市場調查報告書
商品編碼
1184241
生命科學分析中AI全球市場規模,份額和行業趨勢分析報告:按最終用戶(製藥,醫療器械,生物技術,其他),應用,部署,組件,地區展望和預測2022-2028Global AI In Life Science Analytics Market Size, Share & Industry Trends Analysis Report By End-user (Pharmaceutical, Medical Devices, Biotechnology and Others), By Application, By Deployment, By Component, By Regional Outlook and Forecast, 2022 - 2028 |
在預測期內,生命科學分析領域人工智能的全球市場規模預計將以 10.9% 的複合年增長率增長,到 2028 年達到 25 億美元。
此外,由於藥物發現和臨床試驗中對降低成本和提高運營效率的需求不斷增長,人工智能在生命科學領域的應用也在取得進展。 數據驅動的 AI 的快速發展、深度學習的技術進步以及對機器人自主性不斷增長的需求正在推動 AI 在分析中的應用。
這種採用主要是由於研發成本高、臨床試驗成功率低以及對罕見病的關注度增加等變數導致的藥物發現過程效率低下。 機器學習技術改善候選人招聘流程、數據存儲和數據分析的能力有望推動市場擴張。
COVID-19 影響分析
廣泛使用 AI 來跟蹤大量大規模臨床試驗的結果進一步促進了對 AI 和類似技術的更多需求。 此外,大流行期間電子數據捕獲(EDC)系統等技術發展使文件控制監控和遠程電子簽名成為可能,進一步加快了審判進程。 因此,它對許多製藥公司快速開發高效候選藥物有很大幫助。 因此,COVID-19 大流行對生命科學分析領域的 AI 市場產生了積極影響。
市場增長因素
個性化醫療和精準醫療日益受到關注
人工智能技術正在對個性化醫療和精準醫療的發展領域產生重大影響。 與傳統的預測建模或機械假設不同,人工智能解決方案在邏輯上開發了最佳藥物組合。 這些藥物組合是通過對特定於被評估疾病的保守數據集進行有效分析,從真實和成功的實驗證據中開發出來的。 因此,通過擴大 AI 和 ML 在個性化和精準醫療發展中的範圍,生命科學分析中的 AI 市場將會增長。
擴大人工智能在藥物發現中的應用
許多製藥和生物製藥公司正在加大對人工智能係統的投資。 它們被廣泛用於改善疾病靶標識別、從頭開始的藥物設計、毒性和療效預測以及化學篩選。 人工智能深度學習也非常適合藥物開發,因為它能夠從原始數據中提取基本特徵,而不管數據集大小。 這進一步推動了人工智能的採用,從而推動了人工智能在生命科學分析市場的擴張。
市場約束
重要信息的安全和隱私問題
研究機構、軟件公司和臨床研究組織 (CRO) 之間日益共享的數據庫增加了敏感數據洩露的風險。 頻繁訪問信息還會將敏感的患者信息暴露給外人。 應用分析解決方案並遵守隱私政策是生物製藥和製藥公司面臨的主要挑戰,因為大多數數據都是以電子方式管理的。 因此,藥物開發研究和開發可能會受到各種政府法規變化的限制。
最終用戶的觀點
基於最終用戶,生命科學分析市場中的 AI 細分為醫療設備、製藥、生物技術等。 2021 年,製藥領域將在生命科學分析領域佔據 AI 市場的最高收入份額。 在藥物發現、臨床試驗和製造中越來越多地採用人工智能工具是推動這一領域增長的主要因素。 這些工具顯著降低了成本和周期時間,同時改善了臨床結果。
應用展望
根據應用,生命科學分析市場中的 AI 細分為研發、銷售和營銷支持、供應鏈分析等。 在 2021 年生命科學分析的 AI 市場中,供應鏈分析領域增長顯著。 製藥和生物製藥公司的供應鏈包括生產藥品所需的一系列複雜步驟。 供應鏈的重要部分包括採購和供應原材料、製造和分銷流程,以及開發藥物的交付。
部署前景
根據部署,生命科學分析中的 AI 市場分為本地和雲端。 2021 年,雲業務在生命科學分析領域的 AI 市場中佔據了最大的收入份額。 雲服務的不斷發展、互聯網的普及和基於雲的技術的採用是推動這一領域增長的主要因素。 部署基於雲的 AI 服務具有通過消除對專用數據中心的需求而降低投資成本的優勢。
組件視角
基於組件,生命科學分析市場中的人工智能被細分為軟件、硬件和服務。 2021 年,硬件部分在生命科學分析市場的 AI 中取得了顯著的增長。 在生物醫學工程領域,正在集成基於人工智能的系統,以幫助完成任何微創手術的診斷和實時圖像生成等任務。 此外,預配置硬件解決方案的應用有助於支持醫務人員在醫療實踐、療養院和醫院的關鍵工作。
區域展望
按地區劃分,對北美、歐洲、亞太地區和 LAMEA 的生命科學分析市場中的 AI 進行了分析。 2021 年,北美部分在生命科學分析市場中的 AI 中佔據了最大的收入份額。 該地區高水平的數字素養以及生命科學領域的發展正在推動該領域的增長。 此外,政府舉措的增加以及製造商與政府機構之間合作的加強進一步推動了人工智能解決方案的需求和整合。 此外,該地區的許多醫療機構已經開始部署人工智能解決方案來簡化他們的工作流程。
合作夥伴關係是市場進入者採取的主要策略。 根據基數矩陣中的分析,Microsoft是生命科學分析領域 AI 市場的領先先驅。 Oracle Corporation、Accenture PLC 和 IBM Corporation 等公司是生命科學分析領域 AI 市場的領先創新者。
The Global AI In Life Science Analytics Market size is expected to reach $2.5 billion by 2028, rising at a market growth of 10.9% CAGR during the forecast period.
The term artificial intelligence (AI) refers to a heavily data-driven technology. It is frequently used in the R&D departments of the life sciences sector to provide insightful data from fragmented sources. Though the use of AI technologies and tools is still in its early phases in the life sciences sector, yet it is facilitating companies to develop strategic technological skills for establishing a competitive edge.
Since it can deliver data quickly, precisely, and reliably, AI is gaining acceptance in the analytics field. Because of this, businesses are becoming keener to invest in incorporating AI algorithms into analytical solutions. The accelerating development of new technologies, such as artificial intelligence, and their widespread use across a variety of industries have increased demand for AI in the life sciences sector.
In addition, the application of AI in life sciences is also growing as there is a rising need to reduce costs and improve operational efficiencies in drug discovery and clinical trials. The rapid development of data-based AI, technological advancements in deep learning, and the growing requirement to achieve autonomy in robotics has propelled the implementation of AI in analytics.
This adoption is mainly driven by the inefficiency of the drug discovery process as a result of variables such as high costs of research and development, low success rates in clinical trials, and rising attention to rare diseases. The ability of machine learning technology to improve candidate recruitment processes, data storage, and data analytics is expected to drive market expansion.
COVID-19 Impact Analysis
The extensive help of AI in keeping track of the results of numerous clinical trials on an expanded scale further helped in creating more demand for AI and similar technologies. Furthermore, the development of technologies like electronic data capture (EDC) systems during the pandemic enabled document management monitoring and remote electronic signatures and further accelerated the trial processes. As a result, this immensely helped many pharmaceutical companies in developing efficient drug contenders rapidly. Therefore, the COVID-19 pandemic positively impacted the AI in life science analytics market.
Market Growth Factors
Increasing Emphasis On Personalized Drugs And Precision Medicines
AI technology has greatly influenced the personalized medicine and precision medicine development sectors. Unlike the previous methods of predictive modeling and mechanistic assumptions, AI solutions logically develop optimal drug combinations. These drug combinations are developed from genuine and successful experimental proofs by efficient analysis of modest datasets that are specific to the disease being assessed. Hence, by extending the reach of AI and ML in the development of personalized drugs and precision medicines, AI in life science analytics market is bound to grow.
Growing Application Of Ai In Drug Discovery
Many pharmaceutical and biopharmaceutical companies have increased their investments in artificial intelligence systems as these extensively help in improving the identification of disease targets, designing of medication from the first step, toxicity, potency predictions, and chemical screening. In addition, deep learning enabled by AI is well suited for drug development because of its ability to extract essential features from unprocessed data, regardless of the dataset size. . This has further helped the adoption of AI and thus boosts the expansion of AI in life science analytics market.
Market Restraining Factors
Concerns Regarding The Safety And Privacy Of Crucial Information
The rising number of database sharing among research institutions, software companies, and clinical research organizations (CROs) presents a high risk of data leaks of confidential status. Frequent access to information may also result in the leakage of sensitive patient information to unofficial individuals. Since the majority of data is being maintained electronically, the application of analytics solutions and privacy policies compliance laws pose a significant challenge for biopharmaceutical and pharmaceutical companies. As a result, the R&D of drug development may get restricted by different governmental regulation shifts.
End-User Outlook
On the basis of end-user, the AI in life science analytics market is fragmented into medical devices, pharmaceutical, biotechnology, and others. The pharmaceutical segment acquired the highest revenue share in the AI in life science analytics market in 2021. The rising implementation of AI tools in drug discovery, clinical trials, and manufacturing are the primary factors that are advancing the growth of the segment. These tools significantly decrease the costs and cycle times while improving clinical outcomes.
Application Outlook
Based on application, the AI In life science analytics market is segmented into research & development, sales & marketing support, supply chain analytics, and others. The supply chain analytics segment witnessed a considerable growth rate in the AI In life science analytics market in 2021. The supply chains of pharmaceutical and biopharmaceutical companies involve an intricate set of steps that are necessary for the production of drugs. Some prominent parts of the supply chain include raw materials' sourcing and supply, manufacturing and distribution processes, and delivery of developed medications.
Deployment Outlook
On the basis of deployment, the AI In life science analytics market is divided into on-premise and cloud. The cloud segment recorded the maximum revenue share in the AI In life science analytics market in 2021. Increased development of cloud services, penetration of the internet, and adoption of cloud-based technologies are the main factors propelling the growth of the segment. Implementation of cloud-based AI services is beneficial as they eliminate the requirement for dedicated data centers and hence lower the cost of investment.
Component Outlook
Based on component, the AI In life science analytics market is categorized into software, hardware, and services. The hardware segment procured a remarkable growth rate in the AI In life science analytics market in 2021. In the field of biomedical engineering, AI-based systems are integrated to help in tasks like diagnoses and live image production for any minimally invasive surgeries. The further application of preconfigured hardware solutions aid in supporting crucial jobs of medical staff in medical practices, care facilities, and hospitals.
Regional Outlook
On the basis of region, the AI In life science analytics market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The North America segment garnered the maximum revenue share in the AI In life science analytics market in 2021. The higher digital literacy, along with developments in the life science field in the region, has propelled the growth of the segment. In addition, the rising number of government initiatives and increasing collaborations between manufacturers and government bodies have further boosted the demand and integration of AI solutions. Many healthcare institutions in the region have also started adopting AI solutions to organize their workflows.
The major strategies followed by the market participants are Partnerships. Based on the Analysis presented in the Cardinal matrix; Microsoft Corporation is the major forerunner in the AI In Life Science Analytics Market. Companies such as Oracle Corporation, Accenture PLC, and IBM Corporation are some of the key innovators in AI In Life Science Analytics Market.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Wipro Limited, Lexalytics, Inc., Databricks, Inc., SAS Institute, Inc., Sisense, Inc., IQVIA Holdings, Inc., IBM Corporation, Microsoft Corporation, Oracle Corporation, and Accenture PLC.
Strategies deployed in AI In Life Science Analytics Market
Nov-2022: IQVIA teamed up with Clalit, a health services organization in Israel, with an aim to launch the first prime site in the country. Under the collaboration, the capabilities of real-world research, genomics, data, and clinical trial delivery of both companies would be combined, which would allow focus on the delivery of data-driven trials and precision medicine.
Sep-2022: Wipro announced the launch of an AI-enabled Cath lab, to assist with cardiovascular disease. The product contains AutoRight technology, which allows the delivery of precision healthcare, with an aim of minimization of risk and surgical procedures. Cath lab enables intelligent imaging systems to help cardiologists to give appropriate therapies and treatments.
Aug-2022: Databricks make an enhancement to its Brickbuilder Solutions for Healthcare and Life Sciences. New manufacturing and financial services in healthcare would be added, with an aim to reduce cost and elevate time to value across the data transformation journey. Brickbuilder Solutions comprises of AI and data solutions that are expertly designed to address industry-specific business requirements.
Mar-2022: Wipro partnered with Pandorum Technologies, a biotechnology company. Under the partnership, the expertise of Pandorum in regenerative medicines would be combined with the capabilities of Wipro in Artificial Intelligence (AI). This would fuel growth, elevate innovation as well as transform business processes.
Mar-2022: IQVIA released a new workflow tool OCE+, an advancement to its life science customer engagement platform. The tool provides AI-driven recommendations for healthcare professionals (HCP) and this tool would be able to make more informed and smarter decisions. The product maximizes productivity, expands ROI, and advances HCP experiences.
Oct-2021: Oracle took over Cerner, a provider of healthcare solutions, to get more coordinated care and seamless technology in solutions for healthcare. This acquisition would combine the clinical abilities of Cerner with Oracle's enterprise analytics, platform, and automation expertise and aim to expand its global footprint.
Sep-2021: IQVIA added AI-powered technologies to advance the capabilities of Medical Information (MI)services, which comprise Safety and Quality offerings providing customers with end-to-end services and technology. IQVIA's MI Contact Center services would be available in around 170 countries in 50 different languages with highly skilled agents solving to queries.
Apr-2021: IQVIA Holdings Inc. completed the acquisition of Q2 Solutions, clinical laboratory services organization. This acquisition would strengthen its product offering with industry leading suite of services that includes supply chain, biorepository, project management, biospecimen, comprehensive testing as well as consent tracking solutions used in clinical trials.
Mar-2021: Oracle partnered with Saama to provide AI-Enabled Applications to Life Sciences Industry to Advance Clinical Trials. Under the partnership, the smart application of Saam would be combined with the Oracle platform, to provide clinical trial teams with real-time insight. Additionally, this would enable an integrated user experience, agility, and fast outcomes from clinical applications.
Jan-2021: SAS announced the acquisition of Boemska, an IT Services and IT Consulting company. With This acquisition, the acquired technology would be integrated with SAS Viya which would allow the execution and development of decisions and models using no-code and low-code technologies, to perform specific tasks such as decision-making related to a medical event, identifying a manufacturing defect, anticipating fraud and more.
Jan-2020: Accenture came into collaboration with Google Cloud, a suite of cloud computing services. Under the collaboration, artificial intelligence and the cloud of Google would be combined with life sciences services and platforms of Accenture, to assist the life sciences organizations, to make data more secure, valuable, and accessible.
Feb-2019: IQvia announced the acquisition of Linguamatics, a provider of NLP-based text mining for life science and healthcare. With this addition of the AI-based natural language processing solution, the company would be able to uplift the capabilities to help life science and offer better value-based care and good decision-making.
Market Segments covered in the Report:
By End-user
By Application
By Deployment
By Component
By Geography
Companies Profiled
Unique Offerings from KBV Research
List of Figures