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Patient Centricity in Clinical Trials

Clinical Data Management Team


Patient safety has been the primary focus of clinical trial design since 1947 when the Nuremberg code outlined the ethical guidelines for clinical research. Trials must be designed to avoid injury or suffering and patients must give consent and are free to leave the trial at any point. The current world of drug development governed by ICH-GCP makes it mandatory to have all necessary steps taken by sponsors, CROs and investigators to keep patient safety as utmost priority.

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Topics: Clinical Trials, Patient Narratives, Clinical Research Organization, Drug Development, Patient Safety, Wearables in Clinical Trials, Clinical Data Management, mHealth, effective trial design, trial design, Artificial Intelligence, Machine Learning

Using R Programming for Clinical Trial Data Analysis

Clinical Programming Team

The use of R programming in clinical trials has not been the most popular and obvious, despite its recent growth over the past few years, its practical use still seems to be hindered by several factors, sometimes due to misunderstandings, (e.g validation) but also because of a lack of knowledge of its capabilities. Despite these bottlenecks, though, R is doubtlessly creating its own (larger by the day) niche in the pharmaceutical industry.

In this blog we will see how R can be used to create TLFs much like the current combination of PROC REPORT/PROC TABULATE and the ODS currently does, thus showing its power and capability to play an important role in our industry in the years to come, not as a replacement for, but rather as an alternative option to SAS®.

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Topics: Clinical Trials, Statistical Programming, Programming R, Clinical Programming, SAS Programming, SAS Datasets, ADaM Datasets, Open Source, SAS, R

The History and Development of Pinnacle 21

Clinical Programming Team

Until 2007, the Food Drug & Administration (FDA) and the biopharmaceutical industry were grappled by the non-standardized sources of data. Gathering all the heterogenous data and mapping to the internal standards of the pharma companies proved to be the greatest challenge of the time. By the end of 2007, and towards the beginning of 2008, the Clinical Data Interchange Standards Consortium (CDISC) gained ground in its mission to develop a global set of standards. Eventually, CDISC began shaping the entire industry as FDA started requesting submission data in standardized formats, though CDISC compliant software options were limited.1,2 The ‘study data standards’ provide a consistent general framework for organizing data, including templates for datasets, standard names for variables, identify appropriate controlled terminology and standard ways of doing calculations with common variables.3

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Topics: Clinical Trials, CDISC Guidelines, CDISC, FDA, Standardization, Clinical Programming, SDTM, CDISC Standards, ADaM Datasets, CDISC CDASH, Clinical Research Organization, Open Source, Open Standards, CRO, Define.xml, Pinnacle 21

4 ways to Improve Clinical Data Quality in the Digital Era

Clinical Data Management Team

The shift from paper to Electronic Data Capture (EDC) in the clinical trial world saw a shift in the way we look at the quality measurements of clinical data management (CDM) activities. The paper world had a clear understanding that the quality of the clinical data collected was simply the quality of the transcription work teams performed of transferring data from paper to a database. The Quality Control (QC) of paper versus database had a set standard for sampling of √N+1 or 20 subjects, whichever was smaller and a 100% QC of critical variables. Acceptable error rates were 0.5% which was widely agreed across the industry. These thresholds were no longer necessary when EDC enabled sites to enter the data directly and transcription was no longer needed. However, it is the role of the data management teams to be involved in many efforts to prepare data for appropriate analysis and submissions.

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Topics: CDISC, Case Report Form (CRF), Electronic Data Capture, SDTM, CDISC CDASH, Quality Process Improvement, Mobile Device, Wearables in Clinical Trials, Wearables, Clinical Data Management, Electronica Patient Reported Outcome (ePRO)

Real World Evidence in Drug Development [Podcast]

Statistical Consultancy Team

Welcome to our FiresideSTATS Podcast Episode 2. Today we are joined by our Statistical experts, Niccolo and Emily.

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Topics: Clinical Trials, Historical Data, Drug Development, Oncology, Statistics, Real World Data, Statistical Consultancy

Real-Time Oncology Review (RTOR): First Drug Approval

Statistical Consultancy Team


In 1992, the Food and Drug Administration (FDA) introduced four distinct and successful approaches known as Priority Review, Breakthrough Therapy, Accelerated Approval, and Fast Track approval of the investigational drug. Under the ‘accelerated approval’ regulation, surrogate endpoints for serious conditions that filled an unmet medical need are reviewed by FDA, allowing faster approval of drugs. A two-tiered system of review times – Standard Review and Priority Review were introduced by FDA under the Prescription Drug User Act (PDUFA). FDA reviews ‘Priority Review’ designated drugs within 6 months (compared to 10 months under standard review).[i]

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Topics: Clinical Trials, FDA, Clinical Study Design, Oncology, Statistical Consultancy, Real-Time Oncology Review (RTOR)

Respiratory Clinical Trials to Support COVID-19 Survivors

Statistical Consultancy Team


The leading cause of death in patients with coronavirus disease 2019 (COVID-19), caused by the virus ‘severe acute respiratory syndrome coronavirus 2’ (SARS‑CoV‑2), is respiratory failure from acute respiratory distress syndrome.[1] Patients who required invasive mechanical ventilation had an 88% mortality rate in one study in New York, and a 53% mortality rate in one study in the UK.[2][3] While an alarming proportion of patients with respiratory failure are dying, for the those who recover there is an urgent need to consider, and subsequently manage,  their longer-term care.[4] Patients who have survived the COVID‑19 infection continue to experience feelings of fatigue, shortness of breath and reduced exercise tolerance. There is currently limited information regarding the best route to full recovery for post-coronavirus infection patients. Care will likely be multidisciplinary in nature and include a respiratory review along with physiotherapy, nutritional advice, psychiatric support, and potentially other disciplinary involvement.

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Topics: Clinical Trials, Clinical Study Design, Clinical Trial Phases, Clinical Data Management, Statistical Analysis Plan, Statistical Consultancy, Covid-19, Pulmonary, Respiratory

Regulatory Writing – An Integral Part of Clinical Research

Medical Writing Team

There are two main areas in medical writing, medical communications and regulatory writing. This blog focuses on regulatory writing, which involves the preparation of clinical study and regulatory submission documentation.

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Topics: FDA, European Medicines Agency, Medical Writing, Regulatory Writing, Clinical Trial Documentation, Clinical Documents, Clinical Study Report

Remote Monitoring During Clinical Trials - COVID-19 Update

Commercial Team

This article has been updated in May 2020 to reflect the recent guidance by European Medicines Agency and other regulatory bodies on remote monitoring due to the recent coronavirus disease (COVID-19) pandemic.

Within the last few decades the number and complexity of clinical trials has increased considerably, not only across the industry but also within individual companies.  With this increase comes the enhanced pressure of effectively monitoring these trials.

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Topics: Regulatory Requirements, Clinical Trials, Good Clinical Practice (GCP), Clinical Data Storage, FDA, Case Report Form (CRF), Remote Monitoring, Adverse Events (AEs), European Medicines Agency, Ethics, On-Site Monitoring, CRAs, Risk Based Monitoring, Centralized Monitoring, Data Quality Oversight, rSDV, Centralized Statistical Monitoring

A Guide to CDISC SDTM Standards, Theory and Application

Clinical Programming Team

The Clinical Data Interchange Standards Consortium (CDISC) creates standards that is now mandatory for the regulatory submission to the FDA and PMDA. Study Data Tabulation Model (SDTM) is one of the standards which provides a standard for streamlined data in collection, management, analysis and reporting. If your data is not in SDTM standards then a pharmaceutical company or Clinical Research Organizations (CRO) will regard SDTM mapping to the latest version of SDTM standards for regulatory submission.

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Topics: Statistical Programming, CDISC Guidelines, CDISC SDTM, SDTM Domains, CDISC, Standardization, Clinical Programming, SAS Programming, CDISC Interchange

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