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基于人工智慧的药物传递的全球市场：预测（2023-2028）
市场调查报告书
商品编码
1410140

基于人工智慧的药物传递的全球市场：预测（2023-2028）

AI-Driven Drug Delivery Market - Forecasts from 2023 to 2028
出版日期: | 出版商: Knowledge Sourcing Intelligence | 英文 149 Pages | 商品交期: 最快1-2个工作天内

价格
简介目录

预测期内，全球人工智慧驱动的药物输送市场规模预计将以 34.54% 的复合年增长率成长。

人工智慧驱动的药物输送市场改变了製药和医疗领域的游戏规则。这个发展中的产业正在利用人工智慧 (AI) 的力量，透过优化治疗效果和患者结果来彻底改变药物的传递方式。人工智慧驱动的药物输送系统使用复杂的演算法来分析患者资料并实现个人化用药和药物输送。这些系统可以透过融合即时病患监测和自适应剂量来改变药物释放速率，以确保准确和及时的治疗。此外，人工智慧的预测能力将加快药物研究、处方和管理速度，并缩短新治疗方法的上市时间。人工智慧驱动的药物传输市场有望迎来精准医疗和增强患者照护的新时代，能够提高治疗医嘱遵从性、减少副作用并针对特定疾病领域。

人工智慧 (AI) 和机器学习 (ML) 技术的进步促进了人工智慧驱动的药物输送市场的成长

人工智慧 (AI) 和机器学习 (ML) 的进步是人工智慧驱动的药物输送市场的关键市场驱动力。人工智慧和机器学习演算法的不断进步使得资料分析更加准确和复杂，从而带来更好的药物发现、配方和给药技术。包括患者资讯和药物交互作用在内的大型资料集可以透过人工智慧驱动的演算法进行分析，以预测适当的给药方案和个体化治疗计划。人工智慧驱动的药物输送系统可以找到即时患者资料中的模式和相关性，以改变药物释放速率和给药方案，从而最大限度地提高治疗效果，同时最大限度地减少不良反应。人工智慧和机器学习技术的快速发展正在开闢药物输送的新途径，并改变药物研究和患者照护的模式。

利用人工智慧改善药物输送市场的药物配方和输送优化

改进药物配方和递送优化是人工智慧驱动的药物递送市场的关键成长要素。研究人员可以使用人工智慧 (AI) 和机器学习 (ML) 技术来分析复杂的资料集并深入了解药理特性和交互作用。这种先进的分析有助于开发更有效的配方，并提高生物有效性和稳定性。人工智慧驱动的给药系统还可以优化给药方案，确保根据特定患者的需求进行精确和个体化的给药。透过整合即时患者资料，这些系统可以改变药物释放速率和给药方法，从而改善治疗结果并减少副作用。利用人工智慧优化药物成分和输送系统的能力为更有效、以患者为中心的药物治疗打开了大门。

即时病患监测和自适应剂量将推动人工智慧驱动的药物传输市场规模

即时病患监测和自适应剂量是人工智慧驱动的药物传输市场的关键成长要素。透过利用强大的人工智慧 (AI) 和机器学习 (ML) 技术，药物输送系统可以持续监测患者反应并调整给药方案。即时监测能够及早发现患者状态的变化，并允许适当地改变药物输送。为了个人化药物剂量并优化治疗结果，人工智慧主导的自适应剂量会评估个别患者因素，例如年龄、体重和病历。这种动态策略提高了治疗的准确性，减少了副作用，并改善了患者的治疗效果。即时病患监测和自适应剂量的结合将改变药物管理，并开创以患者为中心和响应性药物治疗的新时代。

北美是基于人工智慧的给药市场的领导者

北美是人工智慧驱动的药物输送市场的领导者。该地区的主导地位有多种原因，包括完善的製药和生物技术产业、强大的研发能力以及注重采用创新技术。此外，人工智慧新兴企业与大型製药企业之间的多种合作关係使北美处于医疗保健领域人工智慧应用的前沿。该地区有利的法律规范和人工智慧研究的高支出正在加速人工智慧系统的发展。然而，市场动态可能会改变人工智慧驱动的药物传输市场的领先地区。

加大人工智慧给药市场的研发投入

研发投资的增加是人工智慧驱动的药物输送市场的驱动因素。製药公司、生物技术公司和研究机构正在大力投资开发人工智慧 (AI) 技术并将其整合到药物传输系统中。这些投资旨在利用人工智慧在优化药物配方、给药策略和个体化治疗方面的前景。此外，行业巨头和人工智慧公司之间的合作正在推动药物输送方面的创造性进步并吸引更多资金。对人工智慧驱动的解决方案日益增长的兴趣反映了业界对人工智慧彻底改变药物开发和改善患者照护的潜力的认识。随着研究和开发的进展，人工智慧驱动的药物输送市场也在不断发展，为药物治疗提供了新的方法。

主要进展：

2023 年 6 月，默克公司（在美国和加拿大境外称为 MSD）完成了对 Prometheus Biosciences, Inc.（「Prometheus」）的收购。 Prometheus将成为默克公司的完全子公司，其普通股将不再在纳斯达克全球市场上市或交易。 2023 年 6 月，GSK plc 与 BELLUS Health Inc. 建立了合作伙伴关係。葛兰素史克 (GSK) 宣布，将根据加拿大商业法第 192 条规定，根据清算计划（以下简称“安排”）收购专注于改善难治性慢性咳嗽 (RCC) 患者生活的生物製药企业 BELLUS公司法。最终决定是根据。 Camry是一种潜在的同类最佳、高选择性 P2X3拮抗，目前正在进行 3 期测试，作为成年 RCC 患者的一线治疗药物，作为 BELLUS 收购的一部分而宣布。 2023年4月，赛诺菲完成了对Provention Bio的收购。透过本次收购，赛诺菲获得了治疗第1型糖尿病的First-in-Class新药TZIELD（teplizumab-Azov），扩大了其特色鲜明的非处方药核心资产组合，推动了向药品的策略转型。

公司产品

  • 药物传递：勃林格殷格翰可能正在研究人工智慧驱动的药物输送系统，该系统可以针对特异性部位释放药物，并增加身体特定区域的药物浓度。
  • 预测分析：罗氏利用人工智慧来预测药物反应并识别潜在的副作用，从而有可能实现主动治疗并提高患者安全。
  • 个体化治疗计画：葛兰素史克可能一直在开发一种人工智慧驱动的系统，该系统可以根据特定的患者变数（例如遗传学、病历和治疗反应）个性化药物剂量和治疗策略。
  • 精准药物传递：默克可能正在探索人工智慧驱动的药物传输系统，该系统可以个性化剂量并调整药物释放，以最大限度地提高治疗效果。
  • 人工智慧优化的配方：诺华可以使用人工智慧演算法来分析生物有效性。

目录

第一章简介

  • 市场概况
  • 市场定义
  • 调查范围
  • 市场区隔
  • 货币
  • 先决条件
  • 基准年和预测年时间表

第二章调查方法

  • 调查资料
  • 资讯来源
  • 研究设计

第三章执行摘要

  • 研究亮点

第四章市场动态

  • 市场驱动因素
  • 市场抑制因素
  • 波特五力分析
    • 供应商的议价能力
    • 买方议价能力
    • 新进入者的威胁
    • 替代品的威胁
    • 业内竞争对手之间的对抗关係
  • 产业价值链分析

第五章 基于人工智慧的给药市场：依技术分类

  • 介绍
  • 机器学习
  • 深度学习
  • 自然语言处理（NLP）
  • 电脑视觉
  • 其他的

第六章 基于人工智慧的给药市场：按给药类型

  • 介绍
  • 口服给药
  • 注射给药
  • 经皮经皮
  • 吸入给药
  • 植入式药物输送
  • 其他的

第七章 基于人工智慧的给药市场：按应用分类

  • 介绍
  • 肿瘤学
  • 糖尿病
  • 心血管疾病
  • 呼吸系统疾病
  • 神经系统疾病
  • 自体免疫疾病
  • 其他的

第八章 基于人工智慧的药物输送市场：按最终用户划分

  • 介绍
  • 医院和诊所
  • 製药公司
  • 研究所和学术中心
  • 居家照护环境
  • 其他的
  • 人工智慧驱动的药物输送市场：按地区划分
  • 介绍
  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 南美洲
    • 巴西
    • 阿根廷
    • 其他的
  • 欧洲
    • 英国
    • 德国
    • 法国
    • 义大利
    • 西班牙
    • 其他的
  • 中东/非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 其他的
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 韩国
    • 印尼
    • 台湾
    • 其他的

第九章竞争环境及分析

  • 主要企业及策略分析
  • 新兴企业和市场盈利
  • 併购/协议/合作
  • 供应商竞争力矩阵

第十章 公司简介

  • MEDTRONIC PLC
  • F. HOFFMANN-LA ROCHE AG
  • GLAXOSMITHKLINE PLC
  • NOVARTIS AG
  • ELI LILLY AND COMPANY
  • ASTRAZENECA PLC
  • MERCK & CO., INC.
  • PFIZER INC.
  • SANOFI SA
  • JOHNSON & JOHNSON
简介目录
Product Code: KSI061615807

The AI-driven drug delivery market is estimated to grow at a CAGR of 34.54% during the forecast period.

The AI-driven drug delivery market is a game changer in the pharmaceutical and healthcare sectors. This developing industry intends to revolutionise medicine delivery methods by using the power of artificial intelligence (AI) and optimising treatment efficacy and patient outcomes. AI-powered medication delivery systems analyse patient data using sophisticated algorithms, enabling personalised dosage and drug administration. These systems may alter medication release rates by merging real-time patient monitoring with adaptive dosage, guaranteeing accurate and timely therapeutic treatments. Furthermore, AI's predictive powers expedite drug research, formulation, and administration, reducing time-to-market for new treatments. The AI-driven drug delivery market, with the ability to increase treatment adherence, decrease side effects, and target particular disease areas, promises to usher in a new age of precision medicine and enhanced patient care.

Advancements in Artificial Intelligence (AI) and Machine Learning (ML) Technologies Enhance the AI-Driven Drug Delivery Market Growth.

Artificial intelligence (AI) and machine learning (ML) advancements are significant development drivers in the AI-driven drug delivery market. The constant progress of AI and ML algorithms has enabled more precise and sophisticated data analysis, resulting in better medicine discovery, formulation, and delivery techniques. Large datasets, including patient information and medication interactions, may be analysed by AI-powered algorithms to anticipate appropriate dosage regimens and personalised treatment plans. AI-driven medication delivery systems may alter drug release rates and dosage regimens by finding patterns and correlations in real-time patient data, maximising therapeutic efficacy while minimising unwanted effects. The fast advancement of AI and ML technologies has opened up new avenues for medication delivery, altering the landscape of pharmaceutical research and patient care.

Improved Drug Formulation and Delivery Optimization in AI-Driven Drug Delivery Market.

In the AI-driven drug delivery market, improved medication formulation and delivery optimisation are important growth factors. Researchers can analyse complicated data sets using artificial intelligence (AI) and machine learning (ML) techniques to get insights about pharmacological characteristics and interactions. This sophisticated analysis contributes to the development of more efficient medication formulations with improved bioavailability and stability. AI-powered medication delivery systems optimise dose regimens as well, guaranteeing accurate and personalised administration customised to specific patient demands. These systems can alter medication release rates and administration modalities by incorporating real-time patient data, resulting in enhanced treatment results and lower side effects. The capacity to use AI to optimise medication compositions and delivery systems opens the door to more effective and patient-centred pharmacological therapies.

Real-Time Patient Monitoring and Adaptive Dosing Boosts the AI-Driven Drug Delivery Market Size.

In the AI-driven drug delivery market, real-time patient monitoring and adaptive dosage are critical growth factors. Drug delivery systems can continually monitor patient reactions and adjust dose regimens by utilising powerful artificial intelligence (AI) and machine learning (ML) technology. Real-time monitoring provides for the early detection of changes in patient circumstances, allowing for appropriate drug delivery modifications. To personalise medicine dose and optimise treatment performance, AI-driven adaptive dosing evaluates individual patient factors such as age, weight, and medical history. This dynamic strategy increases treatment accuracy, decreases side effects, and improves patient outcomes. The combination of real-time patient monitoring and adaptive dosage transforms medication administration, ushering in a new era of patient-centred and responsive pharmacological treatments.

North America is the Market Leader in the AI-Driven Drug Delivery Market.

North America was regarded as the market leader in the AI-driven drug delivery market. Several reasons contribute to the region's supremacy, including its well-established pharmaceutical and biotechnology sectors, substantial research and development skills, and a strong emphasis on embracing innovative technologies. Furthermore, with multiple collaborations between AI startups and major pharmaceutical corporations, North America has been at the forefront of AI applications in healthcare. The region's favourable regulatory framework and significant expenditures in AI research have hastened the development of AI-driven drug Delivery systems. However, market dynamics may change the top region in the AI-driven drug delivery market.

Increased Research and Development Investments in AI-Driven Drug Delivery Market.

Increased R&D investments are driving factors in the AI-driven drug delivery market. Pharmaceutical businesses, biotechnology firms, and research institutes are investing heavily in developing and integrating artificial intelligence (AI) technologies into drug delivery systems. These investments seek to capitalise on the promise of AI in optimising medication formulations, dosage tactics, and personalised therapies. Furthermore, cooperation between industry heavyweights and AI companies is fuelling creative advances in medicine delivery, garnering further financing. The increased interest in AI-driven solutions reflects the industry's acknowledgement of AI's potential to revolutionise medication development and improve patient care. As R&D efforts develop, the AI-driven drug delivery market evolves, providing novel ways to pharmaceutical therapies.

Key Developments:

  • In June 2023, Merck, known as MSD outside of the United States and Canada, completed the purchase of Prometheus Biosciences, Inc. ("Prometheus"). Prometheus has become a wholly owned subsidiary of Merck, and its common stock will no longer be listed or traded on the Nasdaq Global Market.
  • In June 2023, GSK plc and BELLUS Health Inc. established a collaboration. GSK has finalised its purchase of BELLUS, a biopharmaceutical business dedicated to improving the lives of patients suffering from refractory chronic cough (RCC), under a plan of arrangement under Section 192 of the Canada Business Corporations Act (the "Arrangement"). Camlipixant, a possible best-in-class and highly selective P2X3 antagonist now in phase III research for the first-line treatment of adult patients with RCC, was announced as part of the BELLUS purchase.
  • In April 2023, Sanofi completed its acquisition of ProventionBio, Inc. ("Provention Bio"). The purchase expands Sanofi's core asset portfolio in General Medicines with the addition of TZIELD (teplizumab-Azov), a novel, wholly owned, first-in-class medication in type 1 diabetes, and furthers the company's strategy shift towards medicines with a distinctive profile.

Company Products:

  • Targeted Drug Delivery: Boehringer Ingelheim may have been investigating AI-driven drug delivery systems that allow for targeted and site-specific medication release, hence increasing drug concentration in certain parts of the body.
  • Predictive Analytics: Roche may have used artificial intelligence to anticipate drug reactions and identify probable side effects, allowing for pre-emptive treatments and enhanced patient safety.
  • Personalized Treatment Plans: GSK might have been working on AI-powered systems to personalise medicine doses and treatment strategies based on specific patient variables including genetics, medical history, and treatment response.
  • Precision Drug Delivery: Merck may have been investigating AI-powered medication delivery systems that allow for personalized dosage and tailored drug release, hence maximizing therapeutic effects.
  • AI-Optimized Drug Formulations: Novartis may be using AI algorithms to analyze medication characteristics and interactions, which might lead to the creation of optimized drug formulations with enhanced bioavailability and stability.

Segmentation:

By Technology

  • Machine Learning
  • Deep Learning
  • Natural Language Processing (Nlp)
  • Computer Vision
  • Others

By Type Of Drug Delivery

  • Oral Drug Delivery
  • Injectable Drug Delivery
  • Transdermal Drug Delivery
  • Inhalation Drug Delivery
  • Implantable Drug Delivery
  • Others

By Application

  • Oncology
  • Diabetes
  • Cardiovascular Diseases
  • Respiratory Disorders
  • Neurological Disorders
  • Autoimmune Diseases
  • Others

By End-User

  • Hospitals And Clinics
  • Pharmaceutical Companies
  • Research Institutes And Academic Centers
  • Home Care Settings
  • Others

By Geography

  • North America
  • United States
  • Canada
  • Mexico
  • South America
  • Brazil
  • Argentina
  • Others
  • Europe
  • United Kingdom
  • Germany
  • France
  • Italy
  • Spain
  • Others
  • Middle East and Africa
  • Saudi Arabia
  • UAE
  • Others
  • Asia Pacific
  • Japan
  • China
  • India
  • South Korea
  • Indonesia
  • Taiwan
  • Others

TABLE OF CONTENTS

1. INTRODUCTION

  • 1.1. Market Overview
  • 1.2. Market Definition
  • 1.3. Scope of the Study
  • 1.4. Market Segmentation
  • 1.5. Currency
  • 1.6. Assumptions
  • 1.7. Base, and Forecast Years Timeline

2. RESEARCH METHODOLOGY

  • 2.1. Research Data
  • 2.2. Sources
  • 2.3. Research Design

3. EXECUTIVE SUMMARY

  • 3.1. Research Highlights

4. MARKET DYNAMICS

  • 4.1. Market Drivers
  • 4.2. Market Restraints
  • 4.3. Porters Five Forces Analysis
    • 4.3.1. Bargaining Power of Suppliers
    • 4.3.2. Bargaining Power of Buyers
    • 4.3.3. Threat of New Entrants
    • 4.3.4. Threat of Substitutes
    • 4.3.5. Competitive Rivalry in the Industry
  • 4.4. Industry Value Chain Analysis

5. AI-DRIVEN DRUG DELIVERY MARKET, BY TECHNOLOGY

  • 5.1. Introduction
  • 5.2. MACHINE LEARNING
  • 5.3. DEEP LEARNING
  • 5.4. NATURAL LANGUAGE PROCESSING (NLP)
  • 5.5. COMPUTER VISION
  • 5.6. OTHERS

6. AI-DRIVEN DRUG DELIVERY MARKET, BY TYPE OF DRUG DELIVERY

  • 6.1. Introduction
  • 6.2. ORAL DRUG DELIVERY
  • 6.3. INJECTABLE DRUG DELIVERY
  • 6.4. TRANSDERMAL DRUG DELIVERY
  • 6.5. INHALATION DRUG DELIVERY
  • 6.6. IMPLANTABLE DRUG DELIVERY
  • 6.7. OTHERS

7. AI-DRIVEN DRUG DELIVERY MARKET, BY APPLICATION

  • 7.1. Introduction
  • 7.2. ONCOLOGY
  • 7.3. DIABETES
  • 7.4. CARDIOVASCULAR DISEASES
  • 7.5. RESPIRATORY DISORDERS
  • 7.6. NEUROLOGICAL DISORDERS
  • 7.7. AUTOIMMUNE DISEASES
  • 7.8. OTHERS

8. AI-DRIVEN DRUG DELIVERY MARKET, BY END-USER

  • 8.1. Introduction
  • 8.2. HOSPITALS AND CLINICS
  • 8.3. PHARMACEUTICAL COMPANIES
  • 8.4. RESEARCH INSTITUTES AND ACADEMIC CENTERS
  • 8.5. HOME CARE SETTINGS
  • 8.6. OTHERS
  • 8.7. AI-DRIVEN DRUG DELIVERY MARKET, BY GEOGRAPHY
  • 8.8. Introduction
  • 8.9. North America
    • 8.9.1. United States
    • 8.9.2. Canada
    • 8.9.3. Mexico
  • 8.10. South America
    • 8.10.1. Brazil
    • 8.10.2. Argentina
    • 8.10.3. Others
  • 8.11. Europe
    • 8.11.1. United Kingdom
    • 8.11.2. Germany
    • 8.11.3. France
    • 8.11.4. Italy
    • 8.11.5. Spain
    • 8.11.6. Others
  • 8.12. Middle East and Africa
    • 8.12.1. Saudi Arabia
    • 8.12.2. UAE
    • 8.12.3. Others
  • 8.13. Asia Pacific
    • 8.13.1. Japan
    • 8.13.2. China
    • 8.13.3. India
    • 8.13.4. South Korea
    • 8.13.5. Indonesia
    • 8.13.6. Taiwan
    • 8.13.7. Others

9. COMPETITIVE ENVIRONMENT AND ANALYSIS

  • 9.1. Major Players and Strategy Analysis
  • 9.2. Emerging Players and Market Lucrativeness
  • 9.3. Mergers, Acquisitions, Agreements, and Collaborations
  • 9.4. Vendor Competitiveness Matrix

10. COMPANY PROFILES

  • 10.1. MEDTRONIC PLC
  • 10.2. F. HOFFMANN-LA ROCHE AG
  • 10.3. GLAXOSMITHKLINE PLC
  • 10.4. NOVARTIS AG
  • 10.5. ELI LILLY AND COMPANY
  • 10.6. ASTRAZENECA PLC
  • 10.7. MERCK & CO., INC.
  • 10.8. PFIZER INC.
  • 10.9. SANOFI S.A.
  • 10.10. JOHNSON & JOHNSON