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市場調査レポート
商品コード
1541326
ライフサイエンスにおける人工知能市場レポート:オファリング、展開、用途、地域別、2024~2032年Artificial Intelligence in Life Sciences Market Report by Offering, Deployment, Application, and Region 2024-2032 |
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ライフサイエンスにおける人工知能市場レポート:オファリング、展開、用途、地域別、2024~2032年 |
出版日: 2024年08月10日
発行: IMARC
ページ情報: 英文 137 Pages
納期: 2~3営業日
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世界のライフサイエンスにおける人工知能市場規模は2023年に24億米ドルに達しました。今後、IMARC Groupは、2024~2032年にかけて22.4%の成長率(CAGR)を示し、2032年までに154億米ドルに達すると予測しています。複雑な疾患の有病率の上昇、医療画像解析におけるAIの採用の増加、ゲノム研究と解析へのAIの統合、AIと新興技術の融合などが、市場を推進する主要要因の一部です。
主要市場促進要因:ライフサイエンスセグメントにおける人工知能は、主にゲノム配列や電子カルテから得られる生物医療データ量の増加により、効果的な管理と分析のために強力なAIツールの組み込みが必要となっています。これに伴い、人工知能は創薬・開発プロセスを加速させ、時間とコストを大幅に削減するのに役立っています。さらに、臨床現場でのAI統合に対する規制当局のサポートや、機械学習と計算アルゴリズムの進歩が、ライフサイエンスにおける人工知能市場の成長をさらに促進しています。
主要市場動向:ライフサイエンスセグメントにおける人工知能の主要市場動向には、クラウドコンピューティングやモノのインターネット(IoT)デバイスとともに人工知能が統合され、データへのアクセス性とリアルタイム分析がさらに強化されることが含まれます。また、病気の進行や患者の転帰を予測し、臨床上の意思決定を改善するAI主導の予測モデルの開発傾向も顕著です。これに伴い、AI技術企業と製薬企業との間で、主に薬剤開発や患者モニタリングにAIを活用することを目的とした協力的な取り組みが増加しています。患者データの安全性とプライバシー遵守を確保するため、倫理的なAIと透明性の高いアルゴリズムに注目が集まっていることも注目すべき動向です。さらに、ロボティック・プロセス・オートメーション(RPA)におけるAIの利用は、医療における管理業務の合理化であり、ライフサイエンスにおける人工知能市場の成長をさらに促進しています。
地理的動向:地理的には、北米がライフサイエンスにおける人工知能市場をリードしており、その主要要因は、先進的な技術インフラ、人工知能と医療への多額の投資、規制機関からの強力なサポートです。欧州は、医療システムにおけるAI導入の増加や、AI研究とデータ保護に関する政府政策からの支援により、著しい成長を遂げ、僅差でこれに続きます。アジア太平洋は、主に中国、日本、インドなどの国々における医療需要の増加、技術の進歩、AIを推進する政府の取り組みによって大きな成長を遂げています。
競合情勢:ライフサイエンスにおける人工知能業界の主要市場参入企業には、AiCure LLC、Apixio Inc.(Centene Corporation)、Atomwise Inc.、Enlitic Inc.、International Business Machines Corporation、Insilico Medicine Inc.、Nuance Communications Inc.、NuMedii Inc.、Sensely Inc.Sophia Genetics SA.など多数あります。
課題と機会:ライフサイエンスにおける人工知能市場は、導入コストの高さ、より熟練した人工知能専門家の必要性、データのプライバシーとセキュリティに対する懸念の高まりなど、さまざまな課題に直面しています。生物学的データは複雑であるため、より洗練されたAIモデルが必要となるが、その開発は困難です。ビジネス機会の面では、人工知能は医薬品開発の効率化、コスト削減、個別化された患者ケアにおいて可能性を示しています。さらに、AIが医療サービスの格差に対処できる新興市場にも大きな成長の可能性があります。
創薬と開発の加速
従来の医薬品開発プロセスでは、新薬の上市までに10年以上を要するなど、長期的でコストがかかり、非効率的な取り組みであることが多いです。AIは、医薬品開発の様々な段階を迅速化することで、この状況を一変させる。例えば、2023年、コグニザントはサンフランシスコに先進人工知能(AI)ラボを立ち上げ、主にAIのコア研究、イノベーション、最先端AIシステムの開発に注力しています。専属のAI研究者・開発者チームを擁するこのラボは、すでに75件の特許を取得・出願中であり、研究機関、顧客、新興企業との連携を図る。機械学習アルゴリズムは、生物学的・化学的情報、臨床試験データ、既存の医薬品データベースなどの膨大なデータセットを分析し、これまでにないスピードと精度で潜在的な医薬品候補を特定します。これにより、研究者は有望な化合物をピンポイントで特定し、その有効性を予測し、特性を最適化することができるため、創薬に必要な時間とコストを大幅に削減することができ、ライフサイエンスにおける人工知能市場の成長を促進します。
個別化医療と医療
従来の治療法は、多くの場合、幅広い集団の平均に基づいて薬や治療法が処方される、画一的なアプローチに従っています。AIはビッグデータと機械学習の力を活用し、個人の遺伝的体質、臨床歴、ライフスタイル要因、リアルタイムの健康データを分析し、高度にオーダーメイドの治療計画を策定します。2023年、OM1は、充実した医療データセットとAI技術を活用した個別化医療のためのAI搭載プラットフォームPhenOMを発表しました。PhenOMは、縦断的な健康履歴データを用いてキャリブレーションされ、疾患に関連する固有のデジタル表現型を特定し、個別化医療に関する洞察を大規模に可能にします。慢性疾患に焦点を当て、OM1は革新的なRWE調査のパイオニアとして、患者の転帰にパーソナライズされたインパクトを提供し、最先端のAIソリューションを通じて医療を前進させる。このレベルのパーソナライゼーションにより、患者はより効果的なだけでなく、副作用を引き起こしにくい治療を確実に受けることができます。また、AI主導の予測モデルは、特定の疾患のリスクが高い患者を特定するのに役立ち、早期介入や予防措置を可能にします。さらに腫瘍学では、AIが患者のがんを引き起こす特定の遺伝子変異をピンポイントで特定するのを支援し、腫瘍医が成功する可能性の高い標的療法を推奨できるようにします。
病気の診断とバイオマーカーの発見
AIアルゴリズムは、X線、MRI、CTスキャンなどの医療画像、患者の電子カルテ、ゲノムプロファイルなど、多様な医療データソースを卓越した精度と効率で分析することができます。放射線医療では、AIを活用した画像解析が放射線科医を支援し、微妙な異常の検出や潜在的な健康問題のフラグを立てることで、早期診断と治療に役立てることができます。2024年、Rad AIはGoogleと提携し、AI技術を活用して放射線科のレポーティングを強化することで、放射線科医の時間を節約し、燃え尽きを減らし、患者ケアの質を向上させることを目指しています。この提携により、ワークフローが合理化され、反復作業が自動化され、放射線科報告の効率性と正確性が向上します。さらに、AIは病気のバイオマーカーの発見にも役立っています。バイオマーカーは、病気を初期段階で特定し、その進行を監視する上で極めて重要です。機械学習モデルは、分子データの微妙なパターンを検出することができ、がん、アルツハイマー病、心血管疾患など、さまざまな疾患に関連する特定のバイオマーカーを特定するのに役立ちます。これらのバイオマーカーは早期警告サインとして機能し、臨床医が患者の治療についてタイムリーで十分な情報に基づいた決定を下す際の指針となります。
Table 7 Global: Artificial Intelligence In Life Sciences Market: Key Players
The global artificial intelligence in life sciences market size reached US$ 2.4 Billion in 2023. Looking forward, IMARC Group expects the market to reach US$ 15.4 Billion by 2032, exhibiting a growth rate (CAGR) of 22.4% during 2024-2032. The rising prevalence of complex diseases, the increasing adoption of AI in medical imaging analysis, the integration of AI into genomics research and analysis, and the convergence of AI with emerging technologies are some of the major factors propelling the market.
Major Market Drivers: Artificial intelligence in life sciences is mainly driven by the increase in the volume of biomedical data from genomic sequences and electronic health records which necessitates the incorporation of powerful AI tools for effective management and analysis. In line with this, artificial intelligence is instrumental in accelerating drug discovery and development processes thereby significantly reducing time and costs. Moreover, regulatory support for AI integration in clinical settings and advancements in machine learning and computational algorithms further propel artificial intelligence in life sciences market growth.
Key Market Trends: Key market trends in artificial intelligence in the life sciences sector include the integration of artificial intelligence along with cloud computing and Internet of Things (IoT) devices further enhancing data accessibility and real-time analysis. There is also a significant trend toward the development of AI-driven predictive models that forecast disease progression and patient outcomes improving clinical decision-making. In line with this, collaborative efforts between AI tech firms and pharmaceutical companies are on the rise mainly aimed at leveraging AI for drug development and patient monitoring. The growing focus on ethical AI and transparent algorithms to ensure patient data security and privacy compliance is another notable trend. Furthermore, the use of AI in robotic process automation (RPA) is a streamlining administrative task in healthcare further driving artificial intelligence in life sciences market growth.
Geographical Trends: Geographically, North America leads the artificial intelligence and life sciences market mainly driven by its advanced technological infrastructure, substantial investment in artificial intelligence and healthcare, and strong support from regulatory bodies. Europe follows closely, with significant growth because of the increase in the adoption of AI in healthcare systems and support from government policies regarding AI research and data protection. Asia Pacific is experiencing significant growth mainly fueled by increasing healthcare demands, technological advancements, and government initiatives to promote AI in countries like China, Japan, and India.
Competitive Landscape: Some of the major market players in the artificial intelligence in life sciences industry include AiCure LLC, Apixio Inc. (Centene Corporation), Atomwise Inc, Enlitic Inc., International Business Machines Corporation, Insilico Medicine Inc., Nuance Communications Inc., NuMedii Inc., Sensely Inc. Sophia Genetics SA., among many others.
Challenges and Opportunities: The artificial intelligence and life sciences market faces various challenges, which include high implementation costs, a need for more skilled artificial intelligence professionals, and growing concerns over data privacy and security. The complexity of biological data requires more sophisticated AI models, which can be difficult to develop. On the opportunity side, artificial intelligence shows potential in improving drug development efficiency, reducing costs, and in personalized patient care. Furthermore, there is also significant potential for growth in emerging markets where AI can address the gaps in healthcare services.
Drug Discovery and Development Acceleration
The traditional drug development process is a lengthy, costly, and often inefficient endeavour, taking over a decade to bring a new drug into the market. AI transforms this landscape by expediting various stages of drug development. For instance, in 2023, Cognizant launched an Advanced Artificial Intelligence (AI) Lab in San Francisco to mainly focus on core AI research, innovation, and development of cutting-edge AI systems. The lab, staffed by a team of dedicated AI researchers and developers, has already produced 75 issued and pending patents and will collaborate with research institutions, customers, and startups. Machine learning algorithms analyse vast datasets, including biological and chemical information, clinical trial data, and existing drug databases, to identify potential drug candidates with unprecedented speed and accuracy. This enables researchers to pinpoint promising compounds, predict their efficacy, and optimize their properties, significantly reducing the time and cost required for drug discovery, thereby propelling the artificial intelligence in life sciences market growth.
Personalized Medicine and Healthcare
Traditional medical treatments often follow a one-size-fits-all approach, with medications and therapies prescribed based on broad population averages. AI harnesses the power of big data and machine learning to analyze an individual's genetic makeup, clinical history, lifestyle factors, and real-time health data to develop highly tailored treatment plans. In 2023, OM1 introduced PhenOM, an AI-powered platform for personalized medicine, leveraging enriched healthcare datasets and AI technology. Calibrated using longitudinal health history data, PhenOM identifies unique digital phenotypes associated with conditions, enabling personalized healthcare insights at scale. With a focus on chronic conditions, OM1 pioneers innovative RWE research, delivering personalized impact on patient outcomes and advancing healthcare through cutting-edge AI solutions.This level of personalization ensures that patients receive treatments that are not only more effective but also less likely to cause adverse side effects. Also, AI-driven predictive models can help identify patients at higher risk of certain diseases, allowing for early intervention and preventive measures. Additionally, in oncology, AI assists in pinpointing the specific genetic mutations driving a patient's cancer, enabling oncologists to recommend targeted therapies that are more likely to be successful.
Disease Diagnosis and Biomarker Discovery
AI algorithms can analyze diverse medical data sources, including medical images, such as X-rays, MRIs, and CT scans, patient electronic health records, and genomic profiles, with exceptional accuracy and efficiency. In radiology, AI-powered image analysis can assist radiologists in detecting subtle abnormalities and flagging potential health issues, aiding in early diagnosis and treatment. In 2024, Rad AI has partnered with Google to enhance radiology reporting by leveraging AI technology, aiming to save radiologists time, reduce burnout, and improve patient care quality. This collaboration will streamline workflows, automate repetitive tasks, and advance the efficiency and accuracy of radiology reporting. Moreover, AI is instrumental in the discovery of disease biomarkers, which are crucial in identifying diseases at their earliest stages and monitoring their progression. Machine learning models can detect subtle patterns in molecular data, helping to identify specific biomarkers associated with various diseases, including cancer, Alzheimer's, and cardiovascular conditions. These biomarkers serve as early warning signs and can guide clinicians in making timely and informed decisions about patient care.
IMARC Group provides an analysis of the key trends in each segment of the global artificial intelligence in life sciences market report, along with forecasts at the global, regional, and country levels for 2024-2032. Our report has categorized the market based on offering, deployment, and application.
Software
Hardware
Services
Software dominates the market
The report has provided a detailed breakup and analysis of the market based on the offering. This includes software, hardware, and services. According to the report, software represented the largest segment.
Software in the context of AI encompasses a wide array of tools, platforms, and applications specifically designed to process, analyze, and interpret the immense volume of data generated in life sciences research. These software solutions utilize machine learning algorithms, natural language processing, deep learning, and other AI techniques to sift through complex biological datasets, making sense of genomics, proteomics, and clinical data. The versatility of AI software allows researchers to explore various aspects of drug discovery, disease diagnosis, and patient care with unprecedented precision and efficiency. Additionally, the scalability and adaptability of AI software make it a preferred choice for organizations operating in the life sciences domain. Researchers can customize and fine-tune AI algorithms to meet their specific research needs, whether it involves drug target identification, biomarker discovery, or patient stratification for clinical trials. This flexibility empowers scientists to adapt to evolving research objectives and swiftly respond to emerging challenges in healthcare and life sciences. Furthermore, AI software offerings are at the forefront of addressing some of the most pressing issues in the industry.
On-premises
Cloud-based
Cloud-based dominate the market
The report has provided a detailed breakup and analysis of the market based on the deployment. This includes on-premises and cloud-based. According to the report, cloud-based represented the largest segment.
Cloud-based deployment offers unparalleled scalability and flexibility, which are crucial for the resource-intensive nature of AI applications in life sciences. Researchers and organizations can tap into cloud resources as needed, scaling up or down depending on the complexity and volume of data being processed. This dynamic scalability ensures that computational resources are optimally allocated, avoiding underutilization or resource bottlenecks, which can occur with on-premises solutions. Additionally, cloud-based deployment eliminates the need for significant upfront hardware and infrastructure investments. This cost-effectiveness is particularly attractive for research institutions, pharmaceutical companies, and healthcare providers looking to leverage AI without the burden of substantial capital expenditures. Cloud services provide pay-as-you-go pricing models, allowing organizations to pay only for the computing resources they consume, thus optimizing cost management. Moreover, cloud-based deployments offer the advantage of accessibility and collaboration. Researchers and scientists can access AI tools and applications from anywhere with an internet connection, facilitating collaboration across geographic boundaries and enabling real-time data sharing and analysis.
Drug Discovery
Medical Diagnosis
Biotechnology
Clinical Trials
Precision and Personalized Medicine
Patient Monitoring
Drug discovery dominates the market
The report has provided a detailed breakup and analysis of the market based on the application. This includes drug discovery, medical diagnosis, biotechnology, clinical trials, precision and personalized medicine, and patient monitoring. According to the report, drug discovery represented the largest segment.
AI-driven drug discovery is not limited to target identification alone. AI models can predict the pharmacokinetics and toxicity profiles of potential drugs, allowing researchers to assess their safety and efficacy earlier in the development pipeline. This risk mitigation not only saves time but also reduces the likelihood of costly late-stage failures, a common challenge in the pharmaceutical industry. Additionally, AI plays a pivotal role in drug repurposing, where existing drugs are explored for new therapeutic applications. By analyzing biological data, AI algorithms can identify overlooked connections between drugs and diseases, potentially unveiling novel treatment options. This approach not only accelerates the availability of treatments for various medical conditions but also leverages existing knowledge and resources more efficiently. Furthermore, the personalized medicine revolution is closely linked to AI-driven drug discovery. As AI models analyze patients' genetic profiles, clinical histories, and real-time health data, they can identify specific genetic markers and mutations that influence drug response.
North America
United States
Canada
Asia Pacific
China
Japan
India
South Korea
Australia
Indonesia
Others
Europe
Germany
France
United Kingdom
Italy
Spain
Russia
Others
Latin America
Brazil
Mexico
Others
Middle East and Africa
North America exhibits a clear dominance, accounting for the largest artificial intelligence in life sciences market share
The market research report has also provided a comprehensive analysis of all the major regional markets, which include North America (the United States and Canada); Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, and others); Europe (Germany, France, the United Kingdom, Italy, Spain, Russia, and others); Latin America (Brazil, Mexico, and others); and the Middle East and Africa. According to the report, North America accounted for the largest market share.
North America boasts significant investments in AI research and development. Government initiatives, private sector funding, and venture capital investments have poured into AI projects and startups, fueling innovation and technological advancements. This financial backing has accelerated the growth of AI-driven solutions, from drug discovery and genomics to healthcare analytics and personalized medicine. Moreover, North America's robust regulatory framework and intellectual property protection create a conducive environment for AI development and commercialization. Several regulatory agencies have been proactive in engaging with AI developers to establish clear guidelines and approval processes for AI-based medical devices and treatments. This regulatory clarity gives businesses confidence to invest in AI projects. Furthermore, North America's healthcare infrastructure is among the most advanced globally, making it a prime testing ground for AI applications. The region's large patient population, extensive electronic health record systems, and well-established pharmaceutical and biotech industries provide ample opportunities for AI-driven healthcare solutions to demonstrate their efficacy and impact.
Numerous companies in this market are focused on using AI to accelerate drug discovery processes. They develop AI algorithms and platforms that analyze biological data, identify potential drug candidates, predict drug interactions, and optimize drug design, all with the goal of bringing new therapies to market faster and more efficiently. Also, AI companies in the life sciences sector work on solutions for genomic analysis. They develop tools that can decipher and interpret genetic information, identify disease markers, predict disease risk, and enable personalized medicine by tailoring treatments based on an individual's genetic profile. Moreover, companies are developing AI-driven solutions that assist radiologists and pathologists in interpreting medical images such as X-rays, MRIs, and CT scans. These tools can help detect diseases and anomalies earlier and with greater accuracy. Companies are also actively engaged in predictive analytics, utilizing AI to identify disease biomarkers, predict patient outcomes, and stratify patients for clinical trials. These AI-driven insights can inform treatment decisions and improve patient care.
AiCure LLC
Apixio Inc. (Centene Corporation)
Atomwise Inc
Enlitic Inc.
International Business Machines Corporation
Insilico Medicine Inc.
Nuance Communications Inc.
NuMedii Inc.
Sensely Inc.
Sophia Genetics SA
(Kindly note that this only represents a partial list of companies, and the complete list has been provided in the report.)
In 2024, Atomwise's AIMS initiative showcased the AtomNet AI Platform's success in discovering novel chemical matter for 235 out of 318 targets, demonstrating its potential as an alternative to high-throughput screening. The study, published in Nature Scientific Reports, highlighted AtomNet's ability to identify hits across various protein classes, emphasizing its broad applicability in drug discovery.
In 2024, IBM, in collaboration with the Government of Canada and Quebec, signed agreements to enhance Canada's semiconductor industry with a significant investment of around CAD 187 million, focusing on advancing chip packaging capabilities and boosting R&D at IBM Canada's Bromont plant. This initiative aims to create high-paying jobs, strengthen supply chains, and position Canada at the forefront of semiconductor innovation, as emphasized by Prime Minister Justin Trudeau and industry leaders.