Human-Induced Pluripotent Stem Cells (hiPSCs) Preclinical Disease Model Market Size is predicted to grow at an 11.2% CAGR during the forecast period for 2024-2031.
Human-induced pluripotent stem cells (hiPSCs) are a pivotal tool in biomedical research, particularly for preclinical disease modelling and drug development. Derived from adult somatic cells like skin or blood cells, hiPSCs are reprogrammed to an embryonic-like pluripotent state. This transformation enables them to differentiate into various cell types, including those affected by specific diseases. Therefore, hiPSCs provide a potent substrate for the investigation of disease mechanisms at the cellular level and the evaluation of potential therapies in controlled laboratory environments. One significant application of hiPSCs is their ability to generate disease-specific cell lines from patients, allowing for personalized disease modelling and tailored drug screening. By differentiating hiPSCs into affected cell types such as cardiomyocytes, neurons, or pancreatic beta cells, researchers can closely investigate disease pathology and explore therapeutic interventions. Moreover, hiPSCs can be genetically modified to correct disease-causing mutations, providing insights into how genetic alterations contribute to disease progression and offering a foundation for developing gene therapies.
The expansive disease modeling capacity of human-induced pluripotent stem cells (hiPSCs) stands as a pivotal driver in the preclinical disease model market. With the ability to simulate a wide array of conditions such as cardiovascular disorders, neurological ailments, and metabolic diseases, hiPSCs offer unmatched versatility. This capability not only enhances our comprehension of disease mechanisms but also accelerates the development and testing of novel therapeutic interventions.
The human-induced pluripotent stem cells (hiPSCs) preclinical disease model market is segmented by disease, products and services. By disease, the market is segmented into neurological disorders and dystrophies, cardiac disorders, retinal eye disease, metabolic disorders, liver disease, and others. The products and services market is categorized into disease model, reprogramming service, differentiation service, screening service, characterization service, and others.
The neurological disorders segment is a driving force in the human induced pluripotent stem cells (hiPSCs) preclinical disease model market for several compelling reasons. Conditions such as Parkinson's, Alzheimer's, Huntington's, ALS, schizophrenia, and various neurodevelopmental disorders represent significant focal points for hiPSC-based disease modelling. HiPSCs offer the unique ability to generate disease-specific cell lines and differentiate into key affected cell types like neurons and glia, providing invaluable insights into neurological disease mechanisms and accelerating drug discovery efforts. Compared to other disease areas, the successful implementation of hiPSC-based models has been particularly pronounced in neurology, likely due to the urgent need for therapeutic advancements and the unprecedented ability of hiPSCs to closely mimic patient-specific disease conditions.
The human-induced pluripotent stem cells (hiPSCs) preclinical disease model market is experiencing significant growth, particularly in Disease Modeling for neurological disorders and cardiac diseases. This growth is fueled by several factors identified in recent searches. Firstly, hiPSC-based models have demonstrated notable success in unravelling the mechanisms of neurological disorders like Parkinson's, Alzheimer's, Huntington's, ALS, and neurodevelopmental conditions, addressing critical gaps in disease understanding. Secondly, there is a shift towards utilizing hiPSC-based models as alternatives to animal testing in preclinical trials, aiming for more predictive endpoints that align better with human physiology and regulatory standards.
North America's hiPSCs preclinical disease model market is increasing due to robust pharmaceutical and biotech sectors, particularly in the U.S. These industries are actively adopting hiPSC-based technologies for drug development. Supported by a favourable regulatory environment and significant funding from entities like the NIH, alongside leading research institutions such as Harvard and Stanford, North America remains at the forefront of advancing hiPSC-based disease modelling and biomedical innovation.
| Report Attribute | Specifications |
| Growth Rate CAGR | CAGR of 11.2 % from 2024 to 2031 |
| Quantitative Units | Representation of revenue in US$ Bn and CAGR from 2024 to 2031 |
| Historic Year | 2019 to 2023 |
| Forecast Year | 2024-2031 |
| Report Coverage | The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
| Segments Covered | By Disease, By Product and Services, and By Region |
| Regional Scope | North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
| Country Scope | U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; France; Italy; Spain; South Korea; Southeast Asia; |
| Competitive Landscape | Axol Bioscience Ltd, DefiniGEN, REPROCELL, The Jackson Laboratory, Creative Biolabs, Cyagen, FUJIFILM Cellular Dynamics, ElevateBio, Bio-Techne, BPS Bioscience, Inc., Catalent, Inc, Ncardia, NEXEL Co, Evotec’s, iXCells Biotechnologies, Elixirgen, Other Prominent Players |
| Customization Scope | Free customization report with the procurement of the report, Modifications to the regional and segment scope. Geographic competitive landscape. |
| Pricing and Available Payment Methods | Explore pricing alternatives that are customized to your particular study requirements. |
Human-Induced Pluripotent Stem Cells (hiPSCs) Preclinical Disease Model Market by Disease-
Human-Induced Pluripotent Stem Cells (hiPSCs) Preclinical Disease Model Market by Products and Services-
Human-Induced Pluripotent Stem Cells (hiPSCs) Preclinical Disease Model Market by Region-
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & Africa-
This study employed a multi-step, mixed-method research approach that integrates:
This approach ensures a balanced and validated understanding of both macro- and micro-level market factors influencing the market.
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.
Secondary data for the market study was gathered from multiple credible sources, including:
These sources were used to compile historical data, market volumes/prices, industry trends, technological developments, and competitive insights.
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.
Primary interviews for this study involved:
Interviews were conducted via:
Primary insights were incorporated into demand modelling, pricing analysis, technology evaluation, and market share estimation.
All collected data were processed and normalized to ensure consistency and comparability across regions and time frames.
The data validation process included:
This ensured that the dataset used for modelling was clean, robust, and reliable.
The bottom-up approach involved aggregating segment-level data, such as:
This method was primarily used when detailed micro-level market data were available.
The top-down approach used macro-level indicators:
This approach was used for segments where granular data were limited or inconsistent.
To ensure accuracy, a triangulated hybrid model was used. This included:
This multi-angle validation yielded the final market size.
Market forecasts were developed using a combination of time-series modelling, adoption curve analysis, and driver-based forecasting tools.
Given inherent uncertainties, three scenarios were constructed:
Sensitivity testing was conducted on key variables, including pricing, demand elasticity, and regional adoption.