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1298445

製藥行業機器學習 (ML) 市場：按組件、按公司規模、按部署：2021-2031 年全球機會分析和行業預測

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
出版日期: | 出版商: Allied Market Research | 英文 280 Pages | 商品交期: 2-3個工作天內

價格

製藥行業機器學習 (ML) 的全球市場預計到 2031 年將達到 262 億美元，從 2021 年的 12 億美元增長到 2022 年至 2031 年的複合年增長率為 37.9%。

機器學習在醫藥行業市場-IMG1

製藥行業的機器學習（ML）是指使用算法和統計模型來分析數據，以對藥物開發、臨床試驗、監管審批、營銷和銷售做出預測和決策。

機器學習在製藥行業中變得越來越重要，尤其是在臨床試驗中。在機器學習算法的幫助下，製藥公司可以分析大量數據並識別模式。這在臨床試驗設計中特別有用，其中機器學習可以幫助優化臨床試驗設計和患者選擇，從而可能節省成本並加速開發過程。例如，機器學習算法可用於分析患者數據，以識別指示特定藥物是否可能有效治療特定疾病的生物標誌物。

監管限制是製藥行業機器學習 (ML) 面臨的主要挑戰之一。機器學習算法被認為是一種新技術，在用於製藥應用之前必須滿足嚴格的監管要求。美國食品和藥物管理局 (FDA) 等監管機構對於開發和驗證機器學習算法有嚴格的指導方針。這些指南要求算法在大型且多樣化的數據集上進行驗證，以證明其準確性、可靠性和安全性。機器學習算法的驗證過程既耗時又昂貴，這給企業採用這些技術帶來了挑戰。

機器學習在製藥行業尤其是藥品安全領域具有巨大潛力。在機器學習的幫助下，可以分析大量數據並識別可用於在潛在安全問題發生之前進行預測的模式。這使得製藥公司能夠採取措施預防藥物不良反應並提高患者安全。機器學習算法可以分析各種數據源，包括電子病歷、社交媒體和其他來源，以檢測副作用。這些算法可以識別人類分析師看不見的模式，使製藥公司能夠在潛在的安全問題蔓延之前發現它們。

COVID-19 大流行給製藥行業帶來了重大變化，包括對創新解決方案、更快的藥物開發流程和更高效的供應鏈管理的需求增加。機器學習是在應對這些挑戰和影響製藥行業方面發揮關鍵作用的技術之一。機器學習算法可以快速準確地分析大量數據，以深入了解疾病模式、識別潛在的藥物靶標並預測正在開發的藥物的功效。機器學習廣泛應用於藥物發現和藥物開發，包括在大流行期間識別潛在的 COVID-19 療法和疫苗。

目錄

第 1 章 簡介

第二章執行摘要

第三章市場概況

  • 市場定義和範圍
  • 主要發現
    • 影響因素
    • 主要投資口袋
  • 波特五力分析
  • 市場動態
    • 促進者
    • 抑製劑
    • 機會
  • COVID-19 市場影響分析
  • 關鍵監管分析
  • 市場份額分析
  • 專利情況
  • 監管指南
  • 價值鏈分析

4 製藥行業機器學習 (ML) 市場（按組成部分）

  • 概述
    • 市場規模及預測
  • 解決方案
    • 主要市場趨勢、增長動力和機遇
    • 市場規模/預測：按地區
    • 市場份額分析：按國家分類
  • 服務
    • 主要市場趨勢、增長動力和機遇
    • 市場規模/預測：按地區
    • 市場份額分析：按國家分類

5 製藥行業機器學習 (ML) 市場（按公司規模）

  • 概述
    • 市場規模及預測
  • 中小企業
    • 主要市場趨勢、增長動力和機遇
    • 市場規模/預測：按地區
    • 市場份額分析：按國家分類
  • 大公司
    • 主要市場趨勢、增長動力和機遇
    • 市場規模/預測：按地區
    • 市場份額分析：按國家分類

6 製藥行業機器學習 (ML) 市場（按應用）

  • 概述
    • 市場規模及預測
  • 雲
    • 主要市場趨勢、增長動力和機遇
    • 市場規模/預測：按地區
    • 市場份額分析：按國家分類
  • 本地
    • 主要市場趨勢、增長動力和機遇
    • 市場規模/預測：按地區
    • 市場份額分析：按國家分類

7 按地區劃分的製藥行業機器學習 (ML) 市場

  • 概述
    • 市場規模/預測：按地區
  • 北美
    • 主要趨勢和機遇
    • 市場規模/預測：按組件
    • 市場規模/預測：按公司規模
    • 市場規模/預測：按部署
    • 市場規模/預測：按國家
      • 美國
      • 主要市場趨勢、增長動力和機遇
      • 市場規模/預測：按組件
      • 市場規模/預測：按公司規模
      • 市場規模/預測：按部署
      • 加拿大
      • 主要市場趨勢、增長動力和機遇
      • 市場規模/預測：按組件
      • 市場規模/預測：按公司規模
      • 市場規模/預測：按部署
      • 墨西哥
      • 主要市場趨勢、增長動力和機遇
      • 市場規模/預測：按組件
      • 市場規模/預測：按公司規模
      • 市場規模/預測：按部署
  • 歐洲
    • 主要趨勢和機遇
    • 市場規模/預測：按組件
    • 市場規模/預測：按公司規模
    • 市場規模/預測：按部署
    • 市場規模/預測：按國家
      • 德國
      • 主要市場趨勢、增長動力和機遇
      • 市場規模/預測：按組件
      • 市場規模/預測：按公司規模
      • 市場規模/預測：按部署
      • 英國
      • 主要市場趨勢、增長動力和機遇
      • 市場規模/預測：按組件
      • 市場規模/預測：按公司規模
      • 市場規模/預測：按部署
      • 法國
      • 主要市場趨勢、增長動力和機遇
      • 市場規模/預測：按組件
      • 市場規模/預測：按公司規模
      • 市場規模/預測：按部署
      • 西班牙
      • 主要市場趨勢、增長動力和機遇
      • 市場規模/預測：按組件
      • 市場規模/預測：按公司規模
      • 市場規模/預測：按部署
      • 意大利
      • 主要市場趨勢、增長動力和機遇
      • 市場規模/預測：按組件
      • 市場規模/預測：按公司規模
      • 市場規模/預測：按部署
      • 歐洲其他地區
      • 主要市場趨勢、增長動力和機遇
      • 市場規模/預測：按組件
      • 市場規模/預測：按公司規模
      • 市場規模/預測：按部署
  • 亞太地區
    • 主要趨勢和機遇
    • 市場規模/預測：按組件
    • 市場規模/預測：按公司規模
    • 市場規模/預測：按部署
    • 市場規模/預測：按國家
      • 中國
      • 主要市場趨勢、增長動力和機遇
      • 市場規模/預測：按組件
      • 市場規模/預測：按公司規模
      • 市場規模/預測：按部署
      • 日本
      • 主要市場趨勢、增長動力和機遇
      • 市場規模/預測：按組件
      • 市場規模/預測：按公司規模
      • 市場規模/預測：按部署
      • 印度
      • 主要市場趨勢、增長動力和機遇
      • 市場規模/預測：按組件
      • 市場規模/預測：按公司規模
      • 市場規模/預測：按部署
      • 韓國
      • 主要市場趨勢、增長動力和機遇
      • 市場規模/預測：按組件
      • 市場規模/預測：按公司規模
      • 市場規模/預測：按部署
      • 澳大利亞
      • 主要市場趨勢、增長動力和機遇
      • 市場規模/預測：按組件
      • 市場規模/預測：按公司規模
      • 市場規模/預測：按部署
      • 亞太其他地區
      • 主要市場趨勢、增長動力和機遇
      • 市場規模/預測：按組件
      • 市場規模/預測：按公司規模
      • 市場規模/預測：按部署
  • 拉丁美洲/中東/非洲
    • 主要趨勢和機遇
    • 市場規模/預測：按組件
    • 市場規模/預測：按公司規模
    • 市場規模/預測：按部署
    • 市場規模/預測：按國家
      • 巴西
      • 主要市場趨勢、增長動力和機遇
      • 市場規模/預測：按組件
      • 市場規模/預測：按公司規模
      • 市場規模/預測：按部署
      • 沙特阿拉伯
      • 主要市場趨勢、增長動力和機遇
      • 市場規模/預測：按組件
      • 市場規模/預測：按公司規模
      • 市場規模/預測：按部署
      • 阿拉伯聯合酋長國
      • 主要市場趨勢、增長動力和機遇
      • 市場規模/預測：按組件
      • 市場規模/預測：按公司規模
      • 市場規模/預測：按部署
      • 南非
      • 主要市場趨勢、增長動力和機遇
      • 市場規模/預測：按組件
      • 市場規模/預測：按公司規模
      • 市場規模/預測：按部署
      • 其他地區
      • 主要市場趨勢、增長動力和機遇
      • 市場規模/預測：按組件
      • 市場規模/預測：按公司規模
      • 市場規模/預測：按部署

第8章 競爭格局

  • 介紹
  • 關鍵成功策略
  • 10大公司產品圖
  • 比賽儀表板
  • 比賽熱圖
  • 2021 年頂級公司定位

第九章公司簡介

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

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