Drug development has traditionally focused entirely on efficacy and selectivity against the biological target. As a result, roughly 50% of drug candidates fail in phase ii and phase iii clinical trials due to unfavorable pharmacokinetic features, such as absorption, distribution, metabolism, excretion, and toxicity (admet). Since the mid-1990s, the pressure to control the rising cost of new medication development has shifted the paradigm. Invitro evaluation of admet characteristics in the early phases of drug discovery has been widely adopted to avoid attrition at more expensive later stages.

1. DRUGDISPOSITION
COMPUTATIONAL
MODELING
PRESENTED BY – MANSHI RANA
AMITY UNIVERSITY HARYANA
M.PHARM 1ST YEAR
(PHARMACEUTICS)

2. CONTENT
Introduction
Modeling Techniques
Drug Absorption (Solubility & Intestional Permeation)
Drug Distribution
Drug Excretion

3. INTRODUCTION
Drug development has traditionally focused entirely on efficacy and selectivity
against the biological target.
As a result, roughly 50% of drug candidates fail in phase ii and phase iii clinical
trials due to unfavorable pharmacokinetic features, such as absorption, distribution,
metabolism, excretion, and toxicity (admet).
Since the mid-1990s, the pressure to control the rising cost of new medication
development has shifted the paradigm.
Invitro evaluation of admet characteristics in the early phases of drug discovery has
been widely adopted to avoid attrition at more expensive later stages.

4. A variety of approaches can be used to improve the solubilization
and bioavailability of poorly water-soluble drugs.
As a result, improving drug solubility and hence oral bioavailability
remains one of the most difficult parts of the drug development
process, particularly for oral drug delivery systems .
Many Invitro ADMET property screening tests with a high speed
have been developed and used successfully.

5. STRATEGIES FOR MODELING
There are two sorts of modeling approaches:
 Pharmacophore modeling and flexible docking studies are quantitative
approaches that investigate the structural requirements for molecular interactions.
Medicines and their goals have an impact on ADMET processes.
Multiple variables analysis is used to link molecular descriptors with admet-related
features in the qualitative techniques represented by quantitative structure-activity
relationship (QSAR) and quantitative structure-property relationship (QSPR)
investigations.
Based on the drug structure a wide range of molecular characteristics can be
determined.

6. For correlating field descriptors with ADMET properties, researchers can use
a variety of statistical algorithms, including simple multiple linear regression
(MLR), multivariate partial least-squares (PLS), and nonlinear regression-type
algorithms like artificial neural networks (ANN) and support vector machines
(SVM).
The correct mathematical tool, such as descriptor selection, is critical for the
most effective admet modelling.
It is sometimes essential to apply different statistical approaches and
compare the results to determine the optimum option.

8. • Fig: 1 In silico modeling
targets of drug disposition.

9. ABSORPTION OF DRUGS
Oral administration is the favored drug delivery method due to its ease and
high patient compliance.
As a result, modeling drug oral absorption, which happens primarily in the
human intestine, has received a lot of attention.
The interaction between medication solubility and intestinal permeability
determines drug bioavailability and absorption.

10. 1. SOLUBILITY
Before a medicine can be absorbed from the intestine, it must first dissolve in the
intestinal lumen.
By calculating the "generic solubility equation" and a drug's logP value (log of the
compound's partition coefficient between water and n-octanol) and melting point,
one can estimate solubility indirectly.
Insilico modeling can be used to estimate the solubility of a molecule even before
it is synthesized.
 Solubility modeling can be divided into two categories. One approach is based
on physiological processes, whereas the other is empirical.
QSPR represents empirical approches that use multivariate studies to find
connections between molecular descriptors and solubility.

11. 2. PERMEATION OF THE INTESTINE
Describes drugs' ability to permeate the intestinal mucosa, which separates the gut
lumen from the portal circulation, is referred to as intestinal permeation.
 To reach their intended site of action, medicines must pass through the intestinal
barrier before entering the systemic circulation.
Both passive diffusion and active transport are involved in the process.
It's a complicated process that’s is difficult to predict purely based on molecular
mechanisms.
As a result, most current models aim to mimic Caco-2, MDCK, or PAMPA membrane
permeability in vitro, which has proved a useful indicator of in vivo drug absorption.

12. DISTRIBUTION OF DRUGS
The pharmacokinetic profile of medicine is influenced by its distribution.
The extent of a drug's distribution is determined by its structural and
physiochemical properties , which are mainly reflected by three parameters:
volume of distribution (VD)
plasma-protein binding (PPB)
blood-brain barrier (BBB) permeability

13. DRUG EXCRETION
The Excretion or clearance of a drug is quantified by plasma clearance, which is
defined as plasma volumethat has been cleared completely free of drug per unit of
time.
Together with Vd, it can assist in the calculation of drug half-life, thus determining
the dosage regimen.
Hepatic and renal clearances are the two main components of plasma clearance.
No model has been reported that is capable of predicting plasma clearance solely
from computed drug structures.

14. Current modeling efforts are mainly focused on estimating in vivo clearance
from in vitro data.
Just like other Pharmacokinetic aspects, the hepatic and renal clearance
process is also complicated by presence of active transporters.