In BDA3 appendix there is a discussion about replicated data in the EXISTING schools and replicated data in NEW schools. Currently I am working with PBPK model. Some parameters have literature values (such as gastric transit times) but some don’t (such as kidney km or vmax). What I found that when tight priors are set on gastric transit times and kidney km/vmax then predictive posterior based on replicated data for EXISTING patients fits very well the observed data (plasma concentration/AUC/tmax/Cmax/fraction absorbed) while predictive posterior based on replicated data for NEW patients is quite off (very large uncertainty). However, when I use tight priors on gastric transit times and vague priors for kidney km/vmax then predictive posterior for EXISTING patients is still perfect while predictive posterior for NEW patients envelops well the actual data. Only trouble is that those kidney km/vmax median values are way beyond realistic values. I am curious if anybody had similar experiences (maybe in different domain) and can we justify the non realistic values for kidney vamx/km. My explanation is that all models are wrong but some are useful and the one with vague priors on kidney parameters have good fit and good predictive capability so those kidney parameters while having mechanistic interpretation become fudge factors like in fitting dissolution profile to Weibull equation.
Many thanks for sharing your experiences.