ヘルスケアにおけるデジタルツイン市場：治療分野別、デジタルツインタイプ別、応用分野別、エンドユーザー別、主要地域別：2035年までの業界動向と世界の予測

世界のヘルスケアにおけるデジタルツインの市場規模は、2035年までの予測期間中に30%のCAGRで拡大し、現在の19億米ドルから2035年までに334億米ドルに成長すると予測されています。

近年、人工知能、ディープラーニング、機械学習、ビッグデータといった技術に関連する進歩が著しくなっています。これらのプログラムは現在、ヘルスケア領域に携わる参入企業の大きな関心を集めています。その結果、業界の利害関係者は、前述のテクノロジーを使ってイノベーションを推進し、既存のプロセスのパフォーマンスを向上させる取り組みを行っています。こうした技術の中で、デジタルツインはヘルスケア分野での利用が有望な技術として浮上しています。この文脈で、デジタルツインとは、本質的には、システムやプロセスのパフォーマンスを予測することができるシミュレーションを作成するために、実世界のデータを使用する仮想モデルであることを言及する価値があります。具体的には、ヘルスケア領域において、デジタルツインはリスク予測、人件費削減、患者ケアの改善、意思決定プロセスの自動化などに応用できます。さらに、ヘルスケア領域に携わる企業は、研究開発コストを削減するためにデジタルツインコンセプトを採用する可能性が高まっています。個別化医療、仮想シミュレーション、自動化技術への需要の高まりに後押しされ、ヘルスケアにおけるデジタルツインは大幅な成長を遂げるとみられています。

現在、90以上のデジタルツインが、診断、健康モニタリング、手術計画など、さまざまなヘルスケア関連用途向けに市販されているか、開発中です。

業界各社が提供するデジタルツインの42%以上はプロセスツインであり、その大半は主に資産/プロセス管理、個別化治療、手術計画向けです。この業界におけるパートナーシップ活動は、過去3年間で20％以上の割合で成長しており、その45％以上が過去2年間に締結されたものであることは注目に値します。現在進行中のイノベーションを支援するため、複数の民間および公的投資家が多額の資本投資を行っています。デジタルツイン市場の新興企業は、競合他社との差別化を図るため、人工知能やブロックチェーンなどの先進的かつ革新的な技術を徐々に採用しています。遠隔患者モニタリング、予測分析、個別化治療、IoT統合への関心が高まっていることから、ヘルスケアにおけるデジタルツイン市場は当面堅調に拡大するとみられています。ヘルスケアや製薬業界におけるデジタルツインテクノロジーの採用が増加していることから、ヘルスケア領域における世界のデジタルツイン市場は、2035年まで年率30％で成長すると予測されています。

当レポートでは、世界のヘルスケアにおけるデジタルツイン市場について調査し、市場の概要とともに、治療分野別、デジタルツインタイプ別、応用分野別、エンドユーザー別、主要地域別の動向、および市場に参入する企業のプロファイルなどを提供しています。

目次

第1章 序文

第2章 調査手法

第3章 経済およびその他のプロジェクト特有の考慮事項

第4章 エグゼクティブサマリー

第5章 イントロダクション

第6章 市場情勢

第7章 重要な洞察

第8章 企業競争力分析

第9章 詳細な企業プロファイル

• 章の概要
• BigBear.ai
• Certara
• Dassault Systemes
• NavvTrack
• Unlearn.ai

第10章 企業プロファイル一覧

第11章 パートナーシップとコラボレーション

第12章 資金調達と投資の分析

第13章 BERKUSスタートアップの評価分析

第14章 市場への影響分析：促進要因、抑制要因、機会、課題

第15章 世界のヘルスケアにおけるデジタルツイン市場

第16章 ヘルスケアにおけるデジタルツイン市場、治療分野別

第17章 ヘルスケアにおけるデジタルツイン市場、デジタルツインタイプ別

第18章 ヘルスケアにおけるデジタルツイン市場、応用分野別

第19章 ヘルスケアにおけるデジタルツイン市場、エンドユーザー別

第20章 ヘルスケアにおけるデジタルツイン市場、主要地域別

第21章 結論

第22章 エグゼクティブ洞察

第23章 付録I：表形式データ

第24章 付録II：企業および団体一覧

List of Tables

• Table 6.1 Digital Twins in Healthcare: Information on Development Status
• Table 6.2 Digital Twins in Healthcare: Information on Therapeutic Area
• Table 6.3 Digital Twins in Healthcare: Information on Areas of Application
• Table 6.4 Digital Twins in Healthcare: Information on Type of Technology Used
• Table 6.5 Digital Twins in Healthcare: Information on End Users
• Table 6.6 Digital Twins in Healthcare: Information on Type of Digital Twin
• Table 6.7 Digital Twins Developers: Information on Year of Establishment, Company Size, Location of Headquarters, Region of Headquarters and Number of Products
• Table 9.1 List of Companies Profiled
• Table 9.2 BigBear.ai: Company Overview
• Table 9.3 BigBear.ai: Recent Developments and Future Outlook
• Table 9.4 Certara: Company Overview
• Table 9.5 Certara: Recent Developments and Future Outlook
• Table 9.6 Dassault Systemes: Company Overview
• Table 9.7 Dassault Systemes: Recent Developments and Future Outlook
• Table 9.8 NavvTrack: Company Overview
• Table 9.9 NavvTrack: Recent Developments and Future Outlook
• Table 9.10 Unlearn.ai: Company Overview
• Table 9.11 Unlearn.ai: Recent Developments and Future Outlook
• Table 10.1 List of Companies Profiled
• Table 10.2 OnScale: Company Overview
• Table 10.3 Phesi: Company Overview
• Table 10.5 Twin Health: Company Overview
• Table 10.6 Verto: Company Overview
• Table 10.7 VictoryXR: Recent Developments and Future Outlook
• Table 10.8 DEO: Company Overview
• Table 10.9 PrediSurge: Company Overview
• Table 10.10 Virtonomy: Company Overview
• Table 10.11 Mesh Bio: Company Overview
• Table 10.12 SingHealth: Company Overview
• Table 11.1 Digital Twins in Healthcare: List of Partnerships and Collaborations, since 2018
• Table 11.2 Partnerships and Collaborations: Information on Type of Agreement (Country-wise and Continent-wise), since 2018
• Table 12.1 Funding and Investments: Information on Year of Investment, Type of Funding, Amount and Investor, since 2018
• Table 12.2 Funding and Investment Analysis: Regional Distribution by Total Amount Invested, since 2018
• Table 13.1 Berkus Start-Up Valuation: Total Valuation of Players
• Table 22.1 Virtonomy: Company Snapshot
• Table 22.2 Decision Lab: Company Snapshot
• Table 22.3 DIGIOTAI Solutions: Company Snapshot
• Table 22.4 TwInsight: Company Snapshot
• Table 22.5 Dassault Systemes: Company Snapshot
• Table 22.6 TwInsight: Company Snapshot
• Table 22.7 Unlearn.AI: Company Snapshot
• Table 22.8 Yokogawa Insilico Biotechnology: Company Snapshot
• Table 23.1 Digital Twins: Distribution by Development Status
• Table 23.2 Digital Twins: Distribution by Therapeutic Area
• Table 23.3 Digital Twins: Distribution by Areas of Application
• Table 23.4 Digital Twins: Distribution by Type of Technology Used
• Table 23.5 Digital Twins: Distribution by End Users
• Table 23.6 Digital Twins in Healthcare: Distribution by Type of Digital Twin
• Table 23.7 Digital Twin Developers: Distribution by Year of Establishment
• Table 23.8 Digital Twin Developers: Distribution by Company Size
• Table 23.9 Digital Twin Developers: Distribution by Location of Headquarters
• Table 23.10 BigBear.ai: Annual Revenues, FY 2021 Onwards (USD Million)
• Table 23.11 Certara: Annual Revenues, FY 2020 Onwards (USD Million)
• Table 23.12 Dassault Systemes: Annual Revenues, FY 2019 Onwards (EUR Billion)
• Table 23.13 Partnerships and Collaborations: Cumulative Year-wise Trend, since 2018
• Table 23.14 Partnerships and Collaborations: Distribution by Type of Partnership
• Table 23.15 Partnerships and Collaborations: Distribution by Year and Type of Partnership
• Table 23.16 Partnerships and Collaborations: Distribution by Type of Partnership and Company Size
• Table 23.17 Most Active Players: Distribution by Number of Partnerships
• Table 23.18 Partnerships and Collaborations: Local and International Agreements
• Table 23.19 Partnerships and Collaborations: Intercontinental and Intracontinental Agreements
• Table 23.20 Funding and Investment Analysis: Cumulative Year-wise Trend, since 2018
• Table 23.21 Funding and Investment Analysis: Cumulative Amount Invested (USD Million), since 2018
• Table 23.22 Funding and Investment Analysis: Distribution of Instances by Type of Funding, since 2018
• Table 23.23 Funding and Investment Analysis: Year-Wise Distribution by Type of Funding, since 2018
• Table 23.24 Funding and Investment Analysis: Distribution of Total Amount Invested (USD Million) by Type of Funding, since 2018
• Table 23.25 Funding and Investment Analysis: Distribution by Geography
• Table 23.26 Most Active Players: Distribution by Number of Funding Instances
• Table 23.27 Most Active Players: Distribution by Amount Raised (USD Million)
• Table 23.28 Global Digital Twins in Healthcare Market, Historical Trends, since 2018 (USD Billion)
• Table 23.29 Global Digital Twins in Healthcare Market, Forecasted Estimates, till 2035, Conservative, Base and Optimistic Scenario (USD Billion)
• Table 23.30 Global Digital Twins in Healthcare Market: Distribution by Therapeutic Area, 2018, 2024 and 2035
• Table 23.31 Digital Twins in Healthcare Market for Cardiovascular Disorders, Historical Trends, since 2018 (USD Billion)
• Table 23.32 Digital Twins in Healthcare Market for Cardiovascular Disorders, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.33 Digital Twins in Healthcare Market for Metabolic Disorders, Historical Trends, since 2018 (USD Billion)
• Table 23.34 Digital Twins in Healthcare Market for Metabolic Disorders, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.35 Digital Twins in Healthcare Market for Orthopedic Disorders, Historical Trends, since 2018 (USD Billion)
• Table 23.36 Digital Twins in Healthcare Market for Orthopedic Disorders, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.37 Digital Twins in Healthcare Market for Other Disorders, Historical Trends, since 2018 (USD Billion)
• Table 23.38 Digital Twins in Healthcare Market for Other Disorders, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.39 Global Digital Twins in Healthcare Market: Distribution by Type of Digital Twin, 2018, 2024 and 2035
• Table 23.40 Digital Twins in Healthcare Market for Process Twins, Historical Trends, since 2018 (USD Billion)
• Table 23.41 Digital Twins in Healthcare Market for Process Twins, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.42 Digital Twins in Healthcare Market for System Twins, Historical Trends, since 2018 (USD Billion)
• Table 23.43 Digital Twins in Healthcare Market for System Twins, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.44 Digital Twins in Healthcare Market for Whole Body Twins, Historical Trends, since 2018 (USD Billion)
• Table 23.45 Digital Twins in Healthcare Market for Whole Body Twins, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.46 Digital Twins in Healthcare Market for Body Part Twins, Historical Trends, since 2018 (USD Billion)
• Table 23.47 Digital Twins in Healthcare Market for Body Part Twins, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.48 Global Digital Twins in Healthcare Market: Distribution by Area of Application, 2018, 2024 and 2035
• Table 23.49 Digital Twins in Healthcare Market for Asset / Process Management, Historical Trends, since 2018 (USD Billion)
• Table 23.50 Digital Twins in Healthcare Market for Asset / Process Management, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.51 Digital Twins in Healthcare Market for Personalized Treatment, Historical Trends, since 2018 (USD Billion)
• Table 23.52 Digital Twins in Healthcare Market for Personalized Treatment, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.53 Digital Twins in Healthcare Market for Surgical Planning, Historical Trends, since 2018 (USD Billion)
• Table 23.54 Digital Twins in Healthcare Market for Surgical Planning, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.55 Digital Twins in Healthcare Market for Diagnosis, Historical Trends, since 2018 (USD Billion)
• Table 23.56 Digital Twins in Healthcare Market for Diagnosis, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.57 Digital Twins in Healthcare Market for Other Application Areas, Historical Trends, since 2018 (USD Billion)
• Table 23.58 Digital Twins in Healthcare Market for Other Application Areas, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.59 Global Digital Twins in Healthcare Market: Distribution by End Users, 2018, 2024 and 2035
• Table 23.60 Digital Twins in Healthcare Market for Pharmaceutical Companies, Historical Trends, since 2018 (USD Billion)
• Table 23.61 Digital Twins in Healthcare Market for Pharmaceutical Companies, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.62 Digital Twins in Healthcare Market for Medical Device Manufacturers, Historical Trends, since 2018 (USD Billion)
• Table 23.63 Digital Twins in Healthcare Market for Medical Device Manufacturers, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.64 Digital Twins in Healthcare Market for Healthcare Providers, Historical Trends, since 2018 (USD Billion)
• Table 23.65 Digital Twins in Healthcare Market for Healthcare Providers, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.66 Digital Twins in Healthcare Market for Patients, Historical Trends, since 2018 (USD Billion)
• Table 23.67 Digital Twins in Healthcare Market for Patients, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.68 Digital Twins in Healthcare Market for Other End Users, Historical Trends, since 2018 (USD Billion)
• Table 23.69 Digital Twins in Healthcare Market for Other End Users, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.70 Global Digital Twins in Healthcare Market: Distribution by Key Geographies, 2018, 2024 and 2035
• Table 23.71 Digital Twins in Healthcare Market in North America, Historical Trends, since 2018 (USD Billion)
• Table 23.72 Digital Twins in Healthcare Market in North America, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.73 Digital Twins in Healthcare Market in the US, Historical Trends, since 2018 (USD Billion)
• Table 23.74 Digital Twins in Healthcare Market in the US, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.75 Digital Twins in Healthcare Market in Canada, Historical Trends, since 2018 (USD Billion)
• Table 23.76 Digital Twins in Healthcare Market in Canada, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.77 Digital Twins in Healthcare Market in Europe, Historical Trends, since 2018 (USD Billion)
• Table 23.78 Digital Twins in Healthcare Market in Europe, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.79 Digital Twins in Healthcare Market in France, Historical Trends, since 2018 (USD Billion)
• Table 23.80 Digital Twins in Healthcare Market in France, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.81 Digital Twins in Healthcare Market in Germany, Historical Trends, since 2018 (USD Billion)
• Table 23.82 Digital Twins in Healthcare Market in Germany, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.83 Digital Twins in Healthcare Market in Italy, Historical Trends, since 2018 (USD Billion)
• Table 23.84 Digital Twins in Healthcare Market in Italy, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.85 Digital Twins in Healthcare Market in Spain, Historical Trends, since 2018 (USD Billion)
• Table 23.86 Digital Twins in Healthcare Market in Spain, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.87 Digital Twins in Healthcare Market in the UK, Historical Trends, since 2018 (USD Billion)
• Table 23.88 Digital Twins in Healthcare Market in the UK, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.89 Digital Twins in Healthcare Market in Rest of the Europe, Historical Trends, since 2018 (USD Billion)
• Table 23.90 Digital Twins in Healthcare Market in Rest of the Europe, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.91 Digital Twins in Healthcare Market in Asia, Historical Trends, since 2018 (USD Billion)
• Table 23.92 Digital Twins in Healthcare Market in Asia, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.93 Digital Twins in Healthcare Market in China, Historical Trends, since 2018 (USD Billion)
• Table 23.94 Digital Twins in Healthcare Market in China, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.95 Digital Twins in Healthcare Market in India, Historical Trends, since 2018 (USD Billion)
• Table 23.96 Digital Twins in Healthcare Market in India, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.97 Digital Twins in Healthcare Market in Japan, Historical Trends, since 2018 (USD Billion)
• Table 23.98 Digital Twins in Healthcare Market in Japan, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.99 Digital Twins in Healthcare Market in Singapore, Historical Trends, since 2018 (USD Billion)
• Table 23.100 Digital Twins in Healthcare Market in Singapore, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.101 Digital Twins in Healthcare Market in South Korea, Historical Trends, since 2018 (USD Billion)
• Table 23.102 Digital Twins in Healthcare Market in South Korea, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.103 Digital Twins in Healthcare Market in Rest of the Asia, Historical Trends, since 2018 (USD Billion)
• Table 23.104 Digital Twins in Healthcare Market in Rest of the Asia, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.105 Digital Twins in Healthcare Market in Latin America, Historical Trends, since 2018 (USD Billion)
• Table 23.106 Digital Twins in Healthcare Market in Latin America, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.107 Digital Twins in Healthcare Market in Middle East and North Africa, Historical Trends, since 2018 (USD Billion)
• Table 23.108 Digital Twins in Healthcare Market in Middle East and North Africa, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.109 Digital Twins in Healthcare Market in Rest of the World, Historical Trends, since 2018 (USD Billion)
• Table 23.110 Digital Twins in Healthcare Market in Rest of the World, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.111 Digital Twins in Healthcare Market in Australia, Historical Trends, since 2018 (USD Billion)
• Table 23.112 Digital Twins in Healthcare Market in Australia, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)
• Table 23.113 Digital Twins in Healthcare Market in New Zealand, Historical Trends, since 2018 (USD Billion)
• Table 23.114 Digital Twins in Healthcare Market in New Zealand, Conservative, Base and Optimistic Scenarios, till 2035 (USD Billion)

List of Figures

• Figure 2.1 Research Methodology: Project Methodology
• Figure 2.2 Research Methodology: Forecast Methodology
• Figure 2.3 Research Methodology: Robust Quality Control
• Figure 2.4 Research Methodology: Key Market Segmentations
• Figure 3.1 Lessons Learnt from Past Recessions
• Figure 4.1 Executive Summary: Market Landscape
• Figure 4.2 Executive Summary: Partnerships and Collaborations
• Figure 4.3 Executive Summary: Funding and Investment Analysis
• Figure 4.4 Executive Summary: Market Forecast (I / II)
• Figure 4.5 Executive Summary: Market Forecast (II / II)
• Figure 5.1 Overview of Digital Twin Technology
• Figure 5.2 Human Digital Twin
• Figure 5.3 Challenges Associated with the Adoption of Digital Twins
• Figure 6.1 Digital Twins: Distribution by Development Status
• Figure 6.2 Digital Twins: Distribution by Therapeutic Area
• Figure 6.3 Digital Twins: Distribution by Areas of Application
• Figure 6.4 Digital Twins: Distribution by Type of Technology Used
• Figure 6.5 Digital Twins: Distribution by End Users
• Figure 6.6 Digital Twins: Distribution by Type of Digital Twin
• Figure 6.7 Digital Twin Developers: Distribution by Year of Establishment
• Figure 6.8 Digital Twin Developers: Distribution by Company Size
• Figure 6.9 Digital Twin Developers: Distribution by Location of Headquarters
• Figure 7.1 Key Insights: Distribution by Area of Application and Development Status
• Figure 7.2 Key Insights: Distribution by Type of Technology Used and Type of Digital Twin
• Figure 7.3 Key Insights: Distribution by Type of End User and Type of Digital Twin
• Figure 7.4 Key Insights: Distribution by Location of Headquarters and Area of Application
• Figure 7.5 Key Insights: Distribution by Company Size and Location of Headquarters
• Figure 8.1 Company Competitiveness Analysis: Benchmarking of Portfolio Strength
• Figure 8.2 Company Competitiveness Analysis: Benchmarking of Partnership Activity
• Figure 8.3 Company Competitiveness Analysis: Benchmarking of Funding Activity
• Figure 8.4 Company Competitiveness Analysis: Dot-plot Analysis of Players Based in North America
• Figure 8.5 Company Competitiveness Analysis: 3-D Bubble Chart Analysis of Players Based in North America
• Figure 8.6 Company Competitiveness Analysis: Dot-plot Analysis of Players Based in Europe
• Figure 8.7 Company Competitiveness Analysis: 3-D Bubble Chart Analysis of Players Based in Europe
• Figure 8.8 Company Competitiveness Analysis: 3-D Bubble Chart Analysis of Players Based in Asia and Rest of the World
• Figure 9.1 BigBear.ai: Annual Revenues, FY 2021 Onwards (USD Million)
• Figure 9.2 Certara: Annual Revenues, FY 2020 Onwards (USD Million)
• Figure 9.3 Dassault Systemes: Annual Revenues, FY 2019 Onwards (EUR Billion)
• Figure 11.1 Partnerships and Collaborations: Cumulative Year-wise Trend, since 2018
• Figure 11.2 Partnerships and Collaborations: Distribution by Type of Partnership
• Figure 11.3 Partnerships and Collaborations: Distribution by Year and Type of Partnership
• Figure 11.4 Partnerships and Collaborations: Distribution by Type of Partnership and Company Size
• Figure 11.5 Most Active Players: Distribution by Number of Partnerships
• Figure 11.6 Partnerships and Collaborations: Local and International Agreements
• Figure 11.7 Partnerships and Collaborations: Intercontinental and Intracontinental Agreements
• Figure 12.1 Funding and Investment Analysis: Cumulative Year-wise Trend, since 2018
• Figure 12.2 Funding and Investment Analysis: Cumulative Amount Invested (USD Million), since 2018
• Figure 12.3 Funding and Investment Analysis: Distribution of Instances by Type of Funding, since 2018
• Figure 12.4 Funding and Investment Analysis: Year-Wise Distribution by Type of Funding, since 2018
• Figure 12.5 Funding and Investment Analysis: Distribution of Total Amount Invested (USD Million) by Type of Funding, since 2018
• Figure 12.6 Funding and Investment Analysis: Distribution by Geography
• Figure 12.7 Most Active Players: Distribution by Number of Funding Instances, since 2018
• Figure 12.8 Most Active Players: Distribution by Amount Raised (USD Million), since 2018
• Figure 12.9 Funding and Investment Summary, since 2018 (USD Million)
• Figure 13.1 Berkus Start-Up Valuation: Total Valuation of Players (USD Million)
• Figure 13.2 AI Body: Benchmarking of Berkus Start-Up Valuation Parameters
• Figure 13.3 AnatoScope: Benchmarking of Berkus Start-Up Valuation Parameters
• Figure 13.4 Antleron: Benchmarking of Berkus Start-Up Valuation Parameters
• Figure 13.5 EmbodyBio: Benchmarking of Berkus Start-Up Valuation Parameters
• Figure 13.6 Klinik Sankt Moritz: Benchmarking of Berkus Start-Up Valuation Parameters
• Figure 13.7 MAI: Benchmarking of Berkus Start-Up Valuation Parameters
• Figure 13.8 Mindbank AI: Benchmarking of Berkus Start-Up Valuation Parameters
• Figure 13.9 Neo PLM: Benchmarking of Berkus Start-Up Valuation Parameters
• Figure 13.10 TwInsight: Benchmarking of Berkus Start-Up Valuation Parameters
• Figure 13.11 Sound Idea: Benchmarking of Players
• Figure 13.12 Prototype: Benchmarking of Players
• Figure 13.13 Management Experience: Benchmarking of Players
• Figure 13.14 Strategic Relationships: Benchmarking of Players
• Figure 13.15 Total Valuation: Benchmarking of Players
• Figure 14.1 Digital Twins in Healthcare: Market Drivers
• Figure 14.2 Digital Twins in Healthcare: Market Restraints
• Figure 14.3 Digital Twins in Healthcare: Market Opportunities
• Figure 14.4 Digital Twins in Healthcare: Market Challenges
• Figure 15.1 Global Digital Twins in Healthcare Market, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 15.2 Global Digital Twins in Healthcare Market, Forecasted Estimates (till 2035): Conservative Scenario (USD Billion)
• Figure 15.3 Global Digital Twins in Healthcare Market, Forecasted Estimates (till 2035): Optimistic Scenario (USD Billion)
• Figure 16.1 Digital Twins in Healthcare Market: Distribution by Therapeutic Area, 2018, 2024 And 2035
• Figure 16.2 Digital Twins in Healthcare Market for Cardiovascular Disorders, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 16.3 Digital Twins in Healthcare Market for Metabolic Disorders, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 16.4 Digital Twins in Healthcare Market for Orthopedic Disorders, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 16.5 Digital Twins in Healthcare Market for Other Disorders, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 17.1 Digital Twins in Healthcare Market: Distribution by Type of Digital Twin, 2018, 2024 And 2035
• Figure 17.2 Digital Twins in Healthcare Market for Process Twins, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 17.3 Digital Twins in Healthcare Market for System Twins, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 17.4 Digital Twins in Healthcare Market for Whole Body Twins, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 17.5 Digital Twins in Healthcare Market for Body Part Twins, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 18.1 Digital Twins in Healthcare Market: Distribution by Area of Application, 2018, 2024 And 2035
• Figure 18.2 Digital Twins in Healthcare Market for Asset / Process Management, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 18.3 Digital Twins in Healthcare Market for Personalized Treatment, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 18.4 Digital Twins in Healthcare Market for Surgical Planning, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 18.5 Digital Twins in Healthcare Market for Diagnosis, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 18.6 Digital Twins in Healthcare Market for Other Application Areas, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 19.1 Digital Twins in Healthcare Market: Distribution by End Users, 2018, 2024 And 2035
• Figure 19.2 Digital Twins in Healthcare Market for Pharmaceutical Companies, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 19.3 Digital Twins in Healthcare Market for Medical Device Manufacturers, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 19.4 Digital Twins in Healthcare Market for Healthcare Providers, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 19.5 Digital Twins in Healthcare Market for Patients, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 19.6 Digital Twins in Healthcare Market for Other End Users, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 20.1 Digital Twins in Healthcare Market: Distribution by Key Geographies, 2018, 2024 And 2035
• Figure 20.2 Digital Twins in Healthcare Market in North America, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 20.3 Digital Twins in Healthcare Market in the US, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 20.4 Digital Twins in Healthcare Market in Canada, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 20.5 Digital Twins in Healthcare Market in Europe, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 20.6 Digital Twins in Healthcare Market in France, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 20.7 Digital Twins in Healthcare Market in Germany, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 20.8 Digital Twins in Healthcare Market in Italy, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 20.9 Digital Twins in Healthcare Market in Spain, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 20.10 Digital Twins in Healthcare Market in the UK, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 20.11 Digital Twins in Healthcare Market in Rest of the Europe, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 20.12 Digital Twins in Healthcare Market in Asia, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 20.13 Digital Twins in Healthcare Market in China, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 20.14 Digital Twins in Healthcare Market in India, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 20.15 Digital Twins in Healthcare Market in Japan, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 20.16 Digital Twins in Healthcare Market in Singapore, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 20.17 Digital Twins in Healthcare Market in South Korea, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 20.18 Digital Twins in Healthcare Market in Rest of the Asia, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 20.19 Digital Twins in Healthcare Market in Latin America, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 20.20 Digital Twins in Healthcare Market in Middle East and North Africa, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 20.21 Digital Twins in Healthcare Market in Rest of the World, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 20.22 Digital Twins in Healthcare Market in Australia, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 20.23 Digital Twins in Healthcare Market in New Zealand, Historical Trends (since 2018) and Forecasted Estimates (till 2035) (USD Billion)
• Figure 21.1 Conclusion: Market Landscape
• Figure 21.2 Conclusion: Partnerships and Collaborations
• Figure 21.3 Conclusion: Funding and Investments
• Figure 21.4 Conclusion: Berkus Start-up Valuation Analysis
• Figure 21.5 Conclusion: Market Forecast (I / II)
• Figure 21.6 Conclusion: Market Forecast (II / II)

DIGITAL TWINS IN HEALTHCARE MARKET: OVERVIEW

As per Roots Analysis, the global digital twins in healthcare market is estimated to grow from USD 1.9 billion in the current year to USD 33.4 billion by 2035, at a CAGR of 30% during the forecast period, till 2035.

The market opportunity for cell and gene therapy supply chain software has been distributed across the following segments:

Therapeutic Area

• Cardiovascular Disorders
• Metabolic Disorders
• Orthopedic Disorders
• Other Disorders

Type of Digital Twin

• Process Twins
• System Twins
• Whole Body Twins
• Body Part Twins

Area of Application

• Asset / Process Management
• Personalized Treatment
• Surgical Planning
• Diagnosis
• Other Applications

End Users

• Pharmaceutical Companies
• Medical Device Manufacturers
• Healthcare Providers
• Patients
• Other End Users

Key Geographical Regions

• North America
• Europe
• Asia
• Latin America
• Middle East and North Africa
• Rest of the World

DIGITAL TWINS IN HEALTHCARE MARKET: GROWTH AND TRENDS

In recent years, there have been significant advancements related to technologies, such as artificial intelligence, deep learning and machine learning and big data. These programs have now garnered significant interest of players engaged in the healthcare domain. Consequently, the industry stakeholders are undertaking efforts to drive innovation and improve the performance of the existing processes, using the aforementioned technologies. Amidst these technologies, digital twins have emerged as a promising technique for use in the healthcare sector. In this context, it is worth mentioning that a digital twin, in its essence, is a virtual model that employs real-world data to create simulations, which are capable of predicting the performance of a system or process. Specifically, in the healthcare domain, digital twins can be applied for risk prediction, lowering labor costs, providing improved patient care and automated decision-making process. Further, players engaged in the healthcare domain may increasingly adopt the digital twin concept to cut down their research and development costs. Driven by the growing demand for personalized medicine, virtual simulation and automated technologies, the digital twin in healthcare is poised to witness substantial growth.

DIGITAL TWINS IN HEALTHCARE MARKET: KEY INSIGHTS

The report delves into the current state of the digital twins in healthcare market and identifies potential growth opportunities within the industry. Some key findings from the report include:

• Currently, over 90 digital twins are either commercially available in the market or are under development for various healthcare related applications including diagnosis, health monitoring and surgical planning.

• Over 42% of the digital twins offered by industry players are process twins; majority of the twins are primarily intended for asset / process management, personalized treatment and surgical planning.
• The partnership activity in this industry has grown at a rate of over 20% in the past three years; it is worth noting that over 45% of the deals have been signed in the last two years.
• To support the ongoing innovations, several private and public investors have made substantial capital investments; notably, most of the funding rounds took place in the past few years.
• Start-ups in the digital twin market are gradually adopting advanced and innovative technologies, such as artificial intelligence and blockchain, in order to differentiate themselves from their competitors.
• Owing to the growing interest towards remote patient monitoring, predictive analytics, personalized treatment, and IoT integration, the market for digital twins in healthcare will increase steadily in the foreseeable future.
• Driven by increasing adoption of digital twin technologies in healthcare and pharmaceutical industries, it is anticipated that the global digital twins market in healthcare domain is likely to grow at an annualized rate of 30%, till 2035.

DIGITAL TWINS IN HEALTHCARE MARKET: KEY SEGMENTS

Cardiovascular Disorders are Likely to Dominate the Digital Twins in Healthcare Market

Based on the therapeutic areas, the market is segmented into cardiovascular disorders, metabolic disorders, orthopedic disorders and other disorders. At present, cardiovascular disorders hold the maximum share of the digital twins in healthcare market. This trend is unlikely to change in the near future.

Asset / Process Management Segment Occupies the Largest Share of the Digital Twins in Healthcare Market

Based on the areas of application, the market is segmented into asset / process management, personalized treatment, surgical planning, diagnosis and other applications. Currently, asset / process management captures the highest portion of the digital twins in healthcare market. However, this trend is expected to gradually shift towards personalized treatment in the future. This can be attributed to the fact that personalized biochemical modeling has experienced an emerging trend in this domain and has demonstrated several promising results, including administrating soft tissue behavior in orthopedic surgical interventions.

Pharmaceutical Companies are Likely to Dominate the Digital Twins in Healthcare Market

Based on the end users, the market is segmented into healthcare providers, medical device manufacturers, patients, pharmaceutical companies and other end users. At present, the pharmaceutical companies hold the maximum share of the digital twins in healthcare market. This trend is likely to remain the same in the forthcoming years.

North America Accounts for the Largest Share of the Market

Based on key geographical regions, the market is segmented into North America, Europe, Asia, Latin America, Middle East and North Africa, and Rest of the World. The majority share is expected to be captured by players based in North America. It is worth highlighting that, over the years, the market in Middle East and North Africa is expected to grow at a higher CAGR.

Example Players in the Digital Twins in Healthcare Market

• BigBear.ai
• Certara
• Dassault Systemes
• DEO
• Mesh Bio
• NavvTrack
• OnScale
• Phesi
• PrediSurge
• SingHealth
• Twin Health
• Unlearn
• Verto
• VictoryXR
• Virtonomy

Primary Research Overview

The opinions and insights presented in this study were influenced by discussions conducted with multiple stakeholders. The research report features detailed transcripts of interviews held with the following industry stakeholders:

• Co-Founder and Chief Scientific Officer, Australia
• Managing Director and Chief Executive Officer, Germany
• Chief Commercial Officer, Germany
• Chief Solutions Officer, Canada
• Co-founder and Chief Technology Officer, US
• Business Consultant, France
• Business Development Executive, US

DIGITAL TWINS IN HEALTHCARE MARKET: RESEARCH COVERAGE

• Market Sizing and Opportunity Analysis: The report features an in-depth analysis of the digital twins in healthcare market, focusing on key market segments, including [A] therapeutic area, [B] type of digital twin, [C] area of application, [D] end users and [E] key geographical regions.
• Market Landscape: A comprehensive evaluation of companies involved in the development of digital twins, considering various parameters, such as [A] year of establishment, [B] company size, [C] location of headquarters, [D] status of development, [E] therapeutic area, [F] areas of application, [G] type of technology used, [H] type of digital twin and [I] end users.
• Key Insights: An in-depth digital twins in healthcare market analysis, highlighting the contemporary market trends, using five schematic representations, based on [A] areas of application and status of development, [B] type of technology used and type of digital twin, [C] type of end user and type of digital twin, [D] area of application and location of headquarters, and [E] company size and location of headquarters.
• Company Competitiveness Analysis: A comprehensive competitive analysis of digital twins developers, examining factors, such as [A] years of experience, [B] portfolio strength, [C] partnership strength and [D] funding strength.
• Company Profiles: In-depth profiles of key industry players offering digital twins, focusing on [A] company overviews, [B] financial information (if available), [C] recent developments and [D] an informed future outlook.
• Partnerships and Collaborations: An analysis of partnerships established in this sector, since 2018, covering acquisitions, mergers, commercialization agreements, licensing agreements, product development agreements, research agreements, service agreements, service alliances, technology development agreements, technology integration agreements, technology utilization agreements and others.
• Funding and Investment Analysis: A detailed evaluation of the investments made in the digital twins market, encompassing grants, seed funding, venture capital investments, initial public offering, secondary offerings, private placements, debt financing and other equity.
• Berkus Start-Up Valuation Analysis: A proprietary analysis designed to assess start-ups in this market, by assigning monetary values to various competition differentiators possessed by a player. This evaluation is based on the Berkus start-up valuation criteria, which include factors such as sound idea, prototype, management experience and strategic relationships undertaken by market players.
• Market Impact Analysis: The report analyzes various factors such as drivers, restraints, opportunities, and challenges affecting the market growth.

KEY QUESTIONS ANSWERED IN THIS REPORT

• How many companies are currently engaged in this market?
• Which are the leading companies in this market?
• What factors are likely to influence the evolution of this market?
• What is the current and future market size?
• What is the CAGR of this market?
• How is the current and future market opportunity likely to be distributed across key market segments?

REASONS TO BUY THIS REPORT

• 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.
• Stakeholders can leverage the report to gain a deeper understanding of the competitive dynamics within the market. By analyzing the competitive landscape, businesses can make informed decisions to optimize their market positioning and develop effective go-to-market strategies.
• The report offers stakeholders a comprehensive overview of the market, including key drivers, barriers, opportunities, and challenges. This information empowers stakeholders to stay abreast of market trends and make data-driven decisions to capitalize on growth prospects.

ADDITIONAL BENEFITS

• Complimentary PPT Insights Packs
• Complimentary Excel Data Packs for all Analytical Modules in the Report
• 10% Free Content Customization
• Detailed Report Walkthrough Session with Research Team
• Free Updated report if the report is 6-12 months old or older

TABLE OF CONTENTS

1. PREFACE

• 1.1. Introduction
• 1.2. Market Share Insights
• 1.3. Key Market Insights
• 1.4. Report Coverage
• 1.5. Frequently Asked Questions
• 1.6. Chapter Outlines

2. RESEARCH METHODOLOGY

• 2.1. Chapter Overview
• 2.2. Research Assumptions
• 2.3. Project Methodology
• 2.4. Forecast Methodology
• 2.5. Robust Quality Control
• 2.6. Key Market Segmentations
• 2.7. Key Considerations
  • 2.7.1. Demographics
  • 2.7.2. Economic Factors
  • 2.7.3. Government Regulations
  • 2.7.4. Supply Chain
  • 2.7.5. COVID Impact
  • 2.7.6. Market Access
  • 2.7.7. Healthcare Policies
  • 2.7.8. Industry Consolidation

3. ECONOMIC AND OTHER PROJECT SPECIFIC CONSIDERATIONS

• 3.1. Chapter Overview
• 3.2. Market Dynamics
  • 3.2.1. Time Period
    • 3.2.1.1. Historical Trends
    • 3.2.1.2. Current and Forecasted Estimates
  • 3.2.2. Currency Coverage and Foreign Exchange Rate
    • 3.2.2.1. Major Currencies Affecting the Market
    • 3.2.2.2. Factors Affecting Currency Fluctuations and Foreign Exchange Rates
    • 3.2.2.3. Impact of Foreign Exchange Rate Volatility on the Market
    • 3.2.2.4. Strategies for Mitigating Foreign Exchange Risk
  • 3.2.3. Trade Policies
    • 3.2.3.1. Impact of Trade Barriers on the Market
    • 3.2.3.2. Strategies for Mitigating the Risks Associated with Trade Barriers
  • 3.2.4. Recession
    • 3.2.4.1. Historical Analysis of Past Recessions and Lessons Learnt
    • 3.2.4.2. Assessment of Current Economic Conditions and Potential Impact on the Market
  • 3.2.5. Inflation
    • 3.2.5.1. Measurement and Analysis of Inflationary Pressures in the Economy
    • 3.2.5.2. Potential Impact of Inflation on the Market Evolution

4. EXECUTIVE SUMMARY

5. INTRODUCTION

• 5.1. Chapter Overview
• 5.2. Overview of Digital Twins in Healthcare
• 5.3. Types of Digital Twins Used in Healthcare
  • 5.3.1. System Twin
  • 5.3.2. Process Twin
  • 5.3.3. Human Digital Twin
• 5.4. Applications of Digital Twins in the Healthcare Domain
  • 5.4.1. Asset / Process Management
  • 5.4.2. Clinical Trial Evaluation
  • 5.4.3. Personalized Medicine
  • 5.4.4. Surgical Planning
• 5.5. Challenges Associated with the Adoption of Digital Twins
• 5.6. Future Perspectives

6. MARKET LANDSCAPE

• 6.1. Chapter Overview
• 6.2. Digital Twins in Healthcare: Overall Market Landscape
  • 6.2.1. Analysis by Development Status
  • 6.2.2. Analysis by Therapeutic Area
  • 6.2.3. Analysis by Area of Application
  • 6.2.4. Analysis by Type of Technology Used
  • 6.2.5. Analysis by End Users
  • 6.2.6. Analysis by Type of Digital Twin
• 6.3. Digital Twins in Healthcare: Developer Landscape
  • 6.3.1. Analysis by Year of Establishment
  • 6.3.2. Analysis by Company Size
  • 6.3.3. Analysis by Location of Headquarters

7. KEY INSIGHTS

• 7.1. Chapter Overview
• 7.2. Analysis by Area of Application and Development Status
• 7.3. Analysis by Type of Technology Used and Type of Digital Twin
• 7.4. Analysis by Type of End User and Type of Digital Twin
• 7.5. Analysis by Location of Headquarters and Area of Application
• 7.6. Analysis by Company Size and Location of Headquarters

8. COMPANY COMPETITIVENESS ANALYSIS

• 8.1. Chapter Overview
• 8.2. Assumptions and Key Parameters
• 8.3. Methodology
• 8.4. Digital Twins in Healthcare: Company Competitiveness Analysis
  • 8.4.1. Company Competitiveness Analysis: Benchmarking of Portfolio Strength
  • 8.4.2. Company Competitiveness Analysis: Benchmarking of Partnership Activity
  • 8.4.3. Company Competitiveness Analysis: Benchmarking of Funding Activity
  • 8.4.4. Company Competitiveness Analysis: Players Based in North America
  • 8.4.5. Company Competitiveness Analysis: Players Based in Europe
  • 8.4.6. Company Competitiveness Analysis: Players Based in Asia and Rest of the World

9. DETAILED COMPANY PROFILES

• 9.1. Chapter Overview
• 9.2. BigBear.ai
  • 9.2.1. Company Overview
  • 9.2.2. Financial Information
  • 9.2.3. Recent Developments and Future Outlook
• 9.3. Certara
  • 9.3.1. Company Overview
  • 9.3.2. Financial Information
  • 9.3.3. Recent Developments and Future Outlook
• 9.4. Dassault Systemes
  • 9.4.1. Company Overview
  • 9.4.2. Financial Information
  • 9.4.3. Recent Developments and Future Outlook
• 9.5. NavvTrack
  • 9.5.1. Company Overview
  • 9.5.2. Recent Developments and Future Outlook
• 9.6. Unlearn.ai
  • 9.6.1. Company Overview
  • 9.6.2. Recent Developments and Future Outlook

10. TABULATED COMPANY PROFILES

• 10.1. Chapter Overview
• 10.2. Players Based in North America
  • 10.2.1. OnScale
  • 10.2.2. Phesi
  • 10.2.3. Twin Health
  • 10.2.4. Verto
  • 10.2.5. VictoryXR
• 10.3. Players Based in Europe
  • 10.3.1. DEO
  • 10.3.2. PrediSurge
  • 10.3.3. Virtonomy
• 10.4. Players Based in Asia
  • 10.4.1. Mesh Bio
  • 10.4.2. SingHealth

11. PARTNERSHIPS AND COLLABORATIONS

• 11.1. Chapter Overview
• 11.2. Digital Twins in Healthcare: Partnerships and Collaborations
  • 11.2.1. Partnership Models
  • 11.2.2. List of Partnerships and Collaborations
  • 11.2.3. Analysis by Year of Partnership
  • 11.2.4. Analysis by Type of Partnership
  • 11.2.5. Analysis by Year and Type of Partnership
  • 11.2.6. Analysis by Type of Partnership and Company Size
  • 11.2.7. Most Active Players: Analysis by Number of Partnerships
  • 11.2.8. Local and International Agreements
  • 11.2.9. Intercontinental and Intracontinental Agreements

12. FUNDING AND INVESTMENTS ANALYSIS

• 12.1. Chapter Overview
• 12.2. Types of Funding
• 12.3. Digital Twins in Healthcare: List of Funding and Investments
  • 12.3.1. Analysis by Number of Funding Instances
  • 12.3.2. Analysis by Amount Invested
  • 12.3.3. Analysis by Type of Funding
  • 12.3.4. Analysis by Geography
  • 12.3.5. Most Active Players: Analysis by Number of Funding Instances
  • 12.3.6. Most Active Players: Analysis by Amount of Funding
• 12.4. Concluding Remarks

13. BERKUS START-UP VALUATION ANALYSIS

• 13.1. Chapter Overview
• 13.2. Assumptions and Key Parameters
• 13.3. Methodology
• 13.4. Berkus Start-Up Valuation: Total Valuation of Players
• 13.5. Digital Twins in Healthcare: Benchmarking of Berkus Start-Up Valuation Parameters
  • 13.5.1. AI Body: Benchmarking of Berkus Start-Up Valuation Parameters
  • 13.5.2. AnatoScope: Benchmarking of Berkus Start-Up Valuation Parameters
  • 13.5.3. Antleron: Benchmarking of Berkus Start-Up Valuation Parameters
  • 13.5.4. EmbodyBio: Benchmarking of Berkus Start-Up Valuation Parameters
  • 13.5.5. Klinik Sankt Moritz: Benchmarking of Berkus Start-Up Valuation Parameters
  • 13.5.6. MAI: Benchmarking of Berkus Start-Up Valuation Parameters
  • 13.5.7. Mindbank AI: Benchmarking of Berkus Start-Up Valuation Parameters
  • 13.5.8. Neo PLM: Benchmarking of Berkus Start-Up Valuation Parameters
  • 13.5.9. Twinsight: Benchmarking of Berkus Start-Up Valuation Parameters
• 13.6. Digital Twins in Healthcare: Benchmarking of Players
  • 13.6.1. Sound Idea: Benchmarking of Players
  • 13.6.2. Prototype: Benchmarking of Players
  • 13.6.3. Management Experience: Benchmarking of Players
  • 13.6.4. Strategic Relationships: Benchmarking of Players
  • 13.6.5. Total Valuation: Benchmarking of Players

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

• 14.1. Chapter Overview
• 14.2. Market Drivers
• 14.3. Market Restraints
• 14.4. Market Opportunities
• 14.5. Market Challenges
• 14.6. Conclusion

15. GLOBAL DIGITAL TWIN IN HEALTHCARE MARKET

• 15.1. Chapter Overview
• 15.2. Assumptions and Methodology
• 15.3. Global Digital Twin in Healthcare Market, Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 15.3.1. Scenario Analysis
    • 15.3.1.1. Conservative Scenario
    • 15.3.1.2. Optimistic Scenario
  • 15.3.2. Key Market Segmentations

16. DIGITAL TWIN IN HEALTHCARE MARKET, BY THERAPEUTIC AREA

• 16.1. Chapter Overview
• 16.2. Assumptions and Methodology
• 16.3. Digital Twin in Healthcare Market: Distribution by Therapeutic Area, 2018, 2024 and 2035
  • 16.3.1. Cardiovascular Disorders: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 16.3.2. Metabolic Disorders: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 16.3.3. Orthopedic Disorders: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 16.3.4. Other Disorders: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 16.3.5. Data Triangulation and Validation

17. DIGITAL TWIN IN HEALTHCARE MARKET, BY TYPE OF DIGITAL TWINS

• 17.1. Chapter Overview
• 17.2. Assumptions and Methodology
• 17.3. Digital Twin in Healthcare Market: Distribution by Type of Digital Twins, 2018, 2024 and 2035
  • 17.3.1. Process Twins: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 17.3.2. System Twins: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 17.3.3. Whole Body Twins: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 17.3.4. Body Part Twins: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 17.3.5. Data Triangulation and Validation

18. DIGITAL TWIN IN HEALTHCARE MARKET, BY AREA OF APPLICATION

• 18.1. Chapter Overview
• 18.2. Assumptions and Methodology
• 18.3. Digital Twin in Healthcare Market: Distribution by Area of Application, 2018, 2024 And 2035
  • 18.3.1. Asset / Process Management: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 18.3.2. Personalized Treatment: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 18.3.3. Surgical Planning: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 18.3.4. Diagnosis: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 18.3.5. Other Applications: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 18.3.6. Data Triangulation and Validation

19. DIGITAL TWIN IN HEALTHCARE MARKET, BY END USERS

• 19.1. Chapter Overview
• 19.2. Assumptions and Methodology
• 19.3. Digital Twin in Healthcare Market: Distribution by End Users, 2018, 2024 and 2035
  • 19.3.1. Pharmaceutical Companies: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 19.3.2. Medical Device Manufacturers: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 19.3.3. Healthcare Providers: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 19.3.4. Patients: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 19.3.5. Other End Users: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 19.3.6. Data Triangulation and Validation

20. DIGITAL TWIN IN HEALTHCARE MARKET, BY GEOGRAPHY

• 20.1. Chapter Overview
• 20.2. Assumptions and Methodology
• 20.3. Digital Twins in Healthcare Market: Distribution by Key Geographies, 2018, 2024 And 2035
  • 20.3.1. North America: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
    • 20.3.1.1. US: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
    • 20.3.1.2. Canada: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 20.3.2. Europe: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
    • 20.3.2.1. France: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
    • 20.3.2.2. Germany: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
    • 20.3.2.3. Italy: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
    • 20.3.2.4. Spain: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
    • 20.3.2.5. UK: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
    • 20.3.2.6. Rest of Europe: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 20.3.3. Asia: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
    • 20.3.3.1. China: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
    • 20.3.3.2. India: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
    • 20.3.3.3. Japan: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
    • 20.3.3.4. Singapore: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
    • 20.3.3.5. South Korea: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
    • 20.3.3.6. Rest of Asia: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 20.3.4. Latin America: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 20.3.5. Middle East and North Africa: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 20.3.6. Rest of the World: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
    • 20.3.6.1. Australia: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
    • 20.3.6.2. New Zealand: Historical Trends (since 2018) and Forecasted Estimates (till 2035)
  • 20.3.7. Data Triangulation and Validation

21. CONCLUSION

22. EXECUTIVE INSIGHTS

• 22.1. Chapter Overview
• 22.2. Company A
  • 22.2.1. Company Snapshot
  • 22.2.2. Interview Transcript: Chief Commercial Officer
• 22.3. Company B
  • 22.3.1. Company Snapshot
  • 22.3.2. Interview Transcript: Chief Solutions Officer
• 22.4. Company C
  • 22.4.1. Company Snapshot
  • 22.4.2. Interview Transcript: Co-founder and Chief Technology Officer
• 22.5. Company D
  • 22.5.1. Company Snapshot
  • 22.5.2. Interview Transcript: Data Scientist
• 22.6. Company E
  • 22.6.1. Company Snapshot
  • 22.6.2. Interview Transcript: Business Consultant
• 22.7. Company F
  • 22.7.1. Company Snapshot
  • 22.7.2. Interview Transcript: Co-Founder and Chief Scientific Officer
• 22.8. Company G
  • 22.8.1. Company Snapshot
  • 22.8.2. Interview Transcript: Head of Business Development
• 22.9. Company H
  • 22.9.1. Company Snapshot
  • 22.9.2. Interview Transcript: Managing Director and Chief Executive Officer

23. APPENDIX I: TABULATED DATA

24. APPENDIX II: LIST OF COMPANIES AND ORGANIZATIONS