Diagnostic PBPK model for S100B

This model describes the kinetic behavior of brain-derived biomarkers such as S100B

Blood biomarkers of neurological diseases are often employed to rule out or confirm the presence of significant intracranial or cerebrovascular pathology or for the differential diagnosis of conditions with similar presentations (e.g., hemorrhagic vs. embolic stroke). More widespread utilization of biomarkers related to brain health is hampered by our incomplete understanding of the kinetic properties, release patterns, and excretion of molecules derived from the brain.

This is, in particular, true for S100B, an astrocyte-derived protein released across the blood-brain barrier (BBB). We developed an open-source pharmacokinetic computer model that allows investigations of biomarker’s movement across the body, the sources of biomarker’s release, and its elimination.

This model was derived from a general in silico model of drug pharmacokinetics adapted for protein biomarkers. We improved the model's predictive value by adding realistic blood flow values, organ levels of S100B, lymphatic and glymphatic circulation, and glomerular filtration for excretion in urine. Three key variables control biomarker levels in blood or saliva: blood-brain barrier permeability, the S100B partition into peripheral organs, and the cellular levels of S100B in astrocytes. A small contribution to steady-state levels of glymphatic drainage was also observed; this mechanism also contributed to the uptake of organs of circulating S100B.

This open-source model can also mimic the kinetic behavior of other markers, such as GFAP or NF-L. Our results show that S100B, after uptake by various organs from the systemic circulation, can be released back into systemic fluids at levels that do not significantly affect the clinical significance of venous blood or salivary levels after an episode of BBB disruption.

The mp4 file explains the goals and utilizations of this model. Robert Murcko describes how to simulate the model and its fundamental features.