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Upcoming webinar: Expanding from Basic Towards Systems Pharmacodynamic Models for Methylprednisolone

From: Rebecca Baillie <rbaillie>
Date: Tue, 14 May 2019 18:30:23 +0000

Expanding from Basic Towards Systems Pharmacodynamic Models for Methylpredn=

Vivaswath S. Ayyar, Ph.D., Research Assistant Professor of Pharmaceutical S=
ciences, University at Buffalo, NY and PK/PD Scientist, Janssen BioTherapeu=
tics, Spring House, PA

Thursday May 23, 2019, 12:00 to 1:00 pm EDT

Register at

Abstract: Evolving upon foundational principles of classical pharmacology m=
ostly applied to static systems, a diversity of basic pharmacokinetic/pharm=
acodynamic (PK/PD) models have emerged. Placing emphasis on parsimony, the =
basic "mechanism-based" models incorporate and relate plasma pharmacokineti=
cs, receptor binding, and/or relevant homeostatic mechanisms controlling dr=
ug response.
Continued refinement of PK/PD models based upon a progressively deeper mech=
anistic appreciation of physiologically-based PK, pharmacology of drug-targ=
et interactions, and systems physiology from the molecular (genomic, proteo=
mic, metabolomic) to cellular to whole body scales have laid the foundation=
 for building mechanistic quantitative systems pharmacology (QSP) models. P=
revious research based on various animal, clinical, and theoretical studies=
 with corticosteroids have provided ideas to broadly advance the fields of =
pharmacokinetics and pharmacodynamics.
Our recent work on modeling diverse aspects of corticosteroid systems pharm=
acology reflect the integration of basic pharmacodynamic models along with =
the assimilation of fundamental insights gained from many focused studies o=
f corticosteroids. These models highlight the application of combined syste=
ms (experimental and modeling) approaches to decipher "horizontal" and "ver=
tical" pharmacokinetic/ pharmacodynamic/ pharmacogenomic (PK/PD/PG) relatio=
nships of the synthetic corticosteroid, methylprednisolone, in relation to =
1) circadian gene expression and inter-tissue responses, 2) biological sign=
aling networks, and 3) sex differences, using systems pharmacology approach=
es supported with data from microarray and proteomics analysis, systemic ph=
ysiological measurements, and/or more focused quantitation of mechanistic b=
iomarker(s). The modeling strategies employed, major findings, and lessons =
learned from these studies are described.

Received on Tue May 14 2019 - 14:30:23 EDT

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