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市場調查報告書
商品編碼
2059555

生物製造中的人工智慧（AI）：科技與全球市場

Artificial Intelligence (AI) in Biomanufacturing: Technologies and Global Markets
出版日期: | 出版商: AMG NewTech | 英文 178 Pages | 訂單完成後即時交付

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簡介目錄

調查範圍概述

本報告檢驗了人工智慧 (AI) 在現代生物製造系統轉型中的作用。報告將 AI 定位為一項關鍵的基礎技術，支援向更有效率、擴充性且數位整合的生物生產平台轉型。本分析重點在於 AI 如何應對生物製造的核心挑戰，例如複雜性、製程變異性、監管限制以及跨產業的工業擴充性。本分析著重於商業性​​化生產運營，而非研發或臨床開發活動。

技術範圍

本報告從市場區隔角度和功能、流程導向角度對生物製造領域的人工智慧解決方案進行了定義。

從最高層面來看，市場區隔主要分為以下兩類：

  • 人工智慧軟體包括獨立式或模組化解決方案。
  • 人工智慧賦能的整合平台：由軟體、硬體、自動化或執行層組成的端到端系統。

此外，本報告還根據人工智慧解決方案在生物製造價值鏈中的功能作用進行分析，並確定了以下關鍵類別：

  • 人工智慧驅動的流程數據基礎設施和製造分析。重點關注數據整合、情境化、生命週期分析和外部互聯製造。
  • 人工智慧整合生物感測和智慧測量系統：實現生物訊號的即時監測和解讀。
  • 基於人工智慧的預測建模和過程監控系統。這包括軟感知、批次預測和異常檢測。
  • AI 驅動的數位雙胞胎整合了機制模型和資料驅動模型，用於消除資料差距、類比、場景測試和封閉回路型製程控制。
  • 這是一個基於人工智慧的最佳化、控制和決策支援系統。它能夠實現即時、多目標最佳化以及人機協作的半自動決策。
  • 人工智慧驅動的流程改善和製造創新技術。這包括用於流程改進和升級的生成式人工智慧和基於代理的推理。
  • 這是一個利用人工智慧技術的整合自動化和機器人執行系統。它將人工智慧驅動的洞察轉化為自主製造行動。

我們會根據每項技術類別的採用情況、擴充性以及在生物製造環境中的作用進行評估。

目標領域和產業

本報告評估了人工智慧在以下生物製造領域的應用：

  • 醫療保健和生物製藥製造
  • 化學與塑膠
  • 能源
  • 食品/飲料
  • 農業
  • 新興產業，例如紡織業、國防和航空航太製造業。

該分析涵蓋了已建立和新興的用例，重點關注採用水平、監管審查和經濟促進因素方面的差異。

市場與產業分析

本研究對生物製造領域的人工智慧市場進行了全球分析，包括以下內容：

  • 人工智慧解決方案：按類型、技術分類、應用和地區分類的市場規模和預測
  • 影響產業採用的趨勢包括數位化、監管變化和自動化策略。
  • 將人工智慧軟體和人工智慧整合平台及其在製造系統中的各自作用進行比較。

競爭格局

本報告對人工智慧生物製造生態系統中的 60 多家公司進行了詳細的競爭分析，重點關注以下方面：

  • 主要軟體供應商（例如 Aizon、Cognite、TetraScience、Seeq、DataHow）
  • 整合平台和工業自動化供應商（例如，西門子、賽多利斯、艾默生、羅克韋爾自動化、霍尼韋爾）
  • 人工智慧原生和新興科技公司（如 Quartic.ai、Katalyze AI、Fero Labs、BioprocessAI）
  • AI基礎設施供應商（輝達、微軟、OpenAI）
  • 生物製藥企業和契約製造（安進、輝瑞、BASF、藥明生物、三星生物）正在擴大人工智慧的應用。

本報告詳細介紹了主要供應商的情況，並簡要概述了其他專業和新興企業，重點關注其技術定位、關注領域和競爭策略。

智慧財產權及相關法規分析

本報告提供以下內容：

  • 對人工智慧驅動的生物製造技術進行專利分析。重點關注主要申請人、創新趨勢和技術重點領域。
  • 一項監管分析，檢驗了美國、歐洲、亞太地區和其他地區的法規結構，特別關注GMP合規性、資料完整性和人工智慧管治。

目標區域和目標時期

目標區域為全球，包括以下區域分析：

  • 北美洲
  • 歐洲
  • 亞太地區
  • 其他地區

本報告提供 2024 年至 2031 年的市場估算、預測和產業趨勢，其中 2026 年為詳細市場估算的基準年。

本報告未涵蓋以下領域。

  • AI驅動的藥物發現、早期研發、臨床開發或純粹基於服務的AI解決方案。
  • 與製造技術無關的消費者採納分析。
  • 專有製造程式參數和機密操作數據
  • 工廠層級的詳細技術規格與設備設計

目錄

摘要整理

介紹

  • 生物製造及其應用
    • 生物製造的應用
  • 生物製造過程的結構複雜性
  • 人工智慧在生物製造中的作用

技術狀態

  • 生物製造中人工智慧技術概述
    • 人工智慧驅動的過程數據基礎設施和製造分析
    • 人工智慧整合生物感測和智慧測量系統
    • 基於人工智慧的預測建模和過程監控系統
    • 人工智慧驅動的數位雙胞胎
    • 人工智慧驅動的最佳化、控制和決策支援系統
    • 人工智慧驅動的流程改善與製造創新技術
    • 人工智慧驅動的整合自動化和機器人執行系統
  • 專利分析

競爭格局

  • 公司概況介紹
  • 公司簡介 - 人工智慧驅動的生物製造解決方案
    • 人工智慧軟體
    • 人工智慧賦能的整合平台
    • 近期行業活動
  • 人工智慧在生物製造領域的商業應用
  • 當地景觀
    • 美國
    • 歐洲
    • 亞太地區
    • 世界其他地區
  • 人工智慧在生物製造領域面臨的產業挑戰
  • 數據室
  • 人才招募

世界市場分析

  • 全球生物製造領域人工智慧市場概況
    • 全球人工智慧解決方案市場（按類型分類）
    • 產業趨勢
    • 全球市場，依技術類別分類
    • 全球市場，按應用領域分類
    • 全球市場（按地區分類）
  • 人工智慧軟體
  • 人工智慧賦能的整合平台

調查方法和資質

簡介目錄
Product Code: MN26001

Scope and Coverage Overview

This report examines the role of artificial intelligence (AI) as a transformative layer within modern biomanufacturing systems. It positions AI as a critical enabling technology supporting the transition toward more efficient, scalable, and digitally integrated biological production platforms. The analysis focuses on how AI addresses core challenges associated with biomanufacturing complexity, process variability, regulatory constraints, and industrial scalability across multiple sectors, with emphasis on commercial manufacturing operations rather than R&D or clinical development activities.

Technology Scope

The report defines AI solutions in biomanufacturing from both a market segmentation perspective and a functional, process-oriented perspective.

At the highest level, the market is segmented into two primary categories:

  • AI software, consisting of standalone or modular solutions.
  • AI-enabled integrated platforms, consisting of end-to-end systems combining software with hardware, automation, or execution layers.

In addition, the report analyzes AI solutions based on their functional role within the biomanufacturing value chain, identifying several core categories:

  • AI-enabled process data infrastructure and manufacturing analytics, focusing on data integration, contextualization, lifecycle analytics, and externally connected manufacturing.
  • AI-integrated biosensing and smart measurement systems, enabling real-time monitoring and interpretation of biological signals.
  • AI-based predictive modeling and process monitoring systems, including soft sensing, batch prediction, and anomaly detection.
  • AI-enabled digital twins, integrating mechanistic and data-driven models for data gap filling, simulation, scenario testing, and closed-loop process control.
  • AI-supported optimization, control, and decision-support systems, enabling real-time, multi-objective optimization, and human-in-the-loop, semi-autonomous decision-making.
  • AI-enabled process improvement and manufacturing innovation technologies, including generative AI and agentic reasoning for process improvement and upgrades.
  • AI-enabled integrated automation and robotic execution systems, translating AI-driven insights into autonomous manufacturing actions.

Each technology category is evaluated in terms of deployment status, scalability, and role within biomanufacturing environments.

Application and Industry Coverage

The report assesses AI adoption across multiple biomanufacturing sectors, including:

  • Healthcare and biopharmaceutical manufacturing
  • Chemicals and plastics
  • Energy
  • Food and beverage
  • Agriculture
  • Emerging sectors such as textiles, defense, and space-based manufacturing

Analysis includes both established applications and emerging use cases, highlighting differences in adoption levels, regulatory intensity, and economic drivers.

Market and Industry Analysis

The study provides global analysis of the AI in biomanufacturing market, including:

  • Market size and forecasts by AI solution type, technology class, application, and region
  • Industry trends shaping adoption, including digitalization, regulatory evolution, and automation strategies
  • Comparison of AI software versus AI-enabled integrated platforms and their respective roles in manufacturing systems

Competitive Landscape

The report features a detailed competitive analysis covering over 60 companies across the AI biomanufacturing ecosystem, such as:

  • Leading software providers (e.g., Aizon, Cognite, TetraScience, Seeq, DataHow)
  • Integrated platforms and industrial automation providers (e.g., Siemens, Sartorius, Emerson, Rockwell Automation, Honeywell)
  • AI-native and emerging technology firms (e.g., Quartic.ai, Katalyze AI, Fero Labs, BioprocessAI)
  • AI infrastructure providers (Nvidia, Microsoft, OpenAI)
  • Biomanufacturers and contract manufacturers scaling up AI (Amgen, Pfizer, BASF, WuXi Biologics, Samsung Biologics).

Company coverage includes detailed profiles for key vendors, along with shorter summaries for additional specialized or emerging players, highlighting technology positioning, sector focus, and competitive strategies.

Intellectual Property and Regulatory Coverage

The report provides:

  • Patent analysis covering AI-driven biomanufacturing technologies, highlighting key applicants, innovation trends, and technology concentration areas
  • Regulatory analysis examining frameworks in the United States, Europe, Asia Pacific, and other regions, with particular focus on GMP compliance, data integrity, and AI governance

Geographic Scope and Time Horizon

Geographic coverage is global, including analysis of:

  • North America
  • Europe
  • Asia Pacific
  • Rest of the world

Market forecasts and industry trends are provided for the 2024–2031 period, with 2026 as the base year for detailed market estimates.

What This Report Does Not Cover

  • AI-driven drug discovery, early-stage R&D, clinical development, or purely service-based AI offerings
  • Consumer-facing adoption analysis unrelated to manufacturing technologies
  • Proprietary manufacturing process parameters or confidential operational data
  • Detailed plant-level engineering specifications or equipment design

Table of Contents

EXECUTIVE SUMMARY

INTRODUCTION

  • BIOMANUFACTURING AND ITS APPLICATIONS
    • APPLICATIONS OF BIOMANUFACTURING
  • STRUCTURAL COMPLEXITY OF BIOMANUFACTURING PROCESSES
  • ROLE OF AI IN BIOMANUFACTURING

TECHNOLOGY STATUS

  • OVERVIEW OF AI TECHNOLOGIES USED IN BIOMANUFACTURING
    • AI-ENABLED PROCESS DATA INFRASTRUCTURE AND MANUFACTURING ANALYTICS
    • AI-INTEGRATED BIOSENSING AND SMART MEASUREMENT SYSTEMS
    • AI-BASED PREDICTIVE MODELING AND PROCESS MONITORING SYSTEMS
    • AI-ENABLED DIGITAL TWINS
    • AI-SUPPORTED OPTIMIZATION, CONTROL, AND DECISION-SUPPORT SYSTEMS
    • AI-ENABLED PROCESS IMPROVEMENT AND MANUFACTURING INNOVATION TECHNOLOGIES
    • AI-ENABLED INTEGRATED AUTOMATION AND ROBOTIC EXECUTION SYSTEMS
  • PATENT ANALYSIS

COMPETITIVE LANDSCAPE

  • INTRODUCTION TO COMPANY PROFILES
  • COMPANY PROFILES – AI-ENABLED BIOMANUFACTURING SOLUTIONS
    • AI SOFTWARE
    • AI-ENABLED INTEGRATED PLATFORMS
    • RECENT INDUSTRY EVENTS
  • COMMERCIAL USE CASES OF AI IN BIOMANUFACTURING
  • REGIONAL LANDSCAPE
    • UNITED STATES
    • EUROPE
    • ASIA PACIFIC
    • REST OF THE WORLD
  • INDUSTRY CHALLENGES FOR AI IN BIOMANUFACTURING
  • DATA QUALITY
  • TALENT ACQUISITION

GLOBAL MARKET ANALYSIS

  • GLOBAL MARKET SUMMARY FOR AI IN BIOMANUFACTURING
    • GLOBAL MARKET BY AI SOLUTION TYPE
    • INDUSTRY TRENDS
    • GLOBAL MARKET BY TECHNOLOGY CLASS
    • GLOBAL MARKET BY APPLICATION
    • GLOBAL MARKET BY REGION
  • AI SOFTWARE
  • AI-ENABLED INTEGRATED PLATFORMS

METHODOLOGY AND CREDENTIALS

  • METHODOLOGY
  • ANALYST CREDENTIALS
  • ABOUT AMG NEWTECH
  • CONTACT