Global Artificial Intelligence-powered (AI) Spatial Biology Market

Report ID : 1358 | Published : 2022-08-30 | Pages: | Format: PDF/EXCEL

The Market size of the Global Artificial Intelligence-powered (AI) Spatial Biology Market is predicted to grow at an 16.4% CAGR during the projected period.

Machine learning algorithms, a subset of artificial intelligence (AI), have the capacity to analyze "big"-sized complex data in a decisive manner. As a result, it appears to be the most helpful instrument for analyzing and comprehending multi-omics data for patient-specific observations. AI-based technology specializes in both rapidly and precisely associating the qualities found in various types of data. The usefulness of using AI is in improving the speed and accuracy of exact diagnosis and, consequently, clinical decision-making. Researchers have identified subtypes within several cancer types using AI and the crucial underlying genes, proteins, RNAs, and miRNAs that could potentially serve as therapeutic targets. Additionally correlated with biological processes are these essential indicators.

The rapidly increasing data-based AI, technological improvements in deep learning, and the growing demand for cost control and operational efficiencies in drug discovery are significantly driving market expansion. Furthermore, the rising need for treatments to treat complicated disorders such as cancer is propelling the market forward. Adopting AI can potentially reduce the extensive progress required in drug discovery and clinical diagnostics research. For instance, Rebus Biosystems Inc recently announced a collaboration with Rosalind, Inc. to co-develop new spatial omics software. The technology will democratize data from Rebus EsperTM system single-cell spatial studies, making critical spatial omics insights available to the broader scientific community.

Market Segmentation:

The Artificial Intelligence-powered (AI) Spatial Biology Market is segmented on the data analysed, and applications. Based on data analysed, the market is segmented as DNA, RNA, and Protein. Based on Applications, the market is segmented as Translation Research, Drug Discovery and Development, Single Cell Analysis, Cell Biology, Clinical Diagnostics, and Other Applications.

In the region, the North America Artificial Intelligence-powered (AI) Spatial Biology Market holds a significant revenue share.

North America dominated the market in 2021. Breakthroughs in technology, the presence of mature research infrastructure and influential companies, and rising investments in drug discovery R&D have all contributed to the growth of the regional market. North America is likely to be the leading market for artificial intelligence applications in spatial omics, driven by the region's substantial and expanding demand from research and the pharmaceutical industry. It is challenging and time-consuming to extract, analyse, and interpret biological information from images, even though new high-complexity spatial imaging approaches are now available.

Competitive Landscape

The major players in the AI-driven Spatial Biology Market have shifted their focus to technological developments in product manufacturing and are launching major strategies, such as mergers, acquisitions, and partnerships with regional and international companies, to increase their product offerings and strengthen their positions in the global market. Some of the major key players in the Artificial Intelligence-powered (AI) Spatial Biology Market are Nucleai, Inc., Reveal Biosciences, Inc., Alpenglow Biosciences, SpIntellx, Inc., ONCOHOST, Pathr.ai, Phenomic AI, BioTuring Inc., Indica Labs, Rebus Biosystems, Inc., Genoskin, Algorithmic Biologics, Castle Biosciences, Inc. (TissueCypher), and Other Prominent Players.

Chapter 1. Global Artificial Intelligence-powered (AI) Spatial Biology Market Research Report-2022

1.1. Research Methodology

1.2. Research Scope & Assumptions

Chapter 2. Executive Summary

Chapter 3. Global Artificial Intelligence-powered (AI) Spatial Biology Market Snapshot

Chapter 4. Global Artificial Intelligence-powered (AI) Spatial Biology Market Variables, Trends & Scope

4.1. Market Segmentation & Scope

4.2. Drivers

4.3. Challenges

4.4. Trends

4.5. Investment and Funding Analysis

4.6. Industry Analysis – Porter’s Five Forces Analysis

4.7. Competitive Landscape & Market Share Analysis

4.8. Impact of Covid-19 Analysis

Chapter 5. Market Segmentation 1: By Data Analyzed Estimates & Trend Analysis

5.1. By Data Analyzed & Market Share, 2020 & 2030

5.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2020 to 2030 for the following By Data Analyzed:

5.2.1. DNA

5.2.2. RNA

5.2.3. Protein

Chapter 6. Market Segmentation 2: By Applications Estimates & Trend Analysis 

6.1. By Applications & Market Share, 2020& 2030

6.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2020 to 2030 for the following By Applications:

6.2.1. Translation Research 

6.2.2. Drug Discovery and Development

6.2.3. Single Cell Analysis

6.2.4. Cell Biology

6.2.5. Clinical Diagnostics

6.2.6. Other Applications

Chapter 7.  Artificial Intelligence-powered (AI) Spatial Biology Market Segmentation 3: Regional Estimates & Trend Analysis

7.1. North America 

7.1.1. North America Artificial Intelligence-powered (AI) Spatial Biology Market revenue (US$ Million) estimates and forecasts By Data Analyzed, 2019-2030

7.1.2. North America Artificial Intelligence-powered (AI) Spatial Biology Market revenue (US$ Million) estimates and forecasts By Therapy, 2019-2030

7.1.3. North America Artificial Intelligence-powered (AI) Spatial Biology Market revenue (US$ Million) estimates and forecasts by Applications, 2019-2030

7.1.4. North America Artificial Intelligence-powered (AI) Spatial Biology Market revenue (US$ Million) estimates and forecasts by country, 2019-2030

7.2. Europe

7.2.1. Europe Artificial Intelligence-powered (AI) Spatial Biology Market revenue (US$ Million) By Data Analyzed, 2019-2030

7.2.2. Europe Artificial Intelligence-powered (AI) Spatial Biology Market revenue (US$ Million) By Therapy, 2019-2030

7.2.3. Europe Artificial Intelligence-powered (AI) Spatial Biology Market revenue (US$ Million) estimates and forecasts by Applications, 2019-2030

7.2.4. Europe Artificial Intelligence-powered (AI) Spatial Biology Market revenue (US$ Million) by country, 2019-2030

7.3. Asia Pacific

7.3.1. Asia Pacific Artificial Intelligence-powered (AI) Spatial Biology Market revenue (US$ Million) By Data Analyzed, 2019-2030

7.3.2. Asia Pacific Artificial Intelligence-powered (AI) Spatial Biology Market revenue (US$ Million) By Therapy, 2019-2030

7.3.3. Asia Pacific Artificial Intelligence-powered (AI) Spatial Biology Market revenue (US$ Million) estimates and forecasts by Applications, 2019-2030

7.3.4. Asia Pacific Artificial Intelligence-powered (AI) Spatial Biology Market revenue (US$ Million) by country, 2019-2030

7.4. Latin America

7.4.1. Latin America Artificial Intelligence-powered (AI) Spatial Biology Market revenue (US$ Million) By Data Analyzed, 2019-2030

7.4.2. Latin America Artificial Intelligence-powered (AI) Spatial Biology Market revenue (US$ Million) By Therapy, 2019-2030

7.4.3. Latin America Artificial Intelligence-powered (AI) Spatial Biology Market revenue (US$ Million) estimates and forecasts by Applications, 2019-2030

7.4.4. Latin America Artificial Intelligence-powered (AI) Spatial Biology Market revenue (US$ Million) by country, 2019-2030

7.5. Middle East & Africa

7.5.1. Middle East & Africa Artificial Intelligence-powered (AI) Spatial Biology Market revenue (US$ Million) By Data Analyzed, 2019-2030

7.5.2. Middle East & Africa Artificial Intelligence-powered (AI) Spatial Biology Market revenue (US$ Million) By Therapy, 2019-2030

7.5.3. Middle East & Africa Artificial Intelligence-powered (AI) Spatial Biology Market revenue (US$ Million) estimates and forecasts by Applications, 2019-2030

7.5.4. Middle East & Africa Artificial Intelligence-powered (AI) Spatial Biology Market revenue (US$ Million) by country, 2019-2030

Chapter 8. Competitive Landscape

8.1. Major Mergers and Acquisitions/Strategic Alliances

8.2. Company Profiles

8.2.1. Nucleai, Inc.

8.2.2. Reveal Biosciences, Inc.

8.2.3. Alpenglow Biosciences

8.2.4. SpIntellx, Inc.

8.2.5. ONCOHOST

8.2.6. Pathr.ai

8.2.7. Phenomic AI 

8.2.8. BioTuring Inc.

8.2.9. Indica Labs

8.2.10. Rebus Biosystems, Inc.

8.2.11. Genoskin

8.2.12. Algorithmic Biologics

8.2.13. Castle Biosciences, Inc. (TissueCypher)

8.2.14. Other Prominent Players

By Data Analyzed

  • DNA
  • RNA
  • Protein

By Application

  • Translation Research
  • Drug Discovery and Development
  • Single Cell Analysis
  • Cell Biology
  • Clinical Diagnostics
  • Other Applications

By Region-

North America-

  • The US
  • Canada
  • Mexico

Europe-

  • Germany
  • The UK
  • France
  • Italy
  • Spain
  • Rest of Europe

Asia-Pacific-

  • China
  • Japan
  • India
  • South Korea
  • Southeast Asia
  • Rest of Asia Pacific

Latin America-

  • Brazil
  • Argentina
  • Rest of Latin America

 Middle East & Africa-

  • GCC Countries
  • South Africa

Rest of Middle East and Africa

InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.

Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.

Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.

Secondary research

The secondary research sources that are typically mentioned to include, but are not limited to:

  • Company websites, financial reports, annual reports, investor presentations, broker reports, and SEC filings.
  • External and internal proprietary databases, regulatory databases, and relevant patent analysis
  • Statistical databases, National government documents, and market reports
  • Press releases, news articles, and webcasts specific to the companies operating in the market

The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista

Primary Research:

Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies

The contributors who typically take part in such a course include, but are not limited to: 

  • Industry participants: CEOs, CBO, CMO, VPs, marketing/ type managers, corporate strategy managers, and national sales managers, technical personnel, purchasing managers, resellers, and distributors.
  • Outside experts: Valuation experts, Investment bankers, research analysts specializing in specific markets
  • Key opinion leaders (KOLs) specializing in unique areas corresponding to various industry verticals
  • End-users: Vary mainly depending upon the market

Data Modeling and Analysis:

In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.

The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.

To know more about the research methodology used for this study, kindly contact us/click here.

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