Richard Zink
Principal Research Statistician Developer

Richard C. Zink is Principal Research Statistician Developer in the JMP Life Sciences division at SAS Institute. He joined SAS in 2011 after eight years in the pharmaceutical industry, where he designed and analyzed clinical trials in multiple therapeutic areas and participated in US and European drug submissions and FDA advisory committee hearings. Richard is the Statistics Section Editor for Therapeutic Innovation & Regulatory Science (formerly Drug Information Journal), and holds a Ph.D. in Biostatistics from the University of North Carolina at Chapel Hill. Follow him at @rczink.

The 2013 JMP Life Sciences European Roadshow

This May, JMP Life Sciences is going on the road in Europe to demo some of the new features that will be available in the upcoming releases of JMP Clinical 4.1 and JMP Genomics 6.1. The Roadshow is an excellent opportunity to hear about new functionality, ask questions or perhaps sneak

We don’t need another hero … or do we?

Those of us who grew up in the 1980s are likely very familiar with Tina Turner’s song from the soundtrack of Mad Max Beyond Thunderdome, the inspiration for the title of today’s post. If not, here is your opportunity to catch up. Now that we’re all on the same page,

Truly efficient clinical reviews – an example

JMP Clinical 4.1 contains example data to help illustrate its new review functionality. This additional data is referred to as Nicardipine Early Snapshot, and includes Nicardipine data only through 01 Aug 1989. There are numerous changes to this data set: 11 subjects have yet to enroll in the trial, the

Truly efficient clinical reviews – it’s all about the keys

In last week’s post, we discussed some of the upcoming features of JMP Clinical 4.1 that identify new and modified records when clinical trial data is updated. These tools can greatly accelerate clinical reviews, allowing the clinician, statistician or data manager to focus exclusively on unreviewed records. Here we discuss

Truly efficient data reviews for clinical trials

Over the next few posts, I discuss the data review process for clinical trials and highlight some new features for JMP Clinical 4.1 that streamline this monumental endeavor. Ideally, the data from a clinical trial should be examined by as many eyes as possible – including data and protocol managers,

Predictive modeling in the life sciences

This past week, Nate Silver held an “Ask Me Anything” chat on Reddit. There were several very good questions, one of which I found particularly important as we begin the International Year of Statistics: “What is the biggest abuse of statistics”? To which Nate replied: “Overfitting.” This response is very

A year for statistics

You may have heard the news that 2013 is the International Year of Statistics, a wordwide celebration of the contributions of statistics, and it couldn’t have come at a better time. Nate Silver’s near-perfect prediction of the presidential election and popular fare such as the recent Oscar-nominated Brad Pitt-starring film Moneyball

Identifying multivariate inliers and outliers

We’re nearing the end of this series of posts on fraud detection in clinical trials and some upcoming features of JMP Clinical 4.1 that help identify unusual observations. We’ve described how visit dates and measurements taken in the clinic can signify problems at the clinical site, and discussed how trial