Comparisons of outlier tests for potency bioassays

Potency bioassays are used to measure biological activity. Consequently, potency is considered a critical quality attribute in manufacturing. Relative potency is measured by comparing the concentration‐response curves of a manufactured test batch with that of a reference standard. If the curve shapes are deemed similar, the test batch is said to exhibit constant relative potency with the reference standard, a critical requirement for calibrating the potency of the final drug product. Outliers in bioassay potency data may result in the false acceptance/rejection of a bad/good sample and, if accepted, may yield a biased relative potency estimate. To avoid these issues, the USP<1032> recommends the screening of bioassay data for outliers prior to performing a relative potency analysis. In a recently published work, the effects of one or more outliers, outlier size, and outlier type on similarity testing and estimation of relative potency were thoroughly examined, confirming the USP<1032> outlier guidance. As a follow‐up, several outlier detection methods, including those proposed by the USP<1010>, are evaluated and compared in this work through computer simulation. Two novel outlier detection methods are also proposed. The effects of outlier removal on similarity testing and estimation of relative potency were evaluated, resulting in recommendations for best practice.     

The current state of Bayesian methods in nonclinical pharmaceutical statistics: Survey results and recommendations from the DIA/ASA-BIOP Nonclinical Bayesian Working Group

The use of Bayesian methods to support pharmaceutical product development has grown in recent years. In clinical statistics, the drive to provide faster access for patients to medical treatments has led to a heightened focus by industry and regulatory authorities on innovative clinical trial designs, including those that apply Bayesian methods. In nonclinical statistics, Bayesian applications have also made advances. However, they have been embraced far more slowly in the nonclinical area than in the clinical counterpart. In this article, we explore some of the reasons for this slower rate of adoption. We also present the results of a survey conducted for the purpose of understanding the current state of Bayesian application in nonclinical areas and for identifying areas of priority for the DIA/ASA-BIOP Nonclinical Bayesian Working Group. The survey explored current usage, hurdles, perceptions, and training needs for Bayesian methods among nonclinical statisticians. Based on the survey results, a set of recommendations is provided to help guide the future advancement of Bayesian applications in nonclinical pharmaceutical statistics.     

Healthy Dating: A Mixed-Gender Date Rape Workshop

Abstract

College communities are increasingly being called upon to institute date rape prevention programs. This article describes a mixed-gender workshop sponsored by a university's Program for Rape Education and Prevention that was given to more than 1,400 undergraduate students in more than 80 presentations. In order to guide modifications of the workshop, formative evaluation data collected from 330 male (mean age 20.3 years) and 314 female (mean age 20.5 years) university students were collected. Results were largely positive. Despite the sensitive nature of the topic, only 10.2% of the men and 8.2% of the women reported being uncomfortable discussing date rape in mixed-gender groups. Furthermore, students were virtually unanimous in their agreement that date rape is a topic worthy of a workshop.