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Global In Silico Clinical Trials Market to reach USD 4.14 billion by 2028.

Global In Silico Clinical Trials Market Size study, by Industry (Medical Devices, Pharmaceutical) by Therapeutic Area (Oncology, Infectious Disease, Hematology, Cardiology, Dermatology, Neurology, Diabetes, Others) by Phase (Phase I, Phase II, Phase III, Phase IV) and Regional Forecasts 2022-2028

Product Code: HLSHS-19140956
Publish Date: 15-05-2022
Page: 200

Global In Silico Clinical Trials Market is valued approximately USD 2.51 billion in 2021 and is anticipated to grow with a healthy growth rate of more than 7.4% over the forecast period 2022-2028. The use of individualized computer simulation in the development or regulatory review of a medicinal product, medical equipment, or medical intervention is referred to as in silico clinical trials. Clinical trials involving animals and humans have a higher risk of negative effects. In silico clinical trials lower the risk of adverse reactions during trials, hence boosting the research study’s safety and efficacy. Furthermore, technical improvements in in silico clinical trials are increasing its market demand. When compared to in silico trials, traditional clinical trials are substantially more expensive. A clinical trial might cost anywhere between USD 4 million and USD 20 million, according to Sofpromed, a clinical research business. As a result, one of the key factors driving the development of computer-based trials is the high cost of traditional clinical trials. Furthermore, in silico trials provide for a better knowledge of a drug’s or device’s safety and efficacy, as well as a reduction in the likelihood of clinical studies being terminated, lowering trial costs. There has been a huge increase in R&D expenditure for drug development in recent years. For example, according to a Congressional Budget Office report (US) on pharmaceutical R&D, the pharmaceutical industry’s R&D spending have climbed from USD 38 billion in 2000 to USD 83 billion in 2019. The increase in R&D spending is expected to have a beneficial effect on market growth. Because of the COVID-19 pandemic, clinical research sites were temporarily shut down, increasing need for in silico clinical trials for research investigations. Clinical research has been disrupted as a result of the COVID-19 epidemic, which has sparked renewed interest in using computer simulations to anticipate clinical trial outcomes. The pandemic had resulted in a worldwide need for medicines and vaccinations. Traditional studies take a long time and cost a lot of money; to solve this problem, researchers used computer simulation trials to validate COVID-19 medicines and vaccines. However, throughout the projected period of 2021-2027, the market’s expansion would be hampered by the high cost of methods and procedures.

The key regions considered for the global In Silico Clinical Trials Market study includes Asia Pacific, North America, Europe, Latin America, and Rest of the World. North America had the highest revenue share. In the United States, a large number of in silico trials are being done. Furthermore, the presence of significant businesses in the region such as GNS Healthcare Inc., Insilico Medicine, Inc., Immunetrics Inc., and others has contributed to regional market growth. Over the projection period, Asia Pacific is expected to be the fastest-growing regional market. The Asia Pacific market is still in its infancy. In silico trials are being used by a number of companies in this region to minimise the overall cost of clinical trials. For example, in November 2021, DSTC, a Japanese preclinical CRO, teamed with InSilicoTrials to use in silico clinical trials to revolutionise the drug development process.

Major market player included in this report are:
Certara, Inc.
Novadiscovery Sas
Insilico Medicine, Inc.
Dassault Systemes SE
GNS Healthcare Inc.
The AnyLogic Company
InSilicoTrials
Immunetrics Inc.
Nuventra Pharma Sciences
Abzena Ltd.

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:
By Industry:
Medical Devices
Pharmaceutical
By Therapeutic Area:
Oncology
Infectious Disease
Hematology
Cardiology
Dermatology
Neurology
Diabetes
Others
By Phase
Phase I
Phase II
Phase III
Phase IV
By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE

Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Rest of the World

Furthermore, years considered for the study are as follows:

Historical year – 2018, 2019, 2020
Base year – 2021
Forecast period – 2022 to 2028

Target Audience of the Global In Silico Clinical Trials Market in Market Study:

Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers
Investors

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2028 (USD Billion)
1.2.1. In Silico Clinical Trials Market, by Region, 2020-2028 (USD Billion)
1.2.2. In Silico Clinical Trials Market, by Industry, 2020-2028 (USD Billion)
1.2.3. In Silico Clinical Trials Market, by Therapeutic Area, 2020-2028 (USD Billion)
1.2.4. In Silico Clinical Trials Market, by Phase, 2020-2028 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global In Silico Clinical Trials Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global In Silico Clinical Trials Market Dynamics
3.1. In Silico Clinical Trials Market Impact Analysis (2020-2028)
3.1.1. Market Drivers
3.1.1.1. Reduction in the chances of adverse reactions during trials
3.1.1.2. High cost associated with traditional clinical trials
3.1.2. Market Challenges
3.1.2.1. High cost of methods and expensive procedures
3.1.3. Market Opportunities
3.1.3.1. Growth in R&D spending
3.1.3.2. Technological advancements in in silico clinical trials
Chapter 4. Global In Silico Clinical Trials Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.1.6. Futuristic Approach to Porter’s 5 Force Model (2018-2028)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
4.5. Top investment opportunity
4.6. Top winning strategies
Chapter 5. Risk Assessment: COVID-19 Impact
5.1.1. Assessment of the overall impact of COVID-19 on the industry
5.1.2. Pre COVID-19 and post COVID-19 Market scenario
Chapter 6. Global In Silico Clinical Trials Market, by Industry
6.1. Market Snapshot
6.2. Global In Silico Clinical Trials Market by Industry, Performance – Potential Analysis
6.3. Global In Silico Clinical Trials Market Estimates & Forecasts by Industry 2018-2028 (USD Billion)
6.4. In Silico Clinical Trials Market, Sub Segment Analysis
6.4.1. Medical Devices
6.4.2. Pharmaceutical
Chapter 7. Global In Silico Clinical Trials Market, by Therapeutic Area
7.1. Market Snapshot
7.2. Global In Silico Clinical Trials Market by Therapeutic Area, Performance – Potential Analysis
7.3. Global In Silico Clinical Trials Market Estimates & Forecasts by Therapeutic Area 2018-2028 (USD Billion)
7.4. In Silico Clinical Trials Market, Sub Segment Analysis
7.4.1. Oncology
7.4.2. Infectious Disease
7.4.3. Hematology
7.4.4. Cardiology
7.4.5. Dermatology
7.4.6. Neurology
7.4.7. Diabetes
7.4.8. Others
Chapter 8. Global In Silico Clinical Trials Market, by Phase
8.1. Market Snapshot
8.2. Global In Silico Clinical Trials Market by Phase, Performance – Potential Analysis
8.3. Global In Silico Clinical Trials Market Estimates & Forecasts by Phase 2018-2028 (USD Billion)
8.4. In Silico Clinical Trials Market, Sub Segment Analysis
8.4.1. Phase I
8.4.2. Phase II
8.4.3. Phase III
8.4.4. Phase IV
Chapter 9. Global In Silico Clinical Trials Market, Regional Analysis
9.1. In Silico Clinical Trials Market, Regional Market Snapshot
9.2. North America In Silico Clinical Trials Market
9.2.1. U.S. In Silico Clinical Trials Market
9.2.1.1. Industry breakdown estimates & forecasts, 2018-2028
9.2.1.2. Therapeutic Area breakdown estimates & forecasts, 2018-2028
9.2.1.3. Phase breakdown estimates & forecasts, 2018-2028
9.2.2. Canada In Silico Clinical Trials Market
9.3. Europe In Silico Clinical Trials Market Snapshot
9.3.1. U.K. In Silico Clinical Trials Market
9.3.2. Germany In Silico Clinical Trials Market
9.3.3. France In Silico Clinical Trials Market
9.3.4. Spain In Silico Clinical Trials Market
9.3.5. Italy In Silico Clinical Trials Market
9.3.6. Rest of Europe In Silico Clinical Trials Market
9.4. Asia-Pacific In Silico Clinical Trials Market Snapshot
9.4.1. China In Silico Clinical Trials Market
9.4.2. India In Silico Clinical Trials Market
9.4.3. Japan In Silico Clinical Trials Market
9.4.4. Australia In Silico Clinical Trials Market
9.4.5. South Korea In Silico Clinical Trials Market
9.4.6. Rest of Asia Pacific In Silico Clinical Trials Market
9.5. Latin America In Silico Clinical Trials Market Snapshot
9.5.1. Brazil In Silico Clinical Trials Market
9.5.2. Mexico In Silico Clinical Trials Market
9.6. Rest of The World In Silico Clinical Trials Market

Chapter 10. Competitive Intelligence
10.1. Top Market Strategies
10.2. Company Profiles
10.2.1. Certara, Inc.
10.2.1.1. Key Information
10.2.1.2. Overview
10.2.1.3. Financial (Subject to Data Availability)
10.2.1.4. Industry Summary
10.2.1.5. Recent Developments
10.2.2. Novadiscovery Sas
10.2.3. Insilico Medicine, Inc.
10.2.4. Dassault Systemes SE
10.2.5. GNS Healthcare Inc.
10.2.6. The AnyLogic Company
10.2.7. InSilicoTrials
10.2.8. Immunetrics Inc.
10.2.9. Nuventra Pharma Sciences
10.2.10. Abzena Ltd.
Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. Research Assumption

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Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
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