CALL US +44 (0)1462 440 084 | +1 919-882-2016 | Contact | Submit RFI
Clinical Programming Team

Clinical Programming Team

Connect with me:

Author's Posts

The Logic of a Clinical Research Organization Programmer

Clinical Programming Team

As a statistical programmer at a leading data focused Clinical Research Organization (CRO), we are requested to become involved with many programming activities on a daily basis, centred around dataset or display generation and quality control (QC). Having the opportunity to develop a process/system which can be used by others is rare. To build any system, a lot of in depth thought is required before any programming begins. We take the requirements and build a robust system to address each potential scenario that may arise, including some which should not.

Within this blog we will explain how statistical programmers can work through a simple request to build a robust system using logic, SAS, UNIX and experience. It will provide a flavour of how robust systems are built and other considerations. 

Read More
Topics: Clinical Programming, SAS Programming, Quality Control, SAS Macros, Quality Process Improvement, SAS

The INTO Statement in PROC SQL to Create Macro Variables

Clinical Programming Team

A member of the Quanticate Programming team writes about their opinions of the INTO statement in PROC SQL.

Read More
Topics: Clinical Programming, SAS Programming, Large Datasets, SAS Macros, PROC SQL

A Review of the Annual PhUSE 2016 Conference

Clinical Programming Team

A number of team members were able to represent Quanticate at the PhUSE 2016 annual conference in Barcelona. The PhUSE annual conference is an opportunity for programmers and statisticians to both learn from and share cutting edge knowledge with the pharmaceutical industry. This year, Quanticate presented on producing high quality SAS graphics using the advanced Graphical Template Language (GTL) to bring individual plots together to aid analysis without sacrificing any aesthetical properties in the process. Conference attendees were spoilt for choice with approximately 5 simultaneous presentations every half-hour across 15 streams in total. Here are some interesting presentations which the team enjoyed over the conference duration.

 

Read More
Topics: Programming R, Clinical Programming, SAS Programming, Visualization, Conferences, SAS Graph

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.

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

Outcomes Research Programming vs Traditional Clinical Trial Programming

Clinical Programming Team

Outcomes research aka health outcomes research, is the study of the end results of particular health care practices and interventions, in other words it is the study of what happens in the real world to patients when they are given a certain treatment or a certain method of care. Outcomes research studies are used to improve the quality and value of healthcare for patients.

Read More
Topics: Statistical Programming, Clinical Study Design, Clinical Programming, Accessible Data, Big Data, Outcomes Research, Real World Data, Teradata SQL

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:

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

Your SAS Secrets Exposed! [4 SAS Tips]

Clinical Programming Team

SAS_Tips

During my time in the life science industry I have learnt a lot of SAS techniques through attending training sessions, however some of the best SAS tips I have picked up were from other programmers: for instance when asking for advice on a coding problem or running programs written by colleagues. I found there are many simple SAS® tips you can use in your day to day SAS programming. This blog will provide explanations and examples of four of these.

Read More
Topics: Clinical Programming, SAS Programming, SAS Datasets, SAS Macros, SAS

The Creation of ADaM Datasets for Pharmacokinetic (PK) Analysis [Video]

Clinical Programming Team

In this recorded presentation a member of the Quanticate's Statistical Programming Team explores the creation of two ADaM datasets; ADPC and ADPP for Pharmacokinetic (PK) Analysis.

 

Read More
Topics: Pharmacokinetics and Pharmacodynamic, CDISC Guidelines, CDISC SDTM, SDTM Domains, CDISC, Clinical Programming, SDTM, CDISC Standards, PK Analysis, ADaM Datasets

An Overview of Efficacy Endpoints in Oncology Studies

Clinical Programming Team

This blog provides an overview of efficacy endpoints in oncology studies. We will focus on RECIST (Response Evaluation Criteria In Solid Tumours).This is a method of assessing how solid tumours change over the course of a study. We will cover the measurements taken for RECIST assessments (Target lesions, Non target lesions, New lesions) and the possible outcomes, (complete response, partial response, stable disease, progressive disease) and what they mean – for example; patient recovered, stayed the same or got worse. We will also cover how visit windows and censoring can be handled. How and why measurement methods are important.  We will cover other endpoints relevant to oncology such as Overall survival, Objective Response Rate, Best overall response, Disease control at X weeks and quality of life.

Read More
Topics: Clinical Programming, Ethics, Oncology

Using Microsoft Excel to write SAS code in Clinical Trials

Clinical Programming Team

Often when we write SAS code in the pharmaceutical industry, there is a high level of repetition. This guide explains ways of writing repetitive SAS code using Excel that will reduce the overall time to write the code and make large scale amendments easier and quicker.

Read More
Topics: Clinical Programming, SAS Programming, Large Datasets, SAS Datasets

Welcome to The Quanticate Blog

We aim to provide information and support written by our experienced staff. We want to share our knowledge and create an archive of information that you will be able to engage with, share and comment on.

Subscribe to Email Updates

Blog Suggestions

Most Read

Posts by Topic

Expand all