세계의 Drug Discovery 분야 인공지능(AI) 시장 보고서(2025년)
Artificial Intelligence (AI) In Drug Discovery Global Market Report 2025
상품코드 : 1824486
리서치사 : The Business Research Company
발행일 : On Demand Report
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한글목차

Drug Discovery 분야 인공지능(AI) 시장 규모는 향후 몇 년 동안 비약적인 성장이 예상됩니다. 2029년에는 CAGR 26.1%로 58억 9,000만 달러로 성장할 것입니다. 예측 기간의 성장은 정부 지원, 헬스케어 지출 증가, 클라우드 기반 애플리케이션 및 서비스 채택 증가에 기인합니다. 예측 기간의 주요 동향으로는 멀티오믹스 데이터 통합, 표적 선택에 AI 활용, 약물 스크리닝에 AI 활용, AI 혁신 연구소 도입, 파트너십 및 협업에 대한 투자 증가 등을 꼽을 수 있습니다.

향후 5년간 26.1%의 성장률 전망은 지난번 예측보다 0.3% 소폭 하락한 수치입니다. 이 감소는 주로 미국과 다른 국가 간의 관세의 영향에 기인합니다. 관세 부과는 영국과 싱가포르에서 수입되는 인공지능(AI) 기반 분자 모델링 소프트웨어와 예측 흡수-분포-대사-대사-배설-독성(ADMET) 플랫폼의 비용을 상승시켜 신약개발을 지연시키고 연구비용을 상승시킬 수 있으며, 미국의 의약품 연구개발(R&D)에 혼란을 야기할 수 있습니다. 또한, 상호 관세와 무역 마찰 및 제한 강화로 인한 세계 경제 및 무역에 대한 악영향으로 인해 그 영향은 더욱 광범위하게 나타날 것으로 보입니다.

맞춤형 의료에 대한 수요 증가는 Drug Discovery 분야 인공지능(AI) 시장의 급격한 성장의 원동력이 되고 있습니다. 맞춤형 의료는 개인의 유전자나 단백질에 대한 지식을 바탕으로 치료를 조정하는 것으로, 그 중요성이 급증하고 있습니다. AI의 중요한 역할은 임상 개발의 다양한 단계와 새로운 맞춤형 의료 솔루션의 창출에 이르기까지 광범위하게 적용되고 있습니다. AI는 적절한 개입 대상을 식별하고 그 효과를 평가하는 데 큰 도움을 줄 수 있습니다. 특히, 미국 FDA가 2022년 12개의 맞춤형 의약품을 승인한 것은 새로 승인된 치료용 분자 실체의 약 34%에 해당하며, 이러한 급격한 증가를 증명합니다. 맞춤형 의료에 대한 수요 증가는 신약개발 AI 시장 확대에 박차를 가하고 있습니다.

목차

제1장 주요 요약

제2장 시장 특징

제3장 시장 동향과 전략

제4장 시장 : 금리, 인플레이션, 지정학, 무역 전쟁과 관세, 그리고 코로나와 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

KSM
영문 목차

영문목차

Artificial intelligence (AI) is a technology that simulates human intelligence in machines, enabling them to think and behave such as humans. AI is known for its ability to perform tasks quickly and with relatively few errors.

The primary technologies employed in AI for drug discovery are deep learning and machine learning. Deep learning is a technique within machine learning and AI that emulates how humans acquire knowledge. Data science, encompassing statistics and predictive modeling, integrates deep learning as a crucial component. Drug discovery involves various types of drugs, including small molecules and large molecules, and encompasses different therapeutic approaches such as c and others. The implementation of AI in drug discovery is seen across various end-users, including pharmaceutical companies, biopharmaceutical companies, academic and research institutes, among others.

Note that the outlook for this market is being affected by rapid changes in trade relations and tariffs globally. The report will be updated prior to delivery to reflect the latest status, including revised forecasts and quantified impact analysis. The report's Recommendations and Conclusions sections will be updated to give strategies for entities dealing with the fast-moving international environment.

The sharp rise in U.S. tariffs and the resulting trade tensions in spring 2025 are having a significant impact on the healthcare sector, especially in the supply of essential medical devices, diagnostic equipment, and pharmaceuticals. Hospitals and healthcare providers are grappling with higher costs for imported surgical tools, imaging systems, and consumables like syringes and catheters, many of which have limited domestic substitutes. These escalating expenses are putting pressure on healthcare budgets, prompting some providers to delay equipment upgrades or pass increased costs on to patients. Furthermore, tariffs on raw materials and components are disrupting the manufacturing of vital drugs and devices, leading to supply chain delays. In response, the industry is adopting diversified sourcing strategies, expanding local production where feasible, and pushing for tariff exemptions on critical medical products.

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

The artificial intelligence (AI) in drug discovery market size has grown exponentially in recent years. It will grow from $1.78 billion in 2024 to $2.33 billion in 2025 at a compound annual growth rate (CAGR) of 30.5%. The growth in the historic period can be attributed to growth in emerging markets, the rising prevalence of chronic diseases, the increased adoption of artificial intelligence (AI) for cost-efficient drug discovery, and the increasing strict quality regulations for drug manufacturers.

The artificial intelligence (AI) in drug discovery market size is expected to see exponential growth in the next few years. It will grow to $5.89 billion in 2029 at a compound annual growth rate (CAGR) of 26.1%. The growth in the forecast period can be attributed to government support, increasing healthcare expenditure, and rising adoption of cloud-based applications and services. Major trends in the forecast period include the integration of multi-omics data, the use of AI in target selection, the use of AI in drug screening, the introduction of AI innovation labs, and increasing investments in partnerships and collaborations.

The forecast of 26.1% growth over the next five years reflects a modest reduction of 0.3% from the previous estimate for this market. This reduction is primarily due to the impact of tariffs between the US and other countries. The imposition of tariffs may disrupt U.S. pharmaceutical Research and Development (R&D) by increasing costs for Artificial intelligence(AI)-based molecular modeling software and predictive Absorption, Distribution, Metabolism, Excretion, and Toxicity(ADMET) platforms imported from the UK and Singapore, potentially delaying new drug development and raising research costs. The effect will also be felt more widely due to reciprocal tariffs and the negative effect on the global economy and trade due to increased trade tensions and restrictions.

The escalating demand for personalized medicine stands as a driving force behind the burgeoning growth of the artificial intelligence (AI) in drug discovery market. Personalized medicine, which tailors treatments based on individual genetic or protein knowledge, has surged in importance. AI's pivotal role spans various phases of clinical development and in the creation of new personalized health solutions. It significantly aids in identifying suitable intervention targets and evaluating their effectiveness. Notably, the US FDA's approval of 12 personalized medicines in 2022, representing about 34% of newly endorsed therapeutic molecular entities, attests to this surge. The heightened demand for personalized medicine is thereby fueling the expansion of the AI in drug discovery market.

The increasing demand for reducing the overall time required for the drug discovery process is a significant driver behind the growth of artificial intelligence (AI) in the drug discovery market. Traditionally, it takes three to five years to identify and optimize molecules using animal models before they are evaluated in humans. In contrast, AI-based start-ups can identify and design new drugs in just a few days or months. In June 2024, Benevolent AI, a UK-based leader in applying advanced AI to accelerate biopharma drug discovery, announced a collaboration with AstraZeneca, a UK-based pharmaceutical and biotechnology company. Their partnership aims to leverage AI to enhance target discovery for chronic kidney disease and idiopathic pulmonary fibrosis. Recently, they reported advancements in developing additional targets, showcasing the effectiveness of AI-driven approaches in drug development.

Major players in the AI drug delivery sector are forging strategic collaborations to delve deeper into drug discovery leveraging AI, a move that's elevating their position within the artificial intelligence in drug discovery market. Take Atomwise, a US-based AI systems company, which partnered with Sanofi in August 2022. This collaboration aims to identify and explore up to five pharmacological targets utilizing Atomwise's AI-driven AtomNet technology. To facilitate the discovery of lead compounds for Sanofi's exclusive targets, Atomwise received an initial payment of $20 million from Sanofi, a prominent French pharmaceutical and healthcare company.

Major corporations are making significant investments in entities operating within the artificial intelligence (AI) in drug discovery domain. These investments aim to facilitate the identification and design of novel therapies, ultimately offering these models to other pharmaceutical firms. Given that drug discovery is both capital-intensive and time-consuming, such strategic investments provide vital funding for research and development of new drugs. This funding often serves as a catalyst for these companies to propel their drug discovery initiatives, expediting the introduction of new treatments into the market. For instance, in July 2023, Nvidia, a leading US-based software company, made a $50 million investment in Recursion Pharmaceuticals, a US-based biotech firm harnessing artificial intelligence (AI) for drug discovery. This infusion of capital is poised to empower Recursion in accelerating the development of its AI foundation models for biology and chemistry by leveraging Nvidia's cloud services.

In December 2022, Tecnotree Corporation, a Finnish telecommunications company, successfully acquired CognitiveScale for a total investment of $6 million. This strategic acquisition is expected to significantly boost Tecnotree's AI capabilities, presenting potential opportunities for the pharmaceutical industry. Leveraging these enhanced AI capabilities, Tecnotree aims to explore and develop innovative AI-powered solutions for drug discovery and advancement. CognitiveScale, a reputable AI software company based in the United States, will contribute to Tecnotree's strategic vision in this evolving landscape.

Major companies operating in the artificial intelligence (AI) in drug discovery market include IBM Corporation, Microsoft Corporation, NVIDIA Corporation, Exscientia, Alphabet, Insilico Medicine, Owkin Inc, Xtalpi Inc, Cloud Pharmaceuticals, Shanghai PharmaceuticS, Standigm, Indegene, Intuition Systems, Innoplexus, Takeda Pharmaceutical Company Ltd., RxPrism, Otsuka Pharmaceutical Co. Ltd., China National Pharmaceutical Group Co., Ltd., Jiangsu Hengrui Medicine Co., Ltd, Cipla Limited, Aurobindo Pharma Limited, Dr. Reddy's Laboratories Ltd., Sun Pharma, Tricog Health Services Pvt. Ltd., Alliance Pharm Pte Ltd., CytoReason, IIPharma, StoneWise, Adagene, GT Apeiron Therapeutics, Xbiome, Accutar Biotech, DeepMind, Renalytix AI, Iktos, Ipsen Pharma, Galderma S.A., BenevolentAI, Deepflare, Novartis, Gero, Ardigen, Botkin, Care Mentor AI, Diagnocat, GNS Healthcare, Merck & Co., Apotex, Pfizer, Gilead Sciences, Roche, Bayer, AbbVie Inc., GlaxoSmithKline, AstraZeneca, Amgen, Sanofi Pasteur, Abbott Laboratories, Teva Canada, Accord Healthcare Inc, Acerus Pharmaceuticals Corporation, AA Pharma Inc, Sanfer, Siegfried Rhein, Atomwise, Inc., Bioage, NuMedii, Envisagenics, Aria Pharmaceuticals, Verge Genomics, Berg LLC, Deep Genomics, Cyclica, IQVIA, Quris, GE Healthcare, Avanade, Group42 Holding Ltd, Ilara Health, Adcock Ingram, Johnson & Johnson, Eurolab, Ranbaxy (SA) (Pty) Ltd, Aspen, Rology, hearX Group, DilenyTech

North America was the largest region in the artificial intelligence (AI) in drug discovery market in 2024. Western Europe was the second largest region in the global artificial intelligence (AI) in drug discovery market share. The regions covered in the artificial intelligence (AI) in drug discovery market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa

The countries covered in the artificial intelligence (AI) in drug discovery market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Italy, Canada, Spain

The artificial intelligence (AI) in drug discovery market includes revenues earned by entities by offering AI for drug discovery. Artificial Intelligence (AI) for drug discovery is a technology that uses a simulation of the human intelligence process by machines to tackle complex problems in the drug discovery process. It helps to find new molecules to identify drug targets and develop personalized medicines in the pharmaceutical industry. 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.

Artificial Intelligence (AI) In Drug Discovery 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 artificial intelligence (ai) in drug discovery 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 artificial intelligence (ai) in drug discovery ? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward, including technological disruption, regulatory shifts, and changing consumer preferences? The artificial intelligence (ai) in drug discovery 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 technological advancements such as AI and automation, Russia-Ukraine war, trade tariffs (government-imposed import/export duties), elevated inflation and interest rates.

Scope

Table of Contents

1. Executive Summary

2. Artificial Intelligence (AI) In Drug Discovery Market Characteristics

3. Artificial Intelligence (AI) In Drug Discovery Market Trends And Strategies

4. Artificial Intelligence (AI) In Drug Discovery Market - Macro Economic Scenario Including The Impact Of Interest Rates, Inflation, Geopolitics, Trade Wars and Tariffs, And Covid And Recovery On The Market

5. Global Artificial Intelligence (AI) In Drug Discovery Growth Analysis And Strategic Analysis Framework

6. Artificial Intelligence (AI) In Drug Discovery Market Segmentation

7. Artificial Intelligence (AI) In Drug Discovery Market Regional And Country Analysis

8. Asia-Pacific Artificial Intelligence (AI) In Drug Discovery Market

9. China Artificial Intelligence (AI) In Drug Discovery Market

10. India Artificial Intelligence (AI) In Drug Discovery Market

11. Japan Artificial Intelligence (AI) In Drug Discovery Market

12. Australia Artificial Intelligence (AI) In Drug Discovery Market

13. Indonesia Artificial Intelligence (AI) In Drug Discovery Market

14. South Korea Artificial Intelligence (AI) In Drug Discovery Market

15. Western Europe Artificial Intelligence (AI) In Drug Discovery Market

16. UK Artificial Intelligence (AI) In Drug Discovery Market

17. Germany Artificial Intelligence (AI) In Drug Discovery Market

18. France Artificial Intelligence (AI) In Drug Discovery Market

19. Italy Artificial Intelligence (AI) In Drug Discovery Market

20. Spain Artificial Intelligence (AI) In Drug Discovery Market

21. Eastern Europe Artificial Intelligence (AI) In Drug Discovery Market

22. Russia Artificial Intelligence (AI) In Drug Discovery Market

23. North America Artificial Intelligence (AI) In Drug Discovery Market

24. USA Artificial Intelligence (AI) In Drug Discovery Market

25. Canada Artificial Intelligence (AI) In Drug Discovery Market

26. South America Artificial Intelligence (AI) In Drug Discovery Market

27. Brazil Artificial Intelligence (AI) In Drug Discovery Market

28. Middle East Artificial Intelligence (AI) In Drug Discovery Market

29. Africa Artificial Intelligence (AI) In Drug Discovery Market

30. Artificial Intelligence (AI) In Drug Discovery Market Competitive Landscape And Company Profiles

31. Artificial Intelligence (AI) In Drug Discovery Market Other Major And Innovative Companies

32. Global Artificial Intelligence (AI) In Drug Discovery Market Competitive Benchmarking And Dashboard

33. Key Mergers And Acquisitions In The Artificial Intelligence (AI) In Drug Discovery Market

34. Recent Developments In The Artificial Intelligence (AI) In Drug Discovery Market

35. Artificial Intelligence (AI) In Drug Discovery Market High Potential Countries, Segments and Strategies

36. Appendix

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