|
市場調査レポート
商品コード
1405226
病理検査におけるAIの世界市場規模、シェア、動向分析レポート:ニューラルネットワーク別、用途別、エンドユーザー別、コンポーネント別、地域別展望と予測、2023年~2030年Global AI in Pathology Market Size, Share & Trends Analysis Report By Neural Network, By Application (Drug Discovery, Disease Diagnosis & Prognosis, Clinical Workflow, and Others), By End User, By Component, By Regional Outlook and Forecast, 2023 - 2030 |
||||||
|
病理検査におけるAIの世界市場規模、シェア、動向分析レポート:ニューラルネットワーク別、用途別、エンドユーザー別、コンポーネント別、地域別展望と予測、2023年~2030年 |
出版日: 2024年01月05日
発行: KBV Research
ページ情報: 英文 305 Pages
納期: 即納可能
![]() |
病理検査におけるAI市場規模は2030年までに6,630万米ドルに達し、予測期間中のCAGRは15.8%の市場成長率で上昇すると予測されます。
ホールスライドイメージングスキャナー、ソフトウェアプラットフォーム、関連インフラストラクチャーを含むデジタル病理システムの取得と導入にかかる初期費用は相当なものになる可能性があります。このような初期投資は、ヘルスケア機関、特に小規模な検査室や予算が限られている検査室にとって財政的な課題となる可能性があります。デジタル病理システムやAIツールを効果的に使用するための病理医や検査スタッフのトレーニングも、全体的なコストに上乗せされます。上記の要因により、市場の成長は今後数年間は妨げられると思われます。
ニューラルネットワークの展望
ニューラルネットワークに基づき、市場は生成的敵対ネットワーク(GAN)、畳み込みニューラルネットワーク(CNN)、リカレントニューラルネットワーク(RNN)、その他に細分化されます。生成的敵対ネットワーク(GAN)セグメントは、2022年の市場で大きな収益シェアを獲得しました。GANは、リアルな画像の生成に広く利用されています。GANは、高解像度画像の生成、アート生成、ディープフェイク生成などに応用されています。GANは様々な領域でデータ増強に採用され、モデルの頑健性を高めるために追加の学習サンプルを生成します。GANは画像の解像度を向上させ、低解像度の入力画像から高品質の画像を生成することができます。GANはテキスト記述からリアルな画像を生成することができ、自然言語とグラフィックコンテンツのギャップを埋めることができます。
用途の展望
用途別では、市場は創薬、疾病診断・予後、臨床ワークフロー、その他に分類されます。2022年には、創薬が市場で最も高い収益シェアを記録しました。AIアルゴリズムは、ハイスループットスクリーニングプロセスから得られる大規模データセットを分析できます。これには、創薬パイプラインで生成される細胞培養、病理組織学的画像、その他のデータの解析が含まれます。分析作業を自動化することで、潜在的な医薬品候補の同定を迅速に行うことができます。AIは薬物と生物学的経路の相互作用を調べることができます。薬物が疾患病態の文脈で特定の経路にどのように影響するかを理解することは、介入を合理化し、潜在的な相乗効果や拮抗作用を特定するのに役立ちます。
エンドユーザーの展望
エンドユーザー別では、市場は製薬・バイオテクノロジー企業、病院・基準検査室、学術・研究機関に分類されます。病院・基準検査室セグメントは、2022年の市場でかなりの収益シェアを占めています。AIは、ガラススライドをデジタル化して遠隔で閲覧・分析するデジタル病理検査の導入をサポートします。これにより、病院内または異なる場所にいる病理医間のコラボレーション、セカンドオピニオン、コンサルテーションが容易になります。AIは病理医の意思決定支援システムであり、診断プロセスにおいてリアルタイムの支援を提供します。AIは病理医の継続的な学習やトレーニングプログラムにも利用できます。バーチャルシミュレーション、インタラクティブ学習モジュール、AI支援トレーニングは、継続的な専門能力開発に貢献します。
コンポーネントの展望
コンポーネント別に見ると、市場はソフトウェアとスキャナーに区分されます。ソフトウェアセグメントは、2022年の市場でかなりの収益シェアを獲得しました。この大きなシェアは、病理医がAIベースのソフトウェアを広く受け入れ、活用していることに起因しています。高い適応性、相互運用性、画像解析、データ抽出、レポート作成を含むさまざまな病理検査の自動化は、ソフトウェアセグメントの利点の一部です。病理学におけるAIソフトウェアの採用と発展は、これらの要因によって推進されており、病気の検出、診断、治療計画の進歩に大きな見通しをもたらしています。
地域別展望
地域別に見ると、市場は北米、欧州、アジア太平洋、LAMEAで分析されます。アジア太平洋地域は、2022年の市場においてかなりの収益シェアを獲得しました。同地域の大規模で多様な患者集団は、AIアルゴリズムのトレーニングと検証に豊富なデータを提供します。病理学におけるAIモデルは、患者の属性や病態の多様性から恩恵を受け、その一般化可能性を高めています。ヘルスケアプロバイダーと、AIを専門とする企業を含むテクノロジー企業とのコラボレーションは、アジア太平洋地域における病理学分野のAIソリューションの開発と展開を加速させます。
市場の大手企業は、市場での競争力を維持するため、多様な革新的製品で競争しています。上図は、同市場における主要企業の収益比率を示しています。市場の大手企業は、さまざまな産業からの需要に応えるため、さまざまな戦略を採用しています。同市場における主要な開発戦略は、買収とパートナーシップ&コラボレーションです。
The Global AI in Pathology Market size is expected to reach $66.3 million by 2030, rising at a market growth of 15.8% CAGR during the forecast period.
Collaborations enable the seamless integration of these technologies into pathology workflows for enhanced diagnostics. Healthcare companies provide valuable clinical data and pathology images, while tech companies offer data management, analytics, and artificial intelligence expertise. Consequently, the disease diagnosis & prognosis segment would generate approximately 25.12% share of the market by 2030. Leveraging advanced machine learning algorithms, AI systems analyze vast amounts of pathological data with unprecedented speed and accuracy, aiding pathologists in identifying and classifying diseases. Some of the factors affecting the market are growing digitalization of pathology, increasing demand for personalized medicine, and high cost of digital pathology systems.
Digital pathology provides high-resolution digital images that can be analyzed more efficiently than traditional microscopy. AI algorithms leverage these images to identify patterns, anomalies, and specific features relevant to disease diagnosis. The digitalization of pathology generates large datasets. AI excels in analyzing big data, extracting patterns, and identifying correlations that may not be easily discernible through traditional methods. Thus, the growing digitalization of pathology will expand the market growth in the coming years. Moreover, AI algorithms analyze pathological data to identify and validate biomarkers associated with specific diseases. These biomarkers serve as indicators for personalized treatment strategies, allowing for more targeted and effective interventions. Thus, the increasing need for personalized medicine is a driving force behind the expansion of market.
The upfront cost of acquiring and implementing digital pathology systems, including whole-slide imaging scanners, software platforms, and associated infrastructure, can be substantial. This initial investment may pose financial challenges for healthcare institutions, particularly smaller laboratories or those with limited budgets. Training pathologists and laboratory staff to effectively use digital pathology systems and AI tools adds to the overall cost. Due to the above factors, market growth will be hampered in the coming years.
Neural Network Outlook
Based on neural network, the market is fragmented into generative adversarial networks (GANs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), and others. The generative adversarial networks (GANs) segment garnered a significant revenue share in the market in 2022. GANs are widely utilized for generating realistic images. They have been applied in creating high-resolution images, art generation, and deepfake generation. GANs are employed for data augmentation in various domains, generating additional training samples to enhance model robustness. They can enhance the resolution of images, generating high-quality versions of low-resolution input images. GANs can generate realistic images from textual descriptions, bridging the gap between natural language and graphic content.
Application Outlook
By application, the market is categorized into drug discovery, disease diagnosis & prognosis, clinical workflow, and others. In 2022, drug discovery registered the highest revenue share in the market. AI algorithms can analyze large-scale datasets resulting from high-throughput screening processes. This includes the analysis of cell cultures, histopathological images, and other data generated in drug discovery pipelines. The automation of analysis tasks expedites the identification of potential drug candidates. AI can examine the interactions between drugs and biological pathways. Understanding how drugs affect specific pathways in the context of disease pathology helps rationalize interventions and identify potential synergies or antagonisms.
End User Outlook
On the basis of end user, the market is classified into pharmaceutical & biotechnology companies, hospitals & reference laboratories, and academic & research institutes. The hospitals & reference laboratories segment covered a considerable revenue share in the market in 2022. AI supports the implementation of digital pathology, where glass slides are digitized for remote viewing and analysis. This facilitates collaboration, second opinions, and consultations among pathologists within the hospital or across different locations. AI is a decision support system for pathologists, providing real-time assistance during the diagnostic process. AI can be used for continuous learning and training programs for pathologists. Virtual simulations, interactive learning modules, and AI-assisted training contribute to ongoing professional development.
Component Outlook
On the basis of component, the market is segmented into software and scanners. The software segment acquired a substantial revenue share in the market in 2022. This significant share can be attributed to pathologists' widespread acceptance and utilization of AI-based software. High adaptability, interoperability, and the automation of a variety of pathology responsibilities, including image analysis, data extraction, and report generation, are a few of the benefits of the software segment. The adoption and development of AI software in pathology are propelled by these factors, which offer significant prospects for progress in disease detection, diagnosis, and treatment planning.
Regional Outlook
Region-wise, the market is analysed across North America, Europe, Asia Pacific, and LAMEA. The Asia Pacific region acquired a substantial revenue share in the market in 2022. The region's large and diverse patient population provides a wealth of data for training and validating AI algorithms. AI models in pathology benefit from the diversity of patient demographics and disease presentations, enhancing their generalizability. Collaboration between healthcare providers and technology companies, including those specializing in AI, accelerates developing and deploying AI solutions in pathology across the Asia Pacific region.
The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Acquisitions, and Partnerships & Collaborations.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Koninklijke Philips N.V., F. Hoffmann-La Roche Ltd., Hologic, Inc., Visiopharm A/S, Paige AI, Inc., PathAI, Inc., Aiforia Technologies Plc, Indica Labs, Inc., Optrascan, Inc. (Optra Ventures, LLC), MindPeak GmbH.
Recent Strategies Deployed in AI in Pathology Market
Partnerships, Collaborations & Agreements:
Oct-2023: F. Hoffmann-La Roche Ltd. has entered into a collaboration with Ibex Medical Analytics Ltd. to provide AI-powered solutions for cancer detection, along with the support of Amazon Web Services, Inc., a cloud service provider. This collaboration aims to give pathology laboratories access to Ibex's AI-driven decision support tools through the navify Digital Pathology software platform. Through this integration, clinicians can receive assistance in the diagnosis of breast and prostate cancer.
Sep-2023: Hologic, Inc. has partnered with Bayer AG to introduce contrast-enhanced mammography (CEM) solutions for improved breast cancer detection in European, Canadian, and Asia Pacific regions. The partnership aims to combine Bayer and Hologic's technologies to facilitate contrast media application in mammography examinations. The partnership focuses on providing radiologists with comprehensive product packages, hands-on training, and seamless integration of CEM into their workflows.
Jul-2023: Aiforia Technologies Plc and Orion Corporation, a Finnish pharmaceutical company, have entered into a collaboration to jointly create artificial intelligence (AI)-driven image analysis solutions for preclinical research and product development. Through this collaboration, Aiforia gains valuable insights from Orion regarding the specific needs of its preclinical customer base. This collaboration empowers Aiforia to refine and customize its product portfolio, ensuring a more targeted approach to meet the unique requirements of the preclinical research community.
Jun-2023: Visiopharm A/S has entered into a collaboration with Minerva Imaging, a preclinical Contract Research Organization (CRO) that specializes in molecular imaging services. Within this collaboration, the two companies will focus on developing AI-based image analysis applications in histology. The collaboration between Minerva and Visiopharm aims to expedite the creation of a toolbox for AI-driven precision pathology. This advancement will empower pharmaceutical companies to enhance clinical development by improving both quantitative and qualitative assessments, particularly in challenging-to-treat cancers.
Jun-2023: Visiopharm A/S has formed a partnership with Grundium Ltd., a well-known provider of high-quality imaging solutions for digital pathology. Through this partnership, the companies aim to broaden the accessibility of digital pathology solutions for clinics and laboratories globally. Within this partnership, Visiopharm will make Grundium's Ocus scanners available alongside its Qualitopix solution. This integration allows labs to automatically upload images for processing. The Qualitopix solution provides labs with the capability to improve staining quality and standardization by monitoring staining consistency.
Jun-2023: MindPeak GmbH has established a partnership with Proscia Inc., a U.S.-based provider of digital and computational pathology solutions. This partnership aims to provide closely integrated AI-powered workflows, supporting pathologists in making more efficient, informed, and reproducible clinical decisions. The goal is to broaden access to improved diagnoses for cancer patients.
Apr-2023: Optrascan, Inc. has formed a collaboration with Lumea Inc., a global leader in integrated digital pathology solutions. This collaboration combines Lumia's comprehensive digital pathology platform with diverse digital scanning solutions, aiming to facilitate the efficient and cost-effective adoption of digital pathology by providers.
Apr-2023: Indica Labs, Inc. and Lunit Inc., a medical software company, have entered into an agreement. As part of this agreement, the two companies will offer a completely interoperable solution, connecting Indica Labs' HALO AP image management software platform with Lunit's suite of AI pathology products. The Collaboration facilitates the smooth integration of Lunit's AI pathology solutions, including Lunit SCOPE PD-L1 designed for non-small cell lung cancer, into the HALO AP platform. It's worth noting that HALO AP holds CE-IVD certification as a clinical image management platform.
Apr-2023: PathAI, Inc. has partnered with ConcertAI LLC, a leading provider of AI software-as-a-service (SaaS) for life sciences and healthcare. The partnership aims to introduce an innovative solution that combines PathAI's PathExplore tumor microenvironment panel with ConcertAI's Patient360 and RWD360 products. This partnership will result in a groundbreaking quantitative histopathology and curated clinical real-world data (RWD) solution. The goal is to offer researchers access to a unique quantitative pathology dataset, allowing exploration beyond the limitations of small, controlled datasets. This includes identifying and analyzing novel histological biomarkers correlated with patient treatment and outcomes.
Mar-2023: Paige AI, Inc. has expanded its Partnership with Leica Biosystems Nussloch GmbH, a leading cancer diagnostics firm. The primary goal of this enhanced partnership is to further progress the adoption of digital pathology workflows across hospitals and laboratories worldwide. As part of this Partnership, Paige will provide software-as-a-service (SaaS) solutions for managing and viewing digital pathology images. Additionally, Paige will integrate various artificial intelligence (AI) solutions directly into the Aperio GT 450 digital pathology slide scanners within Leica Biosystems' product range.
Feb-2022: MindPeak GmbH and Crosscope Inc. have entered into an partnership, integrating MindPeak's image analysis tools into Crosscope's Digital Pathology platform. This partnership enhances Crosscope's AI capabilities, enabling them to provide comprehensive digital pathology solutions. By seamlessly integrating advanced AI tools, the partnership aims to optimize Histopathology workflows, supporting pathologists in improving lab efficiency and delivering timely and impactful diagnoses for ER, PR, and Ki-67 IHC stainings. The integration promises to positively influence patient treatment outcomes.
Oct-2021: F. Hoffmann-La Roche Ltd. and PathAI, Inc. have entered into an agreement to work on the development and distribution of an integrated image analysis workflow tailored for pathologists. Under this agreement, the objective is to jointly create a seamless workflow that incorporates PathAI's AI-powered image analysis algorithms into NAVIFY Digital Pathology, which is Roche's cloud-based iteration of the uPath enterprise software.
Aug-2020: Hologic, Inc. has entered into a collaboration with RadNet, Inc., a leading provider of high-quality outpatient diagnostic imaging services. The collaboration aims to promote the utilization of artificial intelligence (AI) in breast health. As part of this collaboration, RadNet plans to upgrade all its Hologic mammography systems to incorporate Hologic's 3DQuorum imaging technology, which is powered by Genius AI. This technology, working in conjunction with Clarity HD high-resolution imaging technology, significantly reduces tomosynthesis image volume for radiologists by 66 percent.
Product Launches & Product Expansions:
May-2022: Koninklijke Philips N.V. has introduced its state-of-the-art AI-driven enterprise imaging portfolio for complex clinical and operational tasks. Philips unveiled the MR 5300 imaging system, integrating AI-driven technologies designed to automate challenging clinical and operational tasks. This innovative technology from Philips empowers patients and healthcare professionals to harness the power of data for advanced analytics. This development sets the stage for a streamlined and precise diagnostic platform, enhancing both patient and healthcare provider experiences.
Mar-2022: Paige AI, Inc. has launched Paige Breast Lymph Node, an innovative AI medical software aiding pathologists in detecting the spread of breast cancer to lymph nodes. The product enhances efficiency and accuracy, utilizing AI to identify at-risk metastases, including small micrometastases, aiming for over 98% slide-level sensitivity. This advancement seeks to improve diagnostic accuracy for subtle metastatic foci.
Nov-2021: Hologic, Inc. has launched its newest product, the Genius Digital Diagnostics System, now available in Europe. This system integrates deep learning-based AI with advanced volumetric imaging technology to advance cervical cancer screening. The primary goal is to assist in detecting pre-cancerous lesions and cervical cancer cells in women. Using advanced image analysis, the system thoroughly evaluates each cell in a ThinPrep Pap test image, offering a comprehensive view of clinically relevant objects.
Oct-2021: Koninklijke Philips N.V. has introduced its newest digital pathology platform called IntelliSite, designed to cover the entire enterprise. IntelliSite includes a suite of scalable software tools aimed at enhancing workflows, increasing diagnostic confidence, promoting collaboration, incorporating artificial intelligence (AI), and enhancing the overall efficiency of pathology laboratories. Additionally, Philips emphasizes outstanding image quality and advanced algorithms that assist pathologists in both diagnosis and the development of care pathways.
May-2021: Optrascan, Inc. has launched CytoSiA, an intelligent solution for quick and cost-effective scanning and analysis of liquid-based cytology slides and Pap smears. CytoSiA includes OptraSCAN's digital pathology scanner, storage, and advanced AI algorithms, assisting pathologists in screening and detecting cervical cancer, pre-cancerous lesions, atypical cells, and various cytologic categories. It has been adopted globally by many hospitals and pathology labs, leading to improved patient outcomes, increased efficiency, and enhanced productivity in handling cytology cases.
Market Segments covered in the Report:
By Neural Network
By Application
By End User
By Component
By Geography
Companies Profiled
Unique Offerings from KBV Research