生命科學的人工智能的全球市場 - 成長與趨勢,市場預測

Artificial Intelligence in Life Sciences Market - Growth, Trends, and Forecast (2019 - 2024)

出版商 Mordor Intelligence LLP 商品編碼 669987
出版日期 內容資訊 英文 100 Pages
商品交期: 2-3個工作天內
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生命科學的人工智能的全球市場 - 成長與趨勢,市場預測 Artificial Intelligence in Life Sciences Market - Growth, Trends, and Forecast (2019 - 2024)
出版日期: 2019年03月01日內容資訊: 英文 100 Pages


第1章 簡介

  • 調查的成果
  • 調查的前提條件
  • 市場範圍

第2章 調查手法

第3章 摘要整理

第4章 市場動態

  • 市場概要
  • 簡介
  • 促進要素
  • 抑制因素
  • 技術的短評
  • 波特的五力分析

第5章 市場分類

  • 各應用領域
    • 藥物研發
    • 醫療診斷
    • 生物科技
    • 臨床試驗
    • 精密、個體化醫藥品
    • 病患監測
  • 各地區
    • 北美
    • 歐洲
    • 亞太地區
    • 其他

第6章 競爭的展望

  • 企業簡介
    • IBM Corporation
    • NuMedii Inc.
    • Atomwise Inc
    • Lifegraph
    • Cyrcadia Health Inc.
    • Numerate Inc.
    • Sensely Inc.
    • Sophia Genetics SA
    • Insilico Medicine Inc.
    • Enlitic Inc.
    • APIXIO Inc.
    • Zebra Medical Vision
    • Lifegraph Limited
    • twoXAR Inc.
    • AiCure LLC

第7章 市場機會及今後趨勢

  • 投資方案


Product Code: 62326

Market Overview

Artificial Intelligence in Life Sciences Market was valued at USD 902.1 million is expected to grow at a CAGR of over 21.1% during the forecast period (2019-2024). Although artificial intelligence has been in the market in the late 1950s, the technology has become commercially accessible in the past few years. The primary reason for this accelerated growth in recent years is the massive availability of data in the life sciences sector.

As AI operates on large sets of data, the availability of such data becomes a key factor for establishing a suitable environment for the growth of AI-based solutions. With innovations in mobile technology and sensors, even the present day's wearables like smartwatches and fitness trackers, have enough computing power to generate and process vast amounts of data.

In fact, according to the recent estimates of Consumer Technology Association, a prominent standard and trade organization for the consumer electronics industry based in the United States, health and fitness trackers accounted for more than 47% of the wearables devices sold in 2017. This scenario coupled with several medical devices used in healthcare sector generates huge sets of data that could make use of AI to derive useful results.

AI is increasingly becoming popular in drug discovery, personalized medicine, biotechnology, and clinical trials. With increasing healthcare spending in almost all parts of the world, the pharmaceutical industry has been involved in extreme R&D activities in the past few years.

Scope of the Report

Artificial Intelligence (AI) is a highly data-driven technology. In the life sciences sector, it is generally employed to make meaningful relations from loosely coupled data. With the advent of the third wave of AI, it is estimated that advanced AI solutions in the current market scenario can learn and evolve as they are being used.

Key Market Trends

Clinical Trails to Hold Significant Share

Clinical trials are one of the most data-intensive tasks in the life sciences industry. They generate vast sets of data every day monitoring several variables of a patient under observation. Subjecting these data sets to intelligent AI algorithms can help the researchers to screen meaningful correlation even between loosely coupled data.

This is encouraging many pharmaceutical companies and clinical research organizations to invest in technologies, like artificial intelligence. In the current market scenario, rapid adoption of AI is widely seen in the pharmaceutical sector, who are responsible for almost 50% of the clinical trials conducted globally every year.

Novartis claims that the deployment of QuantamBlack's solutions has reduced patient enrolment times by 10-15%. Additionally, as of March 2018, the company has entered a partnership with IBM to make use of IBMs AI platform, IBM-Watson, to improve clinical trial recruitment, and make use of intelligent AI algorithms to predict medication efficacy.

Such initiatives are encouraging many companies to invest in AI solutions tailor-made for clinical trials. Many prominent companies, such as GlaxoSmithKline, Sanofi, Pfizer Mitsubishi Tanabe Pharma, and Genentech among others, are investing in AI-based clinical trails startups and solutions to make clinical trials more affordable.

India to Exhibit Highest Growth

India, the third-largest pharmaceutical market in Asia, is increasingly gaining much-needed government focus on expanding affordable health care. As part of the Union Budget FY19, the government announced the world's largest National Health Protection Scheme, for which the government set aside an investment worth USD 307.6 million, to provide coverage of up to USD 7,690 per year, to 500 million people belonging to financially vulnerable households, for the treatment of serious ailments. Simultaneously, AI and machine learning have already started penetrating various industries across India, with healthcare being one of the biggest beneficiaries of the AI revolution. According to a report by CIS India published in 2018, AI could help add USD 957 billion to the Indian economy by 2035. In the July-September 2017 quarter, around 16 Indian healthcare IT companies received funding. The adoption of AI in life sciences in India is being driven by the likes of Microsoft, and a slew of health-tech startups.

Competitive Landscape

The artificial intelligence in the life sciences market has been gaining a competitive edge in recent years. In terms of market share, few of the major players currently dominate the market. These major players with a prominent share in the market are focusing on expanding their customer base across foreign countries. These companies are leveraging on strategic collaborative initiatives to increase their market share and increase their profitability. In Oct 2018, Lifegraph launched their new app on the Google Play Store. It uses AI in the core to forecast the state of patient health. The app named Lifegraph - AI technology for migraine management, was launched to help track changes in the behavior and weather throughout the day and, using machine learning, predicts an imminent attack for actionable self-care.

Reasons to Purchase this report:

  • The market estimate (ME) sheet in Excel format
  • Report customization as per the client's requirements
  • 3 months of analyst support

Table of Contents


  • 1.1 Study Deliverables
  • 1.2 Study Assumptions
  • 1.3 Scope of the Study




  • 4.1 Market Overview
  • 4.2 Introduction to Market Drivers and Restraints
  • 4.3 Market Drivers
    • 4.3.1 Rising Adoption Of Ai In The Field Of R&D
    • 4.3.2 High Emphasis On The Development Of Precision Medicine And Personalized Drugs
    • 4.3.3 Increasing Demand For AI In Drug Discovery
  • 4.4 Market Restraints
    • 4.4.1 High Initial Costs And Concerns Over The Replacement Of Human Workforce
  • 4.5 Technology Snapshot
  • 4.6 Industry Attractiveness Porters Five Force Analysis
    • 4.6.1 Threat of New Entrants
    • 4.6.2 Bargaining Power of Buyers/Consumers
    • 4.6.3 Bargaining Power of Suppliers
    • 4.6.4 Threat of Substitute Products
    • 4.6.5 Intensity of Competitive Rivalry


  • 5.1 By Application
    • 5.1.1 Drug Discovery
    • 5.1.2 Medical Diagnosis
    • 5.1.3 Biotechnology
    • 5.1.4 Clinical Trails
    • 5.1.5 Precision and Personalized Medicine
    • 5.1.6 Patient Monitoring
  • 5.2 Geography
    • 5.2.1 North America
      • US
      • Canada
    • 5.2.2 Europe
      • Germany
      • UK
      • France
      • Rest of Europe
    • 5.2.3 Asia Pacific
      • China
      • Japan
      • India
      • South Korea
      • Rest of Asia-Pacific
    • 5.2.4 Rest of the World


  • 6.1 Company Profiles
    • 6.1.1 IBM Corporation
    • 6.1.2 NuMedii Inc.
    • 6.1.3 Atomwise Inc
    • 6.1.4 Lifegraph
    • 6.1.5 Cyrcadia Health Inc.
    • 6.1.6 Numerate Inc.
    • 6.1.7 Sensely Inc.
    • 6.1.8 Sophia Genetics SA
    • 6.1.9 Insilico Medicine Inc.
    • 6.1.10 Enlitic Inc.
    • 6.1.11 APIXIO Inc.
    • 6.1.12 Zebra Medical Vision
    • 6.1.13 Lifegraph Limited
    • 6.1.14 twoXAR Inc.
    • 6.1.15 AiCure LLC


  • 7.1 Investment Scenario
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