List of active studies submitted by Roswell Park Cancer Institute (RPCI) to National Cancer Institute (NCI) annually as part of the Cancer Center Report Grant reporting. It includes the primary site, protocol, principal investigator, date opened, phase and study name.

These data are from a human study collected under IRB protocol: ClinicalTrials.gov # NCT01874834. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: These data are from a human study collected under IRB protocol: ClinicalTrials.gov # NCT01874834. As such, it is a violation of Federal Law to publish them. Format: These data are from a human study collected under IRB protocol: ClinicalTrials.gov # NCT01874834. This dataset is associated with the following publication: Stiegel, M., J. Pleil, J. Sobus, T. Stevens, and M. Madden. Linking physiological parameters to perturbations in the human exposome: Environmental exposures modify blood pressure and lung function via inflammatory cytokine pathway. JOURNAL OF TOXICOLOGY AND ENVIRONMENTAL HEALTH - PART A: CURRENT ISSUES. Taylor & Francis, Inc., Philadelphia, PA, USA, 80(9): 485-501, (2017).

The Clinical Trials dataset includes information about Clinical Trials mentioned in Springer Nature publications.See also: https://scigraph.springernature.com/explorer/datasets/data_at_a_glance/NOTE: this dataset was made available by Dimensions.ai.A clinical trial record usually includes information about dates, sponsor organizations, subjects, external identifiers and abstract when available.Version info:* http://scigraph.downloads.uberresearch.com/archives/current/TIMESTAMP.txt* http://scigraph.downloads.uberresearch.com/archives/current/LICENSE.txt

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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

GlobalData's clinical trial report, “Down Syndrome Disease – Global Clinical Trials Review, H2, 2020" provides an overview of Down Syndrome Clinical trials scenario. This report provides top line data relating to the clinical trials on Down Syndrome. Report includes an overview of trial numbers and their average enrollment in top countries conducted across the globe. The report offers coverage of disease clinical trials by region, country (G7 & E7), phase, trial status, end points status and sponsor type. Report also provides prominent drugs for in-progress trials (based on number of ongoing trials). GlobalData Clinical Trial Reports are generated using GlobalData’s proprietary database – Pharma – Clinical trials database. Clinical trials are collated from 80+ different clinical trial registries, conferences, journals, news etc across the globe. Clinical trials database undergoes periodic update by dynamic process. Read More

This deposit contains data associated with a feasibility study evaluating the use of individualized report cards to improve trial transparency at the Charité - Universitätsmedizin Berlin. It primarily includes large raw data files and other files compiled by, or used in the project code repository: https://github.com/quest-bih/tv-ct-transparency/. These data are deposited for documentation and computational reproducibility; they do not reflect the most current/accurate data available from each source.

The deposit contains:

Survey data (survey-data.csv): Participant responses for an anonymous survey conducted to assess the usefulness of the report cards and infosheet. The survey was administered in LimeSurvey and hosted on a server at the QUEST Center for Responsible Research at the Berlin Institute of Health at Charité – Universitätsmedizin Berlin. Any information that could potentially identify participants, such as IP address and free-text fields (e.g., corrections, comments) were removed. This file serves as input for the analysis of the survey data.

Amyotrophic lateral sclerosis (ALS) is a rare disease with urgent need for improved treatment. Despite the acceleration of research in recent years, there is a need to understand the full natural history of the disease. As only 40% of people living with ALS are eligible for typical clinical trials, clinical trial datasets may not generalize to the full ALS population. While biomarker and cohort studies have more generous inclusion criteria, these too may not represent the full range of phenotypes, particularly if the burden for participation is high. To permit a complete understanding of the heterogeneity of ALS, comprehensive data on the full range of people with ALS is needed. The ALS Natural History Consortium (ALS NHC) consists of nine ALS clinics and was created to build a comprehensive dataset reflective of the ALS population. At each clinic, most patients are asked to participate and about 95% do. After obtaining consent, a minimum dataset is abstracted from each participant’s electronic health record. Participant burden is therefore minimal. Data on 1925 ALS patients were submitted as of 9 December 2022. ALS NHC participants were more heterogeneous relative to anonymized clinical trial data from the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database. The ALS NHC includes ALS patients of older age of onset and a broader distribution of El Escorial categories, than the PRO-ACT database. ALS NHC participants had a higher diversity of diagnostic and demographic data compared to ALS clinical trial participants.Key MessagesWhat is already known on this topic: Current knowledge of the natural history of ALS derives largely from regional and national registries that have broad representation of the population of people living with ALS but do not always collect covariates and clinical outcomes. Clinical studies with rich datasets of participant characteristics and validated clinical outcomes have stricter inclusion and exclusion criteria that may not be generalizable to the full ALS population.What this study adds: To bridge this gap, we collected baseline characteristics for a sample of the population of people living with ALS seen at a consortium of ALS clinics that collect extensive, pre-specified participant-level data, including validated outcome measures.How this study might affect research, practice, or policy: A clinic-based longitudinal dataset can improve our understanding of the natural history of ALS and can be used to inform the design and analysis of clinical trials and health economics studies, to help the prediction of clinical course, to find matched controls for open label extension trials and expanded access protocols, and to document real-world evidence of the impact of novel treatments and changes in care practice. What is already known on this topic: Current knowledge of the natural history of ALS derives largely from regional and national registries that have broad representation of the population of people living with ALS but do not always collect covariates and clinical outcomes. Clinical studies with rich datasets of participant characteristics and validated clinical outcomes have stricter inclusion and exclusion criteria that may not be generalizable to the full ALS population. What this study adds: To bridge this gap, we collected baseline characteristics for a sample of the population of people living with ALS seen at a consortium of ALS clinics that collect extensive, pre-specified participant-level data, including validated outcome measures. How this study might affect research, practice, or policy: A clinic-based longitudinal dataset can improve our understanding of the natural history of ALS and can be used to inform the design and analysis of clinical trials and health economics studies, to help the prediction of clinical course, to find matched controls for open label extension trials and expanded access protocols, and to document real-world evidence of the impact of novel treatments and changes in care practice.

This review analyzes current clinical trials investigating large language models’ (LLMs) applications in healthcare. We identified 27 trials (5 published and 22 ongoing) across 4 main clinical applications: patient care, data handling, decision support, and research assistance. Our analysis reveals diverse LLM uses, from clinical documentation to medical decision-making. Published trials show promise but highlight accuracy concerns. Ongoing studies explore novel applications like patient education and informed consent. Most trials occur in the United States of America and China. We discuss the challenges of evaluating rapidly evolving LLMs through clinical trials and identify gaps in current research. This review aims to inform future studies and guide the integration of LLMs into clinical practice.

Objectives: To develop and pilot a tool to measure and improve pharmaceutical companies' clinical trial data sharing policies and practices. Design: Cross sectional descriptive analysis. Setting: Large pharmaceutical companies with novel drugs approved by the US Food and Drug Administration in 2015. Data sources: Data sharing measures were adapted from 10 prominent data sharing guidelines from expert bodies and refined through a multi-stakeholder deliberative process engaging patients, industry, academics, regulators, and others. Data sharing practices and policies were assessed using data from ClinicalTrials.gov, Drugs@FDA, corporate websites, data sharing platforms and registries (eg, the Yale Open Data Access (YODA) Project and Clinical Study Data Request (CSDR)), and personal communication with drug companies. Main outcome measures: Company level, multicomponent measure of accessibility of participant level clinical trial data (eg, analysis ready dataset and metadata); drug and trial level measures of registration, results reporting, and publication; company level overall transparency rankings; and feasibility of the measures and ranking tool to improve company data sharing policies and practices. Results: Only 25% of large pharmaceutical companies fully met the data sharing measure. The median company data sharing score was 63% (interquartile range 58-85%). Given feedback and a chance to improve their policies to meet this measure, three companies made amendments, raising the percentage of companies in full compliance to 33% and the median company data sharing score to 80% (73-100%). The most common reasons companies did not initially satisfy the data sharing measure were failure to share data by the specified deadline (75%) and failure to report the number and outcome of their data requests. Across new drug applications, a median of 100% (interquartile range 91-100%) of trials in patients were registered, 65% (36-96%) reported results, 45% (30-84%) were published, and 95% (69-100%) were publicly available in some form by six months after FDA drug approval. When examining results on the drug level, less than half (42%) of reviewed drugs had results for all their new drug applications trials in patients publicly available in some form by six months after FDA approval. Conclusions: It was feasible to develop a tool to measure data sharing policies and practices among large companies and have an impact in improving company practices. Among large companies, 25% made participant level trial data accessible to external investigators for new drug approvals in accordance with the current study's measures; this proportion improved to 33% after applying the ranking tool. Other measures of trial transparency were higher. Some companies, however, have substantial room for improvement on transparency and data sharing of clinical trials.

Database of clinical trials funded/supported by Wellcome included in grants that were either ongoing at/or awarded after 1st May 2018. Data was collected in April 2021.

GlobalData’s clinical trial report, “Huntington Disease – Global Clinical Trials Review, 2022″ provides an overview of Huntington Disease Clinical trials scenario. This report provides top line data relating to the clinical trials on Huntington Disease. Report includes an overview of trial numbers and their average enrollment in top countries conducted across the globe. The report offers coverage of disease clinical trials by region, country (G7 & E7), phase, trial status, end points status and sponsor type. Report also provides prominent drugs for in-progress trials (based on number of ongoing trials). GlobalData Clinical Trial Reports are generated using GlobalData’s proprietary database – Pharma – Clinical trials database. Clinical trials are collated from 80+ different clinical trial registries, conferences, journals, news etc across the globe. Clinical trials database undergoes periodic update by dynamic process. Read More

This data deposit includes large raw data used for the "IntoValue" dataset, which underlies several projects at the QUEST Center for Responsible Research in the Berlin Institute of Health (BIH) @ Charité. An initial version of the IntoValue dataset is available in Zenodo: https://doi.org/10.5281/zenodo.5141342. Based on this initial version, the dataset is actively developed and maintained in GitHub: https://github.com/maia-sh/intovalue-data. This Zenodo deposit serves to store large raw data files for individual trials and are used in that GitHub repository. These data are deposited for computational reproducibility and documentation; they are not intended to be used for additional projects and do not reflect the most current/accurate data available from each source.

This deposit contains raw data from the following sources:

PubMed (pubmed.zip): PubMed XML files are provided courtesty of the U.S. National Library of Medicine and were accessed via the Entrez Programming Utilities (E-utilities) API. The files were downloaded on 2021-08-15 and do not reflect the most current/accurate data available from NLM. The following scripts were used to download and create these files: get-pubmed.R; download-pubmed.R.

German Clinical Trials Registry (DRKS) (drks.zip): DRKS does not provide an API and was webscrapped on 2022-11-01. The following scripts were used to download and create these XML files: get-drks.R; drks-functions.R

ClinicalTrials.gov (ctgov.zip): ClinicalTrials.gov was accessed via the Clinical Trials Transformation Initiative (CTTI) Aggregate Content of ClinicalTrials.gov (AACT) via its PostgreSQL database API.The API was queried and CSV files were generated on 2022-11-01. The following scripts were used to download and create these files: get-process-aact.R.

ClinicalTrials.gov 2018 (ctgov_2018.zip): Additional trial data for 2018. ClinicalTrials.gov was accessed via the Clinical Trials Transformation Initiative (CTTI) Aggregate Content of ClinicalTrials.gov (AACT) via its PostgreSQL database API.The API was queried and CSV files were generated on 2022-11-01. The following scripts were used to download and create these files: get-process-aact.R.

This study is being conducted to evaluate the effectiveness and safety of LAMICTAL added to the current therapy of pediatric patients age 1-24 months old with partial seizures. The medication used in this study has been approved by FDA for the adjunctive treatment of partial seizures in patients 2 years and older.

Clinical Trial Data Management Software Market Outlook

The global Clinical Trial Data Management Software market is poised for significant growth, with market size projected to reach USD 3.7 billion by 2023, escalating to an impressive USD 9.5 billion by 2032, driven by a robust CAGR of 10.5%. This growth is attributed to an increasing need for efficient data management solutions in the complex and highly regulated clinical trials landscape. The market is buoyed by advancements in technology, a surge in clinical trials, and the pharmaceutical industry's burgeoning focus on drug development, which collectively highlight the transformative potential of Clinical Trial Data Management Software.

A key growth factor propelling the Clinical Trial Data Management Software market is the rapid advancements in technology. The integration of artificial intelligence and machine learning in software solutions has revolutionized data management by enhancing data accuracy, reducing the time required for data processing, and enabling predictive analytics. These advancements are crucial for managing large volumes of data generated during clinical trials, ensuring data integrity, and maintaining compliance with regulatory standards. Furthermore, the adoption of cloud-based solutions has facilitated real-time data access and collaboration among researchers globally, thereby accelerating the overall clinical trial process.

Another significant driver is the increasing number of clinical trials being conducted globally. The rise in prevalence of chronic diseases, the urgency for novel therapeutics, and the growing investments in research and development by pharmaceutical and biotechnology companies have all contributed to this surge. As the volume of clinical trials grows, the demand for sophisticated data management solutions that can handle complex datasets and ensure data security and compliance increases. This is particularly important given the stringent regulatory requirements in the clinical trials industry, which necessitate robust and reliable data management systems.

Moreover, the pharmaceutical industryÂ’s focus on drug development and personalized medicine is also driving the market. The shift towards personalized treatments requires more precise and comprehensive data collection and analysis, further emphasizing the need for advanced data management solutions. Clinical Trial Data Management Software not only facilitates efficient data handling but also supports the integration of various data sources, including genomic data, which is essential for personalized medicine. This trend is expected to continue, further fueling the demand for innovative data management tools in clinical trials.

From a regional outlook, North America holds the largest share of the Clinical Trial Data Management Software market, driven by a well-established pharmaceutical industry and a high number of ongoing clinical trials. The region's robust healthcare infrastructure and favorable regulatory environment also contribute to market growth. Europe follows closely, benefiting from significant investments in research and development, and a strong focus on healthcare innovation. The Asia Pacific region is anticipated to witness the highest growth rate, attributed to increasing clinical trial activities, growing pharmaceutical outsourcing, and government initiatives to boost healthcare IT infrastructure. Latin America and the Middle East & Africa, while currently smaller markets, are expected to see steady growth due to rising healthcare investments and expanding pharmaceutical sectors.

Component Analysis

The Clinical Trial Data Management Software market can be segmented into software and services components. The software component includes various applications and platforms designed to streamline data collection, storage, and analysis during clinical trials. These software solutions are essential for managing the complex datasets generated in trials, ensuring data accuracy, and maintaining regulatory compliance. The software segment is witnessing significant growth due to continuous advancements in technology, such as the incorporation of artificial intelligence and machine learning capabilities, which enhance data processing efficiency and enable predictive analytics. Furthermore, the increasing adoption of cloud-based solutions provides flexibility and real-time data access, further driving the demand for software in clinical trials.

On the other hand, the services component encompasses a range of support services provided by vendors to ensure the effective implementation and use of

Database of European clinical trials containing information on interventional clinical trials on medicines. The information available dates from 1 May 2004 when national medicine regulatory authorities began populating the EudraCT database, the application that is used by national medicine regulatory authorities to enter clinical trial data. The EU Clinical Trials Register website launched on 22 March 2011 enables users to search for information which has been included in the EudraCT database. Users are able to: * view the description of a phase II-IV adult clinical trial where the investigator sites are in European Union member states and the European Economic Area; * view the description of any pediatric clinical trial with investigator sites in the European Union and any trials which form part of a pediatric investigation plan (PIP) including those where the investigator sites are outside the European Union. * download up to 20 results (per request) in a text file (.txt). The details in the clinical trial description include: * the design of the trial; * the sponsor; * the investigational medicine (trade name or active substance identification); * the therapeutic areas; * the status (authorized, ongoing, complete).

GlobalData's clinical trial report, “Osteosarcoma Global Clinical Trials Review, H1, 2016" provides an overview of Osteosarcoma clinical trials scenario. This report provides top line data relating to the clinical trials on Osteosarcoma. Report includes an overview of trial numbers and their average enrollment in top countries conducted across the globe. The report offers coverage of disease clinical trials by region, country (G7 & E7), phase, trial status, end points status and sponsor type. Report also provides prominent drugs for in-progress trials (based on number of ongoing trials). GlobalData Clinical Trial Reports are generated using GlobalData’s proprietary database – Pharma eTrack Clinical trials database. Clinical trials are collated from 80+ different clinical trial registries, conferences, journals, news etc across the globe. Clinical trials database undergoes periodic update by dynamic process. The report enhances the decision making capabilities and helps to create an effective counter strategies to gain competitive advantage. Note: Certain sections in the report may be removed or altered based on the availability and relevance of data for the indicated disease. Read More

GlobalData's clinical trial report, “Cyst Global Clinical Trials Review, H2, 2017" provides an overview of Cyst clinical trials scenario. This report provides top line data relating to the clinical trials on Cyst. Report includes an overview of trial numbers and their average enrollment in top countries conducted across the globe. The report offers coverage of disease clinical trials by region, country (G7 & E7), phase, trial status, end points status and sponsor type. Report also provides prominent drugs for in-progress trials (based on number of ongoing trials). GlobalData Clinical Trial Reports are generated using GlobalData’s proprietary database – Pharma eTrack Clinical trials database. Clinical trials are collated from 80+ different clinical trial registries, conferences, journals, news etc across the globe. Clinical trials database undergoes periodic update by dynamic process. Read More

This dataset from Dimensions.ai contains all published articles, preprints, clinical trials, grants and research datasets that are related to COVID-19. This growing collection of research information now amounts to hundreds of thousands of items, and it is the only dataset of its kind. You can find an overview of the content in this interactive Data Studio dashboard: https://reports.dimensions.ai/covid-19/ The full metadata includes the researchers and organizations involved in the research, as well as abstracts, open access status, research categories and much more. You may wish to use the Dimensions web application to explore the dataset: https://covid-19.dimensions.ai/. This dataset is for researchers, universities, pharmaceutical & biotech companies, politicians, clinicians, journalists, and anyone else who wishes to explore the impact of the current COVID-19 pandemic. It is updated daily, and free for anyone to access. Please share this information with anyone you think would benefit from it. If you have any suggestions as to how we can improve our search terms to maximise the volume of research related to COVID-19, please contact us at support@dimensions.ai. About Dimensions: Dimensions is the largest database of research insight in the world. It contains a comprehensive collection of linked data related to the global research and innovation ecosystem, all in a single platform. This includes hundreds of millions of publications, preprints, grants, patents, clinical trials, datasets, researchers and organizations. Because Dimensions maps the entire research lifecycle, you can follow academic and industry research from early stage funding, through to output and on to social and economic impact. This Covid-19 dataset is a subset of the full database. The full Dimensions database is also available on BigQuery, via subscription. Please visit www.dimensions.ai/bigquery to gain access.Más información

All clinical studies classified as ‘interventional studies’ registered with ClinicalTrials as of 25 October 2012 are shown. The following information was collected from each study: study registration date; the study start date; the primary completion date; study completion date; original primary outcome and date submitted; current primary outcome and date submitted; study phase, data monitoring committee; study sponsor and collaborators.

GlobalData's clinical trial report, “Hyperprolactinaemia Global Clinical Trials Review, H2, 2015" provides an overview of Hyperprolactinaemia clinical trials scenario. This report provides top line data relating to the clinical trials on Hyperprolactinaemia. Report includes an overview of trial numbers and their average enrollment in top countries conducted across the globe. The report offers coverage of disease clinical trials by region, country (G7 & E7), phase, trial status, end points status and sponsor type. Report also provides prominent drugs for in-progress trials (based on number of ongoing trials). GlobalData Clinical Trial Reports are generated using GlobalData’s proprietary database – Pharma eTrack Clinical trials database. Clinical trials are collated from 80+ different clinical trial registries, conferences, journals, news etc across the globe. Clinical trials database undergoes periodic update by dynamic process. The report enhances the decision making capabilities and helps to create an effective counter strategies to gain competitive advantage. Note: Certain sections in the report may be removed or altered based on the availability and relevance of data for the indicated disease. Read More