Financial overview and grant giving statistics of Clinical Data Interchange Standards Consortium Inc.

ACC/AHA = American College of Cardiology/American Heart Association; ATS = American Thoracic Society; CDISC = Clinical Data Interchange Standards Consortium; NCI = National Cancer Institute; SF-36 = Short-form 36 questionnaire.

Diagnostics account for the largest share of the market, driven by the growing demand for early disease detection and monitoring. The therapeutic segment is experiencing steady growth due to the increasing prevalence of chronic diseases and demand for effective treatments. Implants, particularly active implantable medical devices, hold significant potential as technological advancements enable minimally invasive procedures and improve patient outcomes. Recent developments include: In October 2024, SGS Société Générale de Surveillance SA announced the launch of the new CDISC Open Rules consultancy to assist pharmaceutical organizations in navigating compliance with the latest CDISC standards for clinical trial submissions. This service offers comprehensive support from initial consultation to ongoing evaluation, ensuring high-quality data and regulatory adherence. .

The purpose of the NINDS Common Data Elements (CDEs) Project is to standardize the collection of investigational data in order to facilitate comparison of results across studies and more effectively aggregate information into significant metadata results. The goal of the National Institute of Neurological Disorders and Stroke (NINDS) CDE Project specifically is to develop data standards for clinical research within the neurological community. Central to this Project is the creation of common definitions and data sets so that information (data) is consistently captured and recorded across studies. To harmonize data collected from clinical studies, the NINDS Office of Clinical Research is spearheading the effort to develop CDEs in neuroscience. This Web site outlines these data standards and provides accompanying tools to help investigators and research teams collect and record standardized clinical data. The Institute still encourages creativity and uniqueness by allowing investigators to independently identify and add their own critical variables. The CDEs have been identified through review of the documentation of numerous studies funded by NINDS, review of the literature and regulatory requirements, and review of other Institute''s common data efforts. Other data standards such as those of the Clinical Data Interchange Standards Consortium (CDISC), the Clinical Data Acquisition Standards Harmonization (CDASH) Initiative, ClinicalTrials.gov, the NINDS Genetics Repository, and the NIH Roadmap efforts have also been followed to ensure that the NINDS CDEs are comprehensive and as compatible as possible with those standards. CDEs now available: * General (CDEs that cross diseases) Updated Feb. 2011! * Congenital Muscular Dystrophy * Epilepsy (Updated Sept 2011) * Friedreich''s Ataxia * Parkinson''s Disease * Spinal Cord Injury * Stroke * Traumatic Brain Injury CDEs in development: * Amyotrophic Lateral Sclerosis (Public review Sept 15 through Nov 15) * Frontotemporal Dementia * Headache * Huntington''s Disease * Multiple Sclerosis * Neuromuscular Diseases ** Adult and pediatric working groups are being finalized and these groups will focus on: Duchenne Muscular Dystrophy, Facioscapulohumeral Muscular Dystrophy, Myasthenia Gravis, Myotonic Dystrophy, and Spinal Muscular Atrophy The following tools are available through this portal: * CDE Catalog - includes the universe of all CDEs. Users are able to search the full universe to isolate a subset of the CDEs (e.g., all stroke-specific CDEs, all pediatric epilepsy CDEs, etc.) and download details about those CDEs. * CRF Library - (a.k.a., Library of Case Report Form Modules and Guidelines) contains all the CRF Modules that have been created through the NINDS CDE Project as well as various guideline documents. Users are able to search the library to find CRF Modules and Guidelines of interest. * Form Builder - enables users to start the process of assembling a CRF or form by allowing them to choose the CDEs they would like to include on the form. This tool is intended to assist data managers and database developers to create data dictionaries for their study forms.

Large scale analysis of in vivo toxicology studies has been hindered by the lack of a standardized digital format for data analysis. The SEND standard enables the analysis of data from multiple studies performed by different laboratories. The objective of this work is to develop methods to transform, sort, and analyze data to automate cross study analysis of toxicology studies. Cross study analysis can be applied to use cases such as understanding a single compound’s toxicity profile across all studies performed and/or evaluating on- versus off-target toxicity for multiple compounds intended for the same pharmacological target. This collaborative work between BioCelerate and FDA involved development of data harmonization/transformation strategies and analytic techniques to enable cross-study analysis of both numerical and categorical SEND data. Four de-identified SEND data sets from the BioCelerate Toxicology Data Sharing module of DataCelerate® were used for the analyses. Toxicity prof..., Deidentified SEND data was donated by companies participating in BioCelerate’s Toxicology Data Sharing Initiative (TDS module in DataCelerate®).The data included 1-Month Rat and 1-Month Dog SEND datasets for two different compounds intended for the same pharmacological target. To facilitate cross-study analysis of toxicology studies, it is practical to categorize findings within organ systems to provide insights into target organ toxicity. In the proof-of-concept for this application, we focused on the target organs with compound-related effects, namely the kidney, liver, hematopoietic system, endocrine system, and reproductive tract (male). The body weights (BW), food and water consumption (FW), laboratory test results (LB), organ measurements (OM), and microscopic findings (MI) SEND domains were included in the analysis. Each parameter was then assigned to the relevant organ system(s) (Table 1) based on veterinary literature (Faqi 2017) (Stockham 2008), scientific literature on ..., , # Dataset for Cross Study Analyses of SEND Data: Toxicity Profile Classification

https://doi.org/10.5061/dryad.s1rn8pkgr

The data included 1-Month Rat and 1-Month Dog SEND datasets for two different compounds (Compound A and Compound B) intended for the same pharmacological target.Â

Description of the data and file structure

The files contain data from toxicology studies performed in rats and dogs to support clinical development for two different drugs intended for the same pharmacological target. The studies were donated by the pharmaceutical companies involved in development of the compounds. All proprietary and identifying information has been removed and deidentified. Â

The toxicology data is organized based on the CDISC - Standard for Exchange of Nonclinical Data (SEND) data standard (https://www.cdisc.org/standards/foundational/send/sendig-v3-1) and stored in .json a...,

Biostatistics and Programming Services Market Outlook

According to our latest research, the global Biostatistics and Programming Services market size reached USD 2.94 billion in 2024, reflecting robust demand from the pharmaceutical and biotechnology sectors. The market is poised for significant expansion, with a projected CAGR of 8.2% during the forecast period. By 2033, the market is forecasted to reach USD 5.85 billion, driven by increasing clinical trial complexity, stringent regulatory requirements, and the rising adoption of advanced analytics in drug development. The ongoing digital transformation in life sciences and the growing outsourcing trend among pharmaceutical and biotechnology companies are key factors propelling this growth.

One of the primary growth drivers for the Biostatistics and Programming Services market is the escalating demand for efficient data management and statistical analysis in clinical trials. As clinical trials become more complex, encompassing larger and more diverse patient populations, the volume and complexity of data generated have surged. This has necessitated the adoption of advanced biostatistical methods and programming services to ensure data integrity, regulatory compliance, and accelerated timelines. The industry’s focus on reducing time-to-market for new therapeutics has further intensified the need for specialized biostatistics and programming expertise, as these services are pivotal in streamlining data collection, cleaning, and analysis processes. As a result, pharmaceutical and biotechnology companies are increasingly outsourcing these functions to specialized service providers, leading to market expansion.

Technological advancements are also significantly shaping the growth trajectory of the Biostatistics and Programming Services market. The integration of artificial intelligence, machine learning, and big data analytics into clinical data management and statistical programming is enhancing the quality and efficiency of data analysis. These technologies enable the handling of large-scale, multi-source data sets, facilitate predictive modeling, and improve the accuracy of statistical outputs. Moreover, the adoption of cloud-based platforms for clinical data management is enabling real-time access, collaboration, and scalability, which are critical for multi-center and global clinical trials. The ongoing evolution of regulatory standards, such as the implementation of CDISC (Clinical Data Interchange Standards Consortium) standards, is further driving the demand for sophisticated programming and biostatistical services capable of meeting stringent data submission requirements.

Another notable growth factor is the increasing trend of outsourcing biostatistics and programming services to contract research organizations (CROs) and specialized service providers. Pharmaceutical and biotechnology companies are under constant pressure to optimize costs, accelerate timelines, and access specialized expertise. Outsourcing enables these companies to focus on their core competencies while leveraging the technical capabilities and regulatory expertise of external partners. This trend is particularly pronounced among small and mid-sized enterprises, which may lack in-house resources for comprehensive biostatistical and programming support. Additionally, the globalization of clinical trials and the expansion of research activities into emerging markets are fueling the need for region-specific expertise and scalable service delivery models.

From a regional perspective, North America continues to dominate the Biostatistics and Programming Services market, accounting for the largest share in 2024. This is attributed to the presence of a robust pharmaceutical and biotechnology industry, advanced healthcare infrastructure, and a high concentration of clinical trials. The region’s regulatory landscape, characterized by stringent data integrity and compliance requirements, further drives the adoption of specialized biostatistics and programming services. Europe follows closely, supported by strong government initiatives and increasing R&D investments. Meanwhile, the Asia Pacific region is emerging as a high-growth market, propelled by the rising number of clinical trials, expanding pharmaceutical manufacturing capabilities, and favorable regulatory reforms. These regional dynamics are expected to shape the competitive landscape and growth opportunities in the coming years.

Service Type Analysis

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