Global Digital Biology Market
Description
MARKET SCOPE:
The global Digital Biology market is projected to grow significantly, registering a CAGR of 13.1% during the forecast period (2024 – 2032).
Digital biology is an interdisciplinary field that combines principles from biology, computer science, mathematics, and engineering to understand, model, and manipulate biological systems using digital technologies. It involves the use of computational tools, bioinformatics, artificial intelligence (AI), and data analytics to analyze biological data, simulate biological processes, and derive insights that can inform research, healthcare, and various applications in the life sciences. The advent of technologies like next-generation sequencing has led to the generation of massive amounts of biological data. Digital biology provides the tools and methods to handle, analyze, and derive meaningful insights from these large datasets. The shift toward personalized medicine, which tailors medical treatments to individual genetic profiles, demands advanced computational approaches for analyzing genomic data. Digital biology plays a crucial role in interpreting and leveraging personalized health information. The pharmaceutical and biotech industries are increasingly relying on digital biology for drug discovery and development. Computational modeling, virtual screening, and bioinformatics contribute to the identification of potential drug candidates and understanding their mechanisms of action.
MARKET OVERVIEW:
Driver: Increasing biotechnology industry expansions is driving the market growth.
The biotechnology sector encompasses a broad range of applications, including pharmaceuticals, agriculture, environmental science, and healthcare. The continual growth of this sector leads to an expansion of research and development efforts. As biotechnology companies explore novel therapies, diagnostics, and applications, there is a heightened demand for advanced technologies that can enhance research processes, increase efficiency, and provide deeper insights into biological systems. Digital biology solutions, particularly those related to genomics and proteomics, are integral to biotechnology R&D. Tools for high-throughput sequencing, bioinformatics, and computational modeling contribute significantly to understanding biological processes and developing new interventions. The emergence of biotech startups signifies a culture of innovation and entrepreneurship within the biotechnology industry. These startups often focus on disruptive technologies and novel approaches to address unmet needs in the life sciences.
Opportunities: Growing need for technological convergence is anticipated for the market growth in the upcoming years.
Technological convergence refers to the integration of different technologies and fields, breaking down traditional boundaries to create synergies and new possibilities. The convergence of biology, computer science, and engineering in digital biology involves the blending of expertise from these disciplines to develop comprehensive solutions for understanding and manipulating biological systems. Interdisciplinary collaboration involves professionals from different fields working together to address complex challenges and create novel solutions. Interdisciplinary collaboration brings together biologists, computer scientists, engineers, data scientists, and other experts to collaborate on projects in digital biology. This collaboration leverages diverse skill sets to tackle multifaceted challenges at the intersection of biology and technology. Collaboration between biologists and information technology experts leads to the development of bioinformatics tools and platforms. These tools are essential for processing and interpreting large volumes of biological data, such as genomic sequences, proteomic data, and other -omics information.
COVID IMPACT:
Digital biology, particularly next-generation sequencing and bioinformatics tools, has been instrumental in rapidly sequencing the genome of the SARS-CoV-2 virus. Digital techniques help track the emergence and spread of new variants of the virus, providing valuable information for public health measures and vaccine development. Digital biology aids in understanding the three-dimensional structure of the virus and its components, facilitating the design of effective vaccines. Computational models have been used to screen existing drugs for potential repurposing against COVID-19. Digital biology tools help identify molecular targets in the virus that can be exploited for therapeutic interventions. Digital approaches are used for analyzing epidemiological data, predicting the spread of the virus, and assessing the impact of interventions. Computational models help in forecasting the trajectory of the pandemic, aiding in resource allocation and public health planning. Digital biology tools are used in the analysis of diagnostic data, including PCR results and genomic data from infected individuals. Development of digital platforms for rapid and remote analysis of diagnostic results has been accelerated. The integration of digital biology with telehealth technologies enables remote monitoring of COVID-19 patients and the collection of real-time health data.
SEGMENTATION ANALYSIS:
Drug Discovery & Disease Modelling segment is anticipated to grow significantly during the forecast period
Computational tools and bioinformatics are used to analyze biological data, identify potential drug targets, and validate their relevance in disease pathways. Digital biology aids researchers in prioritizing targets for further investigation, increasing the efficiency of the drug discovery process. Molecular modeling and simulations, enabled by digital biology, allow researchers to predict how potential drug candidates will interact with biological targets. Virtual screening helps in identifying promising drug candidates and optimizing their structures before entering experimental phases, reducing costs and time. Genomic data, obtained through techniques like next-generation sequencing, is analyzed using bioinformatics to understand genetic variations associated with diseases.
The Infrastructure & Hardware segment is anticipated to grow significantly during the forecast period
Digital biology involves processing vast amounts of biological data, including genomic sequences, protein structures, and complex biological simulations. High-performance computing systems are essential for handling these computationally intensive tasks efficiently. HPC is used in tasks such as genomic data analysis, molecular modeling, and simulations that aid in understanding biological processes. It enables researchers to conduct complex analyses and simulations, significantly accelerating research timelines. The storage and management of large-scale biological datasets require robust and scalable infrastructure. This includes storage solutions capable of handling the enormous volumes of genomic and bioinformatics data generated in digital biology research. Effective data storage and management are critical for storing genomic sequences, experimental results, and other biological information. This infrastructure supports data retrieval, analysis, and collaboration among researchers.
REGIONAL ANALYSIS:
The Asia Pacific region is set to witness significant growth during the forecast period.
Digital biology involves the application of digital technologies, such as computational tools, bioinformatics, artificial intelligence (AI), and data analytics, to biological research, healthcare, and related fields. The Asia Pacific region has become a global hub for technological innovation. Countries like China, Japan, South Korea, and Singapore are at the forefront of adopting and advancing digital technologies, including those related to biology and healthcare. Digital biology has significantly accelerated biological research, genomics, drug discovery, personalized medicine, and diagnostics by leveraging computational approaches to analyze biological data. Academic institutions, research centers, and biotechnology companies in the region are actively engaged in digital biology research and development. This includes genomics, bioinformatics, and the application of AI in biological studies. Digital biology plays a crucial role in advancing precision medicine initiatives in the Asia Pacific region. Tailoring medical treatments based on individual genetic profiles is becoming increasingly important in healthcare.
COMPETITIVE ANALYSIS:
The global Digital Biology market is reasonably competitive with mergers, acquisitions, and Application launches. See some of the major key players in the market.
Illumina
Thermo Fisher Scientific, Inc.
Schrodinger, Inc.
Compugen
Aganitha AI Inc.
Genedata AG
QIAGEN
Simulations Plus, Inc.
Fios Genomics
SCOPE OF THE REPORT:
By Application
It provides a technological development map over time to understand the industry’s growth rate and indicates how the Digital Biology market is evolving.
The report offers a dynamic method to various factors that drive or restrain the growth of the market and specifies which Digital Biology submarket will be the main driver of the overall market from 2024 to 2032.
It renders a definite analysis of changing competitive dynamics and stipulates the leading players and what are their prospects over the forecast period.
It builds a nine-year estimate based on how the market is predicted to grow and shows what will market shares of the global region change by 2032 and which country will lead the market in 2032.
The global Digital Biology market is projected to grow significantly, registering a CAGR of 13.1% during the forecast period (2024 – 2032).
Digital biology is an interdisciplinary field that combines principles from biology, computer science, mathematics, and engineering to understand, model, and manipulate biological systems using digital technologies. It involves the use of computational tools, bioinformatics, artificial intelligence (AI), and data analytics to analyze biological data, simulate biological processes, and derive insights that can inform research, healthcare, and various applications in the life sciences. The advent of technologies like next-generation sequencing has led to the generation of massive amounts of biological data. Digital biology provides the tools and methods to handle, analyze, and derive meaningful insights from these large datasets. The shift toward personalized medicine, which tailors medical treatments to individual genetic profiles, demands advanced computational approaches for analyzing genomic data. Digital biology plays a crucial role in interpreting and leveraging personalized health information. The pharmaceutical and biotech industries are increasingly relying on digital biology for drug discovery and development. Computational modeling, virtual screening, and bioinformatics contribute to the identification of potential drug candidates and understanding their mechanisms of action.
MARKET OVERVIEW:
Driver: Increasing biotechnology industry expansions is driving the market growth.
The biotechnology sector encompasses a broad range of applications, including pharmaceuticals, agriculture, environmental science, and healthcare. The continual growth of this sector leads to an expansion of research and development efforts. As biotechnology companies explore novel therapies, diagnostics, and applications, there is a heightened demand for advanced technologies that can enhance research processes, increase efficiency, and provide deeper insights into biological systems. Digital biology solutions, particularly those related to genomics and proteomics, are integral to biotechnology R&D. Tools for high-throughput sequencing, bioinformatics, and computational modeling contribute significantly to understanding biological processes and developing new interventions. The emergence of biotech startups signifies a culture of innovation and entrepreneurship within the biotechnology industry. These startups often focus on disruptive technologies and novel approaches to address unmet needs in the life sciences.
Opportunities: Growing need for technological convergence is anticipated for the market growth in the upcoming years.
Technological convergence refers to the integration of different technologies and fields, breaking down traditional boundaries to create synergies and new possibilities. The convergence of biology, computer science, and engineering in digital biology involves the blending of expertise from these disciplines to develop comprehensive solutions for understanding and manipulating biological systems. Interdisciplinary collaboration involves professionals from different fields working together to address complex challenges and create novel solutions. Interdisciplinary collaboration brings together biologists, computer scientists, engineers, data scientists, and other experts to collaborate on projects in digital biology. This collaboration leverages diverse skill sets to tackle multifaceted challenges at the intersection of biology and technology. Collaboration between biologists and information technology experts leads to the development of bioinformatics tools and platforms. These tools are essential for processing and interpreting large volumes of biological data, such as genomic sequences, proteomic data, and other -omics information.
COVID IMPACT:
Digital biology, particularly next-generation sequencing and bioinformatics tools, has been instrumental in rapidly sequencing the genome of the SARS-CoV-2 virus. Digital techniques help track the emergence and spread of new variants of the virus, providing valuable information for public health measures and vaccine development. Digital biology aids in understanding the three-dimensional structure of the virus and its components, facilitating the design of effective vaccines. Computational models have been used to screen existing drugs for potential repurposing against COVID-19. Digital biology tools help identify molecular targets in the virus that can be exploited for therapeutic interventions. Digital approaches are used for analyzing epidemiological data, predicting the spread of the virus, and assessing the impact of interventions. Computational models help in forecasting the trajectory of the pandemic, aiding in resource allocation and public health planning. Digital biology tools are used in the analysis of diagnostic data, including PCR results and genomic data from infected individuals. Development of digital platforms for rapid and remote analysis of diagnostic results has been accelerated. The integration of digital biology with telehealth technologies enables remote monitoring of COVID-19 patients and the collection of real-time health data.
SEGMENTATION ANALYSIS:
Drug Discovery & Disease Modelling segment is anticipated to grow significantly during the forecast period
Computational tools and bioinformatics are used to analyze biological data, identify potential drug targets, and validate their relevance in disease pathways. Digital biology aids researchers in prioritizing targets for further investigation, increasing the efficiency of the drug discovery process. Molecular modeling and simulations, enabled by digital biology, allow researchers to predict how potential drug candidates will interact with biological targets. Virtual screening helps in identifying promising drug candidates and optimizing their structures before entering experimental phases, reducing costs and time. Genomic data, obtained through techniques like next-generation sequencing, is analyzed using bioinformatics to understand genetic variations associated with diseases.
The Infrastructure & Hardware segment is anticipated to grow significantly during the forecast period
Digital biology involves processing vast amounts of biological data, including genomic sequences, protein structures, and complex biological simulations. High-performance computing systems are essential for handling these computationally intensive tasks efficiently. HPC is used in tasks such as genomic data analysis, molecular modeling, and simulations that aid in understanding biological processes. It enables researchers to conduct complex analyses and simulations, significantly accelerating research timelines. The storage and management of large-scale biological datasets require robust and scalable infrastructure. This includes storage solutions capable of handling the enormous volumes of genomic and bioinformatics data generated in digital biology research. Effective data storage and management are critical for storing genomic sequences, experimental results, and other biological information. This infrastructure supports data retrieval, analysis, and collaboration among researchers.
REGIONAL ANALYSIS:
The Asia Pacific region is set to witness significant growth during the forecast period.
Digital biology involves the application of digital technologies, such as computational tools, bioinformatics, artificial intelligence (AI), and data analytics, to biological research, healthcare, and related fields. The Asia Pacific region has become a global hub for technological innovation. Countries like China, Japan, South Korea, and Singapore are at the forefront of adopting and advancing digital technologies, including those related to biology and healthcare. Digital biology has significantly accelerated biological research, genomics, drug discovery, personalized medicine, and diagnostics by leveraging computational approaches to analyze biological data. Academic institutions, research centers, and biotechnology companies in the region are actively engaged in digital biology research and development. This includes genomics, bioinformatics, and the application of AI in biological studies. Digital biology plays a crucial role in advancing precision medicine initiatives in the Asia Pacific region. Tailoring medical treatments based on individual genetic profiles is becoming increasingly important in healthcare.
COMPETITIVE ANALYSIS:
The global Digital Biology market is reasonably competitive with mergers, acquisitions, and Application launches. See some of the major key players in the market.
Illumina
- In 2023, A pioneer in array-based technologies and DNA sequencing worldwide, the company Connected Insights has released new cloud-based software that allows for tertiary analysis of clinical next-generation sequencing (NGS) data.
- In February 2023, Ocean Genomics is an AI and technology business established in the United States that specializes in cutting-edge computational systems. Accenture is one of its investors. It is anticipated that this investment will help biotechnology businesses find and develop customized medications.
Thermo Fisher Scientific, Inc.
Schrodinger, Inc.
Compugen
Aganitha AI Inc.
Genedata AG
QIAGEN
Simulations Plus, Inc.
Fios Genomics
SCOPE OF THE REPORT:
By Application
- Drug Discovery & Disease Modelling
- Preclinical Drug Development
- Infrastructure & Hardware
- Genomics
- Proteomics
- Other Applications
- Databases
- Infrastructure & Hardware
- Software Platform
- North America (the United States & Canada)
- Europe (Germany, UK, France, Spain, Italy, and the Rest of Europe)
- Asia Pacific (China, Japan, India, and Rest of Asia Pacific)
- Rest of the World (the Middle East & Africa, and Latin America)
It provides a technological development map over time to understand the industry’s growth rate and indicates how the Digital Biology market is evolving.
The report offers a dynamic method to various factors that drive or restrain the growth of the market and specifies which Digital Biology submarket will be the main driver of the overall market from 2024 to 2032.
It renders a definite analysis of changing competitive dynamics and stipulates the leading players and what are their prospects over the forecast period.
It builds a nine-year estimate based on how the market is predicted to grow and shows what will market shares of the global region change by 2032 and which country will lead the market in 2032.
Table of Contents
160 Pages
- 1. Executive Summary
- 1.1. Market Snapshot
- 1.2. Regional Analysis
- 1.3. Segment Analysis
- 2. Overview And Scope
- 2.1. Market Vision
- 2.1.1. Market Definition
- 2.2. Market Segmentation
- 3. Global Digital Biology Market Overview By Region: 2019 Vs 2023 Vs 2032
- 3.1. Global Digital Biology Market Size By Regions (2019-2023) (Usd Million)
- 3.1.1. North America Digital Biology Market Size By Country (2019-2023) (Usd Million)
- 3.1.2. Europe Digital Biology Market Size By Country (2019-2023) (Usd Million)
- 3.1.3. Asia Pacific America Digital Biology Market Size By Country (2019-2023) (Usd Million)
- 3.1.4. Rest Of The World Digital Biology Market Size By Country (2019-2023) (Usd Million)
- 3.2. Global Digital Biology Market Size By Regions (2024-2032) (Usd Million)
- 3.2.1. North America Digital Biology Market Size By Country (2024-2032) (Usd Million)
- 3.2.2. Europe Digital Biology Market Size By Country (2024-2032) (Usd Million)
- 3.2.3. Asia Pacific Digital Biology Market Size By Country (2024-2032) (Usd Million)
- 3.2.4. Rest Of The World Digital Biology Market Size By Country (2024-2032) (Usd Million)
- 4. Global Digital Biology Market Dynamics
- 4.1. Market Overview
- 4.1.1. Market Drivers
- 4.1.2. Market Restraints/ Challenges Analysis
- 4.1.3. Market Opportunities
- 4.2. Pestle Analysis
- 4.3. Porter’s Five Forces Model
- 4.3.1. Bargaining Power Of Suppliers
- 4.3.2. Bargaining Power Of Buyers
- 4.3.3. The Threat Of New Entrants
- 4.3.4. Threat Of Substitutes
- 4.3.5. Intensity Of Rivalry
- 4.4. Value Chain Analysis/Supply Chain Analysis
- 4.5. Covid-19 Impact Analysis On Global Digital Biology Market
- ** In – Depth Qualitative Analysis Will Be Provided In The Final Report Subject To Market
- 5. Global Digital Biology Market, By Application
- 5.1. Overview
- 5.2. Global Digital Biology Market Size By Application (2019 - 2032) (Usd Million)
- 5.3. Key Findings For Digital Biology Market - By Application
- 5.3.1. Drug Discovery & Disease Modelling
- 5.3.2. Preclinical Drug Development
- 5.3.3. Infrastructure & Hardware
- 5.3.4. Genomics
- 5.3.5. Proteomics
- 5.3.6. Other Applications
- 6. Global Digital Biology Market, By Type
- 6.1. Overview
- 6.2. Key Findings For Digital Biology Market - By Type
- 6.2.1. Databases
- 6.2.2. Infrastructure & Hardware
- 6.2.3. Software Platform
- 7. Global Digital Biology Market, By Region
- 7.1. Key Findings For Digital Biology Market- By Region
- 7.2. Overview
- 7.3. Global Digital Biology Market, By Application
- 7.4. Global Digital Biology Market, By End – Users
- 8. Global Digital Biology Market- North America
- 8.1. Overview
- 8.2. North America Digital Biology Market Size (2019 - 2032) (Usd Million)
- 8.3. North America Digital Biology Market, By Application
- 8.4. North America Digital Biology Market, By Type
- 8.5. North America Digital Biology Market Size By Countries
- 8.5.1. United States
- 8.5.2. Canada
- 9. Global Digital Biology Market- Europe
- 9.1. Overview
- 9.2. Europe Digital Biology Market Size (2019 - 2032) (Usd Million)
- 9.3. Europe Digital Biology Market, By Application
- 9.4. Europe Digital Biology Market, By Type
- 9.5. Europe Digital Biology Market Size By Countries
- 9.5.1. Germany
- 9.5.2. Uk
- 9.5.3. France
- 9.5.4. Spain
- 9.5.5. Italy
- 9.5.6. Rest Of Europe
- 10. Global Digital Biology Market - Asia Pacific
- 10.1. Overview
- 10.2. Asia Pacific Digital Biology Market Size (2019 - 2032) (Usd Million)
- 10.3. Asia Pacific Digital Biology Market, By Application
- 10.4. Asia Pacific Digital Biology Market, By Type
- 10.5. Asia Pacific Digital Biology Market Size By Countries
- 10.5.1. China
- 10.5.2. Japan
- 10.5.3. India
- 10.5.4. Rest Of Asia Pacific
- 11. Global Digital Biology Market- Rest Of World
- 11.1. Overview
- 11.2. Rest Of World Digital Biology Market Size (2019 - 2032) (Usd Million)
- 11.3. Rest Of World Digital Biology Market, By Application
- 11.4. Rest Of World Digital Biology Market, By Type
- 11.5. Rest Of World Digital Biology Market Size By Regions
- 11.5.1. Middle East & Africa
- 11.5.2. Latin America
- 12. Global Digital Biology Market- Competitive Landscape
- 12.1. Key Strategies Adopted By The Leading Players
- 12.2. Recent Developments
- 12.2.1. Investments & Expansions
- 12.2.2. New End-user Launches
- 12.2.3. Mergers & Acquisitions
- 12.2.4. Agreements, Joint Ventures, And Partnerships
- 13. Global Digital Biology Market- Company Profiles
- 13.1. Dnanexus Inc.
- 13.1.1. Company Overview
- 13.1.2. Financial Overview
- 13.1.3. Application Offered
- 13.1.4. Key Developments
- 13.2. Illumina
- 13.3. Thermo Fisher Scientific, Inc.
- 13.4. Schrodinger, Inc.
- 13.5. Compugen
- 13.6. Aganitha Ai Inc.
- 13.7. Genedata Ag
- 13.8. Qiagen
- 13.9. Simulations Plus, Inc.
- 13.10. Fios Genomics
- 14. Our Research Methodology
- 14.1. Data Triangulation
- 14.2. Data Sources
- 14.2.1. Secondary Sources
- 14.2.2. Primary Sources
- 14.3. Assumptions/ Limitations For The Study
- 14.4. Research & Forecasting Methodology
- 15. Appendix
- 15.1. Disclaimer
- 15.2. Contact Us
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