Computational Biology Market Size, Share, Growth & Industry Analysis, By Offering (Software, Hardware, Services), By Application (Drug Discovery & Disease Modelling, Preclinical Drug Development, Clinical Trial, Computational Genomics, Computational Proteomics, Others), By End User, and Regional Analysis, 2024-2031

Computational Biology Market Size

The global Computational Biology Market size was valued at USD 6.06 billion in 2023 and is projected to grow from USD 7.08 billion in 2024 to USD 21.05 billion by 2031, exhibiting a CAGR of 16.85% during the forecast period. The global market is expanding rapidly, fueled by advancements in artificial intelligence and machine learning technologies.

These innovations enhance data analysis capabilities and streamline drug discovery processes. Furthermore, the growing emphasis on personalized medicine is promoting the development of tailored therapeutic solutions, leading to increased demand for computational biology solutions.

In the scope of work, the report includes solutions offered by companies such as DNAnexus, Inc., Illumina, Inc., Thermo Fisher Scientific, Inc., Schrodinger, Inc., Compugen, Aganitha AI Inc., Genedata AG, QIAGEN, Simulations Plus, Fios Genomics, and others.

The computational biology market is witnessing significant growth, primarily due to the increasing incidence of diseases and the pressing need for effective treatments. The complexity of biological data necessitates advanced analytical tools, prompting healthcare organizations to invest heavily in computational solutions.

• According to the World Economic Forum, over 7,000 diseases currently lack effective treatments, highlighting significant gaps in healthcare access and research funding.
• The World Health Organization indicates that nearly 2 billion people lack access to essential medicines, underscoring the urgency for innovative therapies. Moreover, the high costs of drug development, ranging from USD 1.3 billion to USD 4 billion, and lengthy timelines of 10 to 15 years emphasize the rising demand for more efficient approaches.

Additionally, the rise in governmental and commercial investments in research and development for genetic engineering and novel therapies is boosting the demand for computational biology solutions.

• For instance, in February 2023, Hexagon Bio raised USD 77.3 million in Series B financing to enhance its microbial genome-derived small molecules and computational discovery platform, focusing on oncology and infectious diseases.

The urgent need for innovative treatments, coupled with substantial investments in research and development, significantly drives the growth of the market.

Computational biology is an interdisciplinary field that applies computational techniques and algorithms to analyze and interpret biological data. It integrates principles from biology, computer science, mathematics, and statistics to understand complex biological systems and processes.

This field encompasses various applications, including genomics, proteomics, and systems biology, facilitating the modeling of biological phenomena, the prediction of molecular interactions, and the identification of potential drug targets.

By leveraging large datasets and advanced computational methods, computational biology enables researchers to derive meaningful insights, accelerate drug discovery, and contribute to personalized medicine, thereby enhancing the understanding of life sciences and improving health outcomes.

Analyst’s Review

Increased funding for computational biology research is expected to propel market expansion by facilitating advancements in data analysis tools, AI integration, and high-performance computing. This financial backing improves drug discovery processes, accelerates innovations, and promotes global collaboration, thereby expanding the applications and adoption of computational biology solutions.

• In March 2024, a multidisciplinary research team at Gladstone Institutes, led by Senior Investigator Katie Pollard, PhD, received USD 5 million in funding through a newly launched grant program. This initiative aimed advancing cancer discoveries using computational biology and artificial intelligence.

Furthermore, the growing adoption of next-generation sequencing (NGS) technologies is contributing significantly to the growth of the computational biology market, particularly in human identification and forensic investigations.

• In January 2023, QIAGEN acquired Verogen, a leader in the application of NGS technologies for human identification (HID) and forensic investigations.

The increasing reliance on advanced next-generation sequencing (NGS) tools allows companies to achieve greater accuracy in genetic analysis, enabling rapid identification of genetic markers and variants. This capability accelerates research timelines, enhances decision-making in drug development and personalized medicine, and fuels the growth of the computational biology industry.

Computational Biology Market Growth Factors

Pharmaceutical companies are increasingly leveraging computational biology to revolutionize the drug discovery process by reducing development time and costs, thereby augmenting the growth of the computational biology market. Advanced bioinformatics tools allow researchers to analyze complex biological data, predict drug efficacy, and identify potential side effects more efficiently.

• In June 2023, Simulations Plus, Inc. acquired Immunetrics, Inc., a company specializing in modeling and simulation for oncology, immunology, and autoimmune diseases, to enhance drug development in these rapidly growing therapeutic areas.
• In February 2024, QIAGEN introduced QIAGEN Biomedical KB-AI, a generative AI-powered knowledge base designed to advance drug discovery in the pharmaceutical and biotech sectors. This platform, built upon an extensive collection of biomedical literature, identifies causal links between genes, diseases, and drugs, providing data scientists and bioinformaticians with access to over 600 million additional biomedical relationships compared to its earlier version, QIAGEN Biomedical KB-HD. The tool facilitates deeper investigation into disease mechanisms, pinpoint potential drug targets, and explore opportunities for repurposing existing medications.

These technological advancements are bolstering market growth as companies increasingly adopt computational tools to meet the growing demand for cost-effective, data-driven solutions for innovative therapies.

The computational biology market encounters several challenges, including data privacy concerns, high costs associated with advanced technologies, and the complexity of integrating diverse biological data sources. Furthermore, the rapid advancement of technology can outpace existing regulatory frameworks, resulting in uncertainty for companies seeking to innovate.

These hurdles can significantly impede the growth and adoption of computational biology solutions. Key players are mitigating these challenges by investing in AI-powered technologies that enhance data security and streamline data integration.

Additionally, they are focusing on developing cost-effective solutions that simplify processes and improve compliance with evolving regulations, creating a more secure and efficient research environment. By prioritizing these strategies, companies can better navigate the complexities of the market and foster innovation.

Computational Biology Industry Trends

The adoption of AI and machine learning is boosting the growth of the computational biology market by significantly improving the analysis of complex biological datasets, such as genomics and proteomics. These advanced technologies allow researchers to make faster and more accurate predictions, reducing the time and costs involved in drug discovery.

• In June 2024, scientists at Cold Spring Harbor Laboratory (CSHL) developed a computer tool called Surrogate Quantitative Interpretability for Deepnets (SQUID). This tool was designed to enhance the understanding of AI algorithms’ analysis of DNA. SQUID provides more reliable predictions regarding the impact of genetic modifications compared to traditional methods, while also minimizing data noise. It compiles over 100,000 unique DNA sequences into a comprehensive library, making it a valuable resource for genetic analysis and research.

AI tools enhance precision in identifying drug efficacy and potential side effects, leading to fewer clinical trial failures. Increased use of these technologies by pharmaceutical and biotech companies seeking innovative, cost-efficient solutions is driving the demand for AI-powered computational biology tools, which in turn is fueling market progress.

The increasing adoption of cloud computing in computational biology is stimulating the growth of the computational biology market by making high-performance computing and advanced data analysis more accessible and cost-effective.

Researchers and pharmaceutical companies can now leverage vast computational power without the need for expensive infrastructure, thereby reducing operational costs and accelerating research timelines. Moreover, cloud platforms enable seamless collaboration between global teams, fostering innovation and expediting the development of new drugs and therapies.

• In April 2024, Seed Health launched CODA, a computational biology platform for discovering and developing next-generation precision probiotics and microbiome-directed interventions. CODA's dataset integrates over three million phenotypic data points from more than 13,000 individuals across 40,000 cumulative subject years. The platform combines microbiome analysis with genetic, immune, metabolomic, and proteomic data to drive advanced research in this field.
• In February 2023, the Centre for Development of Advanced Computing (C-DAC) introduced two essential software tools to advance research in life sciences. One of these tools, the Integrated Computing Environment, serves as a cloud-based genomics computational facility tailored for bioinformatics. It combines ICE-cube, a dedicated hardware infrastructure, with ICE flakes. This software is designed to securely store and analyze genomics data at petascale to exascale levels.

Additionally, the scalability and flexibility of cloud solutions allow companies to manage growing data volumes more efficiently, thereby enhancing productivity and contributing to the expansion of the market.

Segmentation Analysis

The global market has been segmented based on offering, application end user, and geography.

By Offering

Based on offering, the market has been categorized into software, hardware, and services. The software segment led the computational biology market in 2023, reaching a valuation of USD 3.03 billion, mainly due to the increasing demand for advanced analytical tools that enhance data interpretation and accelerate research outcomes.

As researchers require sophisticated solutions to manage vast amounts of biological data, software offerings are becoming crucial for improving efficiency and precision in drug discovery.

• In May 2023, Genialis launched Genialis Expressions 3.0, a software solution to expedite the discovery of clinical and translational biomarkers. This innovative platform focuses on complex biological mechanisms, facilitating the development of novel treatment methodologies for diseases.

The ongoing advancements in software technology are expected to further propel segmental growth, as organizations actively seek to leverage data-driven insights for improved healthcare solutions and outcomes.

By Application

Based on application, the market has been categorized into drug discovery & disease modelling, preclinical drug development, clinical trial, computational genomics, computational proteomics, and others. The drug discovery & disease modelling segment captured the largest market share of 35.60% in 2023.

The drug discovery & disease modelling is further divided into target identification, target validation, lead discovery, and lead optimization. The growth of the segment is bolstered by the rising need for faster and more efficient methods to identify therapeutic targets and model disease mechanisms. Pharmaceutical companies are increasingly adopting advanced computational techniques to enhance predictive accuracy and reduce the time-to-market for new therapies.

• In April 2023, IBM and Moderna collaborated to leverage generative AI and quantum computing to advance mRNA technology, specifically for vaccine discovery and development. This partnership highlights innovative strategies in the field, fostering increased investment and interest in computational biology solutions.

The continued integration of cutting-edge technologies is expected to significantly enhance drug discovery processes and improve patient outcomes, thereby supporting segmental expansion.

By End User

Based on end user, the market has been categorized into pharmaceutical & biotechnology companies, academic & research institutions, and hospitals & clinics. The pharmaceutical & biotechnology companies segment is expected to garner the highest revenue of USD 11.04 billion by 2031. This growth is largely attributed to the increasing need for innovative drug development strategies and the rising complexity of biological systems.

Companies in this sector are increasingly leveraging computational biology tools to streamline research and development processes, thereby enhancing the efficiency of drug discovery and personalized medicine.

• In February 2023, Accenture revealed its investment in Ocean Genomics, an AI-focused biotechnology firm dedicated to creating advanced computational platforms. This partnership aimed to assist biotechnology companies in the discovery and development of personalized medicines.

In addition, the integration of artificial intelligence and machine learning with traditional methods allows for the rapid analysis of vast datasets, facilitating better decision-making. Additionally, collaborations between industry leaders and research institutions are fostering innovation.

For instance, advancements in genomic research and precision medicine are propelling investments in computational biology solutions. These factors are expected to contribute significantly to the development of the segment in the near future.

Computational Biology Market Regional Analysis

Based on region, the global market has been classified into North America, Europe, Asia-Pacific, MEA, and Latin America.

North America computational biology market accounted for the largest revenue share of 40.75% in 2023, with a valuation of USD 2.47 billion.  A strong focus on research and development and significant investments in biotechnology and pharmaceutical innovations are supporting this growth. Leading research institutions and biotech companies in the region foster collaboration and accelerates advancements in drug discovery and personalized medicine.

• For instance, in April 2024, Xaira Therapeutics launched with over USD 1 billion in committed funding, aiming to revolutionize drug discovery through artificial intelligence. This investment underscores the region's commitment to enhancing healthcare solutions.

Additionally, favorable regulatory environments and a growing emphasis on precision medicine propel regional market expansion.

Asia-Pacific market is anticipated to grow at a staggering CAGR of 18.50% over the forecast period. This notable expansion is fueled by increasing investments in research and development and advancements in technology. Countries such as Singapore and India are at the forefront of this growth, fostering innovation through collaborative initiatives.

• In July 2024, Singapore’s National Quantum Office (NQO) signed a Memorandum of Understanding with A*STAR, NUS, NSCC, and Quantinuum to access advanced quantum computers. This collaboration seeks to enhance quantum computing applications in computational biology, foster hybrid computing solutions, and develop local talent.
• Additionally, in November 2023, the Indian Institute of Science received funding from Param Hansa Philanthropie to establish a Center for Computational Oncology, promoting cross-disciplinary cooperation in cancer research.

Such initiatives significantly contribute to the region's expanding computational biology landscape, thereby boosting market growth.

Competitive Landscape

The global computational biology market report will provide valuable insight with an emphasis on the fragmented nature of the industry. Prominent players are focusing on several key business strategies such as partnerships, mergers and acquisitions, product innovations, and joint ventures to expand their product portfolio and increase their market shares across different regions.

Companies are implementing impactful strategic initiatives, such as expanding services, investing in research and development (R&D), establishing new service delivery centers, and optimizing their service delivery processes, which are likely to create new opportunities for market growth.

List of Key Companies in Computational Biology Market

• DNAnexus, Inc.
• Illumina, Inc.
• Thermo Fisher Scientific, Inc.
• Schrodinger, Inc.
• Compugen
• Aganitha AI Inc.
• Genedata AG
• QIAGEN
• Simulations Plus
• Fios Genomics

Key Industry Developments

• March 2024 (Product Launch): MiLaboratories, a frontrunner in immunological data analysis software, officially launched Platforma.bio. This innovative computational biology platform, powered by AI large language models, aims to significantly streamline and simplify biological analysis, making it more accessible to researchers across various disciplines.
• August 2024 (Product Launch): Researchers at USC developed a new artificial intelligence model, published in Nature Methods, capable of accurately predicting protein-DNA binding with accuracy across different protein types. This advancement is expected to reduce the time needed to develop new drugs and other medical treatments.

The global computational biology market is segmented as:

By Offering

• Software
• Hardware
• Services

By Application

• Drug Discovery & Disease Modelling
  • Target Identification
  • Target Validation
  • Lead Discovery
  • Lead optimization
• Preclinical Drug Development
  • Pharmacokinetics
  • Pharmacodynamics
• Clinical Trial
  • Phase I
  • Phase II
  • Phase III
  • Phase IV
• Computational Genomics
• Computational Proteomics
• Others

By End User

• Pharmaceutical & Biotechnology Companies
• Academic & Research Institutions
• Hospitals & Clinics

By Region

• North America
  • U.S.
  • Canada
  • Mexico
• Europe
  • France
  • U.K.
  • Spain
  • Germany
  • Italy
  • Russia
  • Rest of Europe
• Asia-Pacific
  • China
  • Japan
  • India
  • South Korea
  • Rest of Asia-Pacific
• Middle East & Africa
  • GCC
  • North Africa
  • South Africa
  • Rest of Middle East & Africa
• Latin America
  • Brazil
  • Argentina
  • Rest of Latin America