Creating Custom or Non-Standard CDISC SDTM Domains

Clinical Programming Team

Within the Clinical Data Interchange Standards Consortium (CDISC) Study Data Tabulation Model (SDTM), standard domains are split into four main types: special purpose, relationships, trial design and general observation classes. General observation classes cover the majority of observations collected during a study and can be divided among three general classes:

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

The Rise of Risk Based Monitoring [Infographic]

Thomas Underwood

Risk Based Monitoring is a term that is not new to the pharmaceutical industry. With increasing demand for budget reduction and reduced time to submission in drug development, both sponsors and vendors are seeking ways to reduce costs whilst still maintaining and potentially improving the quality of the data collected in clinical trials. Study costs can rise considerably for clinical trials with a large number of sites, especially across multiple countries. Risk Based Monitoring can reduce study costs considerably as there is a reduction in the need for CRAs to travel to sites, especially when coupled with a remote monitoring component. Also a reduction in the need to monitor all clinical trial sites and 100% of trial data, as those which are identified as more risk prone are visited more frequently according to targeted or triggered formulas. Even the FDA understands and encourages the desire to move away from 100% source data verification. Why therefore is the general mind-set in clinical operations exhibiting a degree of inertia to change with regard to RBM techniques? 

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Topics: Clinical Trials, Remote Monitoring, Electronic Data Capture, e-Clinical, Source Data Verification (SDV), Adverse Events (AEs), On-Site Monitoring, Serious Adverse Events (SAEs), Clinical Trial Phases, Additional Monitoring, Phase 2 Studies, Technology Trends, CRAs, Risk Based Monitoring

Exploring CDISC Analysis Data Model (ADaM) Datasets

Clinical Programming Team

Clinical Data Interchange Standards Consortium (CDISC) defines and manages industry level data standards that are widely used during the analysis, reporting and submission of clinical data. For instance, the Study Data Tabulation Model (SDTM) is the submission data standard into which raw study data are mapped and collated. ADaM is a companion standard for use with analysis data and it is best practice to use SDTM data as the source for these datasets. Doing this allows for the easy documentation of any data processing with Define-XML, the CDISC standard for data definition files.

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Topics: Traceability, CDISC SDTM, CDISC, Standardization, Adverse Events (AEs), Clinical Trial Documentation, Clinical Programming, SDTM, CDISC Standards, ADaM Datasets, Analysis Data Model, ADSL

Assessing Equivalence in Rheumatoid Arthritis in Clinical Trials

Statistical Consultancy Team

In Rheumatoid Arthritis (RA) clinical trials, treatment response is often assessed via the American College of Rhematology (ACR) composite responder score ACR20. This is a binary criterion that incorporates several indices of treatment activity in terms of symptoms reduction and is equal to 1 if at least 20% of improvement between a baseline and post-baseline measurement is observed in tender and swollen joint counts, in at least three out of five other indicators (C-Reactive Protein, patient global assessment of disease activity, physician global assessment of disease activity, patient pain scale, Health Assessment Questionnaire Disability Index), and 0 otherwise.

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Topics: Statistical Programming, Biostatistics Consulting, Rheumatoid Arthritis (RA), PROC NLMIXED

Preparing for Big Data in Pharma

Nick Burch


 

Today, the Pharmaceutical industry, like many, has its feet in both camps when it comes to Big Data. Some parts of the industry, such as genomics and drug discovery, were early adopters and today couldn't imagine life without Big Data technologies and approaches. Others are pushing their current approaches to near their limits, and are beginning to consider "what's next?"

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Topics: Clinical Data Storage, Large Datasets, Big Data

mHealth Apps and Wearables in Clinical Trials to Consider

Nick Burch

Today, mHealth, Mobile Health, Mobile Apps and Wearables are hot topics with consumers and regulators alike. We're also starting to see consumer-grade wearables and mHealth technologies creeping into clinical trials. We've written this blog for those looking to use this area more.

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Topics: Regulatory Requirements, FDA, European Medicines Agency, Quality Assurance, Mobile Device, Technology Trends, Wearables in Clinical Trials, Wearables, mHealth

Is Lack of Data the Biggest Challenge for Early Phase Pharmacovigilance?

Pharmacovigilance Team

We recently hosted a webinar on the challenges of Pharmacovigilance in early phase clinical trials. During the registration process we had the chance to survey members of the industry, 70% of the respondents were from pharmaceutical, biotechnology or medical device companies. We wanted to present the data from the 150 respondents in this blog.

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Topics: Regulatory Requirements, FDA, Phase I Studies, Adverse Events (AEs), Pharmacovigilance, Serious Adverse Events (SAEs), Clinical Trial Phases, Oncology

Understanding the Proportional Odds Assumption in Clinical Trials

Statistical Consultancy Team


Ordinal scales are commonly used to assess clinical outcomes; however, the choice of analysis is often sub-optimal.  In 2007, the Optimising Analysis of Stroke Trials (OAST) collaboration showed that ordinal-appropriate analyses of ordinal stroke outcome scales were preferable over binary analysis of a chosen ‘favourable’ outcome[1] but uptake of ordinal methods between 2007 and 2014 has been low [2].

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Topics: Randomization, SAS Programming, Biostatistics Consulting, Statistics, Ordinal Logistic Regression, Proportional Odds Assumption, PROC Logistic, Neurology

Celebrating International Clinical Trials Day

Marketing Quanticate

Happy International Clinical Trials Day! For those of you who do not know, International Clinical Trials Day is celebrated each year on 20th May. The event was created to commemorate the day James Lind started the first ever clinical trial to try and cure the deadly disease scurvy.

The clinical trial James Lind conducted consisted of using citrus fruit to cure scurvy. At the time the concept of vitamins were unknown, today we know scurvy is a result of vitamin C deficiency. James Lind was the first to study the effects of citrus fruits by conducting a systematic experiment on sailors in 1747 which is now regarded as one of the first clinical experiments in the history of medicine. 

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Topics: Clinical Trials, Ethics, Clinical Data Services, Statistics, International Clinical Trial Day

The Rise of Risk Based Monitoring in Clinical Trials

Thomas Underwood

During drug development the cost of clinical trials can rise significantly for studies that require several monitoring visits across multiple sites. Traditional monitoring techniques account for a large portion of these costs. Pharmaceutical companies absorb the costs of travel when their own Clinical Research Associates (CRAs) visit sites, while CROs normally charge clients these travel costs as pass through charges. It is estimated that remote monitoring in clinical trials could reduce travel costs (including unproductive time spent travelling) by up to 30%, and in theory the practice should be scalable across small to large clinical studies over several clinical trial phases[1]. The unproductive travel time saved also means CRAs have more time available for monitoring activities, aiding with the current CRA shortages[2].

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Topics: Clinical Trials, Remote Monitoring, Electronic Data Capture, e-Clinical, Source Data Verification (SDV), Adverse Events (AEs), On-Site Monitoring, Serious Adverse Events (SAEs), Clinical Trial Phases, Additional Monitoring, Phase 2 Studies, Technology Trends, CRAs, Risk Based Monitoring

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