A recent study highlights the innovative use of latent representations to connect disjoint longitudinal data in mixed-effects regression, particularly in the context of rare diseases. This approach is crucial as it allows researchers to analyze the effects of treatment switches, which are common when new therapies become available. By leveraging all available data, even with the challenges posed by changing measurement instruments, this method could significantly enhance our understanding of treatment impacts in small patient populations. This advancement is vital for improving patient outcomes in rare disease trials.