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.
To order this 290+ page report, which features 120+ figures and 135+ tables, please visit this link
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
For more information, please visit https://www.rootsanalysis.com/reports/view_document/in-silico-drug-discovery/298.html
Table of Contents
- PREFACE
1.1. Scope of the Report
1.2. Research Methodology
1.3. Chapter Outlines
- EXECUTIVE SUMMARY
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- MARKET FORECAST
13.1. Chapter Overview
13.2. Forecast Methodology and Key Assumptions
13.3. Overall In Silico Drug Discovery Services Market for Large Molecules, 2020-2030
13.3.1. In Silico Drug Discovery Services Market for Large Molecules: Distribution by Drug Discovery Steps, 2020-2030
13.3.1.1. In Silico Drug Discovery Services Market for Large Molecules: Share of Target Identification, 2020-2030
13.3.1.2. In Silico Drug Discovery Services Market for Large Molecules: Share of Target Validation, 2020- 2030
13.3.1.3. In Silico Drug Discovery Services Market for Large Molecules: Share of Hit Generation, 2020-2030
13.3.1.4. In Silico Drug Discovery Services Market for Large Molecules: Share of Hit-to-Lead, 2020-2030
13.3.1.5. In Silico Drug Discovery Services Market for Large Molecules: Share of Lead Optimization, 2020-2030
13.3.2. In Silico Drug Discovery Services Market for Large Molecules: Distribution by Type of Large Molecule, 2020-2030
13.3.2.1. In Silico Drug Discovery Services Market for Large Molecules: Share of Antibodies, 2020-2030
13.3.2.2. In Silico Drug Discovery Services Market for Large Molecules: Share of Proteins, 2020-2030
13.3.2.3. In Silico Drug Discovery Services Market for Large Molecules: Share of Peptides, 2020-2030
13.3.2.4. In Silico Drug Discovery Services Market for Large Molecules: Share of Nucleic Acids, 2020- 2030
13.3.2.5. In Silico Drug Discovery Services Market for Large Molecules: Share of Vectors, 2020-2030
13.3.3. In Silico Drug Discovery Services Market for Large Molecules: Distribution by Company Size, 2020-2030
13.3.3.1. In Silico Drug Discovery Services Market for Large Molecules: Share of Small Companies, 2020-2030
13.3.3.2. In Silico Drug Discovery Services Market for Large Molecules: Share of Mid-sized Companies, 2020-2030
13.3.3.3. In Silico Drug Discovery Services Market for Large Molecules: Share of Large Companies, 2020-2030
13.3.4. In Silico Drug Discovery Services Market for Large Molecules: Distribution by Therapeutic Area, 2020-2030
13.3.4.1.In Silico Drug Discovery Services Market for Large Molecules: Share of Autoimmune Disorders, 2020-2030
13.3.4.2. In Silico Drug Discovery Services Market for Large Molecules: Share of Blood Disorders, 2020-2030
13.3.4.3.In Silico Drug Discovery Services Market for Large Molecules: Share of Cardiovascular Disorders, 2020-2030
13.3.4.4.In Silico Drug Discovery Services Market for Large Molecules: Share of Gastrointestinal and Digestive Disorders, 2020-2030
13.3.4.5. In Silico Drug Discovery Services Market for Large Molecules: Share of Hormonal Disorders, 2020-2030
13.3.4.6. In Silico Drug Discovery Services Market for Large Molecules: Share of Human Immunodeficiency Virus (HIV) / Acquired Immunodeficiency Syndrome (AIDS), 2020-2030
13.3.4.7. In Silico Drug Discovery Services Market for Large Molecules: Share of Infectious Diseases, 2020-2030
13.3.4.8. In Silico Drug Discovery Services Market for Large Molecules: Share of Metabolic Disorders, 2020-2030
13.3.4.9.In Silico Drug Discovery Services Market for Large Molecules: Share of Mental Disorders, 2020-2030
13.3.4.10.In Silico Drug Discovery Services Market for Large Molecules: Share of Musculoskeletal Disorders, 2020-2030
13.3.4.11.In Silico Drug Discovery Services Market for Large Molecules: Share of Neurological Disorders, 2020-2030
13.3.4.12.In Silico Drug Discovery Services Market for Large Molecules: Share of Oncological Disorders 2020-2030
13.3.4.13.In Silico Drug Discovery Services Market for Large Molecules: Share of Respiratory Disorders, 2020-2030
13.3.4.13.In Silico Drug Discovery Services Market for Large Molecules: Share of Skin Disorders, 2020-2030
13.3.4.14.In Silico Drug Discovery Services Market for Large Molecules: Share of Urogenital Disorders, 2020-2030
13.3.4.15.In Silico Drug Discovery Services Market for Large Molecules: Share of Others, 2020-2030
13.3.5. In Silico Drug Discovery Services Market for Large Molecules: Distribution by Type of Sponsor, 2020-2030
13.3.5.1.In Silico Drug Discovery Services Market for Large Molecules: Share of Industry Players, 2020-2030
13.3.5.2.In Silico Drug Discovery Services Market for Large Molecules: Share of Non-Industry Players, 2020-2030
13.3.6. In Silico Drug Discovery Services Market for Large Molecules: Distribution by Key Geographical Regions, 2020-2030
13.3.6.1.In Silico Drug Discovery Services Market for Large Molecules: Share of North America, 2020-2030
13.3.6.1.1.In Silico Drug Discovery Services Market for Large Molecules: Share of US, 2020-2030
13.3.6.1.2.In Silico Drug Discovery Services Market for Large Molecules: Share of Canada, 2020-2030
13.3.6.2.In Silico Drug Discovery Services Market for Large Molecules: Share in Europe, 2020-2030
13.3.6.2.1.In Silico Drug Discovery Services Market for Large Molecules: Share in Germany, 2020-2030
13.3.6.2.2.In Silico Drug Discovery Services Market for Large Molecules: Share in France, 2020-2030
13.3.6.2.3.In Silico Drug Discovery Services Market for Large Molecules: Share in the UK, 2020-2030
13.3.6.2.4.In Silico Drug Discovery Services Market for Large Molecules: Share in Italy, 2020-2030
13.3.6.2.5.In Silico Drug Discovery Services Market for Large Molecules: Share in Spain, 2020-2030
13.3.6.2.6.In Silico Drug Discovery Services Market for Large Molecules: Share in Rest of Europe, 2020-2030
13.3.6.3.In Silico Drug Discovery Services Market for Large Molecules: Share in Asia-Pacific and Rest of the World, 2020-2030
13.3.6.3.1.In Silico Drug Discovery Services Market for Large Molecules: Share in China, 2020-2030
13.3.6.3.2.In Silico Drug Discovery Services Market for Large Molecules: Share in India, 2020-2030
13.3.6.3.3.In Silico Drug Discovery Services Market for Large Molecules: Share in Japan, 2020-2030
- IN SILICO TOOLS AND UPCOMING TRENDS IN DRUG DISCOVERY
14.1. Chapter Overview
14.2. Owing to Potential Cost and Time-related Benefits, Outsourcing of Drug Discovery Operations is Expected to Increase in the Future
14.3. Technological Advancements are Likely to Revolutionize the Current Drug Discovery Processes
14.3.1. Integration of Artificial Intelligence in the Drug Discovery Process is Expected to Improve the Overall Efficiency and Productivity
14.3.2. Increased Adoption of Cloud Based Technology Platforms is Anticipated to Enhance the Scalability and Flexibility of the Drug Discovery Process
14.3.3. Rising Interest in Use of Force Fields for In Silico Drug Discovery
14.4. Concluding Remarks
- EXECUTIVE INSIGHTS
15.1. Chapter Overview
15.2. ProSciens
15.2.1. Company Snapshot
15.2.2. Interview Transcript: Edelmiro Moman, Founder and Chief Executive Officer
15.3. Conifer Point Pharmaceuticals
15.3.1. Company Snapshot
15.3.2. Interview Transcript: John L Kulp, Chief Executive Officer and Chief Technical Officer
15.4. Evotec
15.4.1. Company Snapshot
15.4.2. Interview Transcript: Mark Whittaker, Senior Vice President, Drug Discovery
15.5. Candidum
15.5.1. Company Snapshot
15.5.2. Interview Transcript: Sven Benson, Founder
- APPENDIX I: TABULATED DATA
- APPENDIX II: LIST OF COMPANIES AND ORGANIZATIONS
- APPENDIX III: NON-COMPUTATIONAL METHODS FOR DRUG DISCOVERY
Contact Details
Gaurav Chaudhary
+1 (415) 800 3415
The growing pipeline of biologics that can be produced in microbial systems, such as antibody fragments and plasmid-based therapies, is anticipated to offer lucrative opportunities to service providers serving this niche, but growing market segment London Roots Analysis has announced the addition of the “Microbial Contract Biomanufacturing Market, 2020-2030” report to its list of offerings.
Despite mammalian cell cultures being the preferred manufacturing approach for biologics, recent advances in microbial fermentation have enabled the development of versatile biomanufacturing systems, which are both robust and cost friendly.
Presently, a number of service provider companies claim to offer end-to-end solutions, ranging from product development to commercial production, for microbial biologics.
Europe is currently regarded as a key manufacturing hub for microbial biologicsThere are more than 150 manufacturing facilities, with microbial fermentation capabilities, worldwide; of these, 43% are in Europe, followed by North America (31%).
On the other hand, prominent regions in the Asia Pacific and Middle East, where microbial biologics are manufactured, include (in decreasing order of number of resident manufacturing facilities) China, India, Japan, Australia and Israel.
Further, a large number (~25%) of the partnerships were observed to be focused on the production of microbial biologics; this is followed by process development and manufacturing agreements (20%).
Report Keywords - Next Generation, Inhibitors, Stimulators Market, Roots Analysis, Report Therapies targeting novel inhibitory and stimulatory immune checkpoints have been shown to possess substantial therapeutic potential, both as monotherapies and in combination with other interventions, across multiple disease interventions Roots Analysis is pleased to announce the publication of its recent study, titled, “Next Generation Immune Checkpoint Inhibitors and Stimulators Market, 2020-2030.” The report features an extensive study of the current market landscape, offering an informed opinion on the likely adoption of these therapies over the next decade.
It features an in-depth analysis, highlighting the capabilities of various stakeholders engaged in this domain.
In addition to other elements, the study includes:A detailed assessment of the current market landscape of drug developers engaged in the development of next generation immune checkpoint modulators.
A detailed analysis of more than 590 completed, ongoing and planned clinical studies of next generation immune checkpoint inhibitors and stimulators.Detailed profiles of developers of next generation immune checkpoint modulators (shortlisted on the basis of the number of pipeline products).An in-depth analysis of more than 490 grants that have been awarded to research institutes engaged in next generation immune checkpoint therapy-related projects.An analysis of the partnerships that have been established in this domain, in the recent past.A competitiveness analysis of biological targets, featuring insightful pictorial summaries and representations.An analysis of the initiatives of big biopharma players engaged in this domain.A detailed market forecast, featuring analysis of the current and projected future opportunity across key market segments (listed below) To request for sample report – https://www.rootsanalysis.com/reports/303/request-sample.html Target Disease Indication Breast CancerChronic Lymphocytic LeukemiaColorectal CancerHead and Neck CancerLung CancerLupus NephritisMelanomaMultiple MyelomaPrimary Sjögren's SyndromeOthers Target Immune CheckpointB7-H3CD38CD40CD47OthersMechanism of ActionInhibitoryStimulatoryTherapeutic ModalityMonoclonal AntibodySmall MoleculeType of Therapy Monotherapy Combination TherapyRoute of AdministrationIntravenousSubcutaneousOthersKey Geographical Region North AmericaEuropeAsia-Pacific and the Rest of the World Key companies covered in the reportBristol Myers SquibbGlaxoSmithKlineIncyteNovartisTrillium Therapeutics For more information please click on the following link:https://www.rootsanalysis.com/reports/view_document/immune-checkpoint-inhibitors/303.html Other Recent OfferingsNeoantigen Targeted Therapies Market, 2019-2030Bispecific Antibody Therapeutics Market (4th Edition), 2019-2030Global Stem Cells Market: Focus on Clinical Therapies, 2020-2030 About Roots AnalysisRoots Analysis is one of the fastest growing market research companies, sharing fresh and independent perspectives in the bio-pharmaceutical industry.
The in-depth research, analysis and insights are driven by an experienced leadership team which has gained many years of significant experience in this sector.
If you’d like help with your growing business needs, get in touch at [email protected] Contact InformationRoots Analysis Private LimitedGaurav Chaudhary+1 (415) 800 [email protected] - https://www.facebook.com/RootsAnalysisLinkedIn - https://www.linkedin.com/company/roots-analysis/mycompany/Twitter - https://twitter.com/RootsAnalysis
Therefore, the use of technology can save time and money, while providing a far better understanding of the relationships between different formulations and processes parameters.Key Drivers, Restraints, and Opportunities of AI in Pharma and Biotech MarketAdoption of artificial intelligence (AI) in the drug discovery market in developing regions such as APAC is increasing, thanks to the expansion of pharmaceutical industries by collaborating with other industries and rise in demand to reduce drug discovery time.
Furthermore, the expansion of biotechnology industries is estimated to offer significant opportunities for the market.An estimated 50% of U.S. citizens are affected by at least one chronic condition; consequently, the pharmaceutical segment of the healthcare industry is projected to be positively impacted by the expected trend of AI adoption.All top 10 so-called giant pharma companies (namely Novartis, Roche, Pfizer, Merck, AstraZeneca, GlaxoSmithKline, Sanofi, Abbvie, Bristol-Myers Squibb, and Johnson & Johnson) have either expressly collaborated with or acquired AI technologies to take advantage of the opportunities AI brings to the table.
Industry leaders are presently focused on the development of more efficient methods, and machine learning is emerging as a possible solution.The current machine learning initiatives of the top five pharmaceutical and biotechnology companies reveal trends within the following areas:Digital coaching solutions – Utilization of web-based technologies to simulate one-on-one coaching sessions so that all patients can have the benefit of a uniquely devised medication program.For instance: Johnson & Johnson’s Patient Athlete programPersonalized medicine – Personalized medicine, also called precision medicine, maybe a medical model that separates people into different groups—with medical decisions, practices, interventions, and/or products being tailored to the individual patient supported their predicted response or risk of disease.For instance.
Unlike other applications within healthcare facilities, drug discovery seems to own a clearer path to adoption.Recently, robots became more collaborative with humans and are more easily trained by moving them through the desired task.
Over time, it seems likely that an equivalent improvement in intelligence that we have seen in other areas of AI would be incorporated into physical robots.Surgical robots initially approved in the U.S. in 2000, provided ‘superpowers’ to surgeons, improving their ability to examine, create precise and minimally invasive incisions, and stitch wounds.
Common surgical procedures using robotic surgery include gynecologic surgery, prostate surgery, and head and neck surgery.Pre Book Ai In Pharma And Biotech Market Report – https://www.transparencymarketresearch.com/checkout.php?rep_id=79399=S North America to Capture Major Share of Global Market of AI in Pharma & BiotechNorth America is expected to account for a major share of the global market of AI in Pharma and Biotech due to the high prevalence of chronic diseases among the population.
Softcon Systems brings you automation solutions specific to the pharmaceutical industry – we will work with you to develop and implement ideal solutions specific to your requirements.
Automation at every point of the value chain will enable the pharma companies to get pharmaceuticals from the lab to the patient more quickly.We design systems that help pharmaceutical and biotech companies to achieve operational excellence, reduce time to market and meet all industry standards and regulations.
