According to a 2019 survey of former clinical trial participants, 21 percent of participants worldwide used text messaging during their clinical trial participation. This statistic depicts the percentage of clinical trial participants that used select technologies during their clinical trial participation as of 2019.

In 2021, 27 percent of all clinical drug trials worldwide were started in North America, whereas 30 percent of trials were initiated in Asia. This statistic shows the geographical distribution of clinical drug trials started worldwide from 2012 to 2022, by region.

This data package contains datasets on clinical trials conducted in the United States. Diseases include cervical cancer, diabetes, acute respiratory infection as well as stress. This data package also includes clinical trials registry and results database.

Clinical studies are an important part of drug development globally. The number of registered clinical trials has increased significantly recently. As of November 8, 2024, there were over 515 thousand clinical studies registered globally. The number of clinical studies has increased significantly since there were just 2,119 registered in 2000. In general, clinical trials have grown more complex in recent years and remain vital for the research and development of new drugs and products. Research and development Research and development are an important part of pharmaceutical companies and includes drug development and product development. Among all industry sectors, the pharmaceutical industry spends the largest percentage of their revenue on research and development. Many companies are active in pharmaceutical research and development globally. It is projected Swiss company Roche will remain one of the largest research and development spenders among pharmaceutical companies in the near future. Clinical studies globally Most clinical studies occurring globally are held in countries outside of the U.S. Many clinical trials performed outside the U.S. and EU are done so because it is often easier and cheaper to conduct trials in other locations. Success rates for clinical trials depend heavily on the stage of the trial and the drugs or products being developed. Recent data suggested that only around 29 percent of drugs make it from phase II to phase III.

From 2018 to 2021, the number of clinical drug trials each year increased from around 4,900 to over 6,700. However, since then, a constant decline can be seen. This statistic depicts the annual number of clinical drug trials started worldwide from 2018 to 2024.

This metadata describes the data format for data contributions to the International COVID-19 Data Alliance (ICODA) driver project investigating the safety and efficacy of clinical trials. The first data dictionary was published in December 2020, newer versions are available.

Several thousand clinical COVID-19 trials were in progress globally. As these trials were all evaluating the benefit/risk of potential COVID-19 treatment options, it was vital that the scientific community could interrogate this data as it emerged.

The summary level data from some of these trials across industry, academia and government was included in the ICODA Workbench. In order to provide near-immediate access to results and data from the trials, ICODA has partnered with Certara to provide curated and digitised summary level data from key trials as they were reported in the public domain. In addition, several data contributing organisations provided enriched summary-level data within 5-30 days post top-line reporting of the trial results which allowed a more in depth evaluation of the results.

This Driver project used a Data Dictionary to harmonise variable definitions and subgroup classifications from all trials. This allowed side by side interrogation of the data from these trials making the data readily useable to interpret findings. Researchers could also view data from individual trials in the context of other available trials thus expanding their insights. Our visual analytics and meta-analyses tools further enhanced the researchers’ ability to work quickly.

Website which allows data from completed clinical trials to be distributed to investigators and public. Researchers can download de-identified data from completed NIDA clinical trial studies to conduct analyses that improve quality of drug abuse treatment. Incorporates data from Division of Therapeutics and Medical Consequences and Center for Clinical Trials Network.

The following is an information retrieval test collection that contains:

• 204,855 publicly available clinical trails was crawled from ClinicalTrials.gov.
• 60 topics made up of three types: patient case descriptions, patient case summaries and assessor provided ad-hoc queries, totalling an average of 10.2 queries per topic.
• 4,000 assessor provided relevance assessment for topic, trial pairs.

Further details about the test collection can be found in the following publication:

B. Koopman and G. Zuccon. A test collection for matching patient trials. In Proceedings of the 39th annual international ACM SIGIR conference on research and development in information retrieval, Pisa, July 2016.

The Health Statistics and Health Research Database is Estonian largest set of health-related statistics and survey results administrated by National Institute for Health Development. Use of the database is free of charge.

The database consists of eight main areas divided into sub-areas. The data tables included in the sub-areas are assigned unique codes. The data tables presented in the database can be both viewed in the Internet environment, and downloaded using different file formats (.px, .xlsx, .csv, .json). You can download the detailed database user manual here (.pdf).

The database is constantly updated with new data. Dates of updating the existing data tables and adding new data are provided in the release calendar. The date of the last update to each table is provided after the title of the table in the list of data tables.

A contact person for each sub-area is provided under the "Definitions and Methodology" link of each sub-area, so you can ask additional information about the data published in the database. Contact this person for any further questions and data requests.

Read more about publication of health statistics by National Institute for Health Development in Health Statistics Dissemination Principles.

Worldwide, the total number of clinical studies with posted results was 1,139 at year-end 2009 and increased up to over 67 thousand as of November 8, 2024. This statistic shows the total number of registered clinical studies with posted results worldwide since 2008.

In 2023, there were 2,580 phase I clinical drug trials started, compared to 2,236 phase I trials initiated during the previous year. This statistic depicts the annual number of clinical trials started worldwide from 2018 to 2024, by trial phase.

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.

Correlation; significant (p

This is the dataset we used to train and evaluate for the paper Identifying unreported links between ClinicalTrials.gov trial registrations and their published results. This dataset is collected on 29 September 2020. The corresponding code and the structure of the dataset can be found in https://github.com/evidence-surveillance/unreported_link_identidication. We highly recommend building your own datasets with more specific criteria for specific applications rather than directly applying this dataset. This dataset includes extracted Clinical Trial registrations, extracted PubMed articles' titles and abstracts, the automatically extracted links between clinical trials and PubMed articles (already shuffled), manually curated links and the transformed data with corresponding vectorizers. This dataset contains 27,280 automatically constructed links (used for training and evaluation) and 90 manually curated links (used ​for evaluation only). The first 27,280 links refer to the automatically constructed links and the last 90 links refer to the manually curated links.

E-Clinical Solutions Market size was valued at USD 6.5 Billion in 2023 and is projected to reach USD 15.2 Billion by 2031, growing at a CAGR of 11.2% from 2024 to 2031.

Key Market Drivers
• Rising Demand for Clinical Trials Efficiency: With increasing drug discovery and development, the need for faster and more efficient clinical trials is growing fueling demand for e-clinical solutions.
• Advancements in Healthcare IT: The growing integration of healthcare IT solutions is driving the adoption of advanced clinical management tools.
• Regulatory Pressure: Stricter regulatory requirements for clinical trials, particularly regarding data accuracy and patient safety, are pushing for the adoption of e-clinical solutions.
• Increasing Outsourcing to CROs: Contract Research Organizations (CROs) are increasingly using e-clinical tools to manage outsourced clinical trials, further boosting market growth.

Pharmaceutical obesity RCTs used to evaluate the scope of the missing data problem.pdf (0.27 MB DOC)

This record includes the data associated with the study "Leveraging open tools to increase the potential of self-archiving to increase discoverability: A cohort study in clinical trials". The code used to generate these data is available under an open license in GitHub (https://github.com/delwen/oa-archiving-permissions). The deposit includes:

- `intovalue.csv`: download of the IntoValue dataset (IntoValue 1 and IntoValue 2), which is actively maintained in GitHub (https://github.com/maia-sh/intovalue-data). The data was downloaded on 17 December 2022. More information on the generation of this dataset can be found at: https://doi.org/10.5281/zenodo.5141343. This data corresponds to the start of the trial screening flow diagram in the manuscript (n = 3,788).

- `oa-unpaywall.csv`: dataset containing the results of the Unpaywall API query (query date: 17 December 2022). The dataset queried includes the following adaptations from `intovalue.csv`:

• As updated registry data had been downloaded on 1 November 2022, the IntoValue inclusion criteria were re-applied:
  • Interventional
  • Study completion date between 2009 and 2017
  • Complete based on study status
  • Conducted by a German university medical center.
• The dataset was further limited to:
  • Unique trials (trials from IntoValue 2 were preserved)
  • Unique publications with a DOI

- `oa-syp-permissions.csv`: dataset containing the results of the Shareyourpaper API query (query date: 17 December 2022). The dataset queried is the same as in `oa-unpaywall.csv`.

- `oa-merged-data.csv`: dataset containing the merged Unpaywall and Shareyourpaper data for all clinical trial results publications considered in this study. The dataset was further limited to journal articles that resolved in Unpaywall and were published between 2010 - 2020 (based on the publication date in Unpaywall). This is the main dataset underlying the analyses in the manuscript.

The full anonymised dataset from our recent survey into the attitudes towards clinical trial data sharing. The invitation to participate was distributed to clinical trialists funded by the Wellcome Trust, Bill and Melinda Gates Foundation, Cancer Research UK, and UK Medical Research Council.

Quality scoring components for 8 clinical trials included.

Objective: To investigate clinical trialists’ opinions and experiences of sharing of clinical trial data with investigators who are not directly collaborating with the research team. Design and setting: Cross sectional, web based survey. Participants: Clinical trialists who were corresponding authors of clinical trials published in 2010 or 2011 in one of six general medical journals with the highest impact factor in 2011. Main outcome measures: Support for and prevalence of data sharing through data repositories and in response to individual requests, concerns with data sharing through repositories, and reasons for granting or denying requests. Results: Of 683 potential respondents, 317 completed the survey (response rate 46%). In principle, 236 (74%) thought that sharing de-identified data through data repositories should be required, and 229 (72%) thought that investigators should be required to share de-identified data in response to individual requests. In practice, only 56 (18%) indicated that they were required by the trial funder to deposit the trial data in a repository; of these 32 (57%) had done so. In all, 149 respondents (47%) had received an individual request to share their clinical trial data; of these, 115 (77%) had granted and 56 (38%) had denied at least one request. Respondents’ most common concerns about data sharing were related to appropriate data use, investigator or funder interests, and protection of research subjects. Conclusions: We found strong support for sharing clinical trial data among corresponding authors of recently published trials in high impact general medical journals who responded to our survey, including a willingness to share data, although several practical concerns were identified.