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Cloud-based Solutions for Drug Discovery, Development and Manufacturing Market by Type of Cloud (Private, Public and Hybrid), Type of Service (Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS)), End-User (Biotech Vendors, Contract Research Organizations, Pharmaceutical Companies and Others), and Key Geographical Regions (North America, Europe, Asia, MENA, Latin America, and Rest of the World): Industry Trends and Global Forecasts, 2021-2030

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Example Insights

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Cloud-based-Solutions-for-Drug-Discovery-Development-and-Manufacturing-Market-Company-Competitiveness-Analysis Cloud-based-Solutions-for-Drug-Discovery-Development-and-Manufacturing-Market-Partnerships-and-Collaborations Cloud-based-Solutions-for-Drug-Discovery-Development-and-Manufacturing-Market-Cost-Saving-Analysis
Cloud-based-Solutions-for-Drug-Discovery-Development-and-Manufacturing-Market-Forecast cloud-based-Solutions-for-Drug-Discovery-Development-and-Manufacturing-Market-Future-opportunity  

 

Overview

The process of drug development and manufacturing is estimated to take around 10-15 years. In addition, according to a study published in the Journal of the American Medical Association, it was estimated that approximately USD 1.3 billion in capital investment is required in progressing a single pharmacological lead from the bench to the market. It is also worth highlighting that close to 90% of pharmaceutical product candidates fail to make it past the clinical stage of development. This high attrition rate has long been attributed to certain legacy challenges associated with the drug discovery process, which is, presently, more of a trial-and-error based paradigm. Clinical trials are responsible for nearly 50% of the time and capital expenditure in a drug development program. Therefore, if such studies are delayed, or unsuccessful, developers are liable to bear considerable losses. Amidst the ongoing digital revolution, cloud computing, which was introduced in the 1960s, has recently demonstrated significant potential as an information sharing and analysis solution model. Although the healthcare industry is considered to be among the late adopters of this technology, it is rapidly evolving into an indispensable aspect of pharmaceutical R&D. Today, large volumes of health data can be accessed by medical researchers on dedicated cloud servers through processes that have been designed to comply with the Health Insurance Portability and Accountability Act (HIPAA) of 1996. 

Over time, cloud-based tools and solutions have been gradually deployed and integrated across various processes, including drug discovery, clinical trials and product manufacturing, within the pharma / biotech sector. Primarily, data clouds were designed to store information such that it can be easily accessed when required from multiple terminals. However, advances in online data processing technologies have led to the establishment of solutions that allow rapid analysis of large volumes of clinical / medical data; this aspect is widely used in the initial stages of pharmaceutical R&D. In this context, modern cloud-based solutions offer decentralized / real world data management, and collaborative operating opportunities to users, enabling the delegation of data mining and decision-making responsibilities. According to experts, the aforementioned features are expected to not only improve overall productivity, but also reduce the chances of clinical failure (by enabling drug developers to analyze historical data to inform their respective clinical research activities). Moreover, the implementation of relevant cloud-based solutions is deemed to possess the potential to save over 50% of the total cost and time invested in a drug development program (considering expenditure from the discovery stage to product commercialization). Interestingly, cloud computing is also being used in the development of potential therapeutic / preventive options against the novel coronavirus strain. In May 2020, researchers at the University of Bristol claimed to have used cloud-based solutions to successfully elucidate the structure of a potential preventive intervention, called ADDomer (a new class of synthetic vaccines). Further, several information technology focused companies are exploring ways to incorporate advanced data analysis algorithms, including those powered by artificial intelligence, machine learning, and / or quantum computing technologies, which are anticipated to open up new applications in pharmaceutical development and biotech research. Given how the pharmaceutical industry is advancing, in terms of adopting digital technologies, coupled to the ongoing efforts of service providers to further improve / expand their respective offerings, we believe the cloud-based solutions market is likely to evolve at a steady pace, till 2030.

Scope of the Report

The “Cloud-based Solutions for Drug Discovery, Development and Manufacturing Market by Type of Cloud (Private, Public and Hybrid), Type of Service (Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS)), End-User (Biotech Vendors, Contract Research Organizations, Pharmaceutical Companies and Others), and Key Geographical Regions (North America, Europe, Asia, Middle East and North Africa, Latin America, and Rest of the World): Industry Trends and Global Forecasts, 2021-2030” report features an extensive study of the current market landscape and future opportunity for the players engaged in offering cloud-based services, platforms and tools for the discovery, development and manufacturing of drug candidates. The study presents an in-depth analysis, highlighting the capabilities of various stakeholders engaged in this domain. Amongst other elements, the report features:

  • A detailed review of the current market landscape of companies offering cloud-based services, platforms, and tools for drug discovery, development and manufacturing, providing information on year of establishment, company size (in terms of number of employees), company type, location of headquarters, quality certifications, type of cloud (public, private, hybrid), type of service (IaaS, PaaS, SaaS), area of application (drug discovery, drug development, drug manufacturing), additional capabilities, and additional services offered.
  • An in-depth analysis of the contemporary trends, highlighted through various schematic representations, such as 4D bubble analysis based on type of service, area of application, company size and quality certifications, grid representation based on type of service, area of application, and type of cloud, a waffle chart based on geography and COVID-19-related initiatives, a mekko chart based on geography and additional capabilities and a world map highlighting the location of service providers.
  • An insightful competitiveness analysis of the cloud-based solution providers, taking into consideration their supplier strength (in terms of experience of the service provider), and popularity index (in terms of type of cloud, type of service, area of application, additional capabilities, additional services offered, COVID-19-related initiatives, number of quality certifications, number of partnerships, number of followers on twitter, and Google hits).
  • Elaborate profiles of key players that provide cloud-based solutions for drug discovery, development and manufacturing. Each company profile features a brief overview of the company (including information on year of establishment, number of employees, location of headquarters and key members of the executive team), recent developments and an informed future outlook.
  • An analysis of the partnerships that have been inked by stakeholders in this domain, in the period between 2015 and 2020, covering clinical data management agreements, platform development / improvement agreements, research agreements, research and platform development agreements, regulatory process management agreements, technology / data integration agreements, and other relevant types of deals. 
  • An insightful analysis highlighting the likely cost saving potential associated with the use of cloud-based solutions for drug discovery, development and manufacturing, taking into consideration various parameters, such as pharmaceutical R&D expenditure, drug discovery expenditure / budget, clinical trials expenditure, drug manufacturing expenditure and increase in efficiency by adoption of cloud-based solutions.
  • An in-depth analysis of the opportunities and the overall cost savings associated with integration of key tools and technologies, such as artificial intelligence, deep learning, machine learning, and quantum computing with cloud-based solutions for pharmaceutical product development and manufacturing. Further, it provides a detailed analysis on ease of implementation and associated risk in integrating above-mentioned technologies, based on the trends highlighted in published literature and patents.

One of the key objectives of this report was to estimate the existing market size and the future growth potential within the cloud-based solutions market for drug discovery, development and manufacturing. We have developed informed estimates on the financial evolution of the market, over the period 2021-2030. The report also provides details on the likely distribution of the current and forecasted opportunity across [A] type of cloud (private, public and hybrid) ), [B] type of service (infrastructure as a service (IaaS), platform as a service (PaaS), software as a service (SaaS)), [C] area of application (drug discovery, drug development and drug manufacturing) , [D] end-user (biotech vendors, contract research organizations, pharmaceutical companies and others), and [E] key geographical regions (North America, Europe, Asia, Middle East and North Africa, Latin America and Rest of the World). In order to account for future uncertainties and to add robustness to our forecast model, we have provided three scenarios, namely conservative, base and optimistic scenarios, representing different tracks of the industry’s growth. 
The opinions and insights presented in the report were also influenced by discussions held with multiple stakeholders in this domain. The report features detailed transcripts of interviews held with the following individuals (in alphabetical order):

  • Paolo Colombo (Vice President Growth, InSilicoTrials Technologies)
  • Velizar Natovski (Regional Manager North and South America, CloudSigma)

All actual figures have been sourced and analyzed from publicly available information forums. Financial figures mentioned in this report are in USD, unless otherwise specified.

Key Question Answered

  • Who are the leading players offering cloud-based solutions for drug discovery, development, and manufacturing?
  • Which cloud services are most commonly offered by the companies?
  • Which partnership models are most commonly adopted by stakeholders engaged in this industry?
  • What is the likely cost saving potential associated with the use of cloud-based solutions for drug discovery, development, and manufacturing process?
  • How is the current and future opportunity likely to be distributed across key market segments?
  • What is the likely performance enhancement via integrating artificial intelligence, deep learning, machine learning and quantum computing with cloud-based solutions?
  • What is the likely impact of the ongoing COVID-19 pandemic on the overall cloud-based solutions for drug discovery, development, and manufacturing market?
     

Contents

Chapter Outlines

Chapter 2 is an executive summary of the key insights captured in our research. It offers a high-level view on the current state of cloud-based solutions for drug discovery, development and manufacturing market and its likely evolution in the short-mid term and long term. 

Chapter 3 is an introductory chapter that presents details on implementation of cloud computing in pharmaceutical / biotech sector. It elaborates on the types of cloud and cloud services and provides an overview on applications of cloud-based solutions in drug discovery, development and drug manufacturing process, along with detailed information on its benefits and limitations. 

Chapter 4 provides a review of the current market landscape of companies offering cloud-based services, platforms, and tools for drug discovery, development and manufacturing. It includes a detailed analysis based on year of establishment, company size (in terms of number of employees), company type, location of headquarters, type of cloud (public, private, hybrid), type of service (IaaS, PaaS, SaaS), area of application (drug discovery, drug development, drug manufacturing), additional capabilities, additional services offered and quality certifications.

Chapter 5 features an in-depth analysis of the contemporary trends, highlighted through various schematic representations, including 4D bubble analysis based on type of service, area of application, company size and quality certifications, an insightful grid representation based on type of service, area of application, and type of cloud, a waffle chart based on geography and COVID-19-related initiatives, a mekko chart based on geography and additional capabilities and a world map representation highlighting the location of service providers.

Chapter 6 presents an insightful competitiveness analysis of the cloud-based solution providers, taking into consideration their supplier strength (in terms of experience of the service provider), and popularity index (in terms of type of cloud, type of service, area of application, additional capabilities, additional services offered, COVID-19-related initiatives, number of quality certifications, number of partnerships, number of followers on twitter, and Google hits), highlighting the prominent companies.

Chapter 7 include elaborate profiles of the key players that provide cloud-based solutions for drug discovery, development and manufacturing. Each company profile features a brief overview of the company (including information on year of establishment, number of employees, location of headquarters and key members of the executive team), recent developments and an informed future outlook.

Chapter 8 features an analysis of the partnerships that have been inked by stakeholders in this domain, in the period between 2015 and 2020. It includes a brief description of various partnership models (namely clinical data management agreements, platform development / improvement agreements, research agreements, research and platform development agreements, regulatory process management agreements, technology / data integration agreements, and other agreements). In addition, it includes a detailed analysis of partnerships, based on year of partnership, type of partnership, location of partners and other relevant parameters.

Chapter 9 includes an insightful analysis highlighting the likely cost saving potential associated with the use of cloud-based solutions for drug discovery, development and manufacturing, taking into consideration various parameters, such as pharmaceutical R&D expenditure, drug discovery expenditure / budget, clinical trials expenditure, drug manufacturing expenditure and increase in efficiency by adoption of cloud-based solutions.

Chapter 10 includes estimate of the existing market size and the likely future opportunity within the cloud-based services for drug discovery, development and manufacturing market. It includes estimate on the financial evolution of the market, over the period 202012030. The chapter also provides details on the likely distribution of the current and forecasted opportunity across [A] type of cloud (private, public and hybrid) ), [B] type of service (infrastructure as a service (IaaS), platform as a service (PaaS), software as a service (SaaS)), [C] area of application (drug discovery, drug development and drug manufacturing) , [D] end user (biotech vendors, contract research organizations, pharmaceutical companies and others), and [E] key geographical regions (North America, Europe, Asia, Middle East and North Africa, Latin America and Rest of the World). In order to account for future uncertainties and to add robustness to forecast model, three scenarios, namely conservative, base and optimistic scenarios, representing different tracks of the industry’s growth are provided in this chapter.

Chapter 11 provides an in-depth analysis of the opportunities and the overall cost savings associated with integration of key tools and technologies, such as artificial intelligence, deep learning, machine learning, and quantum computing with cloud-based solutions for pharmaceutical product development and manufacturing. Further, it provides a detailed analysis on ease of implementation and associated risk in integrating above-mentioned technologies, based on the trends highlighted in published literature and patents.

Chapter 12 is a summary of the overall report, wherein we have mentioned all the key facts and figures described in the previous chapters. The chapter also highlights the evolutionary trends that were identified during the course of the study and are expected to influence the future of this market.

Chapter 13 is a collection of interview transcripts of discussions held with key stakeholders in this industry. In this chapter, we have presented the details of our conversations held with Paolo Colombo (Vice President Growth, InSilicoTrials Technologies) and Velizar Natovski (Regional Manager North and South America, CloudSigma).

Chapter 14 is an appendix, which provides tabulated data and numbers for all the figures provided in the report.

Chapter 15 is an appendix, which contains the list of companies and organizations mentioned in the report.

Table Of Contents

1. PREFACE
1.1. Scope of the Report
1.2. Research Methodology
1.3. Key Questions Answered
1.4. Chapter Outlines

2. EXECUTIVE SUMMARY

3. INTRODUCTION 
3.1. Chapter Overview
3.2. Overview of Cloud Computing
3.2.1. Types of Clouds and Cloud Services
3.2.2. Cloud Computing in Drug Discovery, Development and Manufacturing
3.2.3. Benefits and Limitations of Cloud Computing 
3.3. Concluding Remarks

4. MARKET LANDSCAPE 
4.1. Chapter Overview

4.2. Cloud-based Solutions for Drug Discovery, Development and Manufacturing: Developer Landscape
4.2.1. Analysis by Year of Establishment
4.2.2. Analysis by Company Size
4.2.3. Analysis by Company Type
4.2.4. Analysis by Location of Headquarters
4.2.5. Analysis by Quality Certifications
4.3. Cloud-based Solutions for Drug Discovery, Development and Manufacturing: Market Landscape
4.3.1. Analysis by Type of Cloud
4.3.2. Analysis by Type of Service
4.3.3. Analysis by Area of Application 
4.3.4. Analysis by Additional Capabilities
4.3.5. Analysis by Additional Services Offered

4.4. Cloud-based Solutions for Drug Discovery, Development and Manufacturing: COVID-19-related Initiatives
4.5. Cloud-based Solutions for Drug Discovery, Development and Manufacturing: Information on Additional Players

5. KEY INSIGHTS
5.1. Chapter Overview
5.2. Analysis by Type of Service, Area of Application, Company Size and Quality Certifications (4D Bubble Chart)
5.3. Analysis by Type of Service, Area of Application and Type of Cloud (Grid Representation)
5.4. Analysis by Geography and COVID-19-related Initiatives (Waffle Chart)
5.5. Analysis by Geography and Additional Capabilities (Mekko Chart)
5.6. Analysis by Location of Service Providers (World Map Representation)

6. COMPANY COMPETITIVENESS ANALYSIS
6.1. Chapter Overview
6.2. Key Assumptions and Parameters
6.3. Methodology
6.3.1. Company Competitiveness Analysis: Small Companies
6.3.2. Company Competitiveness Analysis: Mid-Sized Companies
6.3.3. Company Competitiveness Analysis: Large Companies
6.4. Benchmarking the Capabilities of Leading Players

7. COMPANY PROFILES
7.1. Chapter Overview
7.2. Accenture
7.2.1. Company Overview
7.2.2. Recent Developments and Future Outlook

7.3. Alibaba Cloud
7.3.1. Company Overview
7.3.2. Recent Developments and Future Outlook

7.4. Amazon Web Services
7.4.1. Company Overview
7.4.2. Recent Developments and Future Outlook

7.5. Google 
7.5.1. Company Overview
7.5.2. Recent Developments and Future Outlook

7.6. IBM
7.6.1. Company Overview
7.6.2. Recent Developments and Future Outlook 

7.7. Nutanix
7.7.1. Company Overview
7.7.2. Recent Developments and Future Outlook 

7.8. XtalPi
7.8.1. Company Overview
7.8.2. Recent Developments and Future Outlook 

8. PARTNERSHIPS AND COLLABORATIONS
8.1. Chapter Overview
8.2. Types of Partnership Models

8.3. Cloud-based Solutions for Drug Discovery, Development and Manufacturing: Partnerships
8.3.1. Analysis by Year of Partnership
8.3.2. Analysis by Type of Partnership
8.3.3. Analysis by Year and Type of Partnership
8.3.4. Analysis by Company Size and Type of Partnership

8.3.5. Analysis by Type of Partner
8.3.5.1. Analysis by Year of Partnership and Type of Partner
8.3.5.2. Analysis by Type of Partnership and Type of Partner
8.3.5.3. Analysis by Company Size and Type of Partner

8.3.6. Analysis by Area of Application 
8.3.6.1. Analysis by Year of Partnership and Area of Application
8.3.6.2. Analysis by Type of Partnership and Area of Application

8.3.7. Most Active Players: Analysis by Number of Partnerships
8.3.8. Regional Analysis
8.3.8.1. Intercontinental and Intracontinental Agreements
8.3.8.2. Local and International Agreements

9. COST SAVING ANALYSIS
9.1. Chapter Overview
9.2. Key Assumptions and Methodology

9.3. Overall Cost Saving Potential of Using Cloud-based Solutions for Drug Discovery, Development and Manufacturing 2021-2030
9.3.1. Likely Cost Savings in Drug Discovery, 2021-2030
9.3.2. Likely Cost Savings in Drug Development, 2021-2030
9.3.3. Likely Cost Savings in Drug Manufacturing, 2021-2030

9.4. Overall Cost Saving Potential of Using Cloud-based Solutions across Different Geographies, 2021 and 2030
9.4.1. Likely Cost Savings in North America, 2021-2030
9.4.2. Likely Cost Savings in Europe, 2021-2030
9.4.3. Likely Cost Savings in Asia, 2021-2030
9.4.4. Likely Cost Savings in Middle East and North Africa, 2021-2030
9.4.5. Likely Cost Savings in Latin America, 2021-2030
9.4.6. Likely Cost Savings in Rest of the World, 2021-2030

9.5. Concluding Remarks: Cost Saving Scenarios

10. MARKET FORECAST
10.1. Chapter Overview
10.2. Forecast Methodology and Key Assumptions
10.3. Global Cloud-based Solutions for Drug Discovery, Development and Manufacturing Market, 2021-2030

10.4. Cloud-based Solutions Market: Distribution by Type of Cloud
10.4.1. Cloud-based Solutions Market for Private Cloud, 2021-2030
10.4.2. Cloud-based Solutions Market for Public Cloud, 2021-2030
10.4.3. Cloud-based Solutions Market for Hybrid Cloud, 2021-2030

10.5. Cloud-based Solutions Market: Distribution by Type of Service
10.5.1. Cloud-based Solutions Market for Infrastructure as a Service (IaaS), 2021-2030
10.5.2. Cloud-based Solutions Market for Platform as a Service (PaaS), 2021-2030
10.5.3. Cloud-based Solutions Market for Software as a Service (SaaS), 2021-2030

10.6. Cloud-based Solutions Market: Distribution by Area of Application
10.6.1. Cloud-based Solutions Market for Drug Discovery, 2021-2030
10.6.2. Cloud-based Solutions Market for Drug Development, 2021-2030
10.6.3. Cloud-based Solutions Market for Drug Manufacturing, 2021-2030

10.7. Cloud-based Solutions Market: Distribution by End-User
10.7.1. Cloud-based Solutions Market for Biotech Vendors, 2021-2030
10.7.2. Cloud-based Solutions Market for Contract Research Organizations, 2021-2030
10.7.3. Cloud-based Solutions Market for Pharmaceutical Companies, 2021-2030
10.7.4. Cloud-based Solutions Market for Others, 2021-2030

10.8. Cloud-based Solutions Market: Distribution by Geography
10.8.1. Cloud-based Solutions Market in North America, 2021-2030
10.8.2. Cloud-based Solutions Market in Europe, 2021-2030
10.8.3. Cloud-based Solutions Market in Asia-Pacific, 2021-2030
10.8.4. Cloud-based Solutions Market in Middle East and North Africa, 2021-2030
10.8.5. Cloud-based Solutions Market in Latin America, 2021-2030
10.8.6. Cloud-based Solutions Market in Rest of the World, 2021-2030

10.9. Cloud-based Solutions Market: Distribution by Area of Application and Geography
10.9.1. Cloud-based Solutions Market for Drug Discovery in North America, 2021-2030
10.9.2. Cloud-based Solutions Market for Drug Discovery in Europe, 2021-2030
10.9.3. Cloud-based Solutions Market for Drug Discovery in Asia-Pacific, 2021-2030
10.9.4. Cloud-based Solutions Market for Drug Discovery in Middle East and North Africa, 2021-2030
10.9.5. Cloud-based Solutions Market for Drug Discovery in Latin America, 2021-2030
10.9.6. Cloud-based Solutions Market for Drug Discovery in Rest of the World, 2021-2030

10.9.7. Cloud-based Solutions Market for Drug Development in North America, 2021-2030
10.9.8. Cloud-based Solutions Market for Drug Development in Europe, 2021-2030
10.9.9. Cloud-based Solutions Market for Drug Development in Asia-Pacific, 2021-2030
10.9.10. Cloud-based Solutions Market for Drug Development in Middle East and North Africa, 2021-2030
10.9.11. Cloud-based Solutions Market for Drug Development in Latin America, 2021-2030
10.9.12. Cloud-based Solutions Market for Drug Development in Rest of the World, 2021-2030

10.9.13. Cloud-based Solutions Market for Drug Manufacturing in North America, 2021-2030
10.9.14. Cloud-based Solutions Market for Drug Manufacturing in Europe, 2021-2030
10.9.15. Cloud-based Solutions Market for Drug Manufacturing in Asia-Pacific, 2021-2030
10.9.16. Cloud-based Solutions Market for Drug Manufacturing in Middle East and North Africa, 2021-2030
10.9.17. Cloud-based Solutions Market for Drug Manufacturing in Latin America, 2021-2030
10.9.18. Cloud-based Solutions Market for Drug Manufacturing in Rest of the World, 2021-2030
10.10. Concluding Remarks

11. ANTICIPATED TECHNOLOGY UPGRADES AFFILIATED OPPORTUNITIES
11.1. Chapter Overview
11.2. Scope and Methodology

11.3. Key Tools and Technologies
11.3.1. Artificial Intelligence
11.3.1.1. Artificial Intelligence in Pharmaceutical Product Development and Manufacturing
11.3.1.2. Likely Cost-Savings by Integrating Artificial Intelligence with Cloud Computing

11.3.2. Deep Learning
11.3.2.1. Deep Learning in Pharmaceutical Product Development and Manufacturing
11.3.2.2. Likely Cost-Savings by Integrating Deep Learning with Cloud Computing

11.3.3. Machine Learning
11.3.3.1. Machine Learning in Pharmaceutical Product Development and Manufacturing
11.3.3.2. Likely Cost-Savings by Integrating Machine Learning with Cloud Computing

11.3.4. Quantum Computing
11.3.4.1. Quantum Computing in Pharmaceutical Product Development and Manufacturing
11.3.4.2. Likely Cost-Savings by Integrating Quantum Computing with Cloud Computing

11.4. Ease of Implementation and Associated Risk Analysis 
11.4.1. Key Assumptions and Methodology
11.4.2. Results and Discussion 

12. CONCLUSION
12.1. Chapter Overview
12.2. Key Takeaways

13. EXECUTIVE INSIGHTS
13.1. Chapter Overview
13.2. CloudSigma
13.2.1. Company Snapshot
13.2.2. Interview Transcript: Velizar Natovski, Regional Manager North and South America
13.3. InSilicoTrials
13.3.1. Company Snapshot
13.3.2. Interview Transcript: Paolo Colombo, Vice President Growth

14. APPENDIX I: TABULATED DATA

15. APPENDIX II: LIST OF COMPANIES AND ORGANIZATION

List Of Figures

Figure 3.1 Components of Cloud Computing
Figure 3.2 Applications of Cloud Computing
Figure 3.3 Key Benefits and Limitations of Cloud Computing
Figure 4.1 Cloud-based Solution Providers: Distribution by Year of Establishment
Figure 4.2 Cloud-based Solution Providers: Distribution by Company Size
Figure 4.3 Cloud-based Solution Providers: Distribution by Type of Company
Figure 4.4 Cloud-based Solution Providers: Distribution by Location of Headquarters
Figure 4.5 Cloud-based Solutions: Distribution by Quality Certifications
Figure 4.6 Cloud-based Solutions: Distribution by Type of Cloud
Figure 4.7 Cloud-based Solutions: Distribution by Type of Service
Figure 4.8 Cloud-based Solutions: Distribution by Area of Application
Figure 4.9 Cloud-based Solutions: Distribution by Additional Capabilities
Figure 4.10 Cloud-based Solutions: Distribution by Additional Services Offered
Figure 5.1 4D Bubble Chart Representation: Distribution by Type of Service, Area of Application, Company Size and Quality Certifications
Figure 5.2 Grid Representation: Distribution by Type of Service, Area of Application and Type of Cloud
Figure 5.3 Waffle Chart Representation: Distribution by Geography and COVID-19-related Initiatives
Figure 5.4 Mekko Chart Representation: Distribution by Geography and Additional Capabilities
Figure 5.5 World Map Representation: Distribution by Location of Service Providers
Figure 6.1 Company Competitiveness Analysis: Small Companies
Figure 6.2 Company Competitiveness Analysis: Mid-Sized Companies
Figure 6.3 Company Competitiveness Analysis: Large Companies
Figure 6.4 Leading Cloud-based Solution Providers for Drug Discovery, Development and Manufacturing
Figure 8.1 Partnerships and Collaborations: Cumulative Year-Wise Trend, 2015-2020
Figure 8.2 Partnerships and Collaborations: Distribution by Type of Partnership
Figure 8.3 Partnerships and Collaborations: Year-Wise Distribution by Type of Partnership
Figure 8.4 Partnerships and Collaborations: Distribution by Company Size and Type of Partnership
Figure 8.5 Partnerships and Collaborations: Distribution by Type of Partner
Figure 8.6 Partnerships and Collaborations: Year-Wise Distribution by Type of Partner
Figure 8.7 Partnerships and Collaborations: Distribution by Type of Partnership and Type of Partner
Figure 8.8 Partnerships and Collaborations: Distribution by Company Size and Type of Partner
Figure 8.9 Partnerships and Collaborations: Distribution by Area of Application
Figure 8.10 Partnerships and Collaborations: Year-Wise Distribution by Area of Application
Figure 8.11 Partnerships and Collaborations: Distribution by Type of Partnership and Area of Application
Figure 8.12 Most Active Players: Distribution by Number of Partnerships
Figure 8.13 Partnerships and Collaborations: Regional Distribution
Figure 8.14 Partnerships and Collaborations: Country-Wise Distribution
Figure 8.15 Partnerships and Collaborations: Intercontinental and Intracontinental Agreements
Figure 9.1 Overall Cost Saving Potential of Using Cloud-based Solutions for DrugDiscovery, Development and Manufacturing, 2021-2030 (USD Million)
Figure 9.2 Likely Cost Savings associated with the Use of Cloud-based Solutions for DrugDiscovery, 2021-2030 (USD Million)
Figure 9.3 Likely Cost Savings associated with the Use of Cloud-based Solutions for DrugDevelopment, 2021-2030 (USD Million)
Figure 9.4 Likely Cost Savings associated with the Use of Cloud-based Solutions for DrugManufacturing, 2021-2030 (USD Million)
Figure 9.5 Overall Cost Saving Potential of Using Cloud-based Solutions across DifferentGeographies, 2021 and 2030
Figure 9.6 Likely Cost Savings associated with the Use of Cloud-based Solutions in NorthAmerica, 2021-2030 (USD Million)
Figure 9.7 Likely Cost Savings associated with the Use of Cloud-based Solutions inEurope, 2021-2030 (USD Million)
Figure 9.8 Likely Cost Savings associated with the Use of Cloud-based Solutions in Asia,2021-2030 (USD Million)
Figure 9.9 Likely Cost Savings associated with the Use of Cloud-based Solutions in MiddleEast and North Africa, 2021-2030 (USD Million)
Figure 9.10 Likely Cost Savings associated with the Use of Cloud-based Solutions in LatinAmerica, 2021-2030 (USD Million)
Figure 9.11 Likely Cost Savings associated with the Use of Cloud-based Solutions in Rest ofthe World, 2021-2030 (USD Million)
Figure 9.12 Likely Cost Savings associated with the Use of Cloud-based Solutions in Drug Discovery, Development and Manufacturing, 2021, 2025 and 2030: Conservative, Base and Optimistic Scenarios (USD Billion)
Figure 10.1 Global Cloud-based Solutions for Drug Discovery, Development and Manufacturing Market, 2021-2030: Conservative, Base and Optimistic Scenarios (USD Billion)
Figure 10.2 Cloud-based Solutions Market: Distribution by Type of Cloud, 2021 and 2030
Figure 10.3 Cloud-based Solutions Market for Private Cloud, 2021-2030 (USD Million)
Figure 10.4 Cloud-based Solutions Market for Public Cloud, 2021-2030 (USD Million)
Figure 10.5 Cloud-based Solutions Market for Hybrid Cloud, 2021-2030 (USD Million)
Figure 10.6 Cloud-based Solutions Market: Distribution by Type of Service, 2021 and 2030
Figure 10.7 Cloud-based Solutions Market for Infrastructure as a Service (IaaS), 2021-2030 (USD Million)
Figure 10.8 Cloud-based Solutions Market for Platform as a Service (PaaS), 2021-2030 (USD Million)
Figure 10.9 Cloud-based Solutions Market for Software as a Service (SaaS), 2021-2030 (USD Million)
Figure 10.10 Cloud-based Solutions Market: Distribution by Area of Application, 2021 and 2030
Figure 10.11 Cloud-based Solutions Market for Drug Discovery, 2021-2030 (USD Million)
Figure 10.12 Cloud-based Solutions Market for Drug Development, 2021-2030 (USD Million)
Figure 10.13 Cloud-based Solutions Market for Drug Manufacturing, 2021-2030 (USD Million)
Figure 10.14 Cloud-based Solutions Market: Distribution by End-User, 2021 and 2030
Figure 10.15 Cloud-based Solutions Market for Biotech Vendors, 2021-2030 (USD Million)
Figure 10.16 Cloud-based Solutions Market for Contract Research Organizations, 2021-2030 (USD Million)
Figure 10.17 Cloud-based Solutions Market for Pharmaceutical Companies, 2021-2030 (USD Million)
Figure 10.18 Cloud-based Solutions Market for Others, 2021-2030 (USD Million)
Figure 10.19 Cloud-based Solutions Market: Distribution by Geography, 2021 and 2030
Figure 10.20 Cloud-based Solutions Market in North America, 2021-2030 (USD Million)
Figure 10.21 Cloud-based Solutions Market in Europe, 2021-2030 (USD Million)
Figure 10.22 Cloud-based Solutions Market in Asia, 2021-2030 (USD Million)
Figure 10.23 Cloud-based Solutions Market in Middle East and North Africa, 2021-2030 (USD Million)
Figure 10.24 Cloud-based Solutions Market in Latin America, 2021-2030 (USD Million)
Figure 10.25 Cloud-based Solutions Market in Rest of the World, 2021-2030 (USD Million)
Figure 10.26 Cloud-based Solutions Market: Distribution by Area of Application and Geography
Figure 10.27 Cloud-based Solutions Market for Drug Discovery in North America, 2021-2030 (USD Million)
Figure 10.28 Cloud-based Solutions Market for Drug Discovery in Europe, 2021-2030 (USD Million)
Figure 10.29 Cloud-based Solutions Market for Drug Discovery in Asia, 2021-2030 (USD Million)
Figure 10.30 Cloud-based Solutions Market for Drug Discovery in Middle East and North Africa, 2021-2030 (USD Million)
Figure 10.31 Cloud-based Solutions Market for Drug Discovery in Latin America, 2021-2030 (USD Million)
Figure 10.32 Cloud-based Solutions Market for Drug Discovery in Rest of the World, 2021-2030 (USD Million)
Figure 10.33 Cloud-based Solutions Market for Drug Development in North America, 2021-2030 (USD Million)
Figure 10.34 Cloud-based Solutions Market for Drug Development in Europe, 2021-2030 (USD Million)
Figure 10.35 Cloud-based Solutions Market for Drug Development in Asia, 2021-2030 (USD Million)
Figure 10.36 Cloud-based Solutions Market for Drug Development in Middle East and North Africa, 2021-2030 (USD Million)
Figure 10.37 Cloud-based Solutions Market for Drug Development in Latin America, 2021-2030 (USD Million)
Figure 10.38 Cloud-based Solutions Market for Drug Development in Rest of the World, 2021-2030 (USD Million)
Figure 10.39 Cloud-based Solutions Market for Drug Manufacturing in North America, 2021-2030 (USD Million)
Figure 10.40 Cloud-based Solutions Market for Drug Manufacturing in Europe, 2021-2030 (USD Million)
Figure 10.41 Cloud-based Solutions Market for Drug Manufacturing in Asia, 2021-2030 (USD Million)
Figure 10.42 Cloud-based Solutions Market for Drug Manufacturing in Middle East and North Africa, 2021-2030 (USD Million)
Figure 10.43 Cloud-based Solutions Market for Drug Manufacturing in Latin America, 2021-2030 (USD Million)
Figure 10.44 Cloud-based Solutions Market for Drug Manufacturing in Rest of theWorld, 2021-2030 (USD Million)
Figure 10.45 Global Cloud-based Solutions for Drug Discovery, Development, andManufacturing Market, 2021, 2025 and 2030: Conservative, Base and Optimistic Scenarios (USD Billion)
Figure 11.1 Likely Cost Savings in Drug Discovery, Development, andManufacturing by Integrating Artificial Intelligence with Cloud Computing
Figure 11.2 Likely Cost Savings in Drug Discovery, Development, andManufacturing by Integrating Deep Learning with Cloud Computing
Figure 11.3 Likely Cost Savings in Drug Discovery, Development, andManufacturing by Integrating Machine Learning with Cloud Computing
Figure 11.4 Likely Cost Savings in Drug Discovery, Development, andManufacturing by Integrating Quantum Computing with Cloud Computing
Figure 11.5 Trends in Intellectual Property related to Integration of Key Tools andTechnologies with Cloud Computing for Drug Discovery, Development, and Manufacturing
Figure 11.6 Ease of Implementation and Associated Risk Analysis for Integration of KeyTools and Technologies with Cloud Computing for Drug Discovery, Development and Manufacturing
Figure 12.1 Concluding Remarks: Current Market Landscape
Figure 12.2 Concluding Remarks: Partnerships and Collaborations
Figure 12.3 Concluding Remarks: Cost Saving Analysis
Figure 12.4 Concluding Remarks: Market Forecast

List Of Tables

Table 4.1 Cloud-based Solution Providers: Information on Year of Establishment, Company Size, Company Type and Location of Headquarters
Table 4.2 Cloud-based Solution Providers: Information on Quality Certifications
Table 4.3 Cloud-based Solutions: Information on Type of Cloud and Type of Service
Table 4.4 Cloud-based Solutions: Information on Area of Application
Table 4.5 Cloud-based Solutions: Information on Additional Capabilities
Table 4.6 Cloud-based Solutions: Information on Additional Services Offered and COVID-19 Initiatives
Table 7.1 Cloud-based Solution Providers: List of Companies Profiled
Table 7.2 Accenture: Company Snapshot
Table 7.3 Accenture: Recent Developments and Future Outlook
Table 7.4 Alibaba Cloud: Company Snapshot
Table 7.5 Alibaba Cloud: Recent Developments and Future Outlook
Table 7.6 Amazon Web Services: Company Snapshot
Table 7.7 Amazon Web Services: Recent Developments and Future Outlook
Table 7.8 Google: Company Snapshot
Table 7.9 Google: Recent Developments and Future Outlook
Table 7.10 IBM: Company Snapshot
Table 7.11 IBM: Recent Developments and Future Outlook
Table 7.12 Nutanix: Company Snapshot
Table 7.13 Nutanix: Recent Developments and Future Outlook
Table 7.14 XtalPi: Company Snapshot
Table 7.15 XtalPi: Recent Developments and Future Outlook
Table 8.1 Cloud-based Solutions: List of Collaborations, 2015-2020
Table 8.2 Cloud-based Solutions: Partnerships and Collaborations, Information on Type of Partner and Type of Agreement, 2015-2020
Table 13.1 CloudSigma: Company Snapshot
Table 13.2 InSilicoTrials Technologies: Company Snapshot
Table 14.1 Cloud-based Solution Providers: Distribution by Year of Establishment
Table 14.2 Cloud-based Solution Providers: Distribution by Company Size
Table 14.3 Cloud-based Solution Providers: Distribution by Type of Company
Table 14.4 Cloud-based Solution Providers: Distribution by Location of Headquarters
Table 14.5 Cloud-based Solutions: Distribution by Quality Certifications
Table 14.6 Cloud-based Solutions: Distribution by Type of Cloud
Table 14.7 Cloud-based Solutions: Distribution by Type of Service
Table 14.8 Cloud-based Solutions: Distribution by Area of Application
Table 14.9 Cloud-based Solutions: Distribution by Additional Capabilities
Table 14.10 Cloud-based Solutions: Distribution by Additional Services Offered
Table 14.11 Distribution by Type of Service, Area of Application, Company Size and Quality Certifications (4D Bubble Chart)
Table 14.12 Distribution by Type of Service, Area of Application and Type of Cloud (Grid Representation)
Table 14.13 Distribution by Geography and COVID-19-related Initiatives (Waffle Chart)
Table 14.14 Distribution by Geography and Additional Capabilities (Mekko Chart)
Table 14.15 Distribution by Location of Service Providers (World Map Representation)
Table 14.16 Partnerships and Collaborations: Cumulative Year-Wise Trend, 2015-2020
Table 14.17 Partnerships and Collaborations: Distribution by Type of Partnership
Table 14.18 Partnerships and Collaborations: Year-Wise Trend by Type of Partnership
Table 14.19 Partnerships and Collaborations: Distribution by Company Size and Type of Partnership
Table 14.20 Partnerships and Collaborations: Distribution by Type of Partner
Table 14.21 Partnerships and Collaborations: Year-Wise Trend by Type of Partner
Table 14.22 Partnerships and Collaborations: Distribution by Type of Partnership and Type of Partner
Table 14.23 Partnerships and Collaborations: Distribution by Company Size and Type of Partner
Table 14.24 Partnerships and Collaborations: Distribution by Area of Application
Table 14.25 Partnerships and Collaborations: Year-Wise Trend by Area of Application
Table 14.26 Partnerships and Collaborations: Distribution by Type of Partnership and Area of Application
Table 14.27 Most Active Players: Distribution by Number of Partnerships
Table 14.28 Partnerships and Collaborations: Regional Distribution
Table 14.29 Partnerships and Collaborations: Country-Wise Distribution
Table 14.30 Partnerships and Collaborations: Intercontinental and Intracontinental Agreements
Table 14.31 Overall Cost Saving Potential of Using Cloud-based Solutions for DrugDiscovery, Development and Manufacturing 2021-2030 (USD Million)
Table 14.32 Likely Cost Savings associated with the Use of Cloud-based Solutions for DrugDiscovery, 2021-2030 (USD Million)
Table 14.33 Likely Cost Savings associated with the Use of Cloud-based Solutions for DrugDevelopment, 2021-2030 (USD Million)
Table 14.34 Likely Cost Savings associated with the Use of Cloud-based Solutions for DrugManufacturing, 2021-2030 (USD Million)
Table 14.35 Overall Cost Saving Potential of Using Cloud-based Solutions across DifferentGeographies, 2021 and 2030
Table 14.36 Likely Cost Savings associated with the Use of Cloud-based Solutions in NorthAmerica, 2021-2030 (USD Million)
Table 14.37 Likely Cost Savings associated with the Use of Cloud-based Solutions inEurope, 2021-2030 (USD Million)
Table 14.38 Likely Cost Savings associated with the Use of Cloud-based Solutions in Asia,2021-2030 (USD Million)
Table 14.39 Likely Cost Savings associated with the Use of Cloud-based Solutions in MiddleEast and North Africa, 2021-2030 (USD Million)
Table 14.40 Likely Cost Savings associated with the Use of Cloud-based Solutions in LatinAmerica, 2021-2030 (USD Million)
Table 14.41 Likely Cost Savings associated with the Use of Cloud-based Solutions in Rest ofthe World, 2021-2030 (USD Million)
Table 14.42 Likely Cost Savings associated with the Use of Cloud-based Solutions in Drug Discovery, Development and Manufacturing, 2021, 2025 and 2030: Conservative, Base and Optimistic Scenarios (USD Billion)
Table 14.43 Global Cloud-based Solutions for Drug Discovery, Development and Manufacturing Services Market, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Billion)
Table 14.44 Cloud-based Solutions Market: Distribution by Type of Cloud, 2021 and 2030
Table 14.45 Cloud-based Solutions Market for Private Cloud, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.46 Cloud-based Solutions Market for Public Cloud, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.47 Cloud-based Solutions Market for Hybrid Cloud, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.48 Cloud-based Solutions Market: Distribution by Type of Service, 2021 and 2030
Table 14.49 Cloud-based Solutions Market for Infrastructure as a Service (IaaS), 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.50 Cloud-based Solutions Market for Platform as a Service (PaaS), 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.51 Cloud-based Solutions Market for Software as a Service (SaaS), 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.52 Cloud-based Solutions Market: Distribution by Area of Application, 2021 and 2030
Table 14.53 Cloud-based Solutions Market for Drug Discovery, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.54 Cloud-based Solutions Market for Drug Development, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.55 Cloud-based Solutions Market for Drug Manufacturing, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.56 Cloud-based Solutions Market: Distribution by End-User, 2021 and 2030
Table 14.57 Cloud-based Solutions Market for Biotech Vendors, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.58 Cloud-based Solutions Market for Contract Research Organizations, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.59 Cloud-based Solutions Market for Pharmaceutical Companies, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.60 Cloud-based Solutions Market for Others, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.61 Cloud-based Solutions Market: Distribution by Geography, 2021 and 2030
Table 14.62 Cloud-based Solutions Market in North America, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.63 Cloud-based Solutions Market in Europe, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.64 Cloud-based Solutions Market in Asia, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.65 Cloud-based Solutions Market in Middle East and North Africa, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.66 Cloud-based Solutions Market in Latin America, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.67 Cloud-based Solutions Market in Rest of the World, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.68 Cloud-based Solutions Market: Distribution by Area of Application and Geography
Table 14.69 Cloud-based Solutions Market for Drug Discovery in North America, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.70 Cloud-based Solutions Market for Drug Discovery in Europe, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.71 Cloud-based Solutions Market for Drug Discovery in Asia, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.72 Cloud-based Solutions Market for Drug Discovery in Middle East and North Africa, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.73 Cloud-based Solutions Market for Drug Discovery in Latin America, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.74 Cloud-based Solutions Market for Drug Discovery in Rest of the World, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.75 Cloud-based Solutions Market for Drug Development in North America, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.76 Cloud-based Solutions Market for Drug Development in Europe, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.77 Cloud-based Solutions Market for Drug Development in Asia, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.78 Cloud-based Solutions Market for Drug Development in Middle East and North Africa, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.79 Cloud-based Solutions Market for Drug Development in Latin America, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.80 Cloud-based Solutions Market for Drug Development in Rest of the World, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.81 Cloud-based Solutions Market for Drug Manufacturing in North America, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.82 Cloud-based Solutions Market for Drug Manufacturing in Europe, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.83 Cloud-based Solutions Market for Drug Manufacturing in Asia, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.84 Cloud-based Solutions Market for Drug Manufacturing in Middle East and North Africa, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.85 Cloud-based Solutions Market for Drug Manufacturing in Latin America, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.86 Cloud-based Solutions Market for Drug Manufacturing in Rest of theWorld, 2021-2030, Conservative, Base and Optimistic Scenarios (USD Million)
Table 14.87 Global Cloud-based Solutions for Drug Discovery, Development andManufacturing Services Market, 2021, 2025 and 2030, Conservative, Base and Optimistic Scenarios (USD Billion)
Table 14.88 Likely Cost Savings in Drug Discovery, Development andManufacturing by Integrating Artificial Intelligence with Cloud Computing
Table 14.89 Likely Cost Savings in Drug Discovery, Development andManufacturing by Integrating Deep Learning with Cloud Computing
Table 14.90 Likely Cost Savings in Drug Discovery, Development andManufacturing by Integrating Machine Learning with Cloud Computing
Table 14.91 Likely Cost Savings in Drug Discovery, Development andManufacturing by Integrating Quantum Computing with Cloud Computing
Table 14.92 Trends in Intellectual Property related to Integration of Key Tools andTechnologies with Cloud Computing for Drug Discovery, Development and Manufacturing
Table 14.93 Ease of Implementation and Associated Risk Analysis for Integration of Key Tools and Technologies with Cloud Computing for Drug Discovery, Development and Manufacturing

List Of Companies

The following companies and organizations have been mentioned in the report.

  1. 5Y Capital
  2. A4A ARLENE FOR ALZHEIMER'S 
  3. Accelagen
  4. Accenture
  5. Acelot
  6. Albany Molecular Research
  7. Alibaba Group
  8. Alnylam Pharmaceuticals
  9. Amazon Web Services
  10. Apriorit 
  11. ArisGlobal
  12. Arithmos 
  13. Arocom IT Solutions 
  14. Asklepion Pharmaceuticals
  15. Axcella Health
  16. Axsome Therapeutics
  17. Bayer Pharmaceuticals
  18. Beacon Targeted Therapies
  19. Beaconcure
  20. Beijing Institute of Genomics
  21. Benchling
  22. BioAscent
  23. Bioclinica
  24. BioTel Research
  25. BioXcel
  26. Box 
  27. C4X Discovery
  28. CANbridge Pharmaceuticals
  29. Cancer Research UK
  30. Captario
  31. Carolinas IT
  32. Catalyst UX 
  33. Celltrion
  34. Centrexion Therapeutics
  35. ChemAxon
  36. China Life Healthcare Fund
  37. Cisco Systems
  38. Citeline
  39. Clarivate Analytics
  40. ClinStatDevice
  41. Cloud Pharmaceuticals
  42. CloudEndure
  43. Cloudera
  44. CloudSigma
  45. Cloudways
  46. Collaborative Drug Discovery 
  47. Collective Scientific
  48. Cyclica
  49. Dassault Systèmes
  50. Databricks
  51. DataRow 
  52. DC Health
  53. Debiopharm 
  54. DeepCure
  55. DigitalOcean
  56. dinCloud
  57. DM Systems 
  58. Dotmatics
  59. DXC Technology
  60. ELEKS
  61. Eli Lilly
  62. Elligo Health Research
  63. Elucidata
  64. Envisagenics 
  65. Equinix
  66. Euretos
  67. Excelra
  68. Exponential-e
  69. FinTech Academy
  70. Fitbit
  71. Fosun Pharma
  72. Fraunhofer-Chalmers Research Centre for Industrial Mathematics
  73. German Cancer Research Center (DKFZ)
  74. GlaxoSmithKline
  75. Google
  76. Graphene Services 
  77. Hewlett Packard Enterprise
  78. Huawei
  79. IBM
  80. IDsManager 
  81. Infoblox
  82. Informatica
  83. Infosys
  84. Infovity
  85. Innovenn
  86. InSilicoTrials
  87. Instana
  88. Iperion Life Sciences
  89. Ipsen
  90. IQVIA
  91. Johnson & Johnson
  92. J-STAR Research 
  93. Kametera
  94. Lab Asset Manager
  95. LEO Pharma
  96. LEXMA Technology
  97. Limestone
  98. Linode
  99. Liquid Web
  100. Looker Data Sciences
  101. LumaCyte
  102. Lundbeck
  103. MassiveGrid
  104. Melbourne Biomedical Precinct
  105. Microsoft
  106. Mind the Byte
  107. Mistral Venture Partners
  108. Moderna
  109. National Institutes of Health
  110. NextDocs 
  111. Nimbix
  112. NNIT Group
  113. NNIT GROUP Johns Hopkins University
  114. Nord cloud 
  115. Novartis
  116. Nutanix
  117. Onix
  118. OpenEye Scientific
  119. OpenNebula Systems
  120. Oracle
  121. Parexel International 
  122. Peachtree BioResearch Solutions
  123. PerkinElmer
  124. Pfizer
  125. Pharma IT
  126. PhoreMost
  127. PICC Capital Investment Management
  128. Pivot Park Screening Centre 
  129. Pivotal
  130. Porton Pharma Solutions
  131. Prognos Health
  132. Pronutria Biosciences 
  133. QMENTA 
  134. Rackspace
  135. Red Dwarf 
  136. Red Hat 
  137. RedHill Biopharma
  138. Regeneron Pharmaceuticals
  139. Rescale
  140. Reverie Labs
  141. Rishabh Software
  142. RMON Networks
  143. Roche
  144. RockStep Solutions
  145. Saama Technologies
  146. Sanofi
  147. SAP
  148. SAS 
  149. ScaleMatrix
  150. SciCord
  151. Selcia
  152. Server Today
  153. Serverspace
  154. ServiceNow
  155. Servier
  156. Signiant
  157. SiteGround
  158. Skyland Analytics
  159. SoftBank
  160. Software Builder
  161. Soterius
  162. Strateos
  163. Sumitomo Dainippon Pharma
  164. SureClinical
  165. Synthace
  166. Takeda Pharmaceutical
  167. Tata Consultancy Services
  168. Tencent Cloud
  169. Teva Pharmaceuticals
  170. Valo Health
  171. VCA-Plus
  172. Veeva Systems
  173. VERSE Solutions
  174. Vium
  175. VmWare
  176. Vultr
  177. Wipro
  178. WP Engine
  179. WuXi AppTec
  180. XenoGesis 
  181. XtalPi
  182. YASH Technologies
  183. YPrime
  184. ZNet Technologies

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