Nonlinear model-based estimates of IC(50) for studies involving continuous therapeutic dose-response data.
We present statistical details for estimating an in vitro 50% inhibitory concentration (IC(50)), based on several models for continuous response data fit to bone-marrow endothelial cell lines replicated in vehicle and at several dose increments. Nonlinear models are fit via maximum likelihood assuming normal errors, and primary attention is given to exponential, Gompertz, and scaled logistic dose-response curves that admit increasing or decreasing monotonic and sigmoidal patterns. Careful consideration is given to dose axis scaling, comparative model fit via mean squared error and graphical assessment, analogues to weighted least squares analysis to address heterogeneity of variance across doses, and potential hormetic effects. Standard error estimation is discussed in detail, highlighting the advantage of reparameterizing dose-response models directly in terms of IC(50). Specific results for two cell lines are provided, along with a sample commercial software-based program for implementing a selection of the methods discussed.
Lyles
Robert H
RH
Department of Biostatistics, The Rollins School of Public Health of Emory University, Atlanta, GA 30322, USA. rlyles@sph.emory.edu
Poindexter
Cliff
C
Evans
Angelo
A
Brown
Milton
M
Cooper
Carlton R
CR
D003627:Data Interpretation, Statistical; D004305:Dose-Response Relationship, Drug; D006801:Humans; D020128:Inhibitory Concentration 50; D016013:Likelihood Functions; D016015:Logistic Models; D015233:Models, Statistical; D017711:Nonlinear Dynamics; D012107:Research Design