Market Overview

Computer-Aided Drug Discovery Services Market, 2018-2030 - Owing to Potential Cost and Time Benefits, Outsourcing of Drug Discovery Operations is Expected to Increase in the Future

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Computer-Aided Drug Discovery Services Market, 2018-2030 - Owing to Potential Cost and Time Benefits, Outsourcing of Drug Discovery Operations is Expected to Increase in the Future

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DUBLIN, Aug 13, 2018 /PRNewswire/ --

The "Computer-Aided Drug Discovery Services Market, 2018-2030" report has been added to ResearchAndMarkets.com's offering.

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The Computer-Aided Drug Discovery Services Market, 2018-2030' report features an extensive study on the current landscape and the likely future potential of the players providing CADD services for drug discovery. The study provides an in-depth analysis, highlighting the capabilities of a diverse set of companies that offer such services across different stages of drug discovery, such as target identification, target validation, hit generation, hit-to-lead and lead optimization.

The early stages of research related to drug discovery, including the identification of a relevant biological target and a viable lead compound, play a crucial role in the overall success of a drug candidate in preclinical and clinical studies. It is also worth noting that the process of drug discovery is extremely demanding, both in terms of capital requirements and time. Moreover, there is always a high risk of failure associated with R&D programs and, considering the increasing regulatory stringency, the approval of new drugs has become significantly more difficult.

Given the increase in complexity of the drug discovery process, the overall R&D spending in the pharmaceutical/biotechnology sector has grown from around USD 128 billion in 2008 to USD 158 billion in 2017. As a result, the industry is currently under tremendous pressure not only to meet the expectations of a growing patient population, but also to identify ways to mitigate the risks associated with novel drug discovery programs to avoid failure.

Over the years, various computational tools and services have emerged, enabling the selection, modeling, analysis and optimization of potential lead candidates. The predictive power of computer-aided drug discovery (CADD) has proven to be extremely advantageous, allowing researchers to bypass the random screening of billions of molecules across hundreds of biological targets. As a result, players offering novel in silico drug discovery services, such as CADD, have now become an integral part of the pharmaceutical industry. According to industry experts, almost 30% of the total cost and time invested in developing a new drug can be saved by utilizing such services. Owing to the significant cost benefits offered by such approaches, the adoption of CADD is anticipated to increase in the coming years. Furthermore, the growing number of drug discovery projects, coupled to their rapid progression through various stages of drug discovery, is expected to continue to create an increasing demand for computational services.

One of the key objectives of this report was to evaluate the current opportunity and the future potential of the CADD market over the coming decade. Based on several parameters, we have provided an informed estimate of the likely evolution of this market in the short to mid-term and long term, for the period 2018-2030.


Key Topics Covered:

1. PREFACE
1.1. Scope of the Report
1.2. Research Methodology
1.3. Chapter Outlines

2. EXECUTIVE SUMMARY

3. INTRODUCTION
3.1. Chapter Overview
3.2. Drug Discovery and Development Timeline
3.3. An Overview of CADD
3.3.1. Historical Evolution of CADD in the Drug Discovery Process
3.3.2. Comparison of Traditional Drug Discovery Approaches and CADD
3.3.3. Classification of CADD
3.4. Applications of CADD in the Drug Discovery Process
3.4.1. Target Identification
3.4.1.1. Chemoinformatic Tools
3.4.1.2. Network Based Drug Discovery
3.4.1.3. Computational Platforms and Interaction Repository
3.4.2. Target Validation
3.4.3. Hit Generation
3.4.3.1. High-Throughput Screening
3.4.3.2. Fragment Based Screening
3.4.3.3. Virtual Screening
3.4.4. Hit-to-Lead
3.4.4.1. Pharmacodynamics and Pharmacokinetics Modeling
3.4.4.2. Other Approaches
3.4.5. Lead Optimization
3.4.5.1. Pharmacophore Modeling
3.4.5.2. Docking
3.4.5.3. SAR/QSAR
3.4.5.4. Molecular Modeling
3.5. Advantages of CADD in the Drug Discovery Process
3.6. Challenges Associated with In-House CADD Operations
3.7. Shift in Trend Towards Outsourcing of CADD Operations
3.8. Concluding Remarks

4. MARKET LANDSCAPE
4.1. Chapter Overview
4.2. CADD Service Providers: List of Industry Players
4.2.1. Distribution by Year of Establishment
4.2.2. Distribution by Geographical Location
4.2.3. Distribution by Company Size
4.2.4. Distribution by Type of Business Model
4.2.5. Distribution by Drug Discovery Steps
4.2.6. Distribution by Type of Molecule
4.2.7. Distribution by Type of Clientele
4.2.8. Distribution by Type of CADD Approaches
4.2.9. Distribution by Type of CADD Service Offering
4.2.10. Distribution by Company Size and Location of Headquarters
4.3. CADD: List of CADD Software/Technologies
4.4. CADD: List of Consulting Service Providers

5. COMPANY PROFILES: NORTH AMERICA
5.1. Chapter Overview
5.2. Established Players
5.2.1. Albany Molecular Research (AMRI)
5.2.2. BioDuro
5.2.3. Charles River Laboratories
5.2.4. Schrdinger
5.3. Emerging Players
5.3.1. ChemBio Discovery Solutions
5.3.2. Colorado Computational
5.3.3. Conifer Point Pharmaceuticals
5.3.4. Cyclica
5.3.5. Fractal Therapeutics
5.3.6. Insilico Medicine
5.3.7. Shechter Computational Solutions
5.3.8. Quantitative Medicine
5.3.9. Zorilla Research

6. COMPANY PROFILES: EUROPE
6.1. Chapter Overview
6.2. Established Players
6.2.1. BioNTech
6.2.2. Concept Life Sciences
6.2.3. Evotec
6.2.4. Selvita
6.2.5. Sygnature Discovery
6.3. Emerging Players
6.3.1. BioAscent
6.3.2. candidum
6.3.3. Fidelta (A Subsidiary of Galapagos)
6.3.4. Genomodel
6.3.5. Micar Innovation
6.3.6. Nostrum Biodiscovery
6.3.7. NovaData Solutions
6.3.8. Synsight

7. COMPANY PROFILES: ASIA-PACIFIC
7.1. Chapter Overview
7.2. Established Players
7.2.1. GVK Biosciences
7.2.2. Pharmaron
7.2.3. Sundia MediTech
7.2.4. WuXi AppTec
7.3. Emerging Players
7.3.1. Aaranya Biosciences
7.3.2. Discover Drugs

8. FUNDING AND INVESTMENT ANALYSIS
8.1. Chapter Overview
8.2. Types of Funding
8.3. CADD Service Providers: Funding and Investment Analysis
8.3.1. Analysis by Cumulative Number of Funding Instances
8.3.2. Analysis by Amount Invested
8.3.3. Analysis by Type of Funding
8.3.4. Analysis by Most Active Players
8.3.5. Analysis by Most Active Investors
8.4. Concluding Remarks

9. COMPANY VALUATION ANALYSIS
9.1. Chapter Overview
9.2. Company Valuation Analysis: Methodology
9.3. Company Valuation Analysis: Categorization by Multiple Parameters
9.3.1. Categorization by Employee Count
9.3.2. Categorization by Google Hits
9.3.3. Categorization by Weighted Average Score
9.3.4. Company Valuation: Proprietary Scores

10. SURVEY ANALYSIS
10.1. Chapter Overview
10.2. Overview of Respondents
10.3. Drug Discovery Steps
10.4. Type of Molecules
10.5. CADD Service Portfolio
10.6. Current Market Opportunity
10.7. Likely Growth Rate
10.8. Cost and Time Reduction using CADD

11. COST SAVING ANALYSIS
11.1. Chapter Overview
11.2. Key Assumptions
11.3. Methodology
11.4. Overall Cost Saving by using CADD, 2018-2030
11.5. Concluding Remarks

12. MARKET FORECAST
12.1. Chapter Overview
12.2. Forecast Methodology and Key Assumptions
12.3. Overall CADD Market, 2018-2030
12.4. CADD Market, 2018-2030: Distribution by Regions

13. CADD AND FUTURE TRENDS IN DRUG DISCOVERY
13.1. Chapter Overview
13.2. Owing to Potential Cost and Time Benefits, Outsourcing of Drug Discovery Operations is Expected to Increase in the Future
13.3. Technological Advancements are Likely to Revolutionize the Current Drug Discovery Processes
13.3.1. Integration of Artificial Intelligence in Drug Discovery is Expected to Improve the Overall Efficiency and Productivity
13.3.2. Increased Adoption of Cloud Based Technology Platforms is Expected to Improve the Scalability and Flexibility of Drug Discovery Processes
13.4. Concluding Remarks

14. EXECUTIVE INSIGHTS
14.1. Chapter Overview
14.2. ProSciens
14.2.1. Company Snapshot
14.2.2. Interview Transcript: Edelmiro Moman, Founder and Chief Executive Officer
14.3. Conifer Point Pharmaceuticals
14.3.1. Company Snapshot
14.3.2. Interview Transcript: John L Kulp, Chief Executive Officer and Chief Technical Officer
14.4. Evotec
14.4.1. Company Snapshot
14.4.2. Interview Transcript: Mark Whittaker, Senior Vice President, Drug Discovery
14.5. candidum
14.5.1. Company Snapshot
14.5.2. Interview Transcript: Sven Benson, Founder

15. APPENDIX 1: TABULATED DATA

16. APPENDIX 2: LIST OF COMPANIES AND ORGANIZATIONS

17. APPENDIX 3: NON-COMPUTATIONAL METHODS FOR DRUG DISCOVERY

For more information about this report visit https://www.researchandmarkets.com/research/kp4t9h/computeraided?w=5

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