Roots Analysis has done a detailed study on “In Silico / Computer-Aided Drug Discovery Services Market: Focus on Large Molecules (Antibodies, Proteins, Peptides, Nucleic Acid, Gene Therapy and Vectors), 2020-2030 (Including Structure Based Drug Discovery, Fragment Based Drug Discovery, Ligand Based Drug Discovery, Target Based Drug Discovery / Multi-Target Drug Design, Interface Based Drug Discovery, Approaches)” covering key aspects of the industry’s evolution and identifying potential future growth opportunities.

Key Market Insights
• Over 90 firms are actively involved in providing in silico services for drug discovery of different types of biologics; of these, over 30 players claim to have the capabilities to offer services for all steps of discovery
• Majority of the companies offer structure-based drug design focused on early stage drug discovery of a range of large molecules, including antibodies, proteins and peptides
• Featuring the presence of small-mid sized firms, the in silico service provider landscape is well-distributed across various regions; these players have adopted various business models to cater to the evolving needs of the clients
• Several players involved in this domain are steadily expanding their capabilities in order to enhance their respective in silico-based service portfolios and maintain a competitive edge in this industry
• The integration of novel computational techniques, such as artificial intelligence and cloud-based platforms, with in silico approaches is likely to revolutionize the overall drug discovery process
• Service providers are adopting various business strategies in order to continue providing significant cost saving advantages, along with expediting discovery timelines and improving product success
• Driven by the growing demand for effective therapeutics and increase in drug discovery efforts of various biologics across a wide range of therapeutic areas, the market is expected to witness sustained growth in future
• In the long-term, the projected opportunity is anticipated to be well distributed across various geographies, type of sponsors and sizes of in silico service providers

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Table of Contents

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 Timelines
3.3. Overview of In Silico Drug Discovery Tools
3.3.1. Historical Evolution of the In Silico Approach
3.3.2. Comparison of Traditional Drug Discovery Approaches and In Silico / Computer Aided Methods
3.3.3. In Silico / Computed Aided Approaches for Drug Design and Development
3.4. Applications of In Silico Tools in the Drug Discovery Process
3.4.1. Target Identification
3.4.1.1. Chemoinformatics-based Tools
3.4.1.2. Network-based Drug Discovery
3.4.1.3. Computational Platforms and Interaction Repositories
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 Novel Approaches
3.4.5. Lead Optimization
3.4.5.1. Pharmacophore Modeling
3.4.5.2. Docking
3.4.5.3. Structure Activity Relationships (SAR) / Quantitative Structure Activity Relationship (QSAR)
3.4.5.4. Molecular Modeling
3.5. Advantages of using In Silico Tools for Drug Discovery Operations
3.6. Challenges Associated with Conducting In Silico Drug Discovery Operations In-house
3.7. Anticipated Rise in Outsourcing In Silico Drug Discovery Operations
3.8. Concluding Remarks

4. MARKET LANDSCAPE
4.1. Chapter Overview
4.2. In Silico Drug Discovery Services for Large Molecules: List of Industry Players
4.2.1. Analysis by Year of Establishment
4.2.2. Analysis by Company Size
4.2.3. Analysis by Location of Headquarters
4.2.4. Analysis by Company Size and Location of Headquarters
4.2.5. Analysis by Type of Business Model
4.2.6. Analysis by Drug Discovery Steps
4.2.7. Analysis by Type of Large Molecule
4.2.7.1. Analysis by Type of Antibody
4.2.7.2. Analysis by Type of Protein
4.2.8. Analysis by Type of In Silico Approach Used
4.2.9. Analysis by Types of In Silico Services Offered
4.2.10. Analysis by Type of Clientele
4.3. In Silico Drug Discovery Services: List of Software / Technologies

5. KEY INSIGHTS
5.1. Chapter Overview
5.2. Logo Landscape: Analysis by Company Size and Location of Headquarters
5.3. Tree Map Representation: Analysis by Company Size and Drug Discovery Steps
5.4. World Map Representation: Regional Analysis of Outsourcing Activity
5.5. Grid Representation: Analysis by Type of Large Molecule, In Silico Approach Used and Type of Clientele

6. COMPANY PROFILES
6.1. Chapter Overview
6.2. Key In Silico Service Providers Based in North America
6.2.1. BioDuro
6.2.1.1. Company Overview
6.2.1.2. Funding and Investment Information
6.2.1.3. In Silico-based Service Portfolio
6.2.1.4. Recent Developments and Future Outlook
6.2.1.5. Peer Group Benchmark Comparison
6.2.2. Creative Biostructure
6.2.2.1. Company Overview
6.2.2.2. Funding and Investment Information
6.2.2.3. In Silico-based Service Portfolio
6.2.2.4. Recent Developments and Future Outlook
6.2.2.5. Peer Group Benchmark Comparison
6.2.3. GenScript
6.2.3.1. Company Overview
6.2.3.2. Funding and Investment Information
6.2.3.3. In Silico-based Service Portfolio
6.2.3.4. Recent Developments and Future Outlook
6.2.3.5. Peer Group Benchmark Comparison
6.2.4. LakePharma
6.2.4.1. Company Overview
6.2.4.2. Funding and Investment Information
6.2.4.3. In Silico-based Service Portfolio
6.2.4.4. Recent Developments and Future Outlook
6.2.4.5. Peer Group Benchmark Comparison
6.3. Leading Players Based in Europe
6.3.1. Abzena
6.3.1.1. Company Overview
6.3.1.2. Funding and Investment Information
6.3.1.3. In Silico-based Service Portfolio
6.3.1.4. Recent Developments and Future Outlook
6.3.1.5. Peer Group Benchmark Comparison
6.3.2. BioNTech
6.3.2.1. Company Overview
6.3.2.2. Funding and Investment Information
6.3.2.3. Recent Developments and Future Outlook
6.3.2.4. Peer Group Benchmark Comparison
6.3.3. Sygnature Discovery
6.3.3.1. Company Overview
6.3.3.2. Funding and Investment Information
6.3.3.3. In Silico-based Service Portfolio
6.3.3.4. Recent Developments and Future Outlook
6.3.3.5. Peer Group Benchmark Comparison
6.4. Leading Players Based in Asia-Pacific
6.4.1. ChemPartner
6.4.1.1. Company Overview
6.4.1.2. In Silico-based Service Portfolio
6.4.1.3. Recent Developments and Future Outlook
6.4.1.4. Peer Group Benchmark Comparison
6.4.2. Sundia MediTech
6.4.2.1. Company Overview
6.4.2.2. Funding and Investment Information
6.4.2.3. In Silico-based Service Portfolio
6.4.2.4. Recent Development and Future Outlook
6.4.2.5. Peer Group Benchmark Comparison
6.4.3. Viva Biotech
6.4.3.1. Company Overview
6.4.3.2. Funding and Investment Information
6.4.3.3. In Silico-based Service Portfolio
6.4.3.4. Recent Development and Future Outlook
6.4.3.5. Peer Group Benchmark Comparison

7. COMPANY COMPETITIVENESS ANALYSIS
7.1. Chapter Overview
7.2. Key Parameters
7.3. Methodology
7.4. Company Competitiveness Analysis: In Silico Drug Discovery Service Providers in North America
7.5. Company Competitiveness Analysis: In Silico Drug Discovery Service Providers in Europe
7.6. Company Competitiveness Analysis: In Silico Drug Discovery Service Providers in Asia-Pacific and Rest of the World

8. KEY OPPORTUNITY AREAS
8.1. Chapter Overview
8.2. Key Assumptions and Parameters
8.3. Methodology
8.4. Antibodies
8.4.1. Developer Landscape
8.4.1.1. Number of Pipeline Molecules
8.4.1.2. Affiliated Market Size and Growth Rate
8.4.2. In Silico Service Providers for Antibodies: 3D Bubble Analysis Based on Number of Drug Discovery Steps, Strength of Service Portfolio and Company Size
8.5. Peptides
8.5.1. Developer Landscape
8.5.1.1. Number of Pipeline Molecules
8.5.1.2. Affiliated Market Size and Growth Rate
8.5.2. In Silico Service Providers for Peptides: 3D Bubble Analysis Based on Number of Drug Discovery Steps, Strength of Service Portfolio and Company Size
8.6. Proteins
8.6.1. Developer Landscape
8.6.1.1. Number of Pipeline Molecules
8.6.1.2. Affiliated Market Size and Growth Rate
8.6.2. In Silico Service Providers for Proteins: 3D Bubble Analysis Based on Number of Drug Discovery Steps, Strength of Service Portfolio and Company Size
8.7. Other Advanced Therapies
8.7.1 Developer Landscape
8.7.1.1 Number of Pipeline Molecules
8.7.1.2 Affiliated Market Size and Growth Rate
8.7.2. In Silico Service Providers for Vectors: 3D Bubble Analysis Based on Number of Drug Discovery Steps, Strength of Service Portfolio and Company Size

9. EMERGING BUSINESS MODELS AND STRATEGIES
9.1. Chapter Overview
9.2. Key Assumptions and Methodology
9.3. In Silico Service Providers: Analysis by Number of Large Molecules and Drug Discovery Steps Covered
9.3.1. Strategies for Short Term Success
9.3.2. Strategies for Long Term Success
9.4. Concluding Remarks

10. CASE STUDY: COMPARISON OF DRUG DISCOVERY PROCESSES OF SMALL MOLECULES AND LARGE MOLECULES
10.1. Chapter Overview
10.2. Small Molecule and Large Molecule Drugs / Therapies
10.2.1. Comparison of Key Specifications
10.2.2. Comparison of Manufacturing Processes
10.2.3. Comparison of Drug Discovery Processes
10.3. Approaches to Improve Discovery Process of Large Molecules

11. SURVEY INSIGHTS
11.1. Chapter Overview
11.2. Overview of Respondents
11.2.1. Designation of Respondents
11.3. Survey Insights
11.3.1. Drug Discovery Steps
11.3.2. Type of Molecules Handled
11.3.3. In Silico Drug Design Focused Service Portfolio
11.3.4. Likely Adoption of In Silico Tools for Large Molecules Drug Discovery
11.3.5. Current Market Opportunity
11.3.6. Likely Growth Rate
11.3.7. Cost Saving Potential of the In Silico Approach

12. COST SAVING ANALYSIS
12.1. Chapter Overview
12.2. Key Assumptions
12.3. Methodology
12.4. Overall Cost Saving Potential of In Silico Tools in Large Molecule Drug Discovery, 2020-2030
12.5. Concluding Remarks

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https://www.rootsanalysis.com/reports/view_document/in-silico-drug-discovery/298.html

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