Gene Therapies For Rare Diseases Market Size, Share & Trends Analysis Report By Product (Zolgensma, Invossa K, Strimvelis, Neovasculgen, Glybera, Luxturna, Zynteglo, and Others), By Disease Type, Region And Segment Forecasts, 2023-2031.

Report Id: 1091 Pages: 185 Last Updated: 08 November 2024 Format: PDF / PPT / Excel / Power BI
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Global Gene Therapies for Rare Diseases Market Segmentation:

 Global Gene Therapies for Rare Diseases Market Based on Product

  • Zolgensma
  • Invossa K
  • Strimvelis
  • Neovasculgen
  • Glybera
  • Luxturna
  • Zynteglo
  • Others

Gene Therapies For Rare Diseases Market

Global Gene Therapies for Rare Diseases Market Based on Disease Type

  • Hemophilia
  • Duchenne Muscular Dystrophy
  • Achromatopsia
  • Cystic Fibrosis
  • Inherited Retinal Dystrophy
  • Fragile X Syndrome
  • Friedreich ataxia
  • Alpha-1 Antitrypsin Deficiency
  • Paroxysmal Nocturnal Hemoglobinuria
  • Retinitis Pigmentosa
  • Others

Global Gene Therapies for Rare Diseases Market Based on Region

Europe Gene Therapies for Rare Diseases Market by Country

  • U.K.
  • Germany
  • France
  • Italy
  • Spain
  • Russia
  • Rest of Europe

North America Gene Therapies for Rare Diseases Market by Country

  • U.S.
  • Canada

Asia Pacific Gene Therapies for Rare Diseases Market by Country

  • India
  • China
  • Japan
  • South Korea
  • Australia & New Zealand

Latin America Gene Therapies for Rare Diseases Market by Country

  • Brazil
  • Mexico
  • Rest of Latin America

Middle East & Africa Gene Therapies for Rare Diseases Market by Country

  • GCC Countries
  • South Africa
  • Rest of Middle East & Africa

Chapter 1. Methodology and Scope

1.1. Research Methodology

1.2. Research Scope & Assumptions

Chapter 2. Executive Summary

Chapter 3. Global Gene Therapies for Rare Diseases Market Snapshot

Chapter 4. Global Gene Therapies for Rare Diseases Market Variables, Trends & Scope

4.1. Market Segmentation & Scope

4.2. Drivers

4.3. Challenges

4.4. Trends

4.5. Penetration & Growth Prospect Mapping

4.6. Clinical Trial/Pipeline Analysis

4.7. Industry Analysis – Porter’s Five Forces Analysis

4.8. Competitive Landscape & Market Share Analysis

4.9. Technology Advancement in Gene Therapies for Rare Diseases Market

Chapter 5. Market Segmentation 1: Product Estimates & Trend Analysis

5.1. Product Type & Market Share, 2020 & 2028

5.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2020 to 2028 for the following Product:

5.2.1. Zolgensma

5.2.2. Invossa K

5.2.3. Strimvelis

5.2.4. Neovasculgen

5.2.5. Glybera

5.2.6. Luxturna

5.2.7. Zynteglo

5.2.8. Others

Chapter 6. Gene Therapies for Rare Diseases Market Segmentation 2: Application Estimates & Trend Analysis

6.1. Disease Type Analysis & Market Share, 2020 & 2028

6.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2020 to 2028 for the following Disease Type:

6.2.1. Human Medicine

6.2.2. Human Medicine

6.2.3. Hemophilia

6.2.4. Duchenne Muscular Dystrophy

6.2.5. Achromatopsia

6.2.6. Cystic Fibrosis

6.2.7. Inherited Retinal Dystrophy

6.2.8. Fragile X Syndrome

6.2.9. Friedreich ataxia

6.2.10. Alpha-1 Antitrypsin Deficiency

6.2.11. Paroxysmal Nocturnal Hemoglobinuria

6.2.12. Retinitis Pigmentosa

6.2.13. Others

Chapter 7. Gene Therapies for Rare Diseases Market Segmentation 3: Regional Estimates & Trend Analysis

7.1. North America

7.1.1. North America Gene Therapies for Rare Diseases Market revenue (US$ Million) estimates and forecasts by product, 2020-2028

7.1.2. North America Gene Therapies for Rare Diseases Market revenue (US$ Million) estimates and forecasts by Disease Type, 2020-2028

7.1.3. North America Gene Therapies for Rare Diseases Market revenue (US$ Million) estimates and forecasts by country, 2020-2028

7.1.3.1. U.S.

7.1.3.2. Canada

7.2. Europe

7.2.1. Europe Gene Therapies for Rare Diseases Market revenue (US$ Million) by product, 2020-2028

7.2.2. Europe Gene Therapies for Rare Diseases Market revenue (US$ Million) by Disease Type, 2020-2028

7.2.3. Europe Gene Therapies for Rare Diseases Market revenue (US$ Million) by country, 2020-2028

7.2.3.1. Germany

7.2.3.2. Poland

7.2.3.3. France

7.2.3.4. Italy

7.2.3.5. Spain

7.2.3.6. UK

7.2.3.7. Rest of Europe

7.3. Asia Pacific

7.3.1. Asia Pacific Gene Therapies for Rare Diseases Market revenue (US$ Million) by product, 2020-2028

7.3.2. Asia Pacific Gene Therapies for Rare Diseases Market revenue (US$ Million) by Disease Type, 2020-2028

7.3.3. Asia Pacific Gene Therapies for Rare Diseases Market revenue (US$ Million) by country, 2020-2028

7.3.3.1. China

7.3.3.2. India

7.3.3.3. Japan

7.3.3.4. Australia

7.3.3.5. Rest of Asia Pacific

7.4. Latin America

7.4.1. Latin America Gene Therapies for Rare Diseases Market revenue (US$ Million) by product, (US$ Million)

7.4.2. Latin America Gene Therapies for Rare Diseases Market revenue (US$ Million) by Disease Type, (US$ Million)

7.4.3. Latin America Gene Therapies for Rare Diseases Market revenue (US$ Million) by country, (US$ Million) 2020-2028

7.4.3.1. Brazil

7.4.3.2. Rest of Latin America

7.5. MEA

7.5.1. MEA revenue Gene Therapies for Rare Diseases Market revenue (US$ Million) by product, (US$ Million) 2020-2028

7.5.2. MEA Gene Therapies for Rare Diseases Market revenue (US$ Million) by Disease Type, (US$ Million)

7.5.3. MEA Gene Therapies for Rare Diseases Market revenue (US$ Million) by country, (US$ Million) 2020-2028

Chapter 8. Competitive Landscape

8.1. Company Profiles

8.1.1. 4d Molecular Therapeutics, LLC

8.1.2. Abeona Therapeutics Inc.

8.1.3. Advaxis

8.1.4. Adverum Biotech

8.1.5. Aevi Genomic

8.1.6. Applied Genetic Technologies Corporation (AGTC)

8.1.7. Alcyone Lifesciences

8.1.8. Allife Medical Science and Technology

8.1.9. Amarna Therapeutics

8.1.10. American Gene Technologies

8.1.11. Amgen

8.1.12. Amicus Therapeutics

8.1.13. Anchiano Therapeutics

8.1.14. AnGes MG

8.1.15. Apic Bio

8.1.16. Armata Pharmaceuticals

8.1.17. Arrowhead

8.1.18. Arthrogen

8.1.19. Asklepios

8.1.20. Astellas

8.1.21. AVROBIO

8.1.22. BCM Families Foundation

8.1.23. Beijing Northland

8.1.24. Benitec

8.1.25. Biogen

8.1.26. BioMarin

8.1.27. Biosidus

8.1.28. bluebird bio

8.1.29. Boryung Group

8.1.30. Brain Neurotherapeuticsy Bio

8.1.31. Celsion Corporation

8.1.32. Chiesi

8.1.33. CRISPR Therapeutics

8.1.34. CSL Behring

8.1.35. Daewoong Pharma

8.1.36. Dicerna

8.1.37. Editas Medicine

8.1.38. Eiger BioPharmaceuticals

8.1.39. Enzo Therapeutics

8.1.40. Esteve

8.1.41. Evox Therapeutics

8.1.42. Expression Therapeutics

8.1.43. Fibrocell

8.1.44. Flexion Therapeutics,

8.1.45. Fortress Biotech

8.1.46. Freeline Therapeutics

8.1.47. Gene Biotherapeutics

8.1.48. Genenta Science

8.1.49. GeneQuine

8.1.50. Genethon

8.1.51. GenSight

8.1.52. Gilead

8.1.53. Gradalis

8.1.54. GSK

8.1.55. Hanugen

8.1.56. Helixmith

8.1.57. Herantis

8.1.58. ID Pharma

8.1.59. Immusoft

8.1.60. Inovio

8.1.61. Intellia Therapeutics

8.1.62. Intrexon

8.1.63. Juventas

8.1.64. Kolon Life Science

8.1.65. Krystal Biotech

8.1.66. Locana

8.1.67. LogicBio Therapeutics

8.1.68. Lysogene

8.1.69. Medigene

8.1.70. MeiraGTx

8.1.71. Miltenyi Biotec

8.1.72. Molecular Templates

8.1.73. Momotaro-Gene

8.1.74. Neuralgene

8.1.75. Novartis

8.1.76. OncoSec

8.1.77. Orchard Therapeutics

8.1.78. Oxford Biomedica

8.1.79. Pfizer

8.1.80. Prevail Therapeutics

8.1.81. PTC Therapeutics

8.1.82. REGENXBIO

8.1.83. Renova Therapeutics

8.1.84. Reyon Pharmaceutical

8.1.85. Roche

8.1.86. Rocket Pharma

8.1.87. Roivant

8.1.88. Sangamo Therapeutics

8.1.89. Sarepta Therapeutics

8.1.90. Seelos Therapeutics

8.1.91. Solid BioSciences

8.1.92. Sterna Biologicals

8.1.93. Sutura Therapeutics

8.1.94. SynerGene

8.1.95. Takara

8.1.96. Takeda

8.1.97. Talee Bio

8.1.98. Theragene Pharma

8.1.99. Transgene

8.1.100. Ultragenyx

8.1.101. uniQure

8.1.102. VBL Therapeutics

8.1.103. Vertex

8.1.104. Voyager Therapeutics

8.1.105. Xalud

8.1.106. Xenon

8.1.107. Ziopharm

Research Design and Approach

This study employed a multi-step, mixed-method research approach that integrates:

  • Secondary research
  • Primary research
  • Data triangulation
  • Hybrid top-down and bottom-up modelling
  • Forecasting and scenario analysis

This approach ensures a balanced and validated understanding of both macro- and micro-level market factors influencing the market.

Secondary Research

Secondary research for this study involved the collection, review, and analysis of publicly available and paid data sources to build the initial fact base, understand historical market behaviour, identify data gaps, and refine the hypotheses for primary research.

Sources Consulted

Secondary data for the market study was gathered from multiple credible sources, including:

  • Government databases, regulatory bodies, and public institutions
  • International organizations (WHO, OECD, IMF, World Bank, etc.)
  • Commercial and paid databases
  • Industry associations, trade publications, and technical journals
  • Company annual reports, investor presentations, press releases, and SEC filings
  • Academic research papers, patents, and scientific literature
  • Previous market research publications and syndicated reports

These sources were used to compile historical data, market volumes/prices, industry trends, technological developments, and competitive insights.

Secondary Research

Primary Research

Primary research was conducted to validate secondary data, understand real-time market dynamics, capture price points and adoption trends, and verify the assumptions used in the market modelling.

Stakeholders Interviewed

Primary interviews for this study involved:

  • Manufacturers and suppliers in the market value chain
  • Distributors, channel partners, and integrators
  • End-users / customers (e.g., hospitals, labs, enterprises, consumers, etc., depending on the market)
  • Industry experts, technology specialists, consultants, and regulatory professionals
  • Senior executives (CEOs, CTOs, VPs, Directors) and product managers

Interview Process

Interviews were conducted via:

  • Structured and semi-structured questionnaires
  • Telephonic and video interactions
  • Email correspondences
  • Expert consultation sessions

Primary insights were incorporated into demand modelling, pricing analysis, technology evaluation, and market share estimation.

Data Processing, Normalization, and Validation

All collected data were processed and normalized to ensure consistency and comparability across regions and time frames.

The data validation process included:

  • Standardization of units (currency conversions, volume units, inflation adjustments)
  • Cross-verification of data points across multiple secondary sources
  • Normalization of inconsistent datasets
  • Identification and resolution of data gaps
  • Outlier detection and removal through algorithmic and manual checks
  • Plausibility and coherence checks across segments and geographies

This ensured that the dataset used for modelling was clean, robust, and reliable.

Market Size Estimation and Data Triangulation

Bottom-Up Approach

The bottom-up approach involved aggregating segment-level data, such as:

  • Company revenues
  • Product-level sales
  • Installed base/usage volumes
  • Adoption and penetration rates
  • Pricing analysis

This method was primarily used when detailed micro-level market data were available.

Bottom Up Approach

Top-Down Approach

The top-down approach used macro-level indicators:

  • Parent market benchmarks
  • Global/regional industry trends
  • Economic indicators (GDP, demographics, spending patterns)
  • Penetration and usage ratios

This approach was used for segments where granular data were limited or inconsistent.

Hybrid Triangulation Approach

To ensure accuracy, a triangulated hybrid model was used. This included:

  • Reconciling top-down and bottom-up estimates
  • Cross-checking revenues, volumes, and pricing assumptions
  • Incorporating expert insights to validate segment splits and adoption rates

This multi-angle validation yielded the final market size.

Forecasting Framework and Scenario Modelling

Market forecasts were developed using a combination of time-series modelling, adoption curve analysis, and driver-based forecasting tools.

Forecasting Methods

  • Time-series modelling
  • S-curve and diffusion models (for emerging technologies)
  • Driver-based forecasting (GDP, disposable income, adoption rates, regulatory changes)
  • Price elasticity models
  • Market maturity and lifecycle-based projections

Scenario Analysis

Given inherent uncertainties, three scenarios were constructed:

  • Base-Case Scenario: Expected trajectory under current conditions
  • Optimistic Scenario: High adoption, favourable regulation, strong economic tailwinds
  • Conservative Scenario: Slow adoption, regulatory delays, economic constraints

Sensitivity testing was conducted on key variables, including pricing, demand elasticity, and regional adoption.

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Frequently Asked Questions

The Gene Therapies For Rare Diseases Market is expected to grow at an 20.0 % CAGR during the forecast period for 2023-2031.

4d Molecular Therapeutics, LLC, Abeona Therapeutics Inc., Advaxis, Adverum Biotech, Aevi Genomic, Applied Genetic Technologies Corporation (AGTC), Alc

Product and Disease Type are the key segments of the Gene Therapies For Rare Diseases Market.

North American region is leading the Gene Therapies For Rare Diseases Market.

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