computer aided drug design

1. COMPUTER SIMULATIONS
IN
PHARMACOKINETICS & PHARMACODYNAMICS
PRESENTED BY
SAGAR TRIVEDI
M.PHARM (PHARMACEUTICS)

2. CHAPTERS
1.INTRODUCTION
2.COMPUTER SIMULATION
3.WHOLE ORGANISM SIMULATION
4.ISOLATED TISSUE SIMULATION
5.ORGANS SIMULATION

3. INTRODUCTION
• A computer simulation or a computer model is a computer program that attempts to simulate
an abstract model of a particular system.
• Computational resources available today, large-scale models of the body can be used to
produce realistic simulations.
• It involves the use of computer simulations of biological systems, including cellular
subsystems (such as the networks of metabolites and enzymes which
comprise metabolism,signal transduction,pathways and gene regulatory networks), to both
analyze and visualize the complex connections of these cellular processes.

5. WHOLE ORGANISM
SIMULATION

6. • Computer simulation being able to model the whole organism is the essential goal of
biocomputing.
• In drug development, it provides the obligatory handle to lead to response from exposure
• The intact organism can be mathematically represented, a whole series of possibilities can
be brought into practice, such as the simulation of clinical trials and of the prospective
behavior of entire populations

7. • In whole organism simulation ,whole body systems are usually
represented in one of two ways.
1.LUMPED-PARAMETER PK-PD
MODEL
2.PHYSIOLOGICAL MODELING

8. LUMPED-PARAMETER PK-PD MODEL
{POPULATION PHARMACOKINETIC AND PHARMACODYNAMIC MODELING }
• The lumped element model (also called lumped parameter model, or lumpedcomponent
model) simplifies the description of the behaviour of spatially distributed physical systems
into a topology consisting of discrete entities that approximate the behaviour of the
distributed system under certain assumptions.
• The purpose of this study is to characterize the pharmacokinetics (PKs) and
pharmacodynamics (PDs) of population by modeling analysis and to predict proper dosage
regimens.
• Plasma concentrations over time were best described by a two‐compartment linear model and
body weight was associated with central volume of distribution.

9. • A relatively small number of differential equations, between one and ten, is used to predict
the system’s behavior over time .
• Often, but not always, some variation of population PK-PD predicated on nonlinear
regression and nonlinear mixed-effects models , is used to estimate both the population
parameter values and their statistical distribution.
• The same approach can be taken in reverse by using models to generate synthetic data,
ultimately performing a full clinical trial simulation from first principles.

11. PHYSIOLOGICAL MODELING
• This model brought into practice by physiologically based pharmacokinetic
(PBPK) models .
• These models are still based on ordinary differential equations,but they
attempt to describe the organism and especially the interacting organs with
more detail, often by increasing the number of differential equations (from 10
to perhaps 30) and building appropriate interactions between the organs that
resemble their physical arrangement in the organism being studied.

13. • Model selection is driven by some kind of parsimony criterion that balances model
complexity with the actual information content provided by the measurements.
• A consensus workshop developed some time ago a set of “good practices” that
can serve as guidance to model development, selection, and application.
• Pbpk models come at the problem from a different angle.
• Pbpk models can suffer greatly in their predictive power if their parameterization
is inaccurate, poorly specified, or not well tailored to the particular drug.
• It is interesting to note that the foremost challenges for the detailed modeling of
the intact organism (computing time, complexity of interactions, model selection)

14. ISOLATED TISSUE &
ORGANS SIMULATION

15. • The heart and the liver were historically the organs most extensively investigated ,
although the kidney and brain have also been the subjects of mathematical modeling
research.
• Many of the computer simulations for the heart and liver were carried out with distributed
blood tissue exchange (BTEX) models , because the increased level of detail and temporal
resolution certainly makes the good mixing and uniformity hypotheses at the basis of
lumped parameter models less tenable.
• It can be speculated that the integration of organ-specific modeling with the above whole-
organism models would result in improvements for the PBPK approach through “better”
(i.e.,more physiologically sensible and plausible) models of individual organs.

16. • The main challenge in doing so is the required shift from lumped to distributed parameter
models.
• National Institute for General Medical Sciences at the NIH, the Center for Modeling
Integrated Metabolic Systems (MIMS) , has as its mission the development and
integration of in vivo, organ-specific mathematical models that can successfully predict
behaviors for a range of parameters, including rest and exercise and various
pathophysiological conditions.
• Microcirculation Physiome and the Cardiome are other multicenter projects focused on
particular aspects of the Physiome undertaking.
• There is an enormous variety of software for pharmacokinetic and pharmacodynamic
simulations

18. • The physiome of an individual's or species' physiological state is the
description of its functional behavior. The physiome describes the
physiological dynamics of the normal intact organism and is built
upon information and structure (genome, proteome, and morphome).

20. REFERENCES
1. Modeling and Simulation of Soft Tissue Deformation
{https://link.springer.com/chapter/10.1007/978-3-642-41083-3_25}
2. COMPUTER APPLICATIONS IN PHARMACEUTICAL RESEARCH
AND DEVELOPMENT BY SEAN EKINS, M.SC., PH.D., D.SC.

21. THANK YOU