Computational Biology Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, 2018-2028 Segmented By Application (Cellular and Biological Simulation, Drug Discovery and Disease Modelling, Preclinical Drug Development, Clinical Trials, Human Body Simulation Software), By Tool (Databases, Infrastructure (Hardware), Analysis Software and Services), By Service (In-house, Contract), By End User (Academics, Industry and Commercials), By Region, By Competition Forecast & Opportunities, 2018-2028F

  • Industry : Healthcare
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  • Published Date : NA
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Summary

Report Description

Forecast Period

2024-2028

Market Size (2022)

USD 4.89 billion

CAGR (2023-2028)

7.49%

Fastest Growing Segment

Industry and Commercials

Largest Market

North America


Market Overview

Global Computational Biology Market has valued at USD 4.89 billion in 2022 and is anticipated to project impressive growth in the forecast period with a CAGR of 7.49% through 2028. The Global Computational Biology Market refers to the application of computational techniques, including algorithms, data analysis, and mathematical modeling, to understand and analyze biological data. It plays a critical role in various areas of life sciences, including genomics, proteomics, drug discovery, and personalized medicine.

Key Market Drivers

Explosion in Biological Data

The field of biology has entered a new era, one characterized by an unprecedented explosion in biological data. From the sequencing of genomes to the study of complex biological systems, the volume and complexity of data being generated are staggering. This deluge of data has given rise to the field of computational biology, which utilizes advanced algorithms and data analysis techniques to make sense of this wealth of information. The sequencing of genomes has been a driving force behind the surge in biological data. The Human Genome Project, completed in 2003, marked a significant milestone in genomics, but it was just the beginning. Today, high-throughput sequencing technologies have made it possible to rapidly and cost-effectively sequence entire genomes. This has led to a vast repository of genomic data, providing critical insights into genetics, evolution, and disease susceptibility. Genomics is just one facet of the biological data explosion. Transcriptomics, which studies gene expression patterns, and proteomics, which focuses on proteins, have also contributed to the data influx. Researchers can now examine the entire transcriptome or proteome of an organism, offering insights into gene regulation, protein function, and disease mechanisms. Single-cell sequencing technologies have taken biological research to a finer level of granularity. Instead of studying tissues or populations of cells, scientists can now analyze individual cells within a tissue. This technology has revolutionized our understanding of cellular heterogeneity, tissue development, and disease progression. However, it generates massive amounts of data that require sophisticated computational analysis. The integration of multiple omics data sources (genomics, transcriptomics, proteomics, metabolomics, etc.) is a powerful approach for understanding complex biological systems comprehensively. However, it multiplies the volume of data exponentially. Computational biology plays a pivotal role in harmonizing and interpreting these integrated datasets, enabling holistic insights into biological phenomena. The pharmaceutical industry relies on computational biology to accelerate drug discovery. By analyzing vast datasets of chemical compounds and their interactions with biological molecules, researchers can identify potential drug candidates, predict their efficacy, and optimize their properties. This data-driven approach significantly reduces the time and cost of bringing new drugs to market.

Advancements in Genomics

The field of genomics has witnessed remarkable advancements over the past few decades, revolutionizing our understanding of genetics, diseases, and the intricacies of life itself. At the heart of this transformation is the synergy between genomics and computational biology. The Human Genome Project, completed in 2003, marked a turning point in genomics. It was a massive collaborative effort to map and sequence all the genes in the human genome. This monumental achievement set the stage for a genomics revolution, catalyzing the rapid development of high-throughput DNA sequencing technologies. Next-generation sequencing (NGS) technologies emerged as game-changers in genomics. These instruments can sequence vast quantities of DNA in a short time, generating terabytes of data in a single run. This exponential increase in data output necessitated advanced computational tools and expertise to process and analyze the data efficiently. The proliferation of high-throughput sequencing has led to an explosion of genomic data. Researchers can now sequence not only human genomes but also the genomes of countless other species, uncovering critical insights into evolution, genetic diversity, and the genetic basis of diseases. This abundance of data fuels the demand for computational biology solutions to extract meaningful information. The advent of affordable direct-to-consumer DNA testing has made genomics accessible to the masses. Individuals can now obtain their genetic information, which can provide insights into ancestry, disease predispositions, and lifestyle recommendations. This growing interest in personal genomics generates a significant need for computational tools that can analyze and interpret these individual genetic profiles. Genomic medicine leverages genomic data to guide clinical decision-making. It enables the identification of genetic mutations linked to diseases, facilitates early diagnosis, and supports personalized treatment plans. As genomic medicine becomes more integrated into healthcare systems, computational biology tools play a central role in translating genomic information into actionable insights. Traditional genomic techniques often analyze populations of cells, masking the diversity within tissues. Single-cell genomics technologies now allow researchers to study individual cells, unveiling intricate cellular heterogeneity. These techniques generate immense datasets, necessitating computational methods to unravel the complex cellular landscapes.

Drug Discovery and Development

The realms of drug discovery and computational biology are experiencing an exciting convergence. As the pharmaceutical industry races to develop innovative drugs, computational biology has emerged as an indispensable ally. The need for novel pharmaceutical compounds to treat a wide range of diseases, from cancer to rare genetic disorders, continues to grow. Drug discovery is a lengthy and resource-intensive process, but it's essential for improving healthcare outcomes and patient quality of life. Computational biology provides crucial support by accelerating various stages of drug development. Computational biology allows researchers to conduct in-silico (computer-based) drug screening. This approach involves simulating the interaction between potential drug compounds and target molecules, such as proteins or enzymes. By virtually screening thousands of compounds, researchers can identify potential drug candidates faster and with lower costs. Computational biology plays a pivotal role in predicting drug-target interactions. Algorithms and machine learning models analyze biological data to determine how a drug molecule will interact with specific cellular targets. This predictive capability significantly shortens the drug development timeline and reduces experimental failures. Once potential drug candidates are identified, computational biology aids in optimizing their properties. Researchers can modify the chemical structure of lead compounds to enhance their efficacy, reduce toxicity, and improve bioavailability. This iterative process, known as lead optimization, relies heavily on computational modeling and simulations. Understanding the underlying biological pathways involved in diseases is critical for drug development. Computational biology tools help elucidate these pathways by analyzing complex omics data. This knowledge guides researchers in identifying key targets and developing drugs that modulate specific biological processes.

Collaboration and Cross-Industry Partnerships

In today's interconnected world, collaboration and partnerships are powerful catalysts for innovation and progress. The Global Computational Biology Market is no exception, benefiting significantly from cross-industry collaborations. Collaborations in the field of computational biology facilitate the exchange of knowledge and expertise. Academic institutions and research organizations often possess cutting-edge research findings, while pharmaceutical companies bring practical drug development experience. When these entities come together, they combine theoretical insights with real-world applications, driving innovation in the field. One of the primary challenges in computational biology is access to high-quality biological data. Collaboration between research organizations and technology firms can provide valuable data resources. Public-private partnerships, for example, can make large datasets accessible to researchers, enabling them to conduct comprehensive analyses and develop more accurate models. Collaborative efforts allow for the pooling of resources, both human and financial. This resource synergy can accelerate research and development processes. When multiple entities contribute to a project, it becomes possible to tackle more extensive and complex tasks, such as large-scale genomic studies or drug discovery initiatives. Computational biology inherently involves multiple disciplines, including biology, computer science, and statistics. Collaborative projects often involve researchers from these diverse backgrounds. This interdisciplinary approach encourages fresh perspectives and creative problem-solving, leading to breakthroughs that might not have been possible within a single organization. The pharmaceutical industry is increasingly turning to computational biology for drug discovery. Collaborations between pharmaceutical companies and computational biology experts can expedite the identification of potential drug candidates. Cross-industry partnerships facilitate the application of computational tools to predict drug-target interactions and optimize lead compounds.


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Key Market Challenges

Data Complexity and Volume

The exponential growth of biological data is a double-edged sword. While it provides a wealth of information, it also presents a significant challenge in terms of data complexity and volume. Handling, storing, and analyzing massive datasets require robust computational infrastructure and efficient algorithms.

Data Privacy and Security

Biological data, especially genomic information, is sensitive and subject to strict privacy regulations. Ensuring data privacy while allowing for meaningful analysis is a delicate balance. The computational biology market must address these concerns to gain public trust and comply with evolving data protection laws.

Interoperability and Standardization

Computational biology tools and platforms often vary in their data formats and analysis methods. This lack of standardization hinders data sharing and collaboration. Establishing common data standards and interoperable tools is essential to overcome this challenge.

Shortage of Skilled Workforce

The field of computational biology requires a multidisciplinary skill set, encompassing biology, computer science, mathematics, and statistics. There is a shortage of professionals with expertise in these areas, making it challenging for organizations to find and retain qualified talent.

Key Market Trends

Single-Cell Omics Revolution

Single-cell sequencing and omics technologies are rapidly gaining momentum. These techniques allow researchers to dissect the molecular profiles of individual cells within complex tissues. As the resolution of single-cell data improves, computational biology will play a critical role in analyzing and interpreting these intricate datasets. Expect innovations in algorithms and tools tailored for single-cell omics analysis.

Spatial Transcriptomics

Spatial transcriptomics is an emerging field that combines genomics with spatial information. It enables researchers to map gene expression within tissues, providing insights into the spatial organization of cells. Computational methods for spatial data analysis will be in high demand, offering new ways to study tissue architecture and disease mechanisms.

Multi-Omics Integration

Integrating multiple omics data sources, such as genomics, transcriptomics, proteomics, and metabolomics, provides a holistic view of biological systems. Computational tools that facilitate the integration and analysis of multi-omics data will be in high demand, enabling researchers to uncover intricate interactions and pathways.

Blockchain for Data Security

Data security and privacy are paramount in computational biology, particularly when handling sensitive genomic information. Blockchain technology holds promise for secure and transparent data management, ensuring the integrity and privacy of biological data. Expect to see blockchain-based solutions for data security and traceability.

Segmental Insights

Service Insights

Based on the category of Service, the Contract segment emerged as the dominant player in the global market for computational biology in 2022. This can be attributed to the cost-effectiveness of contract services compared to the in-house services offered globally. Providers of Contract Research Organization (CRO) services collaborate closely with clients to create tailored plans, thereby acting as a catalyst for market growth.

On the other hand, the in-house segment is projected to experience the most rapid growth. In-house services grant companies’ greater control over their internal operations, as they directly employ these services. This approach offers advantages such as cost savings and time efficiency, contributing to its accelerated growth.

End User Insights

The commercial sector is anticipated to be the primary contributor to market revenue. Increased investments in Research and Development (R&D) in genetic engineering and the development of innovative medicines by both government and commercial entities are significant factors contributing to the heightened demand for computational biology.

As an example, in May 2021, the World Health Organization (WHO) and the Swiss Confederation inked a Memorandum of Understanding (MoU) to establish the inaugural WHO BioHub Facility as part of the WHO BioHub System. Situated in Spiez, Switzerland, this facility serves as a hub for the secure reception, sequencing, storage, and preparation of biological materials for distribution to other laboratories. It also plays a crucial role in risk assessments and supports global preparedness against pathogens. Similarly, substantial investments from the European Commission into the Horizon 2020 program aim to eliminate innovation barriers and promote improved collaboration between the public and private sectors, fostering innovation. These developments are expected to bolster the rising demand for computational biology, consequently driving revenue growth in this market segment.

Regional Insights

North America presently holds the dominant position in the computational biology market and is expected to maintain its leadership for several more years. The United States, in particular, stands as the frontrunner in the field of synthetic biology, which is an emerging discipline focused on the design, manipulation, and reprogramming of biological systems. The U.S. government has been a substantial supporter of computational biology and synthetic biology since 2005, channeling over USD 1 billion toward their development. The annual average investment by the U.S. government in advancing computational biology is estimated at approximately USD 140 million.

The rise of personalized medicine has fostered collaborative initiatives among medical institutions, government bodies, and researchers to expedite the creation of effective treatments. For instance, in 2020, Summit Biolabs Inc. and the Colorado Center for Personalized Medicine (CCPM) established a comprehensive strategic partnership to conduct research, development, and commercialization of saliva liquid-biopsy tests for the early detection of cancer, diagnosis of COVID-19, and other viral infections. Similarly, in April 2020, HealthCare Global Enterprises and Strand Life Sciences introduced the StrandAdvantage500, a Next-Generation Sequencing (NGS) based assay that assesses cancer-related genetic alterations in DNA and RNA extracted from a patient's tumor in a unified workflow. Furthermore, in July 2021, Indivumed GmbH launched "travel," an innovative AI discovery platform designed for oncology and precision medicine. This platform combines IndivuType's extensive multi-omics data with sophisticated disease models, highly advanced automated Machine Learning tools, and a comprehensive suite of advanced analytical capabilities.

The overall computational biology market in the United States is poised for substantial growth in the coming years, primarily due to the significant investments made in drug development, which are the highest worldwide.


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Recent Developments

In April 2021, Peptilogics, a biotechnology platform company employing computational design to discover innovative peptide-based therapies, reported the successful conclusion of Phase I clinical trials for its primary compound, PLG0206. This compound, recognized as a potent and wide-ranging anti-infective agent, has received both the Orphan Drug Designation and Qualified Infectious Disease Product Designation from the United States Food and Drug Administration. Its primary application is in addressing prosthetic joint infections (PJI).

In January 2021, AsclepiX Therapeutics Inc., a biopharmaceutical firm utilizing computational biology to identify highly effective peptide regulators for maintaining vascular and cellular balance, announced the commencement of Phase I/IIa CONGO clinical trials. These trials aim to assess the safety and therapeutic effectiveness of AXT107 in patients with Diabetic Macular Edema (DME), marking a significant milestone as the first patient to receive the dosing.

Key Market Players

  • Dassault Systemes SE
  • Certara Inc
  • Chemical Computing Group ULC
  • Compugen Ltd
  • Rosa & Co. LLC
  • GeneData AG
  • Insilico Biotechnology AG
  • Instem PLC
  • Strand Life Sciences Pvt Ltd
  •  Schrodinger Inc

 By Application

By Tool

By Service

By End User

By Region
  • Cellular and Biological Simulation
  • Drug Discovery and Disease Modelling
  • Preclinical Drug Development
  • Clinical Trials
  • Human Body Simulation Software
  • Databases, Infrastructure (Hardware)
  • Analysis Software and Services
  • In-house
  • Contract
  • Academics
  • Industry and Commercials
  • North America
  • Europe
  • Asia-Pacific
  • South America
  • Middle East & Africa

Report Scope:

In this report, the Global Computational Biology Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

  • Computational Biology Market, By Application:

o   Cellular and Biological Simulation

o   Drug Discovery and Disease Modelling

o   Preclinical Drug Development

o   Clinical Trials

o   Human Body Simulation Software

  • Computational Biology Market, By Tool:

o   Databases

o   Infrastructure (Hardware)

o   Analysis Software and Services

  • Computational Biology Market, By Service:

o   In-house

o   Contact

  • Computational Biology Market, By End User:

o   Academics

o   Industry and Commercials

  • Computational Biology Market, By Region:

o   North America

§  United States

§  Canada

§  Mexico

o   Europe

§  Germany

§  United Kingdom

§  France

§  Italy

§  Spain

o   Asia-Pacific

§  China

§  Japan

§  India

§  Australia

§  South Korea

o   South America

§  Brazil

§  Argentina

§  Colombia

o   Middle East & Africa

§  South Africa

§  Saudi Arabia

§  UAE

§  Kuwait

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Computational Biology Market.

Available Customizations:

Global Computational Biology market report with the given market data, Tech Sci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

  • Detailed analysis and profiling of additional market players (up to five).

Global Computational Biology Market is an upcoming report to be released soon. If you wish an early delivery of this report or want to confirm the date of release, please contact us at [email protected]

Table of content

1.    Product Overview

1.1.  Market Definition

1.2.  Scope of the Market

1.2.1.    Markets Covered

1.2.2.    Years Considered for Study

1.2.3.    Key Market Segmentations

2.    Research Methodology

2.1.  Objective of the Study

2.2.  Baseline Methodology

2.3.  Key Industry Partners

2.4.  Major Association and Secondary Sources

2.5.  Forecasting Methodology

2.6.  Data Triangulation & Validation

2.7.  Assumptions and Limitations

3.    Executive Summary

3.1.  Overview of the Market

3.2.  Overview of Key Market Segmentations

3.3.  Overview of Key Market Players

3.4.  Overview of Key Regions/Countries

3.5.  Overview of Market Drivers, Challenges, Trends

4.    Voice of Customer

5.    Global Computational Biology Market Outlook

5.1.  Market Size & Forecast

5.1.1.    By Value

5.2.  Market Share & Forecast

5.2.1.    By Application (Cellular and Biological Simulation, Drug Discovery and Disease Modelling, Preclinical Drug Development, Clinical Trials, Human Body Simulation Software)

5.2.2.    By Tool (Databases, Infrastructure (Hardware), Analysis Software and Services)

5.2.3.    By Service (In-house, Contact)

5.2.4.    By End User (Academics, Industry and Commercials)

5.2.5.    By Region

5.2.6.    By Company (2022)

5.3.  Product Market Map

5.3.1.    By Application

5.3.2.    By Tool

5.3.3.    By Service

5.3.4.    By End User

5.3.5.    By Region

6.    North America Computational Biology Market Outlook

6.1.  Market Size & Forecast       

6.1.1.    By Value

6.2.  Market Share & Forecast

6.2.1.    By Application (Cellular and Biological Simulation, Drug Discovery and Disease Modelling, Preclinical Drug Development, Clinical Trials, Human Body Simulation Software)

6.2.2.    By Tool (Databases, Infrastructure (Hardware), Analysis Software and Services)

6.2.3.    By Service (In-house, Contact)

6.2.4.    By End User (Academics, Industry and Commercials)

6.2.5.    By Country

6.3.  North America: Country Analysis

6.3.1.    United States Computational Biology Market Outlook

6.3.1.1.        Market Size & Forecast

6.3.1.1.1.           By Value

6.3.1.2.        Market Share & Forecast

6.3.1.2.1.           By Application

6.3.1.2.2.           By Tool

6.3.1.2.3.           By Service

6.3.1.2.4.           By End User

6.3.2.    Canada Computational Biology Market Outlook

6.3.2.1.        Market Size & Forecast

6.3.2.1.1.           By Value

6.3.2.2.        Market Share & Forecast

6.3.2.2.1.           By Application

6.3.2.2.2.           By Tool

6.3.2.2.3.           By Service

6.3.2.2.4.           By End User

6.3.3.    Mexico Computational Biology Market Outlook

6.3.3.1.        Market Size & Forecast

6.3.3.1.1.           By Value

6.3.3.2.        Market Share & Forecast

6.3.3.2.1.           By Application

6.3.3.2.2.           By Tool

6.3.3.2.3.           By Service

6.3.3.2.4.           By End User

7.    Europe Computational Biology Market Outlook

7.1.  Market Size & Forecast       

7.1.1.    By Value

7.2.  Market Share & Forecast

7.2.1.    By Application (Cellular and Biological Simulation, Drug Discovery and Disease Modelling, Preclinical Drug Development, Clinical Trials, Human Body Simulation Software)

7.2.2.    By Tool (Databases, Infrastructure (Hardware), Analysis Software and Services)

7.2.3.    By Service (In-house, Contact)

7.2.4.    By End User (Academics, Industry and Commercials)

7.2.5.    By Country

7.3.  Europe: Country Analysis

7.3.1.    Germany Computational Biology Market Outlook

7.3.1.1.        Market Size & Forecast

7.3.1.1.1.           By Value

7.3.1.2.        Market Share & Forecast

7.3.1.2.1.           By Application

7.3.1.2.2.           By Tool

7.3.1.2.3.           By Service

7.3.1.2.4.           By End User

7.3.2.    United Kingdom Computational Biology Market Outlook

7.3.2.1.        Market Size & Forecast

7.3.2.1.1.           By Value

7.3.2.2.        Market Share & Forecast

7.3.2.2.1.           By Application

7.3.2.2.2.           By Tool

7.3.2.2.3.           By Service

7.3.2.2.4.           By End User

7.3.3.    France Computational Biology Market Outlook

7.3.3.1.        Market Size & Forecast

7.3.3.1.1.           By Value

7.3.3.2.        Market Share & Forecast

7.3.3.2.1.           By Application

7.3.3.2.2.           By Tool

7.3.3.2.3.           By Service

7.3.3.2.4.           By End User

7.3.4.    Italy Computational Biology Market Outlook

7.3.4.1.        Market Size & Forecast

7.3.4.1.1.           By Value

7.3.4.2.        Market Share & Forecast

7.3.4.2.1.           By Application

7.3.4.2.2.           By Tool

7.3.4.2.3.           By Service

7.3.4.2.4.           By End User

7.3.5.    Spain Computational Biology Market Outlook

7.3.5.1.        Market Size & Forecast

7.3.5.1.1.           By Value

7.3.5.2.        Market Share & Forecast

7.3.5.2.1.           By Application

7.3.5.2.2.           By Tool

7.3.5.2.3.           By Service

7.3.5.2.4.           By End User

8.    Asia-Pacific Computational Biology Market Outlook

8.1.  Market Size & Forecast       

8.1.1.    By Value

8.2.  Market Share & Forecast

8.2.1.    By Application (Cellular and Biological Simulation, Drug Discovery and Disease Modelling, Preclinical Drug Development, Clinical Trials, Human Body Simulation Software)

8.2.2.    By Tool (Databases, Infrastructure (Hardware), Analysis Software and Services)

8.2.3.    By Service (In-house, Contact)

8.2.4.    By End User (Academics, Industry and Commercials)

8.2.5.    By Country

8.3.  Asia-Pacific: Country Analysis

8.3.1.    China Computational Biology Market Outlook

8.3.1.1.        Market Size & Forecast

8.3.1.1.1.           By Value

8.3.1.2.        Market Share & Forecast

8.3.1.2.1.           By Application

8.3.1.2.2.           By Tool

8.3.1.2.3.           By Service

8.3.1.2.4.           By End User

8.3.2.    Japan Computational Biology Market Outlook

8.3.2.1.        Market Size & Forecast

8.3.2.1.1.           By Value

8.3.2.2.        Market Share & Forecast

8.3.2.2.1.           By Application

8.3.2.2.2.           By Tool

8.3.2.2.3.           By Service

8.3.2.2.4.           By End User

8.3.3.    India Computational Biology Market Outlook

8.3.3.1.        Market Size & Forecast

8.3.3.1.1.           By Value

8.3.3.2.        Market Share & Forecast

8.3.3.2.1.           By Application

8.3.3.2.2.           By Tool

8.3.3.2.3.           By Service

8.3.3.2.4.           By End User

8.3.4.    Australia Computational Biology Market Outlook

8.3.4.1.        Market Size & Forecast

8.3.4.1.1.           By Value

8.3.4.2.        Market Share & Forecast

8.3.4.2.1.           By Application

8.3.4.2.2.           By Tool

8.3.4.2.3.           By Service

8.3.4.2.4.           By End User

8.3.5.    South Korea Computational Biology Market Outlook

8.3.5.1.        Market Size & Forecast

8.3.5.1.1.           By Value

8.3.5.2.        Market Share & Forecast

8.3.5.2.1.           By Application

8.3.5.2.2.           By Tool

8.3.5.2.3.           By Service

8.3.5.2.4.           By End User

9.    South America Computational Biology Market Outlook

9.1.  Market Size & Forecast       

9.1.1.    By Value

9.2.  Market Share & Forecast

9.2.1.    By Application (Cellular and Biological Simulation, Drug Discovery and Disease Modelling, Preclinical Drug Development, Clinical Trials, Human Body Simulation Software)

9.2.2.    By Tool (Databases, Infrastructure (Hardware), Analysis Software and Services)

9.2.3.    By Service (In-house, Contact)

9.2.4.    By End User (Academics, Industry and Commercials)

9.2.5.    By Country

9.3.  South America: Country Analysis

9.3.1.    Brazil Computational Biology Market Outlook

9.3.1.1.        Market Size & Forecast

9.3.1.1.1.           By Value

9.3.1.2.        Market Share & Forecast

9.3.1.2.1.           By Application

9.3.1.2.2.           By Tool

9.3.1.2.3.           By Service

9.3.1.2.4.           By End User

9.3.2.    Argentina Computational Biology Market Outlook

9.3.2.1.        Market Size & Forecast

9.3.2.1.1.           By Value

9.3.2.2.        Market Share & Forecast

9.3.2.2.1.           By Application

9.3.2.2.2.           By Tool

9.3.2.2.3.           By Service

9.3.2.2.4.           By End User

9.3.3.    Colombia Computational Biology Market Outlook

9.3.3.1.        Market Size & Forecast

9.3.3.1.1.           By Value

9.3.3.2.        Market Share & Forecast

9.3.3.2.1.           By Application

9.3.3.2.2.           By Tool

9.3.3.2.3.           By Service

9.3.3.2.4.           By End User

10. Middle East and Africa Computational Biology Market Outlook

10.1.             Market Size & Forecast        

10.1.1. By Value

10.2.             Market Share & Forecast

10.2.1. By Application (Cellular and Biological Simulation, Drug Discovery and Disease Modelling, Preclinical Drug Development, Clinical Trials, Human Body Simulation Software)

10.2.2. By Tool (Databases, Infrastructure (Hardware), Analysis Software and Services)

10.2.3. By Service (In-house, Contact)

10.2.4. By End User (Academics, Industry and Commercials)

10.2.5. By Country

10.3.             MEA: Country Analysis

10.3.1. South Africa Computational Biology Market Outlook

10.3.1.1.     Market Size & Forecast

10.3.1.1.1.         By Value

10.3.1.2.     Market Share & Forecast

10.3.1.2.1.         By Application

10.3.1.2.2.         By Tool

10.3.1.2.3.         By Service

10.3.1.2.4.         By End User

10.3.2. Saudi Arabia Computational Biology Market Outlook

10.3.2.1.     Market Size & Forecast

10.3.2.1.1.         By Value

10.3.2.2.     Market Share & Forecast

10.3.2.2.1.         By Application

10.3.2.2.2.         By Tool

10.3.2.2.3.         By Service

10.3.2.2.4.         By End User

10.3.3. UAE Computational Biology Market Outlook

10.3.3.1.     Market Size & Forecast

10.3.3.1.1.         By Value

10.3.3.2.     Market Share & Forecast

10.3.3.2.1.         By Application

10.3.3.2.2.         By Tool

10.3.3.2.3.         By Service

10.3.3.2.4.         By End User

10.3.4. Kuwait Computational Biology Market Outlook

10.3.4.1.     Market Size & Forecast

10.3.4.1.1.         By Value

10.3.4.2.     Market Share & Forecast

10.3.4.2.1.         By Application

10.3.4.2.2.         By Tool

10.3.4.2.3.         By Service

10.3.4.2.4.         By End User

11. Market Dynamics

11.1.             Drivers

11.2.             Challenges

12. Market Trends & Developments

12.1.             Recent Development

12.2.             Mergers & Acquisitions

12.3.             Product Launches

13. Porter’s Five Forces Analysis

13.1.             Competition in the Industry

13.2.             Potential of New Entrants

13.3.             Power of Suppliers

13.4.             Power of Customers

13.5.             Threat of Substitute Products

14. Competitive Landscape

14.1.             Business Overview

14.2.             Product Offerings

14.3.             Recent Developments

14.4.             Financials (As Reported)

14.5.             Key Personnel

14.6.             SWOT Analysis

14.6.1.  Dassault Systemes SE

14.6.2.  Certara Inc

14.6.3.  Chemical Computing Group ULC

14.6.4.  Compugen Ltd

14.6.5.  Rosa & Co. LLC

14.6.6.  GeneData AG

14.6.7.  Insilico Biotechnology AG

14.6.8.  Instem PLC

14.6.9.  Strand Life Sciences Pvt Ltd

14.6.10.                Schrodinger Inc

15.  Strategic Recommendations

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Figures and Tables

Frequently asked questions

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The market size of the Global Computational Biology Market was estimated to be USD 4.89 billion in 2022.

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Dassault Systemes SE, Certara Inc, Chemical Computing Group ULC, Compugen Ltd, Rosa & Co. LLC, GeneData AG, Insilico Biotechnology AG, Instem PLC, Strand Life Sciences Pvt Ltd, Schrodinger Inc are some of the key players operating in the Global Computational Biology Market.

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Data complexity and volume, data privacy and security, complexity of biological systems, are some of the major challenges faced by the Global Computational Biology Market in the upcoming years.

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Explosion in biological data, advancements in genomics and artificial intelligence and machine learning are the major drivers for the Global Computational Biology Market.

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Sakshi Bajaal

Business Consultant
Press Release

Computational Biology Market to Grow with a CAGR of 7.49% through 2028

Sep, 2023

Technological innovations, data-driven research, and the increasing importance of biological insights in various industries is expected to drive the Global Computational Biology Market growth in the

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