SummaryVarying-coefficient models provide a useful tool to explore the dynamic pattern in various fields of science, such as epidemiology, medical research and ecology. Crucial issues arise in assessing the dose–response relationship from flexible dose clinical trial data: the current response is affected by not only the current dose level but also past dose levels, i.e. there is a time lag in the effectiveness of treatment and, also, there is considerable variability between subjects. To address these issues, we propose a novel non-linear varying-coefficient model, called a mixed effects historical varying-coefficient model (MEHVCM), for estimating dose–response curves in longitudinal flexible dose trials. This model enables us to describe historical effectiveness curves and subject-specific curves. Unknown parameters included in the MEHVCM are estimated by the maximum penalized likelihood method along with the EM algorithm. Monte Carlo experiments are conducted to investigate the performance of the MEHVCM for evaluating dose–response relationships in flexible dose trials. We apply the proposed model to the analysis of data from a multiple-sclerosis clinical trial.