Introduction

Clinical Trials Statistics: Clinical trials are vital research studies aimed at assessing the safety, effectiveness, and potential benefits of new medical interventions, treatments, drugs, or devices. Participants, often patients, voluntarily engage in these trials to help researchers gather essential data.

Typically conducted in phases, starting with safety evaluations in smaller groups and progressing to larger populations for efficacy assessments, these trials have a paramount role in shaping medical advancements.

They inform treatment decisions, regulatory approvals, and healthcare practices, guided by strict ethical and regulatory standards that safeguard participants' rights and data integrity.

Ultimately, clinical trials underpin evidence-based medicine, driving innovation and improving healthcare outcomes worldwide.

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.

This statistic shows the number of registered clinical studies worldwide by location, as of November 8, 2024. The number of registered clinical studies in non-U.S. areas was at around 284 thousand, while in the U.S. the number was at around 154 thousand.

BackgroundIn medical practice, clinically unexpected measurements might be quite properly handled by the remeasurement, removal, or reclassification of patients. If these habits are not prevented during clinical research, how much of each is needed to sway an entire study?Methods and ResultsBelieving there is a difference between groups, a well-intentioned clinician researcher addresses unexpected values. We tested how much removal, remeasurement, or reclassification of patients would be needed in most cases to turn an otherwise-neutral study positive. Remeasurement of 19 patients out of 200 per group was required to make most studies positive. Removal was more powerful: just 9 out of 200 was enough. Reclassification was most powerful, with 5 out of 200 enough. The larger the study, the smaller the proportion of patients needing to be manipulated to make the study positive: the percentages needed to be remeasured, removed, or reclassified fell from 45%, 20%, and 10% respectively for a 20 patient-per-group study, to 4%, 2%, and 1% for an 800 patient-per-group study. Dot-plots, but not bar-charts, make the perhaps-inadvertent manipulations visible. Detection is possible using statistical methods such as the Tadpole test.ConclusionsBehaviours necessary for clinical practice are destructive to clinical research. Even small amounts of selective remeasurement, removal, or reclassification can produce false positive results. Size matters: larger studies are proportionately more vulnerable. If observational studies permit selective unblinded enrolment, malleable classification, or selective remeasurement, then results are not credible. Clinical research is very vulnerable to “remeasurement, removal, and reclassification”, the 3 evil R's.

In 2020, a total of 221 clinical trials started in Mexico, down from 268 reported a year earlier. 2018 was the year with the highest clinical studies opened in the North American country. As of June 2020, Latin America and Africa concentrated only one percent of the pharmaceutical research and development companies worldwide.

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US Clinical Trials Market Size 2024-2028

The US clinical trials market size is estimated to grow by USD 5 billion at a CAGR of 4.38% between 2023 and 2028. The pharmaceutical industry is experiencing a significant transformation, driven by several key trends. The number of clinical trials for new drugs is on the rise, reflecting increased investment in research and development. This trend is expected to continue, fueled by advancements in technology and a growing understanding of disease mechanisms. Another significant development is the adoption of artificial intelligence (AI) and machine learning-based tools for drug discovery outsourcing and delivery. These technologies enable more precise and efficient drug development, reducing the time and cost of bringing new therapies to market. Additionally, there is a growing demand for personalized medicine and targeted therapies, driven by advances in genetics, genomics, and individualized patient care. These trends are shaping the future of the pharmaceutical industry, offering new opportunities for innovation and growth.

What will be the Size of the US Clinical Trials Market During the Forecast Period?

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US Clinical Trials Market Segmentation

The US clinical trials market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD Billion' for the period 2024-2028, as well as historical data from 2018- 2022 for the following segments.

Type Outlook 

  Phase III
  Phase I
  Phase II
  Phase IV


Service Type Outlook 

  Interventional studies
  Observational studies
  Expanded access studies

By Type

The market share growth by the phase III segment will be significant during the forecast period. The phase III segment in the market plays a significant role in testing the safety and efficacy of new drugs or medical treatments before they can be approved for public use. This phase is the final step in the process of drug development and involves testing the investigational treatment on a larger population to gather more data and assess the potential benefits and risks.

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Phase III was the largest and was valued at USD 9.20 billion in 2018. Phase III segment often involves hundreds or even thousands of participants spread across multiple trial sites across the country. The trials are carefully monitored by medical professionals, including doctors and researchers, who closely follow the progress of each participant and collect data on various parameters such as survival rates, progression-free survival, quality of life, and adverse events. For instance, during phase III trials, the participants receive the investigational treatment and follow a specific treatment regimen. Researchers actively track their progress and document any improvements or adverse reactions they observe. Additionally, medical professionals regularly engage with the participants, providing guidance and monitoring their overall health throughout the trial duration.

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US Clinical Trials Market Dynamics

Biopharmaceutical companies and medical device companies are intensifying R&D investments in collaboration with CROs to advance drug candidates through clinical trials. These trials, managed by clinical research organizations and supported by healthcare workers, evaluate both small-molecule drugs and biologics as well as biosimilars. Leveraging IoT and real-world data, virtual trials are gaining traction, including those investigating treatments like Interferon-beta. This shift marks a departure from traditional clinical trials, offering enhanced efficiency and broader global participation. The globalization of clinical trials is pivotal in accessing diverse patient demographics, thereby accelerating the development of innovative therapies across various therapeutic areas. Our researchers analyzed the market research and growth data with 2023 as the base year, along with the key market growth analysis, trends, and challenges. A holistic analysis of drivers, trends, and challenges will help companies refine their marketing strategies to gain a competitive advantage.

Key Market Driver

Rise in number of clinical trials of drugs is a key factor driving US clinical trials market growth. This increase can be attributed to several factors, including advancements in medical research, the growing need for new and improved treatments, and regulatory changes that have made the process more accessible. Moreover, with the prevalence of cancer becoming more prominent, there has been a rise in the development of new drugs aimed at combating this disease. The FDA has implemented measures to streamline the approval process, allowing for more efficient and timely evaluation of drugs. For instance, the FDA's Fast T

As of April 2024, most of the clinical trials carried out in Mexico were registered as being on phase 3 (2,354). Meanwhile, another 16 clinical trials were recorded as in early phase 1. However, from the nearly 5,000 clinical studies documented in the country, some were either already completed or no longer active, for different reasons. In 2023, Swiss-based company Roche was expected to be the leader firm among the global top pharmaceutical companies, with some 194 products in its R&D pipeline.

The National Database for Clinical Trials Related to Mental Illness (NDCT) is an extensible informatics platform for relevant data at all levels of biological and behavioral organization (molecules, genes, neural tissue, behavioral, social and environmental interactions) and for all data types (text, numeric, image, time series, etc.) related to clinical trials funded by the National Institute of Mental Health. Sharing data, associated tools, methodologies and results, rather than just summaries or interpretations, accelerates research progress. Community-wide sharing requires common data definitions and standards, as well as comprehensive and coherent informatics approaches for the sharing of de-identified human subject research data. Built on the National Database for Autism Research (NDAR) informatics platform, NDCT provides a comprehensive data sharing platform for NIMH grantees supporting clinical trials.

During 2019, 18 percent of participants found out about the clinical trials from an advertisement. This statistic depicts the percentage of clinical trials participants that learned about clinical trials from top sources as of 2019.

BackgroundIn 2007, the initiation of a patient safety campaign led to the introduction of Ward Observational Charts (WOC) and Medical Early Warning Score (MEWS) at Naestved Regional Hospital. This included systematic measuring of vital signs of all patients in order to prevent patient deterioration and assure timely and correct initiation of treatment. The aim of this study was to assess to what degree WOC guidelines being followed by ward staff.Design and SettingA 7-day prospective, observational, randomised, cross-sectional, point prevalence study of WOC guideline compliance in hospitalised patients on twelve wards at Naestved Hospital.ResultsThe study included 132 patients. Of these, 58% had been observed and managed correctly according to WOC guidelines. 77% had all MEWS elements recorded by staff. One patient had no MEWS elements recorded. Only 38% of patients with abnormal MEWS were correctly escalated by nursing staff. Staff was aware of the abnormal MEWS observed by investigator in 60% of the patients. Each element of WOC was on average recorded by staff in 90% of the patients.ConclusionAt the time of our study, the long-term implementation of WOC guidelines has not been completed satisfactorily. The lacking component in the implementation of MEWS and WOC is the documentation of action taken upon finding an abnormal value. Unsuccessful implementation could result in incorrect results from evaluation of an early warning system. We suggest a redesign of the training programme to educate staff in recognising and caring for critically ill patients at Naestved Hospital.

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The oncology clinical trial market share is expected to increase by USD 4.22 billion from 2020 to 2025, and the market’s growth momentum will accelerate at a CAGR of 6.70%.

This oncology clinical trial market research report provides valuable insights on the post COVID-19 impact on the market, which will help companies evaluate their business approaches. Furthermore, this report extensively covers oncology clinical trial market segmentation by design (interventional, observational, and expanded access) and geography (North America, Europe, Asia, and ROW). The oncology clinical trial market report also offers information on several market vendors, including F. Hoffmann-La Roche Ltd., Icon Plc, IQVIA Holdings Inc., Medpace Holdings Inc., Merck and Co. Inc., Novartis AG, Novotech (Australia) Pty Ltd., Parexel International Corp., Pivotal S.L.U, and Syneos Health Inc. among others.

What will the Oncology Clinical Trial Market Size be During the Forecast Period?

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Oncology Clinical Trial Market: Key Drivers and Challenges

The increasing number of cancer cases across the globe is notably driving the oncology clinical trial market growth, although factors such as inefficient clinical trial design for oncology may impede market growth. Our research analysts have studied the historical data and deduced the key market drivers and the COVID-19 pandemic impact on the oncology clinical trial industry. The holistic analysis of the drivers will help in deducing end goals and refining marketing strategies to gain a competitive edge.

Key Oncology Clinical Trial Market Driver

The number of cancer cases is rising on a global level due to increased pollution and frequent changes in lifestyle. Exposure to carcinogens has increased as the global air quality index has degraded. Pharmaceutical companies and various government organizations are developing new and improved treatments for multiple types of cancers and scheduling oncology clinical trials to get the treatments approved by relevant agencies, which, in turn, will drive the demand for oncology clinical trials during the forecast period.

Key Oncology Clinical Trial Market Challenge

Clinical trials are subject to errors, and oncology clinical trials need to be thorough. The data collection method may be inefficient, and the researchers may not get full disclosure from patients participating in trials. This leads to misinformation resulting in wrongful conclusions, which hamper the oncology study for which the clinical trial was conducted. Other factors such as inappropriate selection of clinical trial candidates and error in clinical trial design may damage the study. Hence, the global market for oncology clinical trials can be restricted by inefficient clinical trial designs.

This oncology clinical trial market analysis report also provides detailed information on other upcoming trends and challenges that will have a far-reaching effect on the market growth. The actionable insights on the trends and challenges will help companies evaluate and develop growth strategies for 2021-2025.

Who are the Major Oncology Clinical Trial Market Vendors?

The report analyzes the market’s competitive landscape and offers information on several market vendors, including:

F. Hoffmann-La Roche Ltd.
Icon Plc
IQVIA Holdings Inc.
Medpace Holdings Inc.
Merck and Co. Inc.
Novartis AG
Novotech (Australia) Pty Ltd.
Parexel International Corp.
Pivotal S.L.U
Syneos Health Inc.

This statistical study of the oncology clinical trial market encompasses successful business strategies deployed by the key vendors. The oncology clinical trial market is fragmented and the vendors are deploying growth strategies such as focusing on product innovation and spending in research and development activities to compete in the market.

To make the most of the opportunities and recover from post COVID-19 impact, market vendors should focus more on the growth prospects in the fast-growing segments, while maintaining their positions in the slow-growing segments.

The oncology clinical trial market forecast report offers in-depth insights into key vendor profiles. The profiles include information on the production, sustainability, and prospects of the leading companies.

Which are the Key Regions for Oncology Clinical Trial Market?

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40% of the market’s growth will originate from North America during the forecast period. The US and Canada are the key markets for oncology clinical trials in North America. However, the market growth rate in this region will be slower than the growth of the market in Asia and Europe.

This market research report entails detailed information on the competitive i

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.

The database is created by processing 6558 clinical trial articles from PubMed Central public sample 2014. The articles are obtained by matching PMC and Medline documents. The documents that were selected contained in publication type word "Clinical" in Medline.

The documents were processed using TableDisentangler tool, that is able to create the majority of the database. Then documents were annotated using UMLS/MetaMap and script that is a part of TableDisentangler tool for communication with MetaMap. Three case studies were performed for information extraction from these data: - Extraction of patients' age - Extraction of gender distribution - Extraction of FEV1 measures (this has been performed for COPD studies only)

Information extraction case studies were performed using TabInOut tool for generating table information extraction rules.

Database schema can be seen on the following link: https://github.com/nikolamilosevic86/TableDisentangler/wiki/Database-schema

Files included in the dataset: - Clinicaldata.zip - This file contains raw xml clinical documents from PMC - Database.zip - Contains database with processed data using TableDisentangler and TabInOut

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.

Clinical trial data management (CDM) providers have experienced robust growth in recent years, driven by several key factors. Two major catalysts contributing to this growth are an increasing demand for innovative therapies and treatments and the rising prevalence of chronic diseases worldwide. As pharmaceutical companies race to develop new drugs and biologics to address unmet medical needs, the volume and complexity of clinical trials have surged. A jump in clinical trial activity has fueled the need for efficient and reliable data management solutions to handle the vast amounts of data generated throughout the drug development process. At the same time, regulatory bodies in the US and internationally mounting scrutiny of clinical trial data integrity has prompted pharmaceutical companies to outsource data management to compliance and transparency. In all, revenue has been expanding at a CAGR of 5.9% to an estimated $8.9 billion over the past five years, including expected growth of 2.7% in 2024.

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.

This statistic shows the percentage of clinical studies with posted results worldwide by type, as of November 8, 2024. Some 94 percent of studies with posted results were interventional types.

A major challenge for rare disease clinical trials is the limited amount of available information for making robust statistical inference. While external data present information integration opportunities to enhance statistical inference, conventional data combining methods, for example, meta-analysis, usually do not adequately address study population differences. Matching methods, on the other hand, directly account for population characteristics but often lead to inefficient use of data by underutilizing unmatched data points. Aiming at a better bias-variance tradeoff, we propose an intuitive integrated inference framework to borrow information from all relevant data sources and make inference on the response of interest over a target population precisely characterized by the joint distribution of baseline covariates. The method is easily implemented and can be complemented by modern statistical learning or machine learning tools. Statistical inference is facilitated by the bootstrap. We argue that the integrated inference framework not only provides an intuitive and coherent perspective for a variety of clinical trial inference problems but also has broad application areas in clinical trial settings and beyond, as a quantitative data integration tool for making robust inference in a target population precise manner for policy and decision makers.

Background: The aim of this study was to examine if eligible trials registered on ClinicalTrials.gov provided data sharing statements and if they did to what extent did the data sharing statements fulfil the International Committee of Medical Journal Editors (ICMJE). Methods: This is a retrospective study of publicly available data with results analysed using descriptive statistics. Results: 41% of studies (n=135) said ‘No’ to the ‘Intentions to Share IPD’ question on ClinicalTrials.gov, 27% (N = 90) answered ‘Yes’, 27% (n = 88) left the question blank and 5% (n = 16) have answered ‘Undecided’. None of the studies that answered ‘No’ or ‘Undecided’ have provided reasons why. Out of the 90 studies that answered ‘Yes’ to intentions to share IPD, 3 studies have answered ‘Yes’ but have not provided a DSS or IPD sharing plan. Conclusions: Despite the International Committee of Medical Journal Editors (ICMJE) guidelines strongly encouraged since 2018, many sponsors still do not follow the guidelines and do not provide any reasons as to why. This can have potentially negative implications and result in, for example, deceleration of advancement of medical research and waste of time and resources on research that has already been performed.