and forecast, by Deployment
      • 7.5.5.2. Saudi Arabia
      • 7.5.5.2.1. Key market trends, growth factors and opportunities
      • 7.5.5.2.2. Market size and forecast, by Component
      • 7.5.5.2.3. Market size and forecast, by Enterprise Size
      • 7.5.5.2.4. Market size and forecast, by Deployment
      • 7.5.5.3. United Arab Emirates
      • 7.5.5.3.1. Key market trends, growth factors and opportunities
      • 7.5.5.3.2. Market size and forecast, by Component
      • 7.5.5.3.3. Market size and forecast, by Enterprise Size
      • 7.5.5.3.4. Market size and forecast, by Deployment
      • 7.5.5.4. South Africa
      • 7.5.5.4.1. Key market trends, growth factors and opportunities
      • 7.5.5.4.2. Market size and forecast, by Component
      • 7.5.5.4.3. Market size and forecast, by Enterprise Size
      • 7.5.5.4.4. Market size and forecast, by Deployment
      • 7.5.5.5. Rest of LAMEA
      • 7.5.5.5.1. Key market trends, growth factors and opportunities
      • 7.5.5.5.2. Market size and forecast, by Component
      • 7.5.5.5.3. Market size and forecast, by Enterprise Size
      • 7.5.5.5.4. Market size and forecast, by Deployment

CHAPTER 8: COMPETITIVE LANDSCAPE

  • 8.1. Introduction
  • 8.2. Top winning strategies
  • 8.3. Product Mapping of Top 10 Player
  • 8.4. Competitive Dashboard
  • 8.5. Competitive Heatmap
  • 8.6. Top player positioning, 2021

CHAPTER 9: COMPANY PROFILES

  • 9.1. cyclica inc.
    • 9.1.1. Company overview
    • 9.1.2. Key Executives
    • 9.1.3. Company snapshot
  • 9.2. BioSymetrics Inc.
    • 9.2.1. Company overview
    • 9.2.2. Key Executives
    • 9.2.3. Company snapshot
  • 9.3. Cloud Pharmaceuticals, Inc.
    • 9.3.1. Company overview
    • 9.3.2. Key Executives
    • 9.3.3. Company snapshot
  • 9.4. Deep Genomics
    • 9.4.1. Company overview
    • 9.4.2. Key Executives
    • 9.4.3. Company snapshot
  • 9.5. Atomwise Inc.
    • 9.5.1. Company overview
    • 9.5.2. Key Executives
    • 9.5.3. Company snapshot
  • 9.6. Alphabet Inc.
    • 9.6.1. Company overview
    • 9.6.2. Key Executives
    • 9.6.3. Company snapshot
  • 9.7. NVIDIA Corporation
    • 9.7.1. Company overview
    • 9.7.2. Key Executives
    • 9.7.3. Company snapshot
  • 9.8. International Business Machines Corporation
    • 9.8.1. Company overview
    • 9.8.2. Key Executives
    • 9.8.3. Company snapshot
  • 9.9. Microsoft Corporation
    • 9.9.1. Company overview
    • 9.9.2. Key Executives
    • 9.9.3. Company snapshot
  • 9.10. IBM
    • 9.10.1. Company overview
    • 9.10.2. Key Executives
    • 9.10.3. Company snapshot