This document provides an overview of pharmacokinetics and pharmacodynamics, including definitions, parameters, kinetics, and models related to drug absorption, distribution, metabolism, and excretion. It discusses various pharmacokinetic parameters such as plasma concentration-time profiles, areas under the curve, and the significance of minimum effective and maximum safe concentrations. Additionally, it outlines different kinetic processes (zero-order, first-order, mixed-order) and approaches for pharmacokinetic modeling to aid in the clinical management and evaluation of drug therapies.

1. Prepared By: Dolly Sadrani
Department of Pharmaceutics
IInd Sem M.Pharma
1

2. CONTENTS
 Plasma Drug Concentration Time Profile
 Pharmacokinetic Parameter
 Pharmacodynamic Parameter
 Zero, First Order & Mixed Order Kinetic
 Rates & Order Of Kinetics
 Pharmacokinetic Models
 Application Of Pharmacokinetic
 Reference
 Questions
2

3. Pharmacokinetics
 Pharmacokinetics is define as the kinetics of
drug absorption, distribution, metabolism and
excretion (KADME) and their relationship with
the pharmacologic, therapeutic or toxicologic
response in human and animals.
 The applications of pharmacokinetic principles
in the safe and effective management of
individual patient is called as clinical
pharmacokinetics.
3

4. Pharmacodynamics
 The branch of pharmacology concerned with the
effects of drugs and the mechanisms of their
action.
 In particular, pharmacodynamic is the study how
a drug affects an organism, whereas
pharmacokinetics is the study of how the
organism affects the drug.
4

5. Plasma Drug Concentration-Time
Profile
 A Direct relationship exists between the
Concentration of drug at the site of action
(biophase) and the concentration of drug in
plasma.
 A typical plasma drug concentration- time curve
obtained after a single oral dose of a drug and
showing various pharmacokinetic and
pharmacodynamic parameters.
5

6.  Such a profile can be obtained by measuring the
concentration of drug in plasma sample taken at
various intervals of time after administration of
a dosage form and plotting the concentration of
drug in plasma (Y-axis) versus the
corresponding time at which the plasma sample
was collect (X-axis).
6

7. 7

8. Pharmacokinetic Parameter
 Pharmacokinetic Parameter that describe the
plasma level-time curve and useful in
determining the bioavailability of a drug from
formulation are:
1. Peal Plasma Concentration (Cmax): The point of
maximum Concentration of drug in plasma is
called as the peak and the Concentration of
drug at peak is known as peak plasma
Concentration.
o It is also called as peak high Concentration and
maximum drug Concentration.
8

9. o Cmax is expressed in mcg/ml.
o The peak level depends upon the administered
dose and rate of absorption and elimination.
o The peak represents the point of time when
absorption rate equal to elimination rate of drug.
9

10. 2. Time of peak Concentration (tmax)
o The time for drug to reach peak Concentration in
plasma is called as the time of peak
Concentration.
o It is expressed in hours and is useful in
estimating the rate of absorption.
o Onset time and Onset of action are dependent
upon tmax.
10

11. 3. Area Under the Curve (AUC)
o It represents the total integrated area under the
plasma level-time profile and expresses the total
amount of drug that comes into the systemic
circulation after its administration.
o AUC is expressed in mcg/ml . Hours
o It is the most important parameter in evaluating
the bioavailability of a drug from its dosage
form as it represents the extent of absorption.
11

12. o AUC is also important for drugs that are
administered repetitively for the treatment of
chronic conditions like asthma and epilepsy.
12

13. Pharmacodynamic Parameter
1. Minimum Effective Concentration (MEC)
o It is define as the minimum Concentration of
drug in plasma required to produce the
therapeutic effect.
o It reflects the minimum Concentration of drug at
the receptor site to elicit the desired
pharmacologic response.
o The Concentration of drug below the MEC is
said to be in the subtherapeutic level.
13

14. o In case of antibiotics , the term minimum
inhibitory Concentration (MIC) is used. It
describe the minimum Concentration of
antibiotic in plasma required to kill or inhibit
the growth of microorganisms.
2. Maximum Safe Concentration (MSC)
o Also called as minimum toxic Concentration
(MTC) , it is the Concentration of drug in
plasma above which adverse or unwanted
effects are precipitated.
14

15. o Concentration of drug above MSC is said to be
in the toxic level.
3. Onset of Action
o The beginning of pharmacologic response is
called as onset of action.
o It occurs when the plasma drug Concentration
just exceed the required MEC.
15

16. 4. Onset Time
o It is the required for the drug to start producing
pharmacologic response.
o It corresponds to the time for the plasma
Concentration to reach MEC after
administration of drug.
5. Duration of Action
o The time period for which the plasma
Concentration of drug remains above the MEC
level is called as duration of drug action.
16

17. 6. Intensity of Action
o It is maximum pharmacologic response produced
by the peak plasma Concentration of drug.
o Also called as peak response.
7. Therapeutic Range
o The drug Concentration between MEC and MSC
represents the therapeutic range.
17

18. Rate, Rate Constant and Order of
Reaction
 Pharmacokinetic is the mathematical analysis of
processes of ADME.
 The movement of drug molecules from the site
of application to the systemic circulation,
through various barriers, their conversion in to
another chemical form and finally exit out of the
body can be expressed mathematically by the
rate at which they proceed, the order of such
processes and the rate constant.
18

19.  The velocity with which a reaction or a process
occurs is called as its rate.
 The manner in which the Concentration of drug
influences the rate of reaction or process is
called as the order of reaction or order or
process.
Drug A Drug B
 The rate of forward reaction is expressed as
- dA
dt
 Negative sign indicates that the Concentration of
drug A decreases with time T.
19

20.  As the reaction proceeds, the Concentration of
drug B increases and the rate of reaction can
also be expressed as:
dB
dt
 Experimentally, the rate of reaction is
determined by measuring the decreases in
Concentration of drug A with time t.
20

21.  If C is the Concentration of drug A, the rate of
decreases in C of drug A as it is changed to B can
be described by a general expression as a
function of time t.
dc = -K Cn
dt
where, K = rate constant
n = order of reaction
If n = 0, it’s a zero-order process,
If n = 1, it’s a first-order process
21

22.  The three commonly encountered rate processes
in a physiological system are-
- Zero-order process
- First-order process
- Mixed-order process.
 The pharmacokinetics of most drugs can be
adequately by Zero- and first-order processes.
22

23. Zero-Order Kinetics (Constant Rate
Processes)
If n= 0 dC = -K0 C0 = -K0 (1.0)
dt
where K0 = Zero-order rate constant (mg/ml)
 The Zero- Order process can be defined as the
one whose rate is independent of the
Concentration of drug undergoing reaction i.e.
the rate of reaction cannot be increased further
by increasing the Concentration of reaction.
23

24. Rearrangement of equation (1.0) yields:
dC = -K0 dt (1.1)
Integration of equation (1.1) gives:
C – C0 = -K0 t
or
C = C0 - K0 t (1.2)
where, C0 = Concentration of drug at t = 0
C = Concentration of drug yet to
undergo reaction time t.
24

25.  Equation (1.2) is that of a straight line and states
that the Concentration of reactant decreases
linearly with time.
 A plot of C versus t yields such a straight line
having slope – K0 and y- intercept C0.
25

26. Zero-Order Half-life
 Half-life (t1/2) or Half-time is defined as the time
period required for the Concentration of drugs to
decrease by one-half.
When t = t1/2
C = C0/2
and the equation (1.2) becomes :
C0 = C0 – k0 t1/2
2 (1.3)
26

27. Solving (1.3) we get :
t1/2 = C0 = 0.5 C0
2 K0 K0 (1.4)
Equation (1.4) shows that the t1/2 of a Zero-order
process is not constant but proportional to the
initial Concentration of drug C0 and inversely
proportional to the Zero-order rate constant K0.
 Zero-order equation do not require logarithmic
transformation.
27

28. Examples of Zero-order processes are :
 Metabolism/ protein-drug binding and enzyme or
carrier mediated transport under saturated
conditions. The rate of metabolism, binding or
transport of drug remains constant as long as its
Concentration is in excess of saturating
Concentration.
 Administration of a drug as a constant rate i.v.
infusion
28

29.  Controlled drug delivery such as that form i.m.
implants or osmotic pump.
First-Order Kinetic (Linear Kinetics)
If n=1 Equation (1. ) becomes
dC = K C
dt (1.5)
Where, K= First order rate constant (in time-1 or
per hour)
29

30.  From Equation it is clear that a first-order
process is the one whose rate is directly
proportional to the Concentration of drug
undergoing reaction. (greater the Concentration,
faster the reaction.)
 First-order process is said to be follow linear
kinetics.
30

31. Rearrangement of equation (1.5) yields:
dC =-Kdt
C (1.6)
Integration of equation (1.6)
ln C = ln C0 –Kt (1.7)
Equation (1.7) can also be written in exponential
form as:
C = C0 e-Kt (1.8)
Where e = natural log base.
31

32.  The First-Order process is also called as
monoexponential rate process. Thus, a first-order
process is characterized by logarithmic or
exponential kinetics i.e. A constant fraction of
drug undergoes reaction per unit time.
since ln = 2.303 log, equation (1.7) can be written
as
log C = log C0 – Kt
2.303 (1.9)
 A semilogarithmic plot of equation (1.9) yields a
straight line with slope = - K/2.303 and y –
intercept = log C0
32

33. 33

34. First-Order Half-Life
 Substituting the value of C = C0/2 at t1/2 in
equation (1.9) and solving it yields :
t1/2 = 0.693
K (1.10)
Above equation shows that, in contrast to Zero-
Order process, the Half-life of a First-order
process is constant and independent of initial
drug Concentration i.e. Irrespective of what the
initial drug Concentration is, the time required
for the Concentration to decreases by One-half
remains the same.
34

35.  Most pharmacokinetic processes viz.
Absorption, distribution and elimination follow
first-order kinetics.
Mixed-Order Kinetics (Nonlinear Kinetics)
 A mixture of both first-order and zero-order
kinetics is observed in such cases and therefore
the process is said to be follow mixed-order
kinetics.
35

36.  Deviation from an originally linear
pharmacokinetic profile are observed , the rate
process of such a drug is called as nonlinear
kinetics.
 Mixed-order kinetics is also termed as dose-
dependent kinetics as it is observed at increased
or multiple doses of some drugs.
 Observed in :
- Drug absorption (Vitamin C)
- Drug distribution ( naproxen)
- Drug elimination (riboflavin)
36

37. Pharmacokinetic Analysis Of
Mathematical Data:
Pharmacokinetic Models
 Drug movement with in body is a complex
process.
 The two major approaches in the quantitative
study of various kinetic processes of drug
disposition in the body are :
- Model Approach
- Model-independent approach (Non
compartmental analysis)
37

38. Methods for analysis of Pharmacokinetic Data
Model Approach Model-Independent Approach
Compartment Non Compartmental Analysis
model
- Mammillary
- Catenary
Physiological
model
- Perfusion-limited
- Diffusion-limited
Distributed Parameter
model
38

39. Pharmacokinetic model Approach
 Model are used to describe change in drug
concentration in the body with time.
 A model is a hypothesis that employs
mathematical terms to concisely describe
quantitative relationship.
 Pharmacokinetic models provide concise means
of expressing mathematically or quantitatively,
the time course of drug throughout the body and
compute meaningful pharmacokinetic
parameter.
39

40. Application of Pharmacokinetic
Models:
 Characterizing the behaviour of drugs in
patients.
 Predicting the concentration of drug in various
body fluids with any dosage regimen.
 Predicting the multiple-dose concentration
curves from single dose experiments.
 Calculating the optimum dosage regimen for
individual patients.
40

41.  Evaluating the risk of toxicity with certain
dosage regimens.
 Correlating plasma drug Concentration with
pharmacological response.
 Evaluating the bioequivalence/ bioinequivalence
between different formulation of the same drug.
 Estimating the possibility of drug and/or
metabolites accumulation in the body.
 Determining the influence of altered
physiology/disease state on /drug ADME.
 Explaining drug interaction.
41

42. Types Of Pharmacokinetic Models:
1. Compartment models: Also called as empirical
models
2. Physiological models: are realistic models
3. Distributed parameter model: are also realistic
models
42

43. Compartment Models
 These models simply interpolate the
experimental data and allows an empirical
formula to estimate the drug concentration with
time
 Compartments are hypothetical in nature and
based on certain assumptions:
- The body is represented as a series of
compartments arranged either in series or
parallel to each other, which communicate
reversibly with each other.
43

44. - Each compartment is not a real physiological
and anatomical region but a fictitious or virtual
one and considered as a tissue or group of
tissues that have similar drug distribution
characteristics. (Similar blood flow and affinity).
- Within each compartment, the drug is
considered to be rapidly and uniformly
distributed i.e. The compartment is well-stirred.
- The rate of drug movement between
compartment is described by first-order kinetic.
- Rate constants are used to represent rate of entry
into and exit from the compartment.
44

45. Compartment models are divided in to:
Mammillary model
Catenary model
Mammillary model:
 It consist of one or more peripheral
compartment connected to the central
compartment.
 The central compartment comprises of plasma
and highly perfused tissues such as lungs, liver,
kidneys which rapidly equilibrate with the drug.
 The drug is directly absorbed into this
compartment. 45

46.  The peripheral compartments or tissue
compartment are those with low vascularity and
poor perfusion.
 Distribution of drugs to this compartments is
through blood.
 Movement of drug between compartments is
defined by characteristic first-order rate constant
denoted by K.
 The subscript indicated the direction of drug
movement K12 ( K-one-two) refers to drug
movement from compartment 1 to compartment
2 and reverse for K21.
46

47.  The number of rate constants which will appear in
particular compartment model is given by R.
For intravenous administration R=2n-1 (1.11)
For extravascular administration R = 2n (1.12)
Where n= no. Of compartments.
47

48. 48

49. Catenary Model:
 In this model, the compartments are joined to
one another in a series like compartments of a
train.
 This is not observable physiologically/
anatomically as the various organ are directly
linked to the blood compartment.
 Hence this model is rarely used.
49

50. Advantages and Application of
compartment modelling Approach
 It is a simple and flexible approach and thus
widely used.
 It gives a visual representation of various rate
processes involved in drug disposition.
 It shows how many rate constants are necessary
to describe these processes.
 It enables the pharmacokinetic to write
differential equations for each of the rate
processes in order to describe drug
concentration change in each compartment.
50

51.  It enables monitoring of drug concentration
change with time with a limited amount of data.
 It is useful in predicting drug concentration-time
profile in both normal physiological and in
pathological condition.
 It is important in the development of dosage
regimen.
 It is useful in relating plasma drug levels to
therapeutic and toxic effects in the body.
 It is particularly useful when several therapeutic
agent are compared. Clinically, drug data
comparisons are based on compartment models.
51

52.  Its simplicity allows for easy tabulation of
parameters such as Vd , t1/2.
Disadvantages:
 Extensive efforts are required in the
development of an exact model that predicts and
describes correctly the ADME of a certain
drugs.
 The model is based on curve fitting of plasma
concentration with complex multiexponential
mathematical equations.
 The model may vary within a study population.
52

53.  The approach can be applied only to a specific
drug under study.
 The drug behaviour with in the body may fit
different compartmental models depending upon
the route of administration.
 Difficulties generally arise when using models to
interpret the differences between results from
human and animal experiments.
 Owing to their simplicity, compartmental
models are often misunderstood, overstretched or
even abused.
53

54. Physiological models:
 These models are also known as physiologically
based pharmacokinetic models (PB- PK models).
 The number of compartments to be included in
the model depends upon the disposition
characteristics of the drug.
 organ or tissues such as bones that have no drug
penetration are excluded.
 For example lungs, liver, brain and kidney are
grouped as rapidly equilibrating tissues (RET)
while muscles and adipose as slowly
equilibrating tissues (SET).
54

55.  The rate of drug carried to a tissue/organ or
tissue drug uptake is dependent upon two major
factors:
- rate of blood flow to the organ
- tissue/blood partition coefficient or diffusion
coefficient of drug that governs its tissue
permeability.
 Physiological models are further categorized
into two types:
- Blood flow rate limited models/perfusion rate
limited model : Based on the assumption that the
drug movement within a body region is much
more rapid than its rate of delivery to that region
by the perfusing blood.
55

56. 56

57. Example, thiopental, lidocaine
- Membrane permeation rate-limited model/
Diffusion limited model: these models are more
complex and applicable to highly polar, ionized
and charged drug, in which case the cell
membrane acts as barrier for the drug that
gradually permeates by diffusion.
57

58. Advantages over the conventional
compartment modelling
 Mathematical treatment is straightforward.
 Since it is a realistic approach, the model is
suitable where tissue drug concentration and
binding are known.
 Data fitting is not required since drug
concentration in various body regions can be
predicted on the basis of organ or tissue size,
perfusion rate and experimentally determined
tissue-to-plasma partition coefficient.
58

59.  The model gives exact description of drug
concentration-time profile in any organ or tissue
and thus better picture of drug distribution
characteristics in the body.
 The influence of altered physiology or
pathology on drug disposition can be easily
predicted from changes in the various
pharmacokinetic parameters since the
parameters corresponds to actual physiological
and anatomical measures.
 The method is frequently used in animal because
invasive methods can be used to collect tissue
sample.
59

60.  Correlation of data in several animal species is
possible and with some drugs, can be
extrapolated to human since tissue concentration
of drug is known.
 Mechanism of ADME of drug can be easily
explained by this model.
Disadvantages:
 Obtaining the experimental data is a very
exhaustive process.
 Most physiological model assume an average
blood flow for individuals subjects and hence
predictions of individualized dosing is difficult.
60

61.  The number of data points is less than the
pharmacokinetic parameters to be assessed.
 Monitoring of drug concentration in body is
difficult since exhaustive data is required.
61

62.  Hypothetical /
empirical approach - no
relation with real
physiology or anatomy.
 Experimentally simple
and flexible approach
as far as data collection
is concerned.
 Owing to its simplicity,
it is widely used and is
often the First-model.
 Realistic approach
since it is based on
physiological and
anatomic information.
 Difficult
experimentally since
exhaustive data
collection is required.
 Less commonly used
owing to complexity.
62
Compartment modelling Physiological modelling

63.  Complex multiexponential
mathematical treatment is
necessary for curve fitting.
 Data fitting is required for
predicting drug
concentration in particular
compartment.
 Used when there is little
information about tissue
 Easy to monitor time
course of drug in body
with limited data.
 mathematical treatment is
straight forward.
 Data fitting is not required
for since drug
concentration in various
tissue is practically
determined.
 Used where tissue drug
concentration binding is
known.
 Exhaustive data is
required to monitor tome
course of drug in body.
63

64.  Extrapolation from data to
human and viceversa is
not possible.
 Mechanism of drugs
ADME can not be
explained.
 Effect of pathological
condition on drug ADME
can not be determined.
 Frequently used for data
comparison of various
drug.
 Extrapolation of animal
data to human is easy on
the basis of tissue
concentration of drugs.
 Easy to explained drugs
ADME mechanisms.
 Effect of pathology on
drug ADME can be easily
determined.
 Less commonly used for
data comparisons.
64

65. Distributed Parameter Model
 This model is analogous to physiological model
but has been designed to take in to account:
- Variation in blood flow to an organ,
- Variation in drug diffusion in an organ.
 Such a model is thus specifically useful for
assessing regional differences in drug
concentration in tumours or necrotic tissue.
65

66. Noncompartmental Analysis
 Also called as model-independent method dose
not required the assumption of specific
compartment model.
 Based on the assumption that the drugs and
metabolites follow linear kinetics and on the
basis, this technique can be applied to any
compartment model.
 The noncompartmental approach, based on the
statistical moments theory involves collection of
experimental data following a single dose of
drug.
66

67.  If one considers the time course of drug
concentration in plasma as a statistical
distribution curve then,
MRT = AUMC
AUC (1.13)
where
MRT = mean residence time
AUMC = Area under the First-moment curve
AUC = Area under the Zero-moment curve
67

68.  AUMC is obtained from a plot of product of
plasma drug concentration and time versus time
t from zero to infinity.
 Mathematically it is expressed by equation:
AUMC = t dt (1.14)
 AUC is obtained from a plot of plasma drug
concentration versus time t from zero to infinity.
 Mathematically it is expressed by equation:
AUC = t dt (1.15)
68

69. 69

70.  Practically, the AUMC and AUC can be
calculated from the respective graphs by the
trapezoidal rule.
 MRT is defined as the average amount of time
spent by the drug in the body before being
eliminated.
Application:
 Used to estimate the important pharmacokinetic
parameters like bioavailability, clearance and
apparent volume of distribution.
70

71.  Useful in determining half-life, rate of
absorption and first-order absorption rate
constant of the drug.
Advantages:
 Ease of derivation of pharmacokinetic
parameters by simple algebraic equations.
 The same mathematical treatment can be applied
to almost any drug metabolic provided they
follow first-order kinetics.
71

72. Disadvantages:
 It provides limited information regarding the
plasma drug concentration-time profile.
 The method does not adequately treat non-linear
cases.
72

73. Questions:
1. Explain the term ‘compartment’ what are the
assumption made in compartment modelling.
Discuss the advantages and disadvantages of
same.
2. What are pharmacokinetic models. Discuss the
importance and types of such model.
3. Give detailed classification of compartment.
73

74. Reference:
 Biopharmaceutics and clinical Pharmacokinetics
by Milo Gibaldi and Donald Perrier, fourth
edition philadelphia, lea and febiger,1991
 Biopharmaceutics and Pharmacokinetics by PL
MADAN Second edition, Jaypee Brothers
Medical Publishers (P) LTD.
 Biopharmaceutics and Pharmacokinetics A
TREATISE by D. M. Brahmankar, Sunil B.
Jaiswal, Vallabh Prakashan.
 Applied Biopharmaceutics and
Pharmacokinetics by shargel. Land yu Abc,
Second edition applet on century crofts, 1985.
74

75. Thank you For
Your
Attention!
75