Minimal sampling schedules for identification of dynamic models of metabolic systems of clinical interest: case studies for two liver function tests

摘要: Abstract The parameter estimation problem for dynamic system models designed diagnostic use is often a difficult one, due to severe practical constraints imposed on the clinical procedure. This particularly true in many endocrine and metabolic studies, where blood sampling provides basic data, number of samples or observation interval must be minimized. We have applied some recent developments optimal schedule design, two case studies different liver function tests, determine minimum size schedules these tests. assessed effects accuracy reliability, compared with nonoptimal 2–5 times larger number, using Monte Carlo simulation approach. results are encouraging, as they indicate this approach efficient alternative more conventional ones.