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市場調查報告書
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2041938

量子藥物和材料設計:應用案例和市場預測(2026-2035 年)

Quantum Drug and Materials Design: Use Cases and Market Forecasts: 2026-2035

出版日期: | 出版商: Communications Industry Researchers (CIR) | 英文 54 Pages | 訂單完成後即時交付

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簡介目錄

量子運算徹底改變藥物研發和先進材料設計的未來。儘管該領域仍處於早期階段,但利用量子硬體進行的演示實驗取得進展,領先的製藥、化學、汽車和航太公司探索如何利用量子系統加速發現、模擬和最佳化。

在CIR,密切關注推動這項變革的公司、技術、合作關係和演算法。研究著眼於混合量子-經典工作流程目前在分子模擬、催化劑開發、電池化學、計算流體力學、下一代材料工程以及其他具有檢驗意義的領域中的應用。

這裡湧現的機會並非僅僅是「純粹的量子計算」。相反,市場圍繞著結合人工智慧、高效能運算、GPU 和量子處理器的整合工作流程而發展,目的是解決傳統運算方法難以解決的極其複雜的化學和材料問題。本報告中 CIR 的研究範圍如下:

  • 利用量子技術進行藥物發現與分子建模
  • 先進電池和燃料電池材料的研究
  • 催化劑模擬和化學過程最佳化
  • 半導體和電子材料的發展
  • 計算流體力學和多物理場模擬
  • 二氧化碳捕集和永續性應用
  • 混合量子-經典軟體平台與演算法
  • 製藥、化工、航太和能源產業的終端用戶採納策略。

本報告還分析了 IBM、Quantinuum、Google、Microsoft、IonQ、AstraZeneca、BASF、Pfizer、Airbus和Mercedes-Benz等量子硬體供應商的競爭格局,以及專業軟體公司和企業採用案例。

此外,本報告還包括對量子計算在材料設計和藥物發現領域的預測,並依規模和支出水準列出了試驗數量。

先進材料和製藥業被認為是量子計算首批大規模應用領域。本報告對不斷發展的量子製藥和材料科學生態系統進行了詳細的市場分析、技術評估、夥伴關係關係梳理以及未來十年的預測。

目錄

第1章 引言

  • 本報告背景
    • 量子製藥/材料科學:進展
    • 量子藥物學;量子材料科學
    • 分子:藥物與生物學
    • 催化劑:電池、燃料電池和汽車產業
    • 量子化學、半導體和電子材料
    • 量子與化學工業
    • 計算流體力學(CFD)
    • 凝聚態物質調查
    • 二氧化碳捕集
  • 最終用戶對量子計算的期望
  • 本報告的結構

第2章 專業軟體供應商

  • 介紹
  • 量子藥物發現
  • 量子材料設計
  • 量子演算法在製藥和材料科學中的應用:最新趨勢
  • 1QBit(加拿大)
  • Algorithmiq(芬蘭)
  • Amazon Web Services(美國)
  • AQEMIA SAS(法國)
    • Classiq Technologies(以色列)
  • Dassault Systemes(法國)
  • Blueqat Inc.(日本)
  • HQS Quantum Simulations(德國)
  • Kvantify(丹麥)
  • Phasecraft(英國)
  • Polaris Quantum Biotech(美國)
  • Q-Chem(卡達)
  • Q-CTRL(澳洲)
  • QCWare(美國)
  • Qpurpose ApS(丹麥)
  • QunaSys(日本)
  • Quanscient(芬蘭)
  • Qubit Pharmaceuticals(法國)
  • Quantistry(德國)
  • Quantum Simulation Technologies(美國)
  • Quemix Inc.(日本)
  • Qunova Computing, Inc.(韓國)
  • QuSoft(荷蘭)
  • Schrodinger(美國)
    • 量子化學活動
  • SCM(義大利)
  • Synopsys(德國)
  • Terra Quantum AG(瑞士)
  • XTalPi(中國)

第3章 硬體供應商

  • ujitsu(日本)
  • Google(美國)
  • IBM(美國)
  • Infleqtion(美國)
  • IonQ(美國)
  • IQM Quantum Computers
  • Microsoft Quantum(美國)
  • NVIDIA Island(美國)
  • ORCA Computing
  • Pasqal SAS(法國)
  • PsiQuantum(美國)
  • Quantinuum(美國和英國)
  • QuEra Computing Inc.(美國)
  • Riverlane(英國)
  • SEEQC(美國)
  • Xanadu Quantum Technologies(加拿大)

第4章 最終用戶

  • 介紹
  • Airbus(荷蘭)
  • Amgen(美國)
  • Asahi Kasei(日本)
  • Astex Pharma(英國)
  • AstraZeneca(英國)
  • BASF(德國)
  • Bayer(德國)、Biogen(美國)
  • BMW(德國)
  • Boehringer Ingelhei(德國)
    • 量子化學項目
  • The Boeing Company(美國)
  • BP(英國)
  • Covestro(德國)
  • CSL(澳洲)
  • Dow and Subsidiaries(美國)
  • Evonik(德國)
  • Exxon Mobil(美國)
  • Ford(美國)
  • Fujifilm(日本)
  • GSK(英國)
    • 處理器使用
  • Honeywell(美國)
    • Honeywell Performance Materials and Technologies
  • Hyundai Motor Group((韓國)
  • Johnson & Johnson(美國)
  • Johnson Matthey(英國)
  • JSR Corporation(日本)
    • 應用
  • LG Corporation及其子公司(韓國)
    • 研究領域
  • Mercedes-Benz(德國)
  • Merck KGaA(德國)
    • M Ventures 的角色
    • Merck KGaA作為量子產業的供應商
  • Mitsubishi Chemical(日本)
  • Moderna(美國)
  • Novo Holdings(丹麥)
  • Pfizer(美國)
  • POSCO(韓國)
  • Roche(瑞士)
    • Chugai Pharmaceutical
  • Rolls-Royce(英國)
    • 催化劑計畫
  • Sanofi S.A.(法國)
  • Samsung Group(韓國)
  • Saudi Aramco
    • 應用
  • Shell(英國)
  • Siemens(德國)
  • Sumitomo Group(日本)
  • Toyota Motor Corporation(日本)
  • Volkswagen and Subsidiaries(德國)
    • 車輛電池工作
  • TotalEnergies SE(法國)

第5章 十年預測

  • 調查方法
  • 專案時間表
  • 專案成本
  • 量子藥物發現與設計的預測
  • 量子材料科學的預測
簡介目錄

Quantum computing is reshaping future pharmaceutical research and advanced materials design. This sector remains at an early stage; but with real-world demonstrations on quantum hardware are underway, with leading pharmaceutical, chemical, automotive, and aerospace firms exploring how quantum systems can accelerate discovery, simulation, and optimization.

At CIR, we track the companies, technologies, partnerships, and algorithms driving this transformation. Our research examines how hybrid quantum-classical workflows are being used today for molecular simulation, catalyst development, battery chemistry, computational fluid dynamics, next-generation materials engineering and other strategically vital areas.

The emerging opportunity is not simply “pure quantum.” Instead, the market is evolving around integrated workflows that combine AI, HPC, GPUs, and quantum processors to solve highly complex chemistry and materials problems that challenge classical computing approaches.

CIR’s coverage in this report includes:
  • Quantum-assisted drug discovery and molecular modeling
  • Advanced battery and fuel-cell materials research
  • Catalyst simulation and chemical process optimization
  • Semiconductor and electronics materials development
  • Computational fluid dynamics and multi-physics simulation
  • Carbon capture and sustainability applications
  • Hybrid quantum-classical software platforms and algorithms
  • End-user adoption strategies in the pharma, chemicals, aerospace, and energy sectors.
The report also analyzes the competitive landscape of quantum hardware providers, specialist software firms, and enterprise adopters including IBM, Quantinuum, Google, Microsoft, IonQ,

AstraZeneca, BASF, Pfizer, Airbus, Mercedes-Benz, and many others. In addition, the report contains a forecast of quantum computing in materials design and drug discovery with breakouts of the number of trials by size and expenditure levels.

Advanced materials and pharma are supposedly destined to be the first big application for quantum computing. This report delivers detailed market analysis, technology assessment, partnership mapping, and ten-year forecasts for the evolving quantum pharma and materials science ecosystem.

Table of Contents

Chapter One: Introduction

  • 1.1 Background to this Report
    • 1.1.1 Quantum Pharma/Materials Science: Progress
    • 1.1.2 Quantum Pharma vs. Quantum Materials Science
    • 1.1.3 Molecules: Drugs and Biology
    • 1.1.4 Catalysts: Batteries, Fuel Cells and the Automotive Industry
    • 1.1.5 Quantum Chemistry, Semiconductors and Electronics Materials
    • 1.1.6 Quantum and the Chemical industry
    • 1.1.7 Computational Fluid Dynamics (CFD)
    • 1.1.8 Condensed Matter Research
    • 1.1.9 Carbon Capture
  • 1.2 End-User Expectations for Quantum Computing
  • 1.3 Plan of this Report

Chapter Two: Specialist Software Providers

  • 2.1 Introduction
  • 2.2 Quantum Drug Discovery
  • 2.3 Quantum Materials Design
  • 2.4 Quantum Algorithms for Pharma and Materials Science: Recent Trends
    • 2.4.1 Hybrid Quantum-classical Workflows Remain the Practical Core
  • 2.5 1QBit (Canada)
  • 2.6 Algorithmiq (Finland)
  • 2.7 Amazon Web Services (United States)
  • 2.8 AQEMIA SAS (France)
    • 2.8.1 Classiq Technologies (Israel)
  • 2.9 Dassault Systemes (France)
  • 2.10 Blueqat Inc. (Japan)
  • 2.11 HQS Quantum Simulations (Germany)
  • 2.12 Kvantify (Denmark)
  • 2.13 Phasecraft (United Kingdom)
  • 2.14 Polaris Quantum Biotech (United States)
  • 2.15 Q-Chem (Qatar)
  • 2.16 Q-CTRL (Australia)
  • 2.17 QCWare (United States)
  • 2.18 Qpurpose ApS (Denmark)
  • 2.19 QunaSys (Japan)
  • 2.20 Quanscient? (Finland)
  • 2.21 Qubit Pharmaceuticals (France)
  • 2.22 Quantistry (Germany)
  • 2.23 Quantum Simulation Technologies (United States)
  • 2.24 Quemix Inc. (Japan)
  • 2.25 Qunova Computing, Inc. (South Korea)
  • 2.26 QuSoft (The Netherlands)
  • 2.27 Schrodinger (United States)
    • 2.27.1 Activities in Quantum Chemistry
  • 2.28 SCM (Italy)
  • 2.29 Synopsys (Germany)
  • 2.30 Terra Quantum AG (Switzerland)
  • 2.31 XTalPi (China)

Chapter Three: Hardware Providers

  • 3.1 Fujitsu (Japan)
  • 3.2 Google (United States)
  • 3.3 IBM (United States)
  • 3.4 Infleqtion (United States)
  • 3.5 IonQ (United States)
  • 3.6 IQM Quantum Computers
  • 3.7 Microsoft Quantum (United States)
  • 3.8 NVIDIA Corporation (United States)
  • 3.9 ORCA Computing
  • 3.10 Pasqal SAS (France)
  • 3.11 PsiQuantum (United States)
  • 3.12 Quantinuum (United States and the UK)
  • 3.13 QuEra Computing Inc. (United States)
  • 3.14 Riverlane (United Kingdom)
  • 3.15 SEEQC (United States)
  • 3.16 Xanadu Quantum Technologies (Canada)

Chapter Four: End Users

  • 4.1 Introduction
  • 4.2 Airbus (The Netherlands)
    • 4.2.1 Applications being Pursued
  • 4.3 Amgen (United States)
  • 4.4 Asahi Kasei (Japan)
  • 4.5 Astex Pharma (United Kingdom)
  • 4.6 AstraZeneca (United Kingdom)
  • 4.7 BASF (Germany)
    • 4.7.1 Partnerships
    • 4.7.2 Applications
    • 4.7.3 Processor Choices
  • 4.8 Bayer (Germany)
  • 4.9 Biogen (United States)
  • 4.10 BMW (Germany)
  • 4.11 Boehringer Ingelheim (Germany)
    • 4.11.1 Quantum Chemistry Project
  • 4.12 The Boeing Company (United States)
  • 4.13 BP (United Kingdom)
  • 4.14 Covestro (Germany)
  • 4.15 CSL (Australia)
  • 4.16 Dow and Subsidiaries (United States)
  • 4.17 Evonik (Germany)
  • 4.18 Exxon Mobil (United States)
  • 4.19 Ford (United States)
  • 4.20 Fujifilm (Japan)
  • 4.21 GSK (United Kingdom)
    • 4.21.1 Processors Used
  • 4.22 Honeywell (United States)
    • 4.22.1 Honeywell Performance Materials and Technologies
  • 4.23 Hyundai Motor Group (South Korea)
  • 4.24 Johnson & Johnson (United States)
  • 4.25 Johnson Matthey (United Kingdom)
  • 4.26 JSR Corporation (Japan)
    • 4.26.1 Applications
  • 4.27 LG Corporation and Subsidiaries (South Korea)
    • 4.27.1 Research Areas of Interest
  • 4.28 Mercedes-Benz (Germany)
  • 4.29 Merck KGaA (Germany)
    • 4.29.1 Role of M Ventures
    • 4.29.2 Merck KGaA as Supplier to the Quantum Industry
  • 4.30 Mitsubishi Chemical (Japan)
  • 4.31 Moderna (United States)
  • 4.32 Novo Holdings (Denmark)
  • 4.33 Pfizer (United States)
  • 4.34 POSCO (South Korea)
  • 4.35 Roche (Switzerland)
    • 4.35.1 Chugai Pharmaceutical
  • 4.36 Rolls-Royce (United Kingdom)
    • 4.36.1 Catalyst Project
  • 4.37 Sanofi S.A. (France)
  • 4.38 Samsung Group (South Korea)
  • 4.39 Saudi Aramco
    • 4.39.1 Applications
  • 4.40 Shell (United Kingdom)
  • 4.41 Siemens (Germany)
  • 4.42 Sumitomo Group (Japan)
  • 4.43 Toyota Motor Corporation (Japan)
  • 4.44 Volkswagen and Subsidiaries (Germany)
    • 4.44.1 Work on Vehicle Batteries
  • 4.45 TotalEnergies SE (France)

Chapter Five: Ten-Year Forecasts

  • 5.1 Methodology
  • 5.2 Project Timelines
  • 5.3 Project Costs
  • 5.4 Forecasts of Quantum Drug Design
  • 5.5 Forecasts of Quantum Materials Science