查看購物車
  • English
  • Japanese
封面
市場調查報告書
商品編碼
1919791

人工智慧在製藥製造領域的市場——產業趨勢及2040年全球預測——按產品類型、部署模式、人工智慧解決方案類型、技術類型、應用領域、在製藥製造中的應用、地區及主要公司劃分

AI in Pharma Manufacturing Market, till 2040: Distribution by Type of Offering, Mode of Deployment, Type of AI Solution, Type of Technology, Application Area, Utility in Drug Manufacturing, Geographical Regions and Key Players
出版日期: | 出版商: Roots Analysis | 英文 201 Pages | 商品交期: 最快1-2個工作天內

價格
簡介目錄

人工智慧在製藥製造領域的市場展望

預計到2040年，全球人工智慧在製藥製造領域的市場規模將從目前的12億美元增長至347億美元，預測期內（至2040年）的複合年增長率（CAGR）預計為28%。本報告提供市場規模、成長情境、產業趨勢和未來預測。

人工智慧（AI）是電腦科學的一個分支，它使電腦能夠執行通常需要人類智慧才能完成的複雜任務，例如學習、推理和決策。在醫療保健領域，人工智慧已被應用於藥物研發、臨床試驗、診斷、個人化醫療和資料管理等多個面向。在製藥生產中，人工智慧利用電腦視覺、機器學習、生成式人工智慧和深度學習等技術來改善流程監控、識別低效環節、降低生產成本並提高產品產量。

製藥生產面臨許多效率低下的問題，包括工作流程效率低、設備停機、品質控制問題和供應鏈中斷。這些問題會導致成本增加、生產延誤和產品品質不穩定。人工智慧透過實現流程最佳化、工廠和設備性能監控、主動預測設備故障、供應鏈管理以及品質控制流程自動化來應對這些挑戰。隨著製藥業向 "製藥4.0" 轉型，包括輝瑞、莫德納、諾華、默克和賽諾菲在內的多家製藥公司正在將人工智慧融入其生產營運中。

AI in Pharma Manufacturing Market-IMG1

高階主管策略洞察

人工智慧在製藥製造的應用案例有哪些？

超過 60% 的大型製藥公司正在使用人工智慧來創新其生產流程，並提高效率、品質和靈活性。典型應用包括即時監控、自動化品質檢測、預測性維護和供應鏈優化。

例如，賽諾菲正在應用人工智慧來提高產量和製程效率。諾華正在使用機器學習技術進行即時工廠監控和基於人工智慧的製藥製造供應鏈優化。默克正在使用人工智慧來降低品質評估中的誤判率。 Moderna 也正在利用人工智慧工具來改善其品質控制系統。這些技術不僅簡化了流程，還降低了成本，並改善了人工智慧在製藥生產中的監管環境。

隨著領先的製藥公司和人工智慧解決方案提供商不斷提升自身能力，將人工智慧融入製藥生產對於實現卓越營運和在這個快速變化的行業中保持競爭優勢至關重要。

推動製藥生產領域人工智慧市場成長的關鍵因素

製藥生產領域人工智慧的成長源於對提高流程效率、降低生產成本和確保產品品質一致性的日益增長的需求。此外，監管支持的加強和製藥行業數位轉型的推進也進一步促進了尖端人工智慧技術的應用。

值得注意的是，人工智慧在製藥生產中的應用範圍十分廣泛，包括品質控制、預測性維護、製程開發和優化、工廠和設備性能監控以及供應鏈優化。這種不斷擴展的應用範圍正在顯著推動市場對專為製藥生產設計的人工智慧解決方案的需求。

人工智慧在製藥製造領域的應用市場：競爭格局

目前市場環境包含約 130 家參與公司，涵蓋大型、中型和小型企業。這些企業具備為不同地區的製藥製造提供人工智慧解決方案的必要技能。

值得注意的是，超過 95% 的製藥製造人工智慧應用公司提供先進的軟體解決方案。此外，約 80% 的公司正在採用機器學習技術，實現製藥製造流程各階段的數位化。

區域分析：亞太地區將在未來幾年推動市場成長

根據我們的預測，北美目前佔據市場的大部分份額，預計這一趨勢將持續。這主要歸功於該地區擁有先進的製藥製造基礎設施、在醫療技術領域較早應用人工智慧 (AI) 技術，以及完善的監管框架。

然而，預計亞太市場在預測期內將以較高的複合年增長率成長。這主要得益於較低的實施成本、鼓勵數位化的政府支持政策以及快速擴張的製藥業。

人工智慧在製藥製造中的演進：產業新興趨勢

人工智慧正在透過使流程更聰明、更快速、更可靠來變革製藥製造。新興趨勢包括利用機器學習進行預測性維護，從而及早發現設備問題，減少停機時間和成本。利用人工智慧視覺進行即時品質控制，可以即時檢測生產線上的缺陷，例如裂縫和污染，從而確保藥品品質的一致性並符合法規要求。流程優化利用先進的控制技術和數位孿生技術來微調溫度和混合等參數，從而提高效率並減少浪費。將人工智慧與機器人和物聯網結合，將打造未來的自動化實驗室，實現持續監控和自適應生產。這些創新使製藥公司能夠更快地生產更安全的藥物，同時降低成本並滿足更嚴格的標準。

主要市場挑戰

人工智慧在製藥生產領域的市場應用面臨諸多挑戰，阻礙了其普及。其中一個主要挑戰是資料問題，資料品質差、偏差、資料孤島以及資料可用性有限等問題導致人工智慧模型在精準生產任務中難以可靠運作。高昂的實施成本、與現有系統的整合以及持續的維護費用給預算造成了壓力，尤其對於中小企業而言，這阻礙了它們採用這項技術。此外，GMP 和 FDA 等嚴格法規要求進行驗證、確保透明度和合規性，而人工智慧的 "黑箱" 特性又使審批和倫理問題變得複雜。另外，同時具備人工智慧和製藥專業知識的人才短缺也阻礙了人工智慧在製藥生產領域的有效應用。

人工智慧在製藥製造領域的市場：主要細分市場

產品類型

  • 硬體
  • 軟體
  • 服務

部署模式

  • 雲端部署
  • 本地部署

人工智慧解決方案類型

  • 標準/現成人工智慧解決方案
  • 客製化人工智慧解決方案

技術型別

  • 電腦視覺
  • 深度學習
  • 生成式人工智慧
  • 機器學習
  • 其他技術

應用領域

  • 製程開發與最佳化
  • 工廠/設備效能監控
  • 預測性維護
  • 品質控制
  • 供應鏈優化
  • 其他應用

適用於藥廠生產

  • 缺陷檢測
  • 包裝和標籤檢查
  • 包裝計數
  • 填充液位檢查
  • 其他用途

地理區域

  • 北美洲
  • 美國
  • 加拿大
  • 歐洲
  • 德國
  • 英國
  • 義大利
  • 西班牙
  • 法國
  • 歐洲其他地區
  • 亞太地區
  • 中國
  • 印度
  • 日本
  • 韓國
  • 澳大利亞
  • 拉丁美洲
  • 巴西
  • 阿根廷
  • 其他拉丁美洲國家
  • 中東和北非
  • 沙烏地阿拉伯
  • 阿拉伯聯合大公國阿聯酋
  • 埃及
  • 其他中東和北非地區

人工智慧在製藥製造領域的市場：關鍵市場份額洞察

依產品類型劃分的市佔率

依產品類型，全球市場可分為硬體、軟體和服務。據我們估計，軟體目前佔據了大部分市場份額。這主要歸功於整合了預測分析和流程優化等先進技術的軟體解決方案的日益普及，從而提高了營運效率並促進了製藥製造領域的創新。

按人工智慧解決方案類型劃分的市場佔有率

根據人工智慧解決方案類型，全球市場可分為標準/現成人工智慧解決方案和客製化人工智慧解決方案。據我們估計，標準/現成人工智慧解決方案目前佔據了大部分市場份額。這主要是因為業界更傾向於使用預先驗證、符合規範且可快速部署和擴展的解決方案。

製藥製造領域人工智慧市場的主要參與者

  • C3.AI
  • AMD
  • IBM
  • Kalypso
  • SAS Institute
  • Körber Pharma
  • SDG Group
  • Catalyx
  • Elisa Industriq
  • Straive
  • Axiomtek
  • Appinventiv
  • Amplelogic
  • Precognize

製藥製造領域人工智慧市場：報告範圍

本報告涵蓋製藥製造領域人工智慧市場的以下幾個部分：

  • 市場規模與機會分析：製藥製造領域人工智慧市場的詳細分析。 本報告聚焦在關鍵市場細分，涵蓋[A]產品類型、[B]部署模式、[C]人工智慧解決方案類型、[D]技術類型、[E]應用領域、[F]在製藥生產中的應用、[G]地理區域以及[H]主要參與者。
  • 競爭格局：基於多個相關參數，對參與製藥生產人工智慧市場的公司進行全面分析，例如[A]成立年份、[B]公司規模、[C]總部所在地以及[D]所有權結構。
  • 公司簡介：提供參與製藥生產人工智慧市場主要參與者的詳細簡介，涵蓋[A]總部所在地、[B]公司規模、[C]企業理念、[D]公司業務範圍、[E]管理團隊、[F]聯絡資訊、[G]財務資訊、[H]業務板塊、[I]產品組合以及[J]近期發展動態。以及未來展望。
  • 宏觀趨勢：評估人工智慧在製藥製造業中正在發生的宏觀趨勢。
  • 近期發展：概述人工智慧在製藥製造市場中的最新發展，並基於相關參數進行分析，例如[A] 舉措年份、[B] 舉措類型、[C] 地理分佈和[D] 主要參與者。
  • SWOT 分析：深入的 SWOT 分析框架，突顯該產業的優勢、劣勢、機會和威脅。此外，還提供哈維鮑爾分析，以突出每個 SWOT 參數的相對影響。

目錄

第一章：背景

第二章：研究方法

第三章：市場動態

第四章：宏觀經濟指標

  • 章節概述
  • 市場動態
  • 結論

第五章：執行摘要

第六章：引言

  • 人工智慧在製藥生產上的應用概述
  • 人工智慧在製藥生產上的必要性
  • 人工智慧在製藥生產價值鏈中的作用
  • 製藥生產中使用的人工智慧技術類型
  • 人工智慧在製藥生產的應用
  • 人工智慧在製藥生產中的益處製藥製造
  • 人工智慧在製藥製造中應用的挑戰
  • 近期趨勢與未來展望

第七章 市場概覽：製藥製造人工智慧解決方案供應商

  • 研究方法與關鍵參數
  • 製藥製造人工智慧：市場概覽

第八章：競爭分析

  • 研究方法與關鍵參數
  • 評分標準
  • 同儕概覽
  • 製藥製造人工智慧：競爭分析
  • 製藥製造人工智慧：基準分析

第九章 公司簡介：北美製藥業人工智慧解決方案供應商

  • 概述
  • C3.AI
  • AMD
  • IBM
  • Kalypso：羅克韋爾自動化旗下公司
  • SAS Institute

第十章 公司簡介：歐洲製藥製造領域的人工智慧解決方案提供者

  • 概述
  • Körber Pharma
  • SDG Group
  • Catalyx
  • Elisa Industriq

第十一章 公司簡介：亞太地區製藥製造領域的人工智慧解決方案提供者超越

  • 概述
  • Straive
  • Axiomtek
  • Appinventiv
  • Amplelogic
  • Samson Precognize Solutions

第十二章：夥伴關係與合作

  • 合作模式
  • 人工智慧在製藥製造中的應用：夥伴關係與合作

第十三章：資金與投資分析

  • 資金模式
  • 資金生命週期分析
  • 投資案例：風險與回報
  • 人工智慧在製藥製造的應用：資金與投資分析
  • 資金模式的演變與相對評估
  • 資金與投資機會概述

章節第十四章：新創企業健康指標

  • 章節概述
  • 為製藥製造提供人工智慧解決方案的新創企業
  • 新創企業基準分析

第十五章：製藥製造人工智慧市場：大趨勢分析

  • 大趨勢分析：新興趨勢概述

第十六章：市場影響分析：驅動因素、限制因素、機會與挑戰

  • 章節概述
  • 市場驅動因素
  • 市場限制因素
  • 市場機遇
  • 市場挑戰
  • 結論

第十七章：全球製藥製造人工智慧市場

第十八章：製藥製造人工智慧市場（按產品/服務分類）

第19章：人工智慧在製藥製造領域的市場（按部署模式劃分）

第20章：人工智慧在製藥製造領域的市場（按人工智慧解決方案類型劃分）

第21章：人工智慧在製藥製造領域的市場（按技術劃分）

第22章：人工智慧在製藥製造領域的市場（按應用領域劃分）

第23章：人工智慧在製藥製造領域的市場（按在製藥製造中的應用價值劃分）

第24章：人工智慧在製藥製造領域的市場（按地區劃分）

第25章：人工智慧在製藥製造領域的市場（按主要公司劃分）

第26章：市場機會分析：北美

第27章：市場機會分析：歐洲

第28章：市場機會分析：亞太地區

第29章：市場機會分析：中東與北非

第30章：市場機會分析：拉丁美洲

第31章：結論

第32章：高階主管洞察

第33章：表格資料

第34章：公司和機構列表

簡介目錄
Product Code: RA100621

AI in Pharma Manufacturing Market Outlook

As per Roots Analysis, the global AI in pharma manufacturing market size is estimated to grow from USD 1.20 billion in the current year to USD 34.7 billion by 2040, at a CAGR of 28% during the forecast period, till 2040. The new study provides market size, growth scenarios, industry trends and future forecasts.

Artificial Intelligence (AI) is a subdivision of computer science that enables computers to perform intricate tasks that usually require human intelligence, including learning, reasoning, and making decisions. In the healthcare sector, AI is already being applied in various areas such as drug discovery, clinical trials, diagnostics, personalized medicine, and data management. Within pharmaceutical manufacturing, AI utilizes technologies like computer vision, machine learning, generative AI, and deep learning to improve process monitoring, identify inefficiencies, lower production costs, and enhance product yield.

Pharmaceutical manufacturing faces numerous inefficiencies, including inefficient workflows, equipment downtime, quality control issues, and supply chain interruptions. These inefficiencies can result in higher costs, production delays, and variability in product quality. AI addresses these challenges by enabling process optimization, monitoring the performance of plants and equipment, anticipating equipment failures beforehand, managing supply chains, and automating quality control processes. Several pharmaceutical companies, including Pfizer, Moderna, Novartis, Merck, and Sanofi, are integrating AI into their manufacturing operations as the sector evolves towards Pharma 4.0.

AI in Pharma Manufacturing Market - IMG1

Strategic Insights for Senior Leaders

What are the Use Cases of Artificial Intelligence in Pharmaceutical Manufacturing?

More than 60% of major pharmaceutical companies are utilizing AI to revolutionize their manufacturing processes, improving efficiency, quality, and flexibility. Prominent applications include real-time monitoring, automated quality inspections, predictive maintenance, and optimization of the supply chain.

For example, Sanofi applies AI to enhance production yield and process effectiveness; Novartis uses machine learning techniques for real-time monitoring of plants and AI-powered supply chain optimization in drug production; Merck utilizes AI to decrease false reject rates in quality assessments; and Moderna leverages AI-based tools to improve quality control systems. These technologies not only streamline processes but also lead to cost savings and a better regulatory environment for AI in the drug manufacturing sector.

As top pharmaceutical firms and AI solution providers continue to develop their capabilities, incorporating AI into drug manufacturing has become essential for achieving operational excellence and sustaining a competitive advantage in this swiftly changing industry.

Key Drivers Propelling Growth of AI in Pharma Manufacturing Market

The growth of AI in the drug manufacturing sector is driven by an increasing demand for enhanced process efficiency, lower production costs, and the maintenance of consistent product quality. Additionally, rising regulatory support and the ongoing digital transformation within the pharmaceutical industry further promotes the adoption of cutting-edge AI technologies.

It is worth noting that AI applications in drug manufacturing encompass a range of functions, including quality control, predictive maintenance, process development and optimization, monitoring of plant and equipment performance, as well as supply chain optimization. The broadening range of these applications continues to propel substantial market demand for AI solutions specifically designed for pharmaceutical manufacturing.

AI in Pharma Manufacturing Market: Competitive Landscape of Companies in this Industry

The present market environment consists of approximately 130 participants, including major, large, medium, and small enterprises. These organizations possess the necessary skills to deliver AI solutions for drug production across various geographical areas.

Importantly, over 95% of the companies involved in AI for drug production provide advanced software solutions. Further, nearly 80% of these firms are implementing machine learning to digitize various phases of the drug manufacturing process.

Regional Analysis: Asia-Pacific to Propel the market growth in the Coming Years

According to our projections, currently North America captures the majority of the market, and this trend is unlikely to change in the future as well. This is due to the presence of advanced pharma manufacturing infrastructure, early adoption of artificial intelligence (AI) in healthcare technologies and supportive regulatory framework across the region.

However, it is worth highlighting that the market in Asia-Pacific is expected to grow at a higher CAGR during the forecast period. This is driven by the lower implementation costs, supportive government policies fostering digitalization, and rapidly expanding pharmaceutical sector.

AI in Pharma Manufacturing Evolution: Emerging Trends in the Industry

AI is transforming pharmaceutical manufacturing by making processes smarter, faster, and more reliable. Emerging trends include predictive maintenance using machine learning to spot equipment issues early, cutting downtime and costs. Real-time quality control with AI vision detects defects like cracks or contamination instantly in production lines, ensuring consistent drug quality and regulatory compliance. Process optimization employs advanced controls and digital twins to fine-tune parameters such as temperature and mixing, boosting efficiency and reducing waste. AI combined with robotics and IoT enables automated labs of the future for continuous monitoring and adaptive production. These innovations help pharma companies to produce safer medicines quicker while saving money and meeting strict standards.

Key Market Challenges

The market for AI in pharma manufacturing faces significant challenges that slow its adoption. One of the primary challenges is data issues, with poor quality, biases, silos, and limited availability making AI models unreliable for precise production tasks. High costs for setup, integration with old systems, and ongoing maintenance strain budgets, especially for smaller firms hindering the adoption of such technologies. Additionally, strict regulations like GMP and FDA rules demand validation, transparency, and compliance, but AI's "black box" nature complicates approvals and ethics. Moreover, shortage of personnel skilled in both AI and pharmaceutical expertise hampers effective deployment of AI in the pharmaceutical manufacturing domain.

AI in Pharma Manufacturing Market: Key Market Segmentation

Type of Offering

  • Hardware
  • Software
  • Services

Mode of Deployment

  • Cloud
  • On-premise

Type of AI Solution

  • Standard / Off-the-shelf AI solutions
  • Personalized AI solutions

Type of Technology

  • Computer Vision
  • Deep Learning
  • Generative AI
  • Machine Learning
  • Other Technologies

Application Area

  • Process Development and Optimization
  • Plant / Equipment Performance Monitoring
  • Predictive Maintenance
  • Quality Control
  • Supply Chain Optimization
  • Other Application Areas

Utility in Drug Manufacturing

  • Defect Detection
  • Packaging and Label Inspection
  • Package Counting
  • Fill Level Inspection
  • Other Utilities

Geographical Regions

  • North America
  • US
  • Canada
  • Europe
  • Germany
  • UK
  • Italy
  • Spain
  • France
  • Rest of Europe
  • Asia-Pacific
  • China
  • India
  • Japan
  • Korea
  • Australia
  • Latin America
  • Brazil
  • Argentina
  • Rest of Latin America
  • Middle East and North Africa
  • Saudi Arabia
  • UAE
  • Egypt
  • Rest of MENA

AI in Pharma Manufacturing Market: Key Market Share Insights

Market Share by Type of Offering

Based on the type of offering, the global market is segmented into hardware, software, and services. According to our estimates, currently, software captures majority share of the market. This is driven by the increasing adoption of software-based solutions that integrate advanced techniques, such as predictive analytics, and process optimization, thereby improving operational efficiency and foster innovation in drug manufacturing.

Market Share by Type of AI Solution

Based on the type of AI solution, the global market is segmented into standard / off-the-shelf AI solutions and personalized AI solutions. According to our estimates, currently, standard / off-the-shelf AI solutions capture majority share of the market. This is primarily due to industry's preference towards pre-validated, compliant, and ready-to-deploy solutions that can be deployed and scaled rapidly.

Example Players in AI in Pharma Manufacturing Market

  • C3.AI
  • AMD
  • IBM
  • Kalypso
  • SAS Institute
  • Korber Pharma
  • SDG Group
  • Catalyx
  • Elisa Industriq
  • Straive
  • Axiomtek
  • Appinventiv
  • Amplelogic
  • Precognize

AI in Pharma Manufacturing Market: Report Coverage

The report on the AI in pharma manufacturing market features insights on various sections, including:

  • Market Sizing and Opportunity Analysis: An in-depth analysis of the AI in pharma manufacturing market, focusing on key market segments, including [A] type of offering, [B] mode of deployment, [C] type of AI solution, [D] type of technology, [E] application area, [F] utility in drug manufacturing, [G] geographical regions and [H] key players.
  • Competitive Landscape: A comprehensive analysis of the companies engaged in the AI in pharma manufacturing market, based on several relevant parameters, such as [A] year of establishment, [B] company size, [C] location of headquarters and [D] ownership structure.
  • Company Profiles: Elaborate profiles of prominent players engaged in the AI in pharma manufacturing market, providing details on [A] location of headquarters, [B] company size, [C] company mission, [D] company footprint, [E] management team, [F] contact details, [G] financial information, [H] operating business segments, [I] portfolio, [J] recent developments, and an informed future outlook.
  • Megatrends: An evaluation of ongoing megatrends in the AI in pharma manufacturing industry.
  • Recent Developments: An overview of the recent developments made in the AI in pharma manufacturing market, along with analysis based on relevant parameters, including [A] year of initiative, [B] type of initiative, [C] geographical distribution and [D] most active players.
  • SWOT Analysis: An insightful SWOT framework, highlighting the strengths, weaknesses, opportunities and threats in the domain. Additionally, it provides Harvey ball analysis, highlighting the relative impact of each SWOT parameter.

Key Questions Answered in this Report

  • What is the current and future market size?
  • Who are the leading companies in this market?
  • What are the growth drivers that are likely to influence the evolution of this market?
  • What are the key partnership and funding trends shaping this industry?
  • Which region is likely to grow at higher CAGR till 2040?
  • How is the current and future market opportunity likely to be distributed across key market segments?

Reasons to Buy this Report

  • Detailed Market Analysis: The report provides a comprehensive market analysis, offering detailed revenue projections of the overall market and its specific sub-segments. This information is valuable to both established market leaders and emerging entrants.
  • In-depth Analysis of Trends: Stakeholders can leverage the report to gain a deeper understanding of the competitive dynamics within the market. Each report maps ecosystem activity across partnerships, funding, and patent landscapes to reveal growth hotspots and white spaces in the industry.
  • Opinion of Industry Experts: The report features extensive interviews and surveys with key opinion leaders and industry experts to validate market trends mentioned in the report.
  • Decision-ready Deliverables: The report offers stakeholders with strategic frameworks (Porter's Five Forces, value chain, SWOT), and complimentary Excel / slide packs with customization support.

Additional Benefits

  • Complimentary Dynamic Excel Dashboards for Analytical Modules
  • Exclusive 15% Free Content Customization
  • Personalized Interactive Report Walkthrough with Our Expert Research Team
  • Free Report Updates for Versions Older than 6-12 Months

TABLE OF CONTENTS

1. BACKGROUND

  • 1.1. Context
  • 1.2. Project Objectives

2. RESEARCH METHODOLOGY

  • 2.1. Chapter Overview
  • 2.2. Research Assumptions
    • 2.2.1. Market Landscape and Market Trends
    • 2.2.2. Market Forecast and Opportunity Analysis
    • 2.2.3. Comparative Analysis
  • 2.3. Database Building
    • 2.3.1. Project Commencement
    • 2.3.2. Data Collection
    • 2.3.3. Data Validation
    • 2.3.4. Data Analysis
  • 2.4. Project Methodology
    • 2.4.1. Secondary Research
      • 2.4.1.1. Annual Reports
      • 2.4.1.2. Academic Research Papers
      • 2.4.1.3. Company Websites
      • 2.4.1.4. Investor Presentations
      • 2.4.1.5. Regulatory Filings
      • 2.4.1.6. White Papers
      • 2.4.1.7. Industry Publications
      • 2.4.1.8. Conferences and Seminars
      • 2.4.1.9. Government Portals
      • 2.4.1.10. Media and Press Releases
      • 2.4.1.11. Newsletters
      • 2.4.1.12. Industry Databases
      • 2.4.1.13. Roots Proprietary Databases
      • 2.4.1.14. Paid Databases and Sources
      • 2.4.1.15. Social Media Portals
      • 2.4.1.16. Other Secondary Sources
    • 2.4.2. Primary Research
      • 2.4.2.1. Types of Primary Research
        • 2.4.2.1.1. Qualitative Research
        • 2.4.2.1.2. Quantitative Research
        • 2.4.2.1.3. Hybrid Approach
      • 2.4.2.2. Advantages of Primary Research
      • 2.4.2.3. Techniques for Primary Research
        • 2.4.2.3.1. Interviews
        • 2.4.2.3.2. Surveys
        • 2.4.2.3.3. Focus Groups
        • 2.4.2.3.4. Observational Research
        • 2.4.2.3.5. Social Media Interactions
      • 2.4.2.4. Key Opinion Leaders Considered in Primary Research
        • 2.4.2.4.1. Company Executives (CXOs)
        • 2.4.2.4.2. Board of Directors
        • 2.4.2.4.3. Company Presidents and Vice Presidents
        • 2.4.2.4.4. Research and Development Heads
        • 2.4.2.4.5. Technical Experts
        • 2.4.2.4.6. Subject Matter Experts
        • 2.4.2.4.7. Scientists
        • 2.4.2.4.8. Doctors and Other Healthcare Providers
      • 2.4.2.5. Ethics and Integrity
        • 2.4.2.5.1. Research Ethics
        • 2.4.2.5.2. Data Integrity
    • 2.4.3. Analytical Tools and Databases
  • 2.5. Robust Quality Control

3. MARKET DYNAMICS

  • 3.1. Chapter Overview
  • 3.2. Forecast Methodology
    • 3.2.1. Top-down Approach
    • 3.2.2. Bottom-up Approach
    • 3.2.3. Hybrid Approach
  • 3.3. Market Assessment Framework
    • 3.3.1. Total Addressable Market (TAM)
    • 3.3.2. Serviceable Addressable Market (SAM)
    • 3.3.3. Serviceable Obtainable Market (SOM)
    • 3.3.4. Currently Acquired Market (CAM)
  • 3.4. Forecasting Tools and Techniques
    • 3.4.1. Qualitative Forecasting
    • 3.4.2. Correlation
    • 3.4.3. Regression
    • 3.4.4. Extrapolation
    • 3.4.5. Convergence
    • 3.4.6. Sensitivity Analysis
    • 3.4.7. Scenario Planning
    • 3.4.8. Data Visualization
    • 3.4.9. Time Series Analysis
    • 3.4.10. Forecast Error Analysis
  • 3.5. Key Considerations
    • 3.5.1. Demographics
    • 3.5.2. Government Regulations
    • 3.5.3. Reimbursement Scenarios
    • 3.5.4. Market Access
    • 3.5.5. Supply Chain
    • 3.5.6. Industry Consolidation
    • 3.5.7. Pandemic / Unforeseen Disruptions Impact
  • 3.6. Limitations

4. MACRO-ECONOMIC INDICATORS

  • 4.1. Chapter Overview
  • 4.2. Market Dynamics
    • 4.2.1. Time Period
      • 4.2.1.1. Historical Trends
      • 4.2.1.2. Current and Forecasted Estimates
    • 4.2.2. Currency Coverage
      • 4.2.2.1. Major Currencies Affecting the Market
      • 4.2.2.2. Factors Affecting Currency Fluctuations on the Industry
      • 4.2.2.3. Impact of Currency Fluctuations on the Industry
    • 4.2.3. Foreign Currency Exchange Rate
      • 4.2.3.1. Impact of Foreign Exchange Rate Volatility on the Market
      • 4.2.3.2. Strategies for Mitigating Foreign Exchange Risk
    • 4.2.4. Recession
      • 4.2.4.1. Assessment of Current Economic Conditions and Potential Impact on the Market
      • 4.2.4.2. Historical Analysis of Past Recessions and Lessons Learnt
    • 4.2.5. Inflation
      • 4.2.5.1. Measurement and Analysis of Inflationary Pressures in the Economy
      • 4.2.5.2. Potential Impact of Inflation on the Market Evolution
    • 4.2.6. Interest Rates
      • 4.2.6.1. Interest Rates and Their Impact on the Market
      • 4.2.6.2. Strategies for Managing Interest Rate Risk
    • 4.2.7. Commodity Flow Analysis
      • 4.2.7.1. Type of Commodity
      • 4.2.7.2. Origins and Destinations
      • 4.2.7.3. Values and Weights
      • 4.2.7.4. Modes of Transportation
    • 4.2.8. Global Trade Dynamics
      • 4.2.8.1. Import Scenario
      • 4.2.8.2. Export Scenario
      • 4.2.8.3. Trade Policies
      • 4.2.8.4. Strategies for Mitigating the Risks Associated with Trade Barriers
      • 4.2.8.5. Impact of Trade Barriers on the Market
    • 4.2.9. War Impact Analysis
      • 4.2.9.1. Russian-Ukraine War
      • 4.2.9.2. Israel-Hamas War
    • 4.2.10. COVID Impact / Related Factors
      • 4.2.10.1. Global Economic Impact
      • 4.2.10.2. Industry-specific Impact
      • 4.2.10.3. Government Response and Stimulus Measures
      • 4.2.10.4. Future Outlook and Adaptation Strategies
    • 4.2.11. Other Indicators
      • 4.2.11.1. Fiscal Policy
      • 4.2.11.2. Consumer Spending
      • 4.2.11.3. Gross Domestic Product
      • 4.2.11.4. Employment
      • 4.2.11.5. Taxes
      • 4.2.11.6. Stock Market Performance
      • 4.2.11.7. Cross Border Dynamics
  • 4.3. Conclusion

5. EXECUTIVE SUMMARY

6. INTRODUCTION

  • 6.1. Overview of AI in Pharma Manufacturing
  • 6.2. Need for AI in Pharma Manufacturing
  • 6.3. Role of AI across the Drug Manufacturing Value Chain
  • 6.4. Types of AI Technology used in Drug Manufacturing
  • 6.5. Applications of AI in Pharma Manufacturing
  • 6.6. Advantages of AI in Pharma Manufacturing
  • 6.7. Challenges Associated with AI Adoption in Drug Manufacturing
  • 6.8. Recent Developments and Future Perspectives

7. MARKET LANDSCAPE: AI IN PHARMA MANUFACTURING SOLUTION PROVIDERS

  • 7.1. Methodology and Key Parameters
  • 7.2. AI in Pharma Manufacturing: Market Landscape
    • 7.2.1. Analysis by Year of Establishment
    • 7.2.2. Analysis by Company Size
    • 7.2.3. Analysis by Location of Headquarters (Region)
    • 7.2.4. Analysis by Location of Headquarters (Country)
    • 7.2.5. Analysis by Company Ownership
    • 7.2.6. Analysis by Type of Company
    • 7.2.7. Analysis by Type of AI Solution
    • 7.2.8. Analysis by Type of Offering
    • 7.2.9. Analysis by Type of Technology
    • 7.2.10. Analysis by Mode of Deployment
    • 7.2.11. Analysis by Application Area
    • 7.2.12. Analysis by Utility in Drug Manufacturing

8. COMPANY COMPETITIVENESS ANALYSIS

  • 8.1. Methodology and Key Parameters
  • 8.2. Scoring Criteria
  • 8.3. Overview of Peer Groups
  • 8.4. AI in Pharma Manufacturing: Company Competitiveness Analysis
    • 8.4.1. AI in Pharma Manufacturing Solution Providers in North America: Peer Group I
      • 8.4.1.1. Leading Players in Peer Group I
    • 8.4.2. AI in Pharma Manufacturing Solution Providers in Europe: Peer Group II
      • 8.4.2.1. Leading Players in Peer Group II
    • 8.4.3. AI in Pharma Manufacturing Solution Providers in Asia-Pacific and Rest of the World: Peer Group III
      • 8.4.3.1. Leading Players in Peer Group III
  • 8.5. AI in Pharma Manufacturing: Benchmarking Analysis
    • 8.5.1. Benchmarking based on Supplier Strength Score
    • 8.5.2. Benchmarking based on Technology Strength Score
    • 8.5.3. Benchmarking based on Application Diversity Score

9. COMPANY PROFILES: AI IN PHARMA MANUFACTURING SOLUTION PROVIDERS IN NORTH AMERICA

  • 9.1. Overview
  • 9.2. C3.AI
    • 9.2.1. Company Details
    • 9.2.2. Technology Portfolio
    • 9.2.3. Financial Information
    • 9.2.4. SWOT Analysis
    • 9.2.5. Strategic Framework
    • 9.2.6. Future Outlook
  • 9.3. AMD
  • 9.4. IBM
  • 9.5. Kalypso: A Rockwell Automation Business
  • 9.6. SAS Institute

10. COMPANY PROFILES: AI IN PHARMA MANUFACTURING SOLUTION PROVIDERS IN EUROPE

  • 10.1. Overview
  • 10.2. Korber Pharma
    • 10.2.1. Company Details
    • 10.2.2. Technology Portfolio
    • 10.2.3. Financial Information
    • 10.2.4. SWOT Analysis
    • 10.2.5. Strategic Framework
    • 10.2.6. Future Outlook
  • 10.3. SDG Group
  • 10.4. Catalyx
  • 10.5. Elisa Industriq

11. COMPANY PROFILES: AI IN PHARMA MANUFACTURING SOLUTION PROVIDERS IN ASIA-PACIFIC AND REST OF THE WORLD

  • 11.1. Overview
  • 11.2. Straive
    • 11.2.1. Company Details
    • 11.2.2. Technology Portfolio
    • 11.2.3. SWOT Analysis
    • 11.2.4. Strategic Framework
    • 11.2.5. Future Outlook
  • 11.3. Axiomtek
  • 11.4. Appinventiv
  • 11.5. Amplelogic
  • 11.6. Samson Precognize Solutions

12. PARTNERSHIPS AND COLLABORATIONS

  • 12.1. Partnership Models
  • 12.2. AI in Pharma Manufacturing: Partnerships and Collaborations
    • 12.2.1. Analysis by Year of Partnership
    • 12.2.2. Analysis by Type of Partnership
    • 12.2.3. Analysis by Year and Type of Partnership
    • 12.2.4. Analysis by Type of Partner
    • 12.2.5. Analysis by Geographical Activity
      • 12.2.5.1. Local and International Deals
      • 12.2.5.2. Intracontinental and Intercontinental Deals
    • 12.2.6. Most Active Players: Analysis by Number of Partnerships

13. FUNDING AND INVESTMENT ANALYSIS

  • 13.1. Funding Models
  • 13.2. Funding Lifecycle Analysis
  • 13.3. Investment Case: Risk and Return
  • 13.4. AI in Pharma Manufacturing: Funding and Investment Analysis
    • 13.4.1. Analysis of Instances by Year of Funding
    • 13.4.2. Analysis of Instances by Type of Funding
    • 13.4.3. Analysis of Instances by Year and Type of Funding
    • 13.4.4. Analysis of Amount Raised by Year of funding
    • 13.4.5. Analysis of Amount Raised by Type of Funding
    • 13.4.6. Analysis by Geography
    • 13.4.7. Most Active Players: Analysis by Number of Funding Instances
    • 13.4.8. Most Active Players: Analysis by Amount Raised
    • 13.4.9. Leading Investors: Analysis by Number of Funding Instances
  • 13.5. Evolution and Relative Assessment of Funding Models
    • 13.5.1. Grants / Awards
    • 13.5.2. Venture Capital
    • 13.5.3. Private Placement
  • 13.6. Summary of Funding and Investment Opportunities

14. START-UP HEALTH INDEXING

  • 14.1. Chapter Overview
  • 14.2. Start-ups Offering AI Solutions for Drug Manufacturing
    • 14.2.1. Analysis by Location of Headquarters
  • 14.3. Benchmarking of Start-ups
    • 14.3.1. Analysis by Technology Strength
    • 14.3.2. Analysis by Application Diversity
    • 14.3.3. Analysis by Utility in Drug Manufacturing
    • 14.3.4. Analysis by Funding Activity
    • 14.3.5. Analysis by Revenue
    • 14.3.6. Start-up Health Indexing: Roots Analysis Perspective

15. AI IN PHARMA MANUFACTURING MARKET: MEGATRENDS ANALYSIS

  • 15.1. Megatrends Analysis: An Overview of Emerging Trends
    • 15.1.1. Pharma 4.0 Adoption
    • 15.1.2. Increasing Emphasis on Regulatory Compliance
    • 15.1.3. Transition towards Continuous Manufacturing
    • 15.1.4. Digitization of Batch Records and Manufacturing Documentation
    • 15.1.5. Shift towards Predictive Maintenance Approach
    • 15.1.6. Rise in Strategic Collaborations and Investments

16. MARKET IMPACT ANALYSIS: DRIVERS, RESTRAINTS, OPPORTUNITIES AND CHALLENGES

  • 16.1. Chapter Overview
  • 16.2. Market Drivers
  • 16.3. Market Restraints
  • 16.4. Market Opportunities
  • 16.5. Market Challenges
  • 16.6. Conclusion

17. GLOBAL AI IN PHARMA MANUFACTURING MARKET

  • 17.1. Methodology
  • 17.2. AI in Pharma Manufacturing Market, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 17.2.1. Multivariate Scenario Analysis
      • 17.2.1.1. Conservative Scenario
      • 17.2.1.2. Optimistic Scenario
  • 17.3. Key Market Segmentations
  • 17.4. Key Assumptions and Data Validation

18. AI in Pharma Manufacturing MARKET, BY tYPE OF OFFERINg

  • 18.1. Methodology
  • 18.2. AI in Pharma Manufacturing Market: Distribution by Type of Offering
    • 18.2.1. AI in Pharma Manufacturing Market for Software, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 18.2.2. AI in Pharma Manufacturing Market for Hardware, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 18.2.3. AI in Pharma Manufacturing Market for Services, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 18.3. Data Triangulation and Validation

19. AI IN PHARMA MANUFACTURING MARKET, BY MODe of deployment

  • 19.1. Methodology
  • 19.2. AI in Pharma Manufacturing Market: Distribution by Mode of Deployment
    • 19.2.1. AI in Pharma Manufacturing Market for Cloud-based Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 19.2.2. AI in Pharma Manufacturing Market for On-premise Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 19.3. Data Triangulation and Validation

20. AI IN PHARMA MANUFACTURING MARKET, BY TYPE OF AI solution

  • 20.1. Methodology
  • 20.2. AI in Pharma Manufacturing Market: Distribution by Type of AI Solution
    • 20.2.1. AI in Pharma Manufacturing Market for Off-the-Shelf AI Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 20.2.2. AI in Pharma Manufacturing Market for Personalized AI Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 20.3. Data Triangulation and Validation

21. AI IN PHARMA MANUFACTURING MARKET, BY TYPE OF Technology

  • 21.1. Methodology
  • 21.2. AI in Pharma Manufacturing Market: Distribution by Type of Technology
    • 21.2.1. AI in Pharma Manufacturing Market for Computer Vision, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 21.2.2. AI in Pharma Manufacturing Market for Machine Learning, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 21.2.3. AI in Pharma Manufacturing Market for Deep Learning, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 21.2.4. AI in Pharma Manufacturing Market for Generative AI, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 21.2.5. AI in Pharma Manufacturing Market for Other Technologies, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 21.3. Data Triangulation and Validation

22. AI IN PHARMA MANUFACTURING MARKET, BY Application AREA

  • 22.1. Methodology
  • 22.2. AI in Pharma Manufacturing Market: Distribution by Application Area
    • 22.2.1. AI in Pharma Manufacturing Market for Quality Control, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 22.2.2. AI in Pharma Manufacturing Market for Predictive Maintenance, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 22.2.3. AI in Pharma Manufacturing Market for Process Development and Optimization, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 22.2.4. AI in Pharma Manufacturing Market for Plant or Equipment Performance Monitoring, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 22.2.5. AI in Pharma Manufacturing Market for Supply Chain Optimization, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 22.2.6. AI in Pharma Manufacturing Market for Other Application Areas, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 22.3. Data Triangulation and Validation

23. AI IN PHARMA MANUFACTURING MARKET, BY Utility in Drug Manufacturing

  • 23.1. Methodology
  • 23.2. AI in Pharma Manufacturing Market: Distribution by Utility in Drug Manufacturing
    • 23.2.1. AI in Pharma Manufacturing Market for Defect Detection, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 23.2.2. AI in Pharma Manufacturing Market for Packaging and Label Inspection, Historical Trends (since 2023) and Forecasted Estimates (till 2040)
    • 23.2.3. AI in Pharma Manufacturing Market for Package Counting, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 23.2.4. AI in Pharma Manufacturing Market for Fill Level Inspection, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 23.2.5. AI in Pharma Manufacturing Market for Other Utilities, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 23.3. Data Triangulation and Validation

24. AI IN PHARMA MANUFACTURING MARKET, BY Geographical Regions

  • 24.1. Methodology
  • 24.2. AI in Pharma Manufacturing Market: Distribution by Geographical Regions
    • 24.2.1. AI in Pharma Manufacturing Market in North America, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
      • 24.2.1.1. AI in Pharma Manufacturing Market in the US, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
      • 24.2.1.2. AI in Pharma Manufacturing Market in Canada, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 24.2.2. AI in Pharma Manufacturing Market in Europe, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
      • 24.2.2.1. AI in Pharma Manufacturing Market in Germany, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
      • 24.2.2.2. AI in Pharma Manufacturing Market in France, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
      • 24.2.2.3. AI in Pharma Manufacturing Market in Spain, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
      • 24.2.2.4. AI in Pharma Manufacturing Market in Italy, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
      • 24.2.2.5. AI in Pharma Manufacturing Market in the UK, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
      • 24.2.2.6. AI in Pharma Manufacturing Market in the Rest of Europe, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 24.2.3. AI in Pharma Manufacturing Market in Asia-Pacific, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
      • 24.2.3.1. AI in Pharma Manufacturing Market in Australia, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
      • 24.2.3.2. AI in Pharma Manufacturing Market in China, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
      • 24.2.3.3. AI in Pharma Manufacturing Market in Japan, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
      • 24.2.3.4. AI in Pharma Manufacturing Market in India, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
      • 24.2.3.5. AI in Pharma Manufacturing Market in South Korea, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
      • 24.2.3.6. AI in Pharma Manufacturing Market in the Rest of Asia-Pacific, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 24.2.4. AI in Pharma Manufacturing Market in the Middle East and North Africa, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
      • 24.2.4.1. AI in Pharma Manufacturing Market in Saudi Arabia, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
      • 24.2.4.2. AI in Pharma Manufacturing Market in UAE, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
      • 24.2.4.3. AI in Pharma Manufacturing Market in Egypt, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
      • 24.2.4.4. AI in Pharma Manufacturing Market in the Rest of Middle East and North Africa, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 24.2.5. AI in Pharma Manufacturing Market in Latin America, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
      • 24.2.5.1. AI in Pharma Manufacturing Market in Brazil, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
      • 24.2.5.2. AI in Pharma Manufacturing Market in Argentina, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
      • 24.2.5.3. AI in Pharma Manufacturing Market in the Rest of Latin America, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 24.3. AI in Pharma Manufacturing Market, By Geographical Regions: Market Dynamics Assessment
    • 24.3.1. Penetration-Growth (P-G) Matrix
    • 24.3.2. Market Movement Analysis

25. AI IN PHARMA MANUFACTURING MARKET, BY KEY Players

26. MARKET OPPORTUNITY ANALYSIS: NORTH AMERICA

  • 26.1. AI in Pharma Manufacturing Market in North America: Distribution by Type of Offering
    • 26.1.1. AI in Pharma Manufacturing Market in North America for Software, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 26.1.2. AI in Pharma Manufacturing Market in North America for Hardware, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 26.1.3. AI in Pharma Manufacturing Market in North America for Services, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 26.2. AI in Pharma Manufacturing Market in North America: Distribution by Type of AI Solution
    • 26.2.1. AI in Pharma Manufacturing Market in North America for Off-the-Shelf AI Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 26.2.2. AI in Pharma Manufacturing Market in North America for Personalized AI Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 26.3. AI in Pharma Manufacturing Market in North America: Distribution by Mode of Deployment
    • 26.3.1. AI in Pharma Manufacturing Market in North America Cloud-based Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 26.3.2. AI in Pharma Manufacturing Market in North America for On-premise Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 26.4. AI in Pharma Manufacturing Market in North America: Distribution by Type of Technology
    • 26.4.1. AI in Pharma Manufacturing Market in North America for Computer Vision, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 26.4.2. AI in Pharma Manufacturing Market in North America for Machine Learning, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 26.4.3. AI in Pharma Manufacturing Market in North America for Deep Learning, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 26.4.4. AI in Pharma Manufacturing Market in North America for Generative AI, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 26.4.5. AI in Pharma Manufacturing Market in North America for Other Technologies, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 26.5. AI in Pharma Manufacturing Market in North America: Distribution by Application Area
    • 26.5.1. AI in Pharma Manufacturing Market in North America for Quality Control, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 26.5.2. AI in Pharma Manufacturing Market in North America for Predictive Maintenance, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 26.5.3. AI in Pharma Manufacturing Market in North America for Process Development and Optimization, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 26.5.4. AI in Pharma Manufacturing Market in North America for Supply Chain Optimization, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 26.5.5. AI in Pharma Manufacturing Market in North America for Other Application Areas, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 26.6. AI in Pharma Manufacturing Market in North America: Distribution by Utility in Drug Manufacturing
    • 26.6.1. AI in Pharma Manufacturing Market in North America for Defect Detection, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 26.6.2. AI in Pharma Manufacturing Market in North America for Packaging and Label Inspection, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 26.6.3. AI in Pharma Manufacturing Market in North America for Package Counting, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 26.6.4. AI in Pharma Manufacturing Market in North America for Fill Level Inspection, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 26.6.5. AI in Pharma Manufacturing Market in North America for Other Utilities, Historical Trends (since 2021) and Forecasted Estimates (till 2040)

27. MARKET OPPORTUNITY ANALYSIS: EUROPE

  • 27.1. AI in Pharma Manufacturing Market in Europe: Distribution by Type of Offering
    • 27.1.1. AI in Pharma Manufacturing Market in Europe for Software, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 27.1.2. AI in Pharma Manufacturing Market in Europe for Hardware, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 27.1.3. AI in Pharma Manufacturing Market in Europe for Services, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 27.2. AI in Pharma Manufacturing Market in Europe: Distribution by Type of AI Solution
    • 27.2.1. AI in Pharma Manufacturing Market in Europe for Off-the-Shelf AI Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 27.2.2. AI in Pharma Manufacturing Market in Europe for Personalized AI Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 27.3. AI in Pharma Manufacturing Market in Europe: Distribution by Mode of Deployment
    • 27.3.1. AI in Pharma Manufacturing Market in Europe Cloud-based Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 27.3.2. AI in Pharma Manufacturing Market in Europe for On-premise Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 27.4. AI in Pharma Manufacturing Market in Europe: Distribution by Type of Technology
    • 27.4.1. AI in Pharma Manufacturing Market in Europe for Computer Vision, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 27.4.2. AI in Pharma Manufacturing Market in Europe for Machine Learning, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 27.4.3. AI in Pharma Manufacturing Market in Europe for Deep Learning, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 27.4.4. AI in Pharma Manufacturing Market in Europe for Generative AI, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 27.4.5. AI in Pharma Manufacturing Market in Europe for Other Technologies, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 27.5. AI in Pharma Manufacturing Market in Europe: Distribution by Application Area
    • 27.5.1. AI in Pharma Manufacturing Market in Europe for Quality Control, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 27.5.2. AI in Pharma Manufacturing Market in Europe for Predictive Maintenance, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 27.5.3. AI in Pharma Manufacturing Market in Europe for Process Development and Optimization, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 27.5.4. AI in Pharma Manufacturing Market in Europe for Supply Chain Optimization, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 27.5.5. AI in Pharma Manufacturing Market in Europe for Other Application Areas, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 27.6. AI in Pharma Manufacturing Market in Europe: Distribution by Utility in Drug Manufacturing
    • 27.6.1. AI in Pharma Manufacturing Market in Europe for Defect Detection, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 27.6.2. AI in Pharma Manufacturing Market in Europe for Packaging and Label Inspection, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 27.6.3. AI in Pharma Manufacturing Market in Europe for Package Counting, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 27.6.4. AI in Pharma Manufacturing Market in Europe for Fill Level Inspection, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 27.6.5. AI in Pharma Manufacturing Market in Europe for Other Utilities, Historical Trends (since 2021) and Forecasted Estimates (till 2040)

28. MARKET OPPORTUNITY ANALYSIS: ASIA-PACIFIC

  • 28.1. AI in Pharma Manufacturing Market in Asia-Pacific: Distribution by Type of Offering
    • 28.1.1. AI in Pharma Manufacturing Market in Asia-Pacific for Software, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 28.1.2. AI in Pharma Manufacturing Market in Asia-Pacific for Hardware, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 28.1.3. AI in Pharma Manufacturing Market in Asia-Pacific for Services, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 28.2. AI in Pharma Manufacturing Market in Asia-Pacific: Distribution by Type of AI Solution
    • 28.2.1. AI in Pharma Manufacturing Market in Asia-Pacific for Off-the-Shelf AI Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 28.2.2. AI in Pharma Manufacturing Market in Asia-Pacific for Personalized AI Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 28.3. AI in Pharma Manufacturing Market in Asia-Pacific: Distribution by Mode of Deployment
    • 28.3.1. AI in Pharma Manufacturing Market in Asia-Pacific Cloud-based Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 28.3.2. AI in Pharma Manufacturing Market in Asia-Pacific for On-premise Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 28.4. AI in Pharma Manufacturing Market in Asia-Pacific: Distribution by Type of Technology
    • 28.4.1. AI in Pharma Manufacturing Market in Asia-Pacific for Computer Vision, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 28.4.2. AI in Pharma Manufacturing Market in Asia-Pacific for Machine Learning, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 28.4.3. AI in Pharma Manufacturing Market in Asia-Pacific for Deep Learning, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 28.4.4. AI in Pharma Manufacturing Market in Asia-Pacific for Generative AI, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 28.4.5. AI in Pharma Manufacturing Market in Asia-Pacific for Other Technologies, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 28.5. AI in Pharma Manufacturing Market in Asia-Pacific: Distribution by Application Area
    • 28.5.1. AI in Pharma Manufacturing Market in Asia-Pacific for Quality Control, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 28.5.2. AI in Pharma Manufacturing Market in Asia-Pacific for Predictive Maintenance, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 28.5.3. AI in Pharma Manufacturing Market in Asia-Pacific for Process Development and Optimization, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 28.5.4. AI in Pharma Manufacturing Market in Asia-Pacific for Supply Chain Optimization, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 28.5.5. AI in Pharma Manufacturing Market in Asia-Pacific for Other Application Areas, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 28.6. AI in Pharma Manufacturing Market in Asia-Pacific: Distribution by Utility in Drug Manufacturing
    • 28.6.1. AI in Pharma Manufacturing Market in Asia-Pacific for Defect Detection, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 28.6.2. AI in Pharma Manufacturing Market in Asia-Pacific for Packaging and Label Inspection, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 28.6.3. AI in Pharma Manufacturing Market in Asia-Pacific for Package Counting, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 28.6.4. AI in Pharma Manufacturing Market in Asia-Pacific for Fill Level Inspection, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 28.6.5. AI in Pharma Manufacturing Market in Asia-Pacific for Other Utilities, Historical Trends (since 2021) and Forecasted Estimates (till 2040)

29. MARKET OPPORTUNITY ANALYSIS: MIDDLE EAST AND NORTH AFRICA

  • 29.1. AI in Pharma Manufacturing Market in Middle East and North Africa: Distribution by Type of Offering
    • 29.1.1. AI in Pharma Manufacturing Market in Middle East and North Africa for Software, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 29.1.2. AI in Pharma Manufacturing Market in Middle East and North Africa for Hardware, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 29.1.3. AI in Pharma Manufacturing Market in Middle East and North Africa for Services, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 29.2. AI in Pharma Manufacturing Market in Middle East and North Africa: Distribution by Type of AI Solution
    • 29.2.1. AI in Pharma Manufacturing Market in Middle East and North Africa for Off-the-Shelf AI Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 29.2.2. AI in Pharma Manufacturing Market in Middle East and North Africa for Personalized AI Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 29.3. AI in Pharma Manufacturing Market in Middle East and North Africa: Distribution by Mode of Deployment
    • 29.3.1. AI in Pharma Manufacturing Market in Middle East and North Africa Cloud-based Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 29.3.2. AI in Pharma Manufacturing Market in Middle East and North Africa for On-premise Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 29.4. AI in Pharma Manufacturing Market in Middle East and North Africa: Distribution by Type of Technology
    • 29.4.1. AI in Pharma Manufacturing Market in Middle East and North Africa for Computer Vision, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 29.4.2. AI in Pharma Manufacturing Market in Middle East and North Africa for Machine Learning, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 29.4.3. AI in Pharma Manufacturing Market in Middle East and North Africa for Deep Learning, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 29.4.4. AI in Pharma Manufacturing Market in Middle East and North Africa for Generative AI, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 29.4.5. AI in Pharma Manufacturing Market in Middle East and North Africa for Other Technologies, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 29.5. AI in Pharma Manufacturing Market in Middle East and North Africa: Distribution by Application Area
    • 29.5.1. AI in Pharma Manufacturing Market in Middle East and North Africa for Quality Control, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 29.5.2. AI in Pharma Manufacturing Market in Middle East and North Africa for Predictive Maintenance, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 29.5.3. AI in Pharma Manufacturing Market in Middle East and North Africa for Process Development and Optimization, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 29.5.4. AI in Pharma Manufacturing Market in Middle East and North Africa for Supply Chain Optimization, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 29.5.5. AI in Pharma Manufacturing Market in Middle East and North Africa for Other Application Areas , Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 29.6. AI in Pharma Manufacturing Market in Middle East and North Africa: Distribution by Utility in Drug Manufacturing
    • 29.6.1. AI in Pharma Manufacturing Market in Middle East and North Africa for Defect Detection, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 29.6.2. AI in Pharma Manufacturing Market in Middle East and North Africa for Packaging and Label Inspection, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 29.6.3. AI in Pharma Manufacturing Market in Middle East and North Africa for Package Counting, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 29.6.4. AI in Pharma Manufacturing Market in Middle East and North Africa for Fill Level Inspection, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 29.6.5. AI in Pharma Manufacturing Market in Middle East and North Africa for Other Utilities, Historical Trends (since 2021) and Forecasted Estimates (till 2040)

30. MARKET OPPORTUNITY ANALYSIS: LATIN AMERICA

  • 30.1. AI in Pharma Manufacturing Market in Latin America: Distribution by Type of Offering
    • 30.1.1. AI in Pharma Manufacturing Market in Latin America for Software, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 30.1.2. AI in Pharma Manufacturing Market in Latin America for Hardware, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 30.1.3. AI in Pharma Manufacturing Market in Latin America for Services, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 30.2. AI in Pharma Manufacturing Market in Latin America: Distribution by Type of AI Solution
    • 30.2.1. AI in Pharma Manufacturing Market in Latin America for Off-the-Shelf AI Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 30.2.2. AI in Pharma Manufacturing Market in Latin America for Personalized AI Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 30.3. AI in Pharma Manufacturing Market in Latin America: Distribution by Mode of Deployment
    • 30.3.1. AI in Pharma Manufacturing Market in Latin America Cloud-based Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 30.3.2. AI in Pharma Manufacturing Market in Latin America for On-premise Solutions, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 30.4. AI in Pharma Manufacturing Market in Latin America: Distribution by Type of Technology
    • 30.4.1. AI in Pharma Manufacturing Market in Latin America for Computer Vision, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 30.4.2. AI in Pharma Manufacturing Market in Latin America for Machine Learning, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 30.4.3. AI in Pharma Manufacturing Market in Latin America for Deep Learning, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 30.4.4. AI in Pharma Manufacturing Market in Latin America for Generative AI, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 30.4.5. AI in Pharma Manufacturing Market in Latin America for Other Technologies, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 30.5. AI in Pharma Manufacturing Market in Latin America: Distribution by Application Area
    • 30.5.1. AI in Pharma Manufacturing Market in Latin America for Quality Control, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 30.5.2. AI in Pharma Manufacturing Market in Latin America for Predictive Maintenance, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 30.5.3. AI in Pharma Manufacturing Market in Latin America for Process Development and Optimization, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 30.5.4. AI in Pharma Manufacturing Market in Latin America for Supply Chain Optimization, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 30.5.5. AI in Pharma Manufacturing Market in Latin America for Other Application Areas, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
  • 30.6. AI in Pharma Manufacturing Market in Latin America: Distribution by Utility in Drug Manufacturing
    • 30.6.1. AI in Pharma Manufacturing Market in Latin America for Defect Detection, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 30.6.2. AI in Pharma Manufacturing Market in Latin America for Packaging and Label Inspection, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 30.6.3. AI in Pharma Manufacturing Market in Latin America for Package Counting, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 30.6.4. AI in Pharma Manufacturing Market in Latin America for Fill Level Inspection, Historical Trends (since 2021) and Forecasted Estimates (till 2040)
    • 30.6.5. AI in Pharma Manufacturing Market in Latin America for Other Utilities, Historical Trends (since 2021) and Forecasted Estimates (till 2040)

31. CONCLUDING INSIGHTS

32. EXECUTIVE INSIGHTS

33. TABULATED DATA

34. LIST OF COMPANIES AND ORGANIZATIONS