TY - JOUR
T1 - Informing Pharmacokinetic Models With Physiological Data
T2 - Oral Population Modeling of L-Serine in Humans
AU - Bosley, J. R.
AU - Björnson, Elias
AU - Zhang, Cheng
AU - Turkez, Hasan
AU - Nielsen, Jens
AU - Uhlen, Mathias
AU - Borén, Jan
AU - Mardinoglu, Adil
N1 - Funding Information:
The authors are grateful to Mr. Ricardo Paxson and Dr Florian Augustin of Mathworks, Inc. for their helpful criticisms and insight into the Simbiology nlme fitting routine.
Publisher Copyright:
© Copyright © 2021 Bosley, Björnson, Zhang, Turkez, Nielsen, Uhlen, Borén and Mardinoglu.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/5/13
Y1 - 2021/5/13
N2 - To determine how to set optimal oral L-serine (serine) dose levels for a clinical trial, existing literature was surveyed. Data sufficient to set the dose was inadequate, and so an (n = 10) phase I-A calibration trial was performed, administering serine with and without other oral agents. We analyzed the trial and the literature data using pharmacokinetic (PK) modeling and statistical analysis. The therapeutic goal is to modulate specific serine-related metabolic pathways in the liver using the lowest possible dose which gives the desired effect since the upper bound was expected to be limited by toxicity. A standard PK approach, in which a common model structure was selected using a fit to data, yielded a model with a single central compartment corresponding to plasma, clearance from that compartment, and an endogenous source of serine. To improve conditioning, a parametric structure was changed to estimate ratios (bioavailability over volume, for example). Model fit quality was improved and the uncertainty in estimated parameters was reduced. Because of the particular interest in the fate of serine, the model was used to estimate whether serine is consumed in the gut, absorbed by the liver, or entered the blood in either a free state, or in a protein- or tissue-bound state that is not measured by our assay. The PK model structure was set up to represent relevant physiology, and this quantitative systems biology approach allowed a broader set of physiological data to be used to narrow parameter and prediction confidence intervals, and to better understand the biological meaning of the data. The model results allowed us to determine the optimal human dose for future trials, including a trial design component including IV and tracer studies. A key contribution is that we were able to use human physiological data from the literature to inform the PK model and to set reasonable bounds on parameters, and to improve model conditioning. Leveraging literature data produced a more predictive, useful model.
AB - To determine how to set optimal oral L-serine (serine) dose levels for a clinical trial, existing literature was surveyed. Data sufficient to set the dose was inadequate, and so an (n = 10) phase I-A calibration trial was performed, administering serine with and without other oral agents. We analyzed the trial and the literature data using pharmacokinetic (PK) modeling and statistical analysis. The therapeutic goal is to modulate specific serine-related metabolic pathways in the liver using the lowest possible dose which gives the desired effect since the upper bound was expected to be limited by toxicity. A standard PK approach, in which a common model structure was selected using a fit to data, yielded a model with a single central compartment corresponding to plasma, clearance from that compartment, and an endogenous source of serine. To improve conditioning, a parametric structure was changed to estimate ratios (bioavailability over volume, for example). Model fit quality was improved and the uncertainty in estimated parameters was reduced. Because of the particular interest in the fate of serine, the model was used to estimate whether serine is consumed in the gut, absorbed by the liver, or entered the blood in either a free state, or in a protein- or tissue-bound state that is not measured by our assay. The PK model structure was set up to represent relevant physiology, and this quantitative systems biology approach allowed a broader set of physiological data to be used to narrow parameter and prediction confidence intervals, and to better understand the biological meaning of the data. The model results allowed us to determine the optimal human dose for future trials, including a trial design component including IV and tracer studies. A key contribution is that we were able to use human physiological data from the literature to inform the PK model and to set reasonable bounds on parameters, and to improve model conditioning. Leveraging literature data produced a more predictive, useful model.
KW - L-Serine (ser)
KW - NAFLD (non alcoholic fatty liver disease)
KW - oral supplementation
KW - Pharmacokinectics
KW - systems biology
UR - http://www.scopus.com/inward/record.url?scp=85107074491&partnerID=8YFLogxK
U2 - 10.3389/fphar.2021.643179
DO - 10.3389/fphar.2021.643179
M3 - Article
AN - SCOPUS:85107074491
SN - 1663-9812
VL - 12
JO - Frontiers in Pharmacology
JF - Frontiers in Pharmacology
M1 - 643179
ER -