Overview

Weiliang Qiu1, Cheng Wenren1, Tamara Slavnic2, Els Pattyn1, Luc Essermeant1

1Non-Clinical Efficacy & Safety, Early Development & Research, Biostatistics & Programming, Sanofi

2 IT&M Stats

Dose–response relationships are important in assessing the efficacy and potency of drugs, which can usually be characterized by a 4-parameter logistic (4-PL) model: EC50, slope, lower asymptote, and upper asymptote. EC50, the concentration of a drug that induces a response halfway between the baseline and maximum, is a key quantity to evaluate drug potency. For multi-donor dose-response data, it is often the interest to estimate the overall EC50 and its 95% confidence interval (CI). A few multi-donor EC50 estimation methods have been proposed in literature. Jiang and Kopp-Schneider (2014) systematically compared meta-analysis and nonlinear mixed-effects approaches and concluded that meta-analysis approach is simple and robust to summarize EC50 estimates from multiple experiments, especially suited in the case of small number of experiments, while nonlinear mixed-effects approach has issue of convergence failure probably due to overparameterization. In this talk, we investigated ways to improve nonlinear mixed-effects approach to alleviates its issue of convergence failure.

Weiliang Qiu, Els Pattyn, Cheng Wenren and Luc Essermeant are Sanofi employees and may hold shares and/or stock options in the company. Tamara Slavnic has nothing to disclose.

Who is this event intended for? Statisticians in the Pharmaceutical Industry.

What is the benefit of attending? EC50, the concentration of a drug that induces a response halfway between the baseline and maximum, is a key quantity to evaluate drug potency. In this talk, attendees will hear from Weiliang and Cheng who will be presenting their investigations on EC50 estimation based on multi-donor dose-response data via different approaches.