Systems, methods, and devices predict pharmacokinetic parameters following administration of a formulation, such as a medium-chain
triglyceride (MCT). The method includes generating training data indicating
human metabolism outcomes of the formulation. The training data includes
stomach emptying parameters, a
digestion rate, an absorption constant, or a conversion rate with a training target variable being
ketone concentration or
plasma free
fatty acid concentration. The method also includes training a physiologically based
biopharmaceutics (PBB) model with the training data and using the PBB model to predict, using the
patient data, at least one of a target
plasma free
fatty acid concentration or a target
ketone concentration. Furthermore, as part of a parameter
sensitivity analysis of the PBB model, the method varies input parameters of the training data against a simulated mean
plasma free
fatty acid profile or a simulated mean
ketone plasma profile.