This document discusses pharmacometrics, which involves analyzing and interpreting pharmacological data through quantitative models to improve drug development and patient outcomes. It describes using pharmacokinetic, pharmacodynamic, and pharmacokinetic/pharmacodynamic models to understand dose-exposure-response relationships and optimize dosing strategies. Population modeling and stochastic simulation are also covered as tools to estimate parameters from sparse data and evaluate study designs. Examples demonstrate how pharmacometrics informed decisions that improved drug development or approval processes. Software and online resources relevant to pharmacometrics are also listed.

1. Pharmacometrics-
Quantitative Systems
Pharmacology
Shivankan Kakkar, MD
Assistant Professor,
SMS Medical College Hospital, Jaipur,
INDIA

2. “Measuring
Pharmacology”
Through-
Pharmacokinetic (PK) models,
Pharmacodynamic (PD) models,
Pharmacodynamic-biomarker–outcomes
link models, Data visualization, Statistics,
Stochastic Simulation, and Computer
Programming.

3. RELEVANT TEXT- www.pdfdrive.com

4. Introduction
Pharmacometrics is concerned
with the analysis and
interpretation of pharmacological
data.
The aim is to enhance the quantitative
understanding of how drug treatments impact
human biology and to improve outcomes for
patients.
Through pharmacometrics one can quantify the
uncertainty of information about model behavior
and rationalize knowledge-driven decision making
in the drug development process.

5. Pharmacometrics
Drug Development and
Pharmacotherapy
When applied to drug development,
pharmacometrics often involves the
development or estimation of
pharmacokinetic, pharmacodynamic,
pharmcodynamic–outcomes linking, and
disease progression models. These models
can be linked and applied to competing
study designs to aid in understanding the
impact of varying dosing strategies, patient
selection criteria, differing statistical
methods, and different study endpoints.
In the realm of pharmacotherapy,
pharmacometrics can be employed to
customize patient drug therapy through
therapeutic drug monitoring and improved
population dosing strategies.

6. PK, PD and PK/PD
modeling
PK linked to PD
Pharmacometrics begins with pharmacokinetics PK.
Rational drug therapy is based on the assumption
of a causal relationship between exposure and
response. PK has great utility when linked to
pharmacodynamics PD and the examination of PD is
of paramount importance.
PD most often involves mathematical models, which
relate some concentration (serum, blood, urine) to
a physiologic effect (blood pressure, liver function
tests) and clinical outcome (survival, adverse
effect).
PK/PD modeling provides the seamless integration
of PK and PD models to arrive at an enlightened
understanding of the dose–exposure–response
relationship. PK/PD modeling can be done either
sequentially or simultaneously.

7. ● NONMEM
● WinNonlin
● XLMEM
● Boomer
● JGuiB
● TOPFIT
● ADAPT II
Softwares used in PK/PD modeling

8. Biomarkers
Biomarkers Definitions Working
Group (BDWG)
“characteristic that is objectively measured
and evaluated as an indicator of normal
biological processes, pathogenic process or
pharmacologic responses to a therapeutic
intervention.”
Biomarkers often have the advantage of
changing in drug therapy prior to the clinical
endpoint that will ultimately be employed to
determine drug effect, thus providing
evidence early in clinical drug development
of potential efficacy or safety.
A surrogate endpoint is “a biomarker that is
intended to substitute for a clinical
endpoint.”

9. Population
Modeling
The PM
With the advent of population approaches,
one could now obtain estimates of PM
parameters from sparse data from large
databases and also obtain improved
estimates of the random effects (variances)
in the parameters of interest. These models
first found great applicability by taking
massive amounts of data obtained during
therapeutic drug monitoring (TDM) from
which typical values and variability of PK
parameters were obtained.
These are helpful in estimating initial doses
optimizing the dosing strategies. Population
methods are applied to pharmacokinetics,
pharmacodynamics, and models linking
biomarkers to clinical outcomes.

10. Stochastic
Simulation
Stochastic is “Random probable
distribution”
Stochastic simulation is another step
forward in the arena of pharmacometrics.
Simulation had been widely used in the
aerospace industry, engineering, and
econometrics prior to its application in
pharmacometrics.
“Simulation is a useful tool to provide
convincing objective evidence of the merits
of a proposed study design and analysis.
Simulating a planned study offers a
potentially useful tool for evaluating and
understanding the consequences of
different study designs”

11. Examples of
benefits
1. Propose best doses
2. Rescue discarding good drug
3. Maximizing value of prior
data
1. Highly variable PK of Tacrolimus between
ulcerative colitis patients in Phase II studies
presented challenges to further development.
Simulation of dose titration based on
exposure-response was effective for
identifying target trough concentration,
demonstrating effectiveness and justifying
Phase III studies.
2. A new dosing regimen was selected based
on pharmacometric analyses and evaluated
in an additional clinical trial. Nesiritide was
finally approved by FDA.
3. Approval of oxcarbazepine monotherapy in
pediatrics was based on demonstrating
similar exposure –response relationship for
seizure frequency in pediatrics and adults
using prior data from adjunctive therapy
trials. No additional monotherapy pediatric
trials were required.

12. Materials

13. DDMoRe
DDMoRe Foundation: http://www.ddmore.foundation The
Drug Disease Model Resources (DDMoRe) Foundation
maintains and drives development of a universally
applicable, open source, model based framework,
intended as the gold standard for future collaborative drug
and disease Modelling & Simulation.
The DDMoRe Model Repository provides a
community-driven, fully-searchable hub for storing
published and unpublished pharmacometric models.
The DDMoRe Language Community provides a resource
for encoding models with model description language
MDL, helps with understanding MDL structure and
features, and provides a place for logging bugs, issues,
feature requests and suggestions.

14. 1
Interactive Clinical
Pharmacology
The site has been designed to increase
understanding of important and sometimes difficult
concepts and principles in Clinical Pharmacology.
It has been developed using JavaScript to enable
user interaction. A hands-on exercise will help
understanding the utility of this website.
A must visit site based on Instant Clinical
Pharmacology by Evan J. Begg.

15. Online Learning
Options
A Basic understanding of Pharmacokinetic and
Clinical Pharmacology principles may be useful
prior to more in depth study of
pharmacometrics. The following are some
online resources in these two disciplines.
Pharmacokinetic Courses: Basic
Pharmacology. A course by David Bourne from
the University of Oklahoma.
Clinical Pharmacology Course: Principles of
Clinical Pharmacology. This is a comprehensive
course sponsored by NIH Clinical Center. It has
videos of lectures and downloadable slides.