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.

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.

This statistic shows the percentage of clinical studies with posted results worldwide by type, as of April 15, 2024. Some 94 percent of studies with posted results were interventional types.

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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

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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 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.

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.

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.

As of April 2024, Brazil led the ranking of Latin American countries with most clinical trials, with close to 10,000 studies. Mexico ranked second, with nearly 5,000 clinical trials. Brazil concentrated 4.3 percent of the clinical trials performed worldwide regarding infectious diseases in 2021.

Dataset

This dataset was created by Kevin Gonzalez Garcia

Contents

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 Clinical Trials Registry and Results Database compiles information on publicly and privately supported clinical trial studies on a wide range of diseases and conditions. Its main goal is to provide an easy access to both privately and publicly funded clinical trials information for patients, their family members, healthcare professionals, researchers, and the public.

The global big data analytics for clinical research market size was USD XX Mn in 2022 and is likely to reach USD XX Mn by 2031, expanding at a CAGR of XX % during 2023–2031. Rising need for data analysis in clinical research operations to develop novel drug and treatment therapies is projected to fuel the market.



Clinical research is a data-driven domain that comprises heavily regulated processes and an enormous amount of data analysis to optimize and improve clinical research operations. During clinical research operations, huge silos of data are collected from various sources and stored in different formats.

Diverse sets of data such as drug databases, historical clinical trials, electronic medical records, human genome, sensors data, and scientific publications data are mined through clinical data analytics in clinical research operations. This data is used to develop improved clinical research designs, site selection, and suitable patient recruitment to fast-track clinical research processes.



Clinical scientists leverage data to make comprehensive data-driven decisions with the help of prescriptive and predictive analytics on clinical trial data. Big data analytics in healthcare and clinical research provide accessible data repository system aimed at improving enterprise-level decision-making that helps clinicians formulate effective R&D strategy and execution during clinical research operations.



Big data analytics for clinical research offers valuable insights through centralized clinical data lakes by compiling structured, semi-structured, and unstructured data from various sources. The compiled data is then used to reduce the risks and costs associated with clinical research operations. Data sources such as genomics, biomarker, electronic health records, and real-world data serve as an instrument to accelerate and improve the drug development processes significantly.

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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.

Clinical Trial Data Visualization Market Outlook

The global clinical trial data visualization market size is projected to grow from USD 0.75 billion in 2023 to USD 2.62 billion by 2032, reflecting a compound annual growth rate (CAGR) of 15.2% during the forecast period. This growth is driven by the increasing complexity of clinical trials, the need for enhanced data transparency, and the rising adoption of digital tools in the healthcare sector.

One of the key drivers for the growth of the clinical trial data visualization market is the escalating complexity and volume of data generated during clinical trials. The pharmaceutical and biotechnology sectors are witnessing a surge in clinical trials, which demand sophisticated data management and visualization tools to make sense of the vast amounts of data collected. These tools enable researchers to identify patterns, trends, and outliers more efficiently, thereby accelerating the decision-making process and improving clinical trial outcomes.

Another significant factor contributing to market growth is the increasing emphasis on data transparency and regulatory compliance. Regulatory bodies, such as the FDA and EMA, are mandating greater transparency in clinical trial data to ensure patient safety and data integrity. Data visualization tools facilitate the clear presentation of complex data, making it easier for regulatory bodies and stakeholders to review and approve clinical trial processes. This ensures that clinical trials are conducted in a more transparent and compliant manner, thus driving the adoption of these tools.

The advent of advanced technologies, such as artificial intelligence (AI) and machine learning (ML), is also playing a crucial role in the growth of the clinical trial data visualization market. These technologies are being increasingly integrated into data visualization tools to enhance their capabilities. AI and ML algorithms can analyze large datasets quickly and provide insights that were previously unattainable. This not only improves the efficiency of clinical trials but also enhances the accuracy and reliability of the data being presented.

Regionally, North America is expected to dominate the clinical trial data visualization market due to the presence of a large number of pharmaceutical and biotechnology companies, a well-established healthcare infrastructure, and a strong focus on research and development. Europe is also expected to witness significant growth, driven by the increasing adoption of digital technologies in clinical trials and supportive regulatory frameworks. The Asia Pacific region is poised to grow at the fastest rate, fueled by the expanding pharmaceutical industry, growing investments in healthcare technology, and an increasing number of clinical trials being conducted in countries like China and India.

Component Analysis

The clinical trial data visualization market is segmented into software and services based on components. The software segment is expected to hold the largest market share during the forecast period. This can be attributed to the increasing demand for advanced software solutions that offer real-time data analysis and visualization capabilities. These software tools are designed to handle large volumes of data and provide intuitive visual representations that facilitate better understanding and decision-making.

Furthermore, the integration of AI and ML technologies into data visualization software is enhancing their capabilities, making them more efficient and accurate. These advanced software solutions are capable of analyzing complex datasets and providing actionable insights, which are critical for the successful execution of clinical trials. As a result, the adoption of software solutions is expected to grow significantly in the coming years.

On the other hand, the services segment is also expected to witness substantial growth. Services such as implementation, training, and support are crucial for the successful deployment and utilization of data visualization tools. These services ensure that organizations can effectively integrate these tools into their existing systems and workflows, thereby maximizing their benefits. Additionally, ongoing support and maintenance services are essential to address any technical issues and ensure the smooth functioning of the software.

Moreover, the increasing outsourcing of clinical trial processes to contract research organizations (CROs) is driving the demand for data visualization services. CROs are increasingly relying on specialized service provide

Meta-analyses of clinical trials often treat the number of patients experiencing a medical event as binomially distributed when individual patient data for fitting standard time-to-event models are unavailable. Assuming identical drop-out time distributions across arms, random censorship and low proportions of patients with an event, a binomial approach results in a valid test of the null hypothesis of no treatment effect with minimal loss in efficiency compared to time-to-event methods. To deal with differences in follow-up - at the cost of assuming specific distributions for event and drop-out times - we propose a hierarchical multivariate meta-analysis model using the aggregate data likelihood based on the number of cases, fatal cases and discontinuations in each group, as well as the planned trial duration and groups sizes. Such a model also enables exchangeability assumptions about parameters of survival distributions, for which they are more appropriate than for the expected proportion of patients with an event across trials of substantially different length. Borrowing information from other trials within a meta-analysis or from historical data is particularly useful for rare events data. Prior information or exchangeability assumptions also avoid the parameter identifiability problems that arise when using more flexible event and drop-out time distributions than the exponential one. We discuss the derivation of robust historical priors and illustrate the discussed methods using an example. We also compare the proposed approach against other aggregate data meta-analysis methods in a simulation study.

As of mid-April 2024, the number of registered clinical studies in non-U.S. regions stood at some 267 thousand - or 54 percent of all studies worldwide. This statistic shows the distribution of registered clinical studies worldwide by location.

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