Presenter: Melanie Quintana, PhD (Statistical Scientist, Berry Consultants)
Title: Bayesian Disease Progression Modeling in Clinical Trial Design
Abstract: We will focus our discussion on understanding the unique challenges that are encountered in designing clinical trials in slowly progressive and sporadic diseases and how disease progression models can help to overcome some of those challenges. Examples will be given to demonstrate the usefulness of disease progression modeling in conjunction with natural history data to guide decision making for key trial parameters and to provide an analysis model for determining if a novel therapy is effective in altering disease progression. Some examples of diseases in which there are currently no approved therapies that have been shown to alter disease progression include: 1) Alzheimer’s Disease – the leading cause of dementia globally and 2) GNE Myopathy – a rare slowly progressive muscle wasting disorder. One common challenge in designing clinical trials in these areas is understanding expected rates and the variability of natural progression in different patient populations that are likely to be enrolled in the trial. If the trial population is largely made up of an early staged population or a late stage population there may be little expected progression in terms of key clinical outcome measures over the course of the trial and little hope for demonstrating differences in decline between treatment and control patients. The development of disease progression models within this context provides a better understanding of key clinical outcome measures that capture progression over the entire course of the disease and within different patient populations.
Skype Meeting Link: https://meet.lilly.com/natanegara_fanni/6T31HJQ8
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Conference ID: 1407450