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Seminar notes "S-PLUS Clinical Safety Miner" (March 10, 2005). Category: Statistical computing

I attended a web seminar by Michael O’Connell, "Applications in Drug Discovery and Development. S-PLUS® Clinical Safety Miner." Michael O’Connell is the Director, Life Science Solutions at Insightful Corporation, the company that produces S-plus software. Insightful also produces a range of other products that work with S-plus, such as

  • S+SeqTrial, for design and analysis of group sequential trials with interim stopping rules.
  • S+ArrayAnalyzer, which analyzes data from microarray experiments.

This talk focused on S-plus Clinical Safety Miner which integrates features from

The seminar showed three applications of Clinical Safety Miner that emphasized the ability to produce interactive and easily updateable web reports. These web reports allow you to drill down from aggregated measures of adverse event risk to get subgroup information or data on individual patient events. The web report has an Rich Text Format (RTF) template which makes it easy for you to produce high quality printed reports.

Dr. O'Connell also demonstrated the capability for this software to document validation as required in 21 CFR 11. This rule presents

criteria under which FDA will consider electronic records to be equivalent to paper records, and electronic signatures equivalent to traditional handwritten signatures.

This rule has six components:

  1. validation;
  2. the ability to generate accurate and complete copies of records;
  3. archival protection of records;
  4. use of computer-generated, time-stamped audit trails;
  5. use of appropriate controls over systems documentation; and
  6. a determination that persons who develop, maintain, or use electronic records and signature systems have the education, training, and experience to perform their assigned tasks.

Anyone submitting data to FDA needs to know about 21 CFR 11.

Perhaps the most interesting of the three applications involved data from the FDA AERS database on four COX-2 inhibitors. The software computed and displayed observed versus expected counts of adverse events for each drug. It used a Bayesian Poisson model implemented with a Markov Chain Monte Carlo (MCMC). This model relied on a newly released S+Bayes library. I asked at the end of the seminar whether this software could be used for reporting to IRBs that are providing continuing review of research studies. Dr. O'Connell said that this would be an excellent application of the software and would allow the IRBs to better understand the flow of data.

The Insightful web site has materials from the talk at

This webpage was written by Steve Simon and was last modified on 07/08/2008.