The purest type of electronic clinical data which is obtained at the point of care at a medical facility, hospital, clinic or practice. Often referred to as the electronic medical record (EMR), the EMR is generally not available to outside researchers. The data collected includes administrative and demographic information, diagnosis, treatment, prescription drugs, laboratory tests, physiologic monitoring data, hospitalization, patient insurance, etc.

Individual organizations such as hospitals or health systems may provide access to internal staff. Larger collaborations, such as the NIH Collaboratory Distributed Research Network provides mediated or collaborative access to clinical data repositories by eligible researchers. Additionally, the UW De-identified Clinical Data Repository (DCDR) and the Stanford Center for Clinical Informatics allow for initial cohort identification.

About Dataset:

333 scholarly articles cite this dataset.

Unique identifier: DOI

Dataset updated: 2023

Authors: Haoyang Mi

In this dataset, we have two dataset:

1- Clinical Data_Discovery_Cohort: Name of columns: Patient ID Specimen date Dead or Alive Date of Death Date of last Follow Sex Race Stage Event Time

2- Clinical_Data_Validation_Cohort Name of columns: Patient ID Survival time (days) Event Tumor size Grade Stage Age Sex Cigarette Pack per year Type Adjuvant Batch EGFR KRAS

Feel free to put your thought and analysis in a notebook for this datasets. And you can create some interesting and valuable ML projects for this case. Thanks for your attention.

The Clinical Questions Collection is a repository of questions that have been collected between 1991 – 2003 from healthcare providers in clinical settings across the country. The questions have been submitted by investigators who wish to share their data with other researchers. This dataset is no-longer updated with new content. The collection is used in developing approaches to clinical and consumer-health question answering, as well as researching information needs of clinicians and the language they use to express their information needs. All files are formatted in XML.

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US Clinical Trials Market Size 2025-2029

The us clinical trials market size is forecast to increase by USD 6.5 billion, at a CAGR of 5.3% between 2024 and 2029.

The Clinical Trials Market in the US is witnessing significant growth, driven by the increasing number of clinical trials for drugs and advancements in technology and scientific research. The rise in clinical trials is attributed to the development of new therapies and treatments across various therapeutic areas, leading to a surge in demand for clinical trial services. However, this market faces challenges, including the escalating costs of clinical trials. The complexity and intricacy of clinical trials have resulted in increased expenses, making it essential for market participants to optimize their resources and processes. Another challenge is the regulatory landscape, which is constantly evolving, necessitating clinical trial sponsors to stay updated and adapt to new regulations to ensure compliance. To capitalize on market opportunities and navigate challenges effectively, companies must focus on implementing innovative solutions, improving operational efficiency, and maintaining regulatory compliance.

What will be the size of the US Clinical Trials Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The clinical trials market in the US is characterized by continuous advancements in drug development, driven by the integration of technology and data-driven insights. In vitro studies and preclinical research pave the way for efficacy trials in neurological, cancer, cardiovascular, and other therapeutic areas. Big data analytics plays a pivotal role in drug metabolism studies, enabling the optimization of phase III trials through precision medicine and biomarker discovery. Wearable devices and mobile health (mHealth) facilitate real-time monitoring in clinical pharmacology, while cloud computing streamlines clinical trial software and dose-finding studies. Gene therapy and regenerative medicine are gaining traction in orphan drug development, with animal studies and target validation shaping the landscape. Safety trials in phase I and II are complemented by digital health solutions, while phase IV trials ensure long-term safety monitoring. Drug interactions and phase I trials are addressed through device development and clinical trial software, respectively. Overall, the US clinical trials market is dynamic, with innovation at the forefront of drug development, from first-in-human studies to phase iv trials.

How is this market segmented?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. TypePhase IIIPhase IPhase IIPhase IVService TypeInterventional studiesObservational studiesExpanded access studiesIndicationOncologyCNSAutoimmune/inflammationOthersGeographyNorth AmericaUS

By Type Insights

The phase iii segment is estimated to witness significant growth during the forecast period.

The clinical trials market in the US is characterized by the involvement of various entities in the intricate process of testing new drugs and medical treatments for public use. In the final phase of this process, the phase III clinical trials play a pivotal role in assessing the safety and efficacy of investigational treatments on a larger population. This data-intensive stage is crucial for determining the potential benefits and risks before regulatory approval. Personalized medicine and adaptive designs have become integral to clinical trials, enabling customized treatment plans and flexible trial designs. Medical device companies and diagnostic firms collaborate to integrate devices and diagnostics into clinical trials, enhancing data collection and analysis. Data privacy and security are paramount, with stringent regulations ensuring patient data confidentiality and integrity. Pharmaceutical companies invest heavily in clinical trials, collaborating with academic research centers, biotechnology firms, and venture capitalists to share resources and expertise. Informed consent, ethical considerations, and regulatory submissions are critical components of the clinical trial process. Machine learning and artificial intelligence are increasingly used for data analysis, clinical trial optimization, and patient recruitment. Government funding and patient advocacy also play significant roles in advancing clinical trials. Real-world evidence and observational studies provide valuable insights into the effectiveness and safety of treatments in diverse populations. Biomarker analysis and interim analysis help monitor treatment progress and adjust trial designs accordingly. Q

The PTSD-Repository is a comprehensive database of PTSD trials. The PTSD-Repository allows clinical, research, education, and policy stakeholders to understand current research on treatment effectiveness and harms, and enable informed decisions about future research, mental health policy, and clinical care priorities. This report updates the studies and variables included in the PTSD-Repository to include recently published trials, interventions targeting comorbid PTSD/SUD (substance use disorder), variables related to comorbidities such as suicide and SUDs, and risk of bias (ROB) assessment.

The Comparative Effectiveness Review (Update Report) and Evidence Tables (Appendix E, F-1, & G-1) are included in the downloadable .zip file. For more information, visit AHRQ's page, and open the "Previous Versions" tab: https://effectivehealthcare.ahrq.gov/products/ptsd-pharm-non-pharm-treatment/research

CheckUp: Stages of the optimisation process (objective, sample, and results by optimisation processes).

This is the current Medical Service Study Area. California Medical Service Study Areas are created by the California Department of Health Care Access and Information (HCAI).Check the Data Dictionary for field descriptions.Search for the Medical Service Study Area data on the CHHS Open Data Portal.Checkout the California Healthcare Atlas for more Medical Service Study Area information.This is an update to the MSSA geometries and demographics to reflect the new 2020 Census tract data. The Medical Service Study Area (MSSA) polygon layer represents the best fit mapping of all new 2020 California census tract boundaries to the original 2010 census tract boundaries used in the construction of the original 2010 MSSA file. Each of the state's new 9,129 census tracts was assigned to one of the previously established medical service study areas (excluding tracts with no land area), as identified in this data layer. The MSSA Census tract data is aggregated by HCAI, to create this MSSA data layer. This represents the final re-mapping of 2020 Census tracts to the original 2010 MSSA geometries. The 2010 MSSA were based on U.S. Census 2010 data and public meetings held throughout California.Source of update: American Community Survey 5-year 2006-2010 data for poverty. For source tables refer to InfoUSA update procedural documentation. The 2010 MSSA Detail layer was developed to update fields affected by population change. The American Community Survey 5-year 2006-2010 population data pertaining to total, in households, race, ethnicity, age, and poverty was used in the update. The 2010 MSSA Census Tract Detail map layer was developed to support geographic information systems (GIS) applications, representing 2010 census tract geography that is the foundation of 2010 medical service study area (MSSA) boundaries. ***This version is the finalized MSSA reconfiguration boundaries based on the US Census Bureau 2010 Census. In 1976 Garamendi Rural Health Services Act, required the development of a geographic framework for determining which parts of the state were rural and which were urban, and for determining which parts of counties and cities had adequate health care resources and which were "medically underserved". Thus, sub-city and sub-county geographic units called "medical service study areas [MSSAs]" were developed, using combinations of census-defined geographic units, established following General Rules promulgated by a statutory commission. After each subsequent census the MSSAs were revised. In the scheduled revisions that followed the 1990 census, community meetings of stakeholders (including county officials, and representatives of hospitals and community health centers) were held in larger metropolitan areas. The meetings were designed to develop consensus as how to draw the sub-city units so as to best display health care disparities. The importance of involving stakeholders was heightened in 1992 when the United States Department of Health and Human Services' Health and Resources Administration entered a formal agreement to recognize the state-determined MSSAs as "rational service areas" for federal recognition of "health professional shortage areas" and "medically underserved areas". After the 2000 census, two innovations transformed the process, and set the stage for GIS to emerge as a major factor in health care resource planning in California. First, the Office of Statewide Health Planning and Development [OSHPD], which organizes the community stakeholder meetings and provides the staff to administer the MSSAs, entered into an Enterprise GIS contract. Second, OSHPD authorized at least one community meeting to be held in each of the 58 counties, a significant number of which were wholly rural or frontier counties. For populous Los Angeles County, 11 community meetings were held. As a result, health resource data in California are collected and organized by 541 geographic units. The boundaries of these units were established by community healthcare experts, with the objective of maximizing their usefulness for needs assessment purposes. The most dramatic consequence was introducing a data simultaneously displayed in a GIS format. A two-person team, incorporating healthcare policy and GIS expertise, conducted the series of meetings, and supervised the development of the 2000-census configuration of the MSSAs.MSSA Configuration Guidelines (General Rules):- Each MSSA is composed of one or more complete census tracts.- As a general rule, MSSAs are deemed to be "rational service areas [RSAs]" for purposes of designating health professional shortage areas [HPSAs], medically underserved areas [MUAs] or medically underserved populations [MUPs].- MSSAs will not cross county lines.- To the extent practicable, all census-defined places within the MSSA are within 30 minutes travel time to the largest population center within the MSSA, except in those circumstances where meeting this criterion would require splitting a census tract.- To the extent practicable, areas that, standing alone, would meet both the definition of an MSSA and a Rural MSSA, should not be a part of an Urban MSSA.- Any Urban MSSA whose population exceeds 200,000 shall be divided into two or more Urban MSSA Subdivisions.- Urban MSSA Subdivisions should be within a population range of 75,000 to 125,000, but may not be smaller than five square miles in area. If removing any census tract on the perimeter of the Urban MSSA Subdivision would cause the area to fall below five square miles in area, then the population of the Urban MSSA may exceed 125,000. - To the extent practicable, Urban MSSA Subdivisions should reflect recognized community and neighborhood boundaries and take into account such demographic information as income level and ethnicity. Rural Definitions: A rural MSSA is an MSSA adopted by the Commission, which has a population density of less than 250 persons per square mile, and which has no census defined place within the area with a population in excess of 50,000. Only the population that is located within the MSSA is counted in determining the population of the census defined place. A frontier MSSA is a rural MSSA adopted by the Commission which has a population density of less than 11 persons per square mile. Any MSSA which is not a rural or frontier MSSA is an urban MSSA. Last updated December 6th 2024.

🔭 Overview

  R2MED: First Reasoning-Driven Medical Retrieval Benchmark

R2MED is a high-quality, high-resolution synthetic information retrieval (IR) dataset designed for medical scenarios. It contains 876 queries with three retrieval tasks, five medical scenarios, and twelve body systems.

Dataset

Q

D

Avg. Pos Q-Len D-Len

Biology 103 57359 3.6 115.2 83.6

Bioinformatics77 47473 2.9 273.8 150.5

Medical Sciences 88 34810 2.8 107.1 122.7

MedXpertQA-Exam 97… See the full description on the dataset page: https://huggingface.co/datasets/R2MED/PMC-Clinical.

Explore the historical Whois records related to update-medical-oncology.com (Domain). Get insights into ownership history and changes over time.

ABSTRACT Recent advances in the understanding of tumor driver mutations, signaling pathways that lead to tumor progression, and the better understanding of the interaction between tumor cells and the immune system are revolutionizing cancer treatment. The pace at which new treatments are approved and the prices at which they are set have made it even more difficult to offer these treatments in countries like Brazil. In this review we present for the non-oncologist these new treatments and compare their availability in Brazilian public health system and private health system with that of developed countries.

This dataset contains the following accompanying material: 1) The two codebooks of the qualitative analysis of interviews conducted with healthcare delivery organizations and medical device manufacturers, 2) The Interview protocols used for the same interviews, and 3) Table 3, depicting update cases for specific connected medical devices.

Primary Care Networks were created in July 2019 to provide accessible and integrated primary, mental health, and community care for patients. The bulk of the PCN workforce consists of Direct Patient Care staff, funded by the Additional Roles Reimbursement Scheme (ARRS), and each PCN has the flexibility and autonomy to determine which roles are required to meet the specific needs of their local populations. Initially, recruitment focused on clinical pharmacists and social prescribing link workers, with more roles being included over subsequent years. Information about the PCN workforce is provided directly by each PCN and recorded in the National Workforce Reporting Service (NWRS), the same system used to collect information about the general practice workforce. This snapshot report includes England, Integrated Care Board (ICB), Sub-ICB Location and PCN-level figures for Clinical Directors, Direct Patient Care Workers and Admin/Non-Clinical staff working in PCNs on the last day of each calendar month. The level of detail in the information that we can collect about each individual varies, as there are different ways that individuals can be contracted to work for their PCN. Please read the Background Data Quality section for more information. The data were first published to a quarterly schedule beginning in March 2020. As both the proportion of PCNs submitting data to NWRS and data quality have improved, monthly publications began in January 2023. We are working continually to improve our publications and we welcome feedback from all users by email to: PrimaryCareWorkforce@nhs.net. Links to other publications presenting healthcare workforce information can be found under Related Links. Information about the PCN workforce is provided directly by each PCN and recorded in the National Workforce Reporting Service (NWRS), which is the same system that is used to collect information about the general practice workforce. This snapshot report includes England, Integrated Care Board (ICB), Sub-ICB Location and PCN-level figures for Clinical Directors, Direct Patient Care Workers and Admin/Non-Clinical staff working in PCNs on the last day of each calendar month. The level of detail in the information that we can collect about each individual varies, as there are different ways that individuals can be contracted to work for their PCN. Please read the Background Data Quality section for more information. The data were first published to a quarterly schedule beginning in March 2020. As both the proportion of PCNs submitting data to NWRS and data quality have improved, monthly publications began in January 2023. We are working continually to improve our publications and we welcome feedback from all users by email to: PrimaryCareWorkforce@nhs.net. Links to other publications presenting healthcare workforce information can be found under Related Links.

The guidance documents contain information for applicants seeking authorization to conduct COVID-19 drug and medical device clinical trials under Interim Order (IO) No. 2.

Clinical Trials Dataset

  Overview

This dataset contains information extracted from clinical trial records collected from ClinicalTrials.gov (Date Accessed: 05/02/2025). It focuses on key descriptive fields that provide insight into trial objectives, eligibility criteria, and study design. The dataset is designed for researchers, healthcare professionals, and AI/ML practitioners interested in analyzing clinical trial data, understanding treatment development, or building… See the full description on the dataset page: https://huggingface.co/datasets/cyrilzakka/clinical-trials.

The 1987 National Medical Expenditure Survey (NMES) Public Use Tape 6 contains data from a survey of two kinds of long-term care facilities: those for the mentally retarded, and nursing and personal care homes. The Facility Questionnaire was completed by administrators or designated staff of the participating facilities. The items include number of beds, type of ownership, facility certification, services routinely provided, staffing, average cost, sources of payment for residents, and levels of basic costs. Additional variables were collected on the facilities for the mentally retarded: education and habilitation services, licensure and accreditation, and sources of revenue in addition to direct client fees. Public Use Tape 6 differs from the data in the Facility Questionnaire file of Public Use Tape 2, National Medical Expenditure Survey, 1987: Institutional Population Component (ICPSR 9280) only in the provision of a revised sampling weight variable. The new sampling weight includes adjustment not only for different probabilities of a facility being selected, nonresponse, and stratification measures, but also for duplication in the sampling frame.

Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve. The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj. The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 . The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 . The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed. COVID-19 cases, hospitalizations, and associated deaths that have been reported among Connecticut residents. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Hospitalization data were collected by the Connecticut Hospital Association and reflect the number of patients currently hospitalized with laboratory-confirmed COVID-19. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the daily COVID-19 update. Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical examiner) using their best clinical judgment. Additionally, all COVID-19 deaths, including suspected or related, are required to be reported to OCME. On April 4, 2020, CT DPH and OCME released a joint memo to providers and facilities within Connecticut providing guidelines for certifying deaths due to COVID-19 that were consistent with the CDC’s guidelines and a reminder of the required reporting to OCME.25,26 As of July 1, 2021, OCME had reviewed every case reported and performed additional investigation on about one-third of reported deaths to better ascertain if COVID-19 did or did not cause or contribute to the death. Some of these investigations resulted in the OCME performing postmortem swabs for PCR testing on individuals whose deaths were suspected to be due to COVID-19, but antemortem diagnosis was unable to be made.31 The OCME issued or re-issued about 10% of COVID-19 death certificates and, when appropriate, removed COVID-19 from the death certificate. For standardization and tabulation of mortality statistics, written cause of death statements made by the certifiers on death certificates are sent to the National Center for Health Statistics (NCHS) at the CDC which assigns cause of death codes according to the International Causes of Disease 10th Revision (ICD-10) classification system.25,26 COVID-19 deaths in this report are defined as those for which the death certificate has an ICD-10 code of U07.1 as either a primary (underlying) or a contributing cause of death. More information on COVID-19 mortality can be found at the following link: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Mortality/Mortality-Statistics Data are reported d

The Clinical Data Analytics market is experiencing robust growth, projected to reach a substantial size driven by several key factors. The market's Compound Annual Growth Rate (CAGR) of 27.53% from 2019 to 2024 indicates significant expansion. This rapid growth is fueled by increasing healthcare data volumes, the rising adoption of electronic health records (EHRs), and a growing need for improved patient outcomes and operational efficiency. The demand for sophisticated analytics to support clinical decision-making, enhance quality improvement initiatives, and ensure regulatory compliance is driving investment in this sector. Key application areas such as clinical decision support systems, regulatory reporting, and comparative effectiveness research are experiencing particularly strong growth. The market is segmented by end-user vertical (payers and providers), deployment model (cloud and on-premise), and application, offering diverse opportunities for vendors. While on-premise solutions still hold a significant share, the cloud-based segment is experiencing faster growth, driven by scalability, cost-effectiveness, and accessibility benefits. The North American market currently dominates, reflecting the region's advanced healthcare infrastructure and high adoption rates of advanced technologies. However, Asia Pacific and Europe are also witnessing significant growth, driven by increasing government initiatives to improve healthcare infrastructure and the expanding adoption of digital health technologies. The competitive landscape is characterized by a mix of large established players and emerging specialized companies. Established players like IBM, Oracle, and SAS leverage their existing infrastructure and expertise to offer comprehensive analytics solutions. Smaller, specialized companies often focus on niche applications or specific clinical areas, offering innovative solutions and tailored services. The market is also witnessing increased mergers and acquisitions, indicating industry consolidation and the ongoing push for advanced capabilities. Future growth will likely be influenced by factors such as advancements in artificial intelligence (AI) and machine learning (ML) technologies, increasing cybersecurity concerns, and the evolving regulatory landscape surrounding data privacy and interoperability. The continued integration of data analytics into clinical workflows and the broader adoption of value-based care models will further fuel market growth in the coming years. This comprehensive report provides an in-depth analysis of the Clinical Data Analytics industry, encompassing market dynamics, growth trends, regional insights, product landscape, and key player analysis. The study period covers 2019-2033, with 2025 as the base and estimated year. The report forecasts market growth from 2025-2033 and analyzes historical data from 2019-2024. The total market size is estimated at xx Million in 2025 and is projected to reach xx Million by 2033. This report is essential for healthcare professionals, investors, and businesses seeking to understand this rapidly evolving market. Recent developments include: September 2023 - Allscripts Healthcare, LLC has announced a strategic collaboration to support primary care providers in improving patients’ health outcomes while strengthening their practices’ financial foundation, where Veradigm’s innovative solutions help to promote value-based care initiatives for healthcare providers and most importantly, the patients they serve., January 2023: Global healthcare industry's platform, American Hospital Dubai, announced the launch of its new digital health information channel. The Digital Channel is a one-stop shop for knowledge and advice on healthcare topics, providing answers and solutions to all health and wellness concerns on a user-friendly digital platform, ushering in a new era in healthcare information. The digital channel, led by internationally certified doctors and specialists from American Hospital Dubai, will provide expert advice, in-depth insights, healthy lifestyle tips, and emerging healthcare developments, technologies, treatments, and breakthroughs. Furthermore, the channel's all-encompassing content includes healthy lifestyle education, guidance, tips, expert opinions and counseling, healthcare myths and realities, diet, nutrition, fitness, holistic health, and healthcare updates. It also provides information on medical breakthroughs, Med-Tech awareness, disease management, disease profiles, mental health, and the most recent treatments and medical technologies, such as AI and Robotics.. Key drivers for this market are: Increasing Focus on Population Health Management, Government Healthcare Policies; Clinical Data Analytics Enabling Personalized Patient Care; Growing Need to Contain Healthcare Expenditure. Potential restraints include: Data Privacy and Security Concerns, High Cost of Implementation of EDI. Notable trends are: Cloud Deployment Model to Hold a Dominant Position in the Market.

The U.S. Department of Veterans Affairs (VA) has established a long-term partnership to commission AHRQ to utilize its Evidence-based Practice Centers to develop update reviews to inform the VA’s PTSD-Repository – a publicly accessible clinical trials database maintained by the National Center for PTSD (NCPTSD). The 2023 Report, Executive Summary and Evidence Tables (Appendix E, F, G1, & G2) are included in the downloadable .zip file. For more information, visit AHRQ's page: https://effectivehealthcare.ahrq.gov/products/ptsd-pharm-non-pharm-treatment/research

The global sales of non-alcoholic steatohepatitis clinical trials market is estimated to be worth USD 2,964.4 million in 2025 and anticipated to reach a value of USD 5,806.8 million by 2035. Sales are projected to rise at a CAGR of 7.0% over the forecast period between 2025 and 2035. The revenue generated by Non-Alcoholic Steatohepatitis Clinical Trials in 2024 was USD 2,829.5 million.

Attributes	Key Insights
Historical Size, 2024	USD 2,829.5 million
Estimated Size, 2025	USD 2,964.4 million
Projected Size, 2035	USD 5,806.8 million
CAGR (2025 to 2035)	7.0%

Semi-Annual Market Update for the NASH Clinical Trials Market

Particular	Value CAGR
H1	8.0% (2024 to 2034)
H2	7.6% (2024 to 2034)
H1	7.0% (2025 to 2035)
H2	6.7% (2025 to 2035)

Analysis of Top Countries Conducting and Supporting NASH Clinical Trials

Countries	Value CAGR (2025 to 2035)
United States	7.6%
Germany	7.0%
France	6.8%
UK	6.0%
China	8.3%
India	9.0%
South Korea	4.9%

NASH Clinical Trials Industry Analysis by Top Investment Segments

By Study Design	Interventional
Value Share (2025)	45.9%

By Phase	Phase 3
Value Share (2025)	40.2%