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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.

 

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

Comparing treatment response curves: a practical example in rheumatoid arthritis

Statistical Consultancy Team

Nowadays, more and more studies are being designed to collect information on treatment response at several time points during the treatment period of the study. Although the primary endpoint is often the comparison at the end of the study of the absolute response or of the change to baseline between study treatments, analyses involving intermediate time points in the assessment of treatment effects, e.g., repeated measures modeling, are now widely used.

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Topics: Programming R, SAS Programming, Therapeutic Areas, Biostatistics Consulting, Phase 3 Studies, Rheumatoid Arthritis (RA), PROC NLMIXED, PROC IML

Using Historical Data to Inform Future Decisions in Clinical Trials

Statistical Consultancy Team

The majority of companies within the Pharmaceutical Industry have large historical clinical databases, much of which may never be used beyond its original purpose: to prove that the drug in question is safe and efficacious. This historical data can be used to better inform future decisions in clinical trials. 

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Topics: Bayesian Statistics, Programming R, Phase I Studies, Adverse Events (AEs), Clinical Study Design, Historical Data

Using the Statistical Programming Language R in the Pharma Industry

Statistical Consultancy Team

The statistical programming language R is often underrated within the Pharmaceutical Industry. Often the default is to pay for expensive software when R could be a viable option. R is freely available and runs on almost all operating systems including Unix, MacOS, and Microsoft Windows.

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Topics: Statistical Programming, Programming R, Large Datasets, Visualization

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