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세계의 제약 업계 머신러닝(ML) 시장 보고서(2025년)
Machine Learning (ML) in The Pharmaceutical Industry Global Market Report 2025
상품코드 : 1693203
리서치사 : The Business Research Company
발행일 : On Demand Report
페이지 정보 : 영문 200 Pages
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한글목차

제약 업계 머신러닝(ML) 시장 규모는 향후 몇 년 동안 비약적인 성장을 보일 것으로 예상되며, 2029년에는 35.8%의 연평균 성장률(CAGR)로 139억 9,000만 달러에 달할 것으로 예상됩니다. 예측 기간의 성장은 생물학적 데이터의 복잡성 증가, 컴퓨팅 성능 향상, 업계 인식 및 교육, 환자 중심 의료 솔루션의 증가에 기인합니다. 예측 기간의 주요 동향으로는 AI와 제약사 간 제휴 및 협력, 약물 진단 치료, ML 시스템의 상호운용성, 임상시험의 분산화, AI 기반 바이오마커 발견 등이 있습니다.

인공지능(AI)의 활용 확대가 제약 분야에서의 머신러닝(ML) 확대에 박차를 가하고 있습니다. 분석, 추론, 학습과 같은 복잡한 작업을 수행하기 위해 인간의 인지 능력을 모방하는 AI는 복잡한 작업을 수행할 수 있는 모델을 생성하기 위해 데이터에 대해 훈련된 알고리즘을 채택하는 AI의 하위 집합인 ML을 뒷받침하는 중요한 원동력입니다. 제약 기술 및 약물전달 설계에 활용되어 복잡한 과제에 대한 가속화된 솔루션을 제공하고 있습니다. 이들은 약물전달 프로세스를 혁신하고, 의사결정 도구를 개선하며, 보다 효과적인 의사결정을 위해 방대한 양의 데이터를 관리할 수 있는 잠재력을 가지고 있습니다. 예를 들어, 2023년 6월 포브스(Forbes)가 보도한 바에 따르면, 영국에서는 약 43만 2,000개의 조직, 즉 6곳 중 1곳이 적어도 하나의 AI 기술을 도입하고 있습니다. 또한 대기업의 68%, 중견기업의 33%, 중소기업의 15%가 적어도 하나의 AI 기술을 채택하고 있습니다. 결과적으로 AI 도입의 증가는 제약 산업에서 ML을 촉진할 수 있는 태세를 갖추고 있습니다.

제약 업계 머신러닝(ML) 분야의 주요 기업들은 신약개발 역량을 강화하기 위해 신약개발 소프트웨어를 포함한 사용자 친화적인 소프트웨어 플랫폼 구축에 집중하고 있습니다. 신약개발 소프트웨어는 신약 발굴 및 개발에 활용되는 다양한 전문 도구와 플랫폼을 포괄합니다. 예를 들어, 2023년 12월 Merck &Co.Inc.는 신약개발 소프트웨어 AIDDISON을 발표했습니다. AIDDISON은 생성적 AI, ML, 컴퓨터 지원 약물 설계를 통해 신약개발과 합성을 통합하는 최초의 서비스형 소프트웨어 플랫폼으로, 연구실은 AIDDISON을 통해 방대한 화학적 공간에서 적절한 약물 후보를 찾아낼 수 있습니다. 600억 개가 넘는 화학적 표적에서 화합물을 가상으로 스크리닝하고, 보다 안전하고 비용 효율적이며 수율이 높은 약물 제조를 위한 합성 경로를 평가할 수 있습니다.

목차

제1장 주요 요약

제2장 시장 특징

제3장 시장 동향과 전략

제4장 시장 - 금리, 인플레이션, 지정학, 코로나, 회복이 시장에 미치는 영향을 포함한 거시경제 시나리오

제5장 세계의 성장 분석과 전략 분석 프레임워크

제6장 시장 세분화

제7장 지역별·국가별 분석

제8장 아시아태평양 시장

제9장 중국 시장

제10장 인도 시장

제11장 일본 시장

제12장 호주 시장

제13장 인도네시아 시장

제14장 한국 시장

제15장 서유럽 시장

제16장 영국 시장

제17장 독일 시장

제18장 프랑스 시장

제19장 이탈리아 시장

제20장 스페인 시장

제21장 동유럽 시장

제22장 러시아 시장

제23장 북미 시장

제24장 미국 시장

제25장 캐나다 시장

제26장 남미 시장

제27장 브라질 시장

제28장 중동 시장

제29장 아프리카 시장

제30장 경쟁 구도와 기업 개요

제31장 기타 주요 기업과 혁신적 기업

제32장 세계의 시장 경쟁 벤치마킹과 대시보드

제33장 주요 인수합병

제34장 최근의 시장 동향

제35장 시장 잠재력이 높은 국가, 부문, 전략

제36장 부록

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영문 목차

영문목차

Machine learning (ML) in the pharmaceutical industry market involves the application of artificial intelligence (AI) algorithms and techniques to enhance drug discovery, development, and manufacturing processes. Regulatory compliance and overcoming challenges related to data quality, research gaps, and regulatory uncertainty are essential for implementing ML solutions in this industry.

The primary components of machine learning in the pharmaceutical industry are solutions and services. Solutions are applications or systems that use ML algorithms to tackle specific challenges or tasks in the pharmaceutical sector. These solutions can be deployed on the cloud or on-premise and cater to enterprises of various sizes, including small and medium enterprises (SMEs) and large enterprises.

The machine learning (ML) in the pharmaceutical industry market research report is one of a series of new reports from The Business Research Company that provides machine learning (ML) in the pharmaceutical industry market statistics, including machine learning (ML) in the pharmaceutical industry global market size, regional shares, competitors with machine learning (ML) in the pharmaceutical industry market share, detailed machine learning (ML) in the pharmaceutical industry market segments, market trends, and opportunities, and any further data you may need to thrive in the machine learning (ML) in the pharmaceutical industry. This machine learning (ML) in the pharmaceutical industry market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenarios of the industry.

The machine learning (ML) in the pharmaceutical industry market size has grown exponentially in recent years. It will grow from $3.02 billion in 2024 to $4.11 billion in 2025 at a compound annual growth rate (CAGR) of 35.9%. The growth in the historic period can be attributed to increased adoption of federated learning, accelerated drug discovery timelines, enhanced drug safety and pharmacovigilance, expansion of precision medicine applications.

The machine learning (ML) in the pharmaceutical industry market size is expected to see exponential growth in the next few years. It will grow to $13.99 billion in 2029 at a compound annual growth rate (CAGR) of 35.8%. The growth in the forecast period can be attributed to increasing complexity of biological data, growing computational power, increasing industry awareness and education, patient-centric healthcare solutions. Major trends in the forecast period include AI-pharma partnerships and collaborations, drug-agnostic therapies, interoperability of ML systems, decentralized clinical trials, AI-driven biomarker discovery.

The growing use of artificial intelligence (AI) is fueling the expansion of machine learning (ML) in the pharmaceutical sector. AI, which mimics human cognition to execute intricate tasks such as analysis, reasoning, and learning, is a key driver behind ML, a subset of AI that employs algorithms trained on data to generate models capable of performing complex tasks. AI and ML have been harnessed in pharmaceutical technology and drug delivery design, providing accelerated solutions to intricate challenges. They hold the potential to revolutionize the drug delivery process, improve decision-making tools, and manage vast amounts of data for more effective decision-making. For example, as reported by Forbes in June 2023, around 432,000 UK organizations, or one in six, have adopted at least one AI technology. Furthermore, 68% of large businesses, 33% of medium-sized businesses, and 15% of small businesses have adopted at least one AI technology. Consequently, the increasing adoption of AI is poised to propel ML in the pharmaceutical industry.

Key players in the machine learning (ML) sector of the pharmaceutical industry are concentrating on creating user-friendly software platforms, including drug discovery software, to enhance their drug discovery capabilities. Drug discovery software encompasses various specialized tools and platforms utilized in identifying and developing new pharmaceutical drugs. For instance, in December 2023, Merck & Co. Inc., a US-based pharmaceutical company, introduced the AIDDISON drug discovery software. This software-as-a-service platform is the first of its kind, integrating drug discovery and synthesis through generative AI, ML, and computer-aided drug design. AIDDISON allows laboratories to pinpoint suitable drug candidates within a vast chemical space, virtually screen compounds from over 60 billion chemical targets, and assess synthesis routes for safer, more cost-effective, and higher-yield drug production.

In July 2023, BioNTech SE, a Germany-based biopharmaceutical company, acquired InstaDeep for $541 million. This acquisition is anticipated to enhance BioNTech's leading position in AI-powered drug discovery, design, and development. InstaDeep, a UK-based technology company, provides a variety of AI solutions and machine learning services tailored for the pharmaceutical sector.

Major companies operating in the machine learning (ML) in the pharmaceutical industry market report are Amazon.com Inc., Alphabet Inc., Microsoft Corporation, Dell Technologies Inc., Hitachi Ltd., International Business Machines Corporation, Cisco Systems Inc., Oracle Corporation, Honeywell International Inc., Hewlett Packard Enterprise, NVIDIA Corporation, Thales SA, Atos SE, Hexagon AB, Palantir Technologies Inc., Verient Systems Inc., Alteryx Inc., Comet ML Inc., GAVS Technologies, NEC Corporation, Veritone Inc., H2O.ai Inc., Sparkcognition Inc., Akira AI, Deep Genomics Inc., Cloud Pharmaceuticals Inc., Atomwise Inc., Cyclica Inc., BioSymetrics Inc., Neptune Labs

North America was the largest region in the machine learning in the pharmaceutical industry market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the machine learning (ml) in the pharmaceutical industry market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

The countries covered in the machine learning (ml) in the pharmaceutical industry market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The machine learning (ML) in the pharmaceutical industry market consists of revenues earned by entities by providing components of machine learning (ML) in the pharmaceutical industry market such as solutions and services. The market value includes the value of related goods sold by the service provider or included within the service offering. The machine learning (ML) in the pharmaceutical industry market also includes sales of central processing units (CPUs), random access memory, storage systems, and graphics processing units (GPUs). Values in this market are 'factory gate' values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

Machine Learning (ML) in The Pharmaceutical Industry Global Market Report 2025 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.

This report focuses on machine learning (ml) in the pharmaceutical industry market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.

Reasons to Purchase

Where is the largest and fastest growing market for machine learning (ml) in the pharmaceutical industry ? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward? The machine learning (ml) in the pharmaceutical industry market global report from the Business Research Company answers all these questions and many more.

The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market's historic and forecast market growth by geography.

The forecasts are made after considering the major factors currently impacting the market. These include the Russia-Ukraine war, rising inflation, higher interest rates, and the legacy of the COVID-19 pandemic.

Scope

Table of Contents

1. Executive Summary

2. Machine Learning (ML) in The Pharmaceutical Industry Market Characteristics

3. Machine Learning (ML) in The Pharmaceutical Industry Market Trends And Strategies

4. Machine Learning (ML) in The Pharmaceutical Industry Market - Macro Economic Scenario Including The Impact Of Interest Rates, Inflation, Geopolitics, Covid And Recovery On The Market

5. Global Machine Learning (ML) in The Pharmaceutical Industry Growth Analysis And Strategic Analysis Framework

6. Machine Learning (ML) in The Pharmaceutical Industry Market Segmentation

7. Machine Learning (ML) in The Pharmaceutical Industry Market Regional And Country Analysis

8. Asia-Pacific Machine Learning (ML) in The Pharmaceutical Industry Market

9. China Machine Learning (ML) in The Pharmaceutical Industry Market

10. India Machine Learning (ML) in The Pharmaceutical Industry Market

11. Japan Machine Learning (ML) in The Pharmaceutical Industry Market

12. Australia Machine Learning (ML) in The Pharmaceutical Industry Market

13. Indonesia Machine Learning (ML) in The Pharmaceutical Industry Market

14. South Korea Machine Learning (ML) in The Pharmaceutical Industry Market

15. Western Europe Machine Learning (ML) in The Pharmaceutical Industry Market

16. UK Machine Learning (ML) in The Pharmaceutical Industry Market

17. Germany Machine Learning (ML) in The Pharmaceutical Industry Market

18. France Machine Learning (ML) in The Pharmaceutical Industry Market

19. Italy Machine Learning (ML) in The Pharmaceutical Industry Market

20. Spain Machine Learning (ML) in The Pharmaceutical Industry Market

21. Eastern Europe Machine Learning (ML) in The Pharmaceutical Industry Market

22. Russia Machine Learning (ML) in The Pharmaceutical Industry Market

23. North America Machine Learning (ML) in The Pharmaceutical Industry Market

24. USA Machine Learning (ML) in The Pharmaceutical Industry Market

25. Canada Machine Learning (ML) in The Pharmaceutical Industry Market

26. South America Machine Learning (ML) in The Pharmaceutical Industry Market

27. Brazil Machine Learning (ML) in The Pharmaceutical Industry Market

28. Middle East Machine Learning (ML) in The Pharmaceutical Industry Market

29. Africa Machine Learning (ML) in The Pharmaceutical Industry Market

30. Machine Learning (ML) in The Pharmaceutical Industry Market Competitive Landscape And Company Profiles

31. Machine Learning (ML) in The Pharmaceutical Industry Market Other Major And Innovative Companies

32. Global Machine Learning (ML) in The Pharmaceutical Industry Market Competitive Benchmarking And Dashboard

33. Key Mergers And Acquisitions In The Machine Learning (ML) in The Pharmaceutical Industry Market

34. Recent Developments In The Machine Learning (ML) in The Pharmaceutical Industry Market

35. Machine Learning (ML) in The Pharmaceutical Industry Market High Potential Countries, Segments and Strategies

36. Appendix

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