AI in Cell and Gene Therapy Market; By Technology (Machine Learning (ML) {Deep Learning, Supervised Learning, Unsupervised Learning}, Generative AI, Natural Language Processing), By Indication (Oncology, Immunology, Cardiology & Neurology, Infectious Disease), By Application (Clinical Trials, Drug Discovery, Precision Medicine), By End-User (Biopharmaceutical Companies, Research Institutes, Healthcare Providers) and By Region; Global Insights & Forecast (2024 - 2030)

The acquisition of smaller players and product innovations by major players are driving the AI in cell and gene therapy market. The AI in cell and gene therapy market is a competitive market, the prominent players in the global market include Dyno Therapeutics, Exelixis, Form Bio, Généthon, DeepMind (Google), IBM, Insilico, Microsoft, Nosis Bio, Oxford BioMedica, SK Pharmteco, Thales

Published: February, 2024
| Report ID: HC3010
| LifeSciences & Healthcare

The cell and gene therapies (CGT) treat, prevent, and even cure diseases. These methods have the potential to help address the root causes of both genetic and acquired diseases. In recent years, there have been several advances in AI technology have enabled the application of AI in complex operations including CGT. Research spanning from preclinical development to post-market surveillance underscores the growing significance of AI in this context. Its potential to improve and expedite various phases of therapy development and application has become increasingly apparent. The market is expected to grow due to the generation of large and complex healthcare datasets by AI.

The integration of AI is becoming prevalent in the CGT sector, driven by advancements in digital technologies, computing power, and the influx of data. The transformative surge of AI is creating an incredible mark on every field including CGT and anticipated to transform both the ecosystem and value chain of CGT.

Major market players in CGT sector are adopting collaboration and partnerships strategies to gain market share

Technology and pharmaceutical players increasing their investments in AI to expand their businesses. Various companies such as Microsoft, Google, and Thales, amongst others, are investing with emerging players in biopharmaceutical companies to establish themselves in the field of AI in CGT market. For instance, in March 2023, researchers used the Goggles' DeepMind AI system "AlphaFold" to develop a tiny syringe that can inject proteins into the cells. Moreover, in June 2022, Microsoft collaborated with Oxfort BioMedica, UK headquartered company to use their AI technology to make CGT manufacturing easier and cheaper.

Increasing complexities, data breaches, and concerns about data privacy are hindering market growth

While AI has found multiple applications across various industries, its integration into the field of CGT remains somewhat constrained. This limitation primarily stems from the intricate challenges faced by healthcare providers. Similar to other health information technologies, AI raises concerns about data privacy and security. This is especially pertinent in today's landscape, marked by the prevalence of cyberattacks, where patients' protected health information has become a lucrative target for identity thieves and cybercriminals. This aids complexity in the rapid adoption of AI in CGT sector.

High potential of AI technology in genomics and drug discovery is projected to drive market growth opportunities

AI is accelerating R&D in the pharmaceutical industry by efficiently handling complex molecular data. In CGT, AI is optimizing delivery methods through deep learning, allowing for the design of immune-evasive viral vectors, and enhancing treatment effectiveness. For clinical trials, AI streamlines patient recruitment by analyzing medical records and offers a solution in the form of synthetic control arms, reducing costs and ethical concerns.

AI-driven digital twins transform manufacturing for consistent product quality, optimize supply chains, ensure regulatory compliance, streamline processes, and accelerate the development of advanced cell and gene therapies. The transformative potential of AI in the CGT sector is substantial, offering benefits in R&D, manufacturing, and beyond.

Accelerating research, optimizing patient matching, and enhancing treatment outcomes in healthcare with machine learning technology

Machine learning (ML) technology has witnessed remarkable growth in recent years, it is mainly driven by the increasing adoption of AI and data-driven solutions across various industries. ML, a subset of AI, empowers computers to learn and make predictions or decisions without being programmed, making it an invaluable tool for businesses. Natural language processing (NLP) and predictive analytics are also employed in the CGT segment. NLP has the capability to examine unstructured data sourced from medical records, enabling the identification of individuals exhibiting particular symptoms, biomarkers, and/or diagnoses aligning with the inclusion criteria for clinical trials. It is revolutionizing the cell and gene therapy market by accelerating research and development processes, optimizing patient matching, and improving treatment outcomes.

Dominance of clinical trials application fuels growth in AI for CGT market

Clinical trials application segment held the largest market share in the AI in CGT market. Increased revenue from this segment is attributed to substantial investments in research, drug discovery, drug development, and clinical trials for newly developed medications. Factors such as patent expirations, an increasing demand for accelerated clinical trial outcomes, and the need for innovative drug advancements is expected to drive segment growth. Moreover, AI's integration into patient recruitment processes is expected to reduce time and costs, further fueling the demand for AI in CGT market.

Source: Intent Market Research Analysis

Biopharmaceutical companies accounted for highest market share in 2023

Biopharmaceutical companies accounted for highest market share in 2023 owing to widespread applications of AI in various technologies. This trend is attributed to the extensive research efforts and adoption of AI within various biopharmaceutical companies. The widespread applications of AI across diverse technologies have spurred its integration into the strategies and operations of these companies, solidifying their position in the AI in CGT market.

North America's market thrives, fuelled by the strong influence and prevalence of key industry players

North America accounted for the highest market share in 2023 as the region is characterized by an increased inclination towards the advanced and latest digital technologies. The strong and developed healthcare, IT, and telecommunications infrastructure in North America has supported the growth of AI in CGT market. Additionally, the North American market experiences growth fueled by the substantial presence of key industry players.

The acquisition of smaller players and product innovations by major players are driving the market growth

The AI in CGT market is characterized by intense competition due to the presence of numerous international and emerging players. These industry leaders are primarily focused on acquiring smaller players and innovating their product lines to cater to changing consumer preferences and needs.

  • In July 2023, Généthon and Thales collaborated to develop digital models for improving gene therapy bio-production yields. The objective of this collaboration is to improve production yields, reducing the production costs of innovative therapy drugs
  • In July 2023, CF Foundation funds Nosis Bio to design gene therapy using AI
  • In September 2022, WhiteLab Genomics raises $10.0 million for AI-powered genomic therapies platform.
  • In August 2022, IBM Research REPROCELL and STFC announced a new initiative using AI to advance the discovery of new drug cell and gene therapies and improve the design of clinical trials. This collaboration aims to build discovery-driven communities that make a lasting impact, including in the areas of drug discovery, CGT and clinical trial
  • In July 2021, NJII partnered with McKinsey & Company to establish a new center aimed at advancing manufacturing excellence and operations in the field of CGT

AI in Cell and Gene Therapy Market Coverage

The report provides key insights into the AI in cell and gene therapy market, and it focuses on technological developments, trends, and initiatives taken by the government in this sector. The report delves into market drivers, restraints, and opportunities, and analyses key players as well as the competitive landscape within the market

Report Scope

Report Features

Description

Market Size (2023-e)

USD XX billion

Forecast Revenue (2030)

USD XX billion

CAGR (2024-2030)

XX%

Base Year for Estimation

2023-e

Historic Year

2022

Forecast Period

2024-2030

Report Coverage

Revenue Forecast, Market Dynamics, Competitive Landscape, Recent Developments

Segments Covered

By Technology (Machine Learning (ML) {Deep Learning, Supervised Learning, Unsupervised Learning, Other ML technologies}, Generative AI, Natural Language Processing, Others), By Indication (Oncology, Immunology, Cardiology & Neurology, Infectious Disease, Others), By Application (Clinical Trials, Drug Discovery, Precision Medicine, Others), By End-User (Biopharmaceutical Companies, Research Institutes, Healthcare Providers, Others)

Regional Analysis

North America (US, Canada), Europe (Germany, France, UK, Spain, Italy), Asia Pacific (China, Japan, South Korea, India) Latin America (Brazil, Argentina), Middle East and Africa (Saudi Arabia, South Africa, Turkey, United Arab Emirates)

Competitive Landscape

Dyno Therapeutics, Exelixis, Form Bio, Généthon, DeepMind (Google), IBM, Insilico, Microsoft, Nosis Bio, Oxford BioMedica, SK Pharmteco, Thales

Customization Scope

Customization for segments, region/country-level will be provided. Moreover, additional customization can be done based on the requirements.

Purchase Options

We have three licenses to opt for Single User License, Multi-User License (Up to 5 Users), Corporate Use License (Unlimited User and Printable PDF)

1.Introduction

1.1.Study Assumptions and Market Definition

1.2.Scope of the Study

2.Research Methodology

3.Executive Summary

4.Market Dynamics

4.1.Market Growth Drivers

4.1.1.Generation of Large and Complex Healthcare Datasets

4.1.2.Improving Computing Power and Declining Hardware Cost Fuelling

4.1.3.Rising Number of Partnerships and Collaborations

4.2.Market Growth Challenges

4.2.1.Increasing Complexities, and Data Breaches Issues

4.2.2.Data Privacy Concerns

4.3.Market Growth Opportunities

4.3.1.Rising Potential of AI Technology in Genomics and Drug Discovery

5.Pestle Analysis 

6.Porter’s Five Forces Analysis

7.Market Outlook

7.1.Supply Chain Analysis

7.2.Cell and Gene Industry Outlook

7.3.Regulatory Analysis

7.4.Technological Advancement

7.5.Pipeline Analysis

7.6.Investment Scenario

7.7.Evolution of AI Technology

7.8.Value Chain Analysis

7.9.Pricing Model Analysis

7.10. Business Model Analysis

7.11. Key Conferences and Events

7.12. Case Studies

8.Market Segment Outlook

8.1.Segment Synopsis

8.2.By Technology (Market Size and Forecast by Value - USD billion, 2024 - 2030)

8.2.1.Machine Learning

8.2.1.1.Deep Learning

8.2.1.2.Supervised Learning

8.2.1.3.Unsupervised Learning

8.2.1.4.Other ML technologies

8.2.2.Generative AI

8.2.3.Natural Language Processing

8.2.4.Others

8.3.By Indication (Market Size and Forecast by Value - USD billion, 2024 - 2030)

8.3.1.Oncology

8.3.2.Immunology

8.3.3.Cardiology & Neurology

8.3.4.Infectious Disease

8.3.5.Others

8.4.By Application (Market Size and Forecast by Value - USD billion, 2024 - 2030)

8.4.1.Clinical Trials

8.4.2.Drug Discovery and Development

8.4.3.Precision Medicine

8.4.4.Others

8.5.By End-User (Market Size and Forecast by Value - USD billion, 2024 - 2030)

8.5.1.Biopharmaceutical Companies

8.5.2.Research Institutes

8.5.3.Healthcare Providers

8.5.4.Others

9.Regional Outlook

9.1.Global Market Synopsis

9.2.North America (Market Size and Forecast by Value - USD billion, 2024 - 2030)

9.2.1.North America AI in Cell and Gene Therapy Market Outlook

9.2.2.US

9.2.2.1.US AI in CGT Market, By Technology

9.2.2.2.US AI in CGT Market, By Indication

9.2.2.3.US AI in CGT Market, By Application

9.2.2.4.US AI in CGT Market, By End-User

9.2.3.Canada

                         *Note: Cross-segmentation by segments for each region will be covered as shown above

9.3.Europe (Market Size and Forecast by Value - USD billion, 2024 - 2030)

9.3.1.Europe AI in CGT Market Outlook

9.3.2.Germany

9.3.3.UK

9.3.4.France

9.3.5.Spain

9.3.6.Italy

9.4.Asia-Pacific (Market Size and Forecast by Value - USD billion, 2024 - 2030)

9.4.1.Asia-Pacific AI in CGT Market Outlook

9.4.2.China

9.4.3.India

9.4.4.Japan

9.5.Latin America (Market Size and Forecast by Value - USD billion, 2024 - 2030)

9.5.1.Latin America AI in CGT Market Outlook

9.5.2.Brazil

9.5.3.Argentina

9.6.Middle East & Africa (Market Size and Forecast by Value - USD billion, 2024 - 2030)

9.6.1.Middle East & Africa AI in CGT Market Outlook

9.6.2.Saudi Arabia

9.6.3.South Africa

9.6.4.Turkey

9.6.5.United Arab Emirates

10. Competitive Landscape

10.1. Market Share Analysis

10.2. Product/Service Benchmarking

10.3. Company Strategy Analysis

10.4. Competitive Matrix

11. Company Profiles

11.1. AI in CGT Market (Supply-Side)

11.1.1. Dyno Therapeutics

11.1.1.1. Company Synopsis

11.1.1.2. Company Financials

11.1.1.3. Product/Service Portfolio

11.1.1.4. Recent Developments

    *Note: All the companies in the section 11.1 will cover same sub-chapters as above

11.1.2. Exelixis

11.1.3. Form Bio

11.1.4. Généthon

11.1.5. DeepMind (Google)

11.1.6. IBM

11.1.7. Insilico

11.1.8. Microsoft

11.1.9. Nosis Bio

11.1.10. Oxford BioMedica

11.1.11. SK Pharmteco

11.1.12. Thales

11.2.  AI in CGT Market (Demand-Side)

11.2.1.AstraZeneca

11.2.1.1.Company Synopsis

11.2.1.2.Company Financials

11.2.1.3.Recent Developments

              *Note: All the companies in the section 11.2 will cover same sub-chapters as above

11.2.2.Bayer

11.2.3.Bio-Techne 

11.2.4.bioMérieux

11.2.5.Biogen

11.2.6.Cytiva 

11.2.7.Dendreon Pharmaceuticals

11.2.8.Helixmith

11.2.9.JCR Pharmaceuticals

11.2.10.Kolon TissueGene

11.2.11.Merck

11.2.12.Novartis

11.2.13.Pfizer

 

 

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The research factors used in our methodology vary depending on the specific market being analyzed. To begin with, we incorporate both demand and supply side information into our model to identify and address market gaps. Additionally, we also employ approaches such as Macro-Indicator Analysis, Factor Analysis, Value Chain-Based Sizing, and forecasting to further increase the accuracy of the numbers and validate the findings.

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