Research and Development by Bishnu Adhikari

“RESEARCH AND DEVELOPMENT”
Presented by: BISHNU ADHIKARI
rubdbishnu@gmail.com
1

Milestones in the Development
Compound
discovered
Years
* GMP = Good Manufacturing Practice
The above shows a general representation of the development of a new medicine. Various processes may differ from country to country
and between different compounds.

Clinical Studies
Preparation of initial
clinical plan. Selection of
clinical study locations
Human
trials with
healthy
volunteers
to test
tolerability
Trials to
determine
dose ranging,
safety and
efficacy
Large scale trials to
determine definitive safety
and efficacy in patients
0 5 8 12 15
-►
Years* GMP = Good Manufacturing Practice
The above shows a general representation of the development of a new medicine. Various processes may differ from country to country and between different
compounds.

Toxicology
Determine effects of
medicine in animals
when administered
over 2 to 13 weeks
(depending upon length
of planned use in
humans)
Test to determine
mutagenic potential
Determine
the effect on
impregnation
and
implantation
in animals
and whether
the active
substance
can affect
the fetus
Determine the
reproductive
effect upon
future
generations in
animals
Longer term animal studies.
Does the active substance have
long-term side effects?
0 5 8 12 15
-►
Years
The above shows a general representation of the development of a new medicine. Various processes may differ from country to country and between different compounds.

Pharmacokinetics / Metabolism
Determination of how the
medicine is absorbed,
distributed, metabolised
and excreted in animals
Determination of the effects of
the medicine on specific
populations such as the elderly,
different races and sexes.
Determination
of how and to
what extent the
medicine is
absorbed by
humans
Determination of
how the medicine
is distributed,
metabolised, and
excreted by
humans
Research and
Discovery
Early
Development
Final construction
of the
pharmacokinetic
profile of the
medicine
Full
Development
Pre-Market
Activity
0 5 8 12 15
Years
The above shows a general representation of the development of a new medicine. Various processes may differ from country to country and between
different compounds.

Dosage Form
Pre-formulation
activities -
consultations
with
pharmacists /
determination of
physical and
chemical
properties of
compound, e.g.
particle size, solubility
e.t.c
Research and
Discovery
Development of
clinical trial
formulation
Process development for
large scale production of
the dosage form. Testing of
stability of the dosage and
determination of shelf-life
First
dosage
form for
volunteer
trials
Develop Market formulation based
on known characteristics of
medicine and patient group
involved, e.g. age and condition. For
example tablets, capsules, injectables
or transdermal patches
Early
Development
Process validation and
production of the dosage
form for launch
Full
Development
Pre-Market
Activity
0 5 8 12 15
-►
Years

Active Ingredient
The therapeutically active component in a medicine's final formulation that is responsible for its physiological or pharmacological action.
Years

Marketing
Early stage
commercial
assessment of
the medicine
taking into
account medical
need and
existing
therapies on the
market
Research and
Discovery
Marketing
input to the
design of
clinical
trials
especially in
the choice
of
comparator
medicines
Full
development
commercial
assessment
Selection of a
trade name
begins
Trade Name ™
chosen for the
medicine
Profiling - development of comparative
studies on, for example, specific patient
groups and other similar medicines. Study
possible applications of the medicine to other
diseases
Early
Development
Full
Development
Medicine
information
formulated into
brochures and
videos. Displays at
congresses and
symposia
Pre-Market
Activity
0 5 8 12 15
-►
Years

Pharmacoeconomics
Assessment of
the potential
impact of the
new medicine
on healthcare
costs
Definition of
the
healthcare
costs caused
by the
disease
Research for the
appropriate
pharmacoecon-
omic and quality
of life parameters
(linked to clinical
trials Phase II)
Compilation and publication
of the pharmacoeconomic
results
Economic evaluation
parallel to clinical trials
to determine the
economic value of a
new medicine, e.g. cost
saving and cost-
effectiveness
0 5 8 12 15
-►
Years

Regulatory Affairs
Application for
trial authorization
to begin trials on
healthy
volunteers
Application for trial
authorisation to
begin trials in
patients
(early
development)
Application for
trial
authorisation to
begin trials in
patients
(full
development)
Interaction Interaction Interaction
with health with health with health
authorities authorities authorities
Compilation of
registration
dossier
Formulation of
medicine labelling
and doctor/patient
medicine information
Interaction
with health
authorities
Review of registration
documentation by
regulatory authorities
0 5 8 12 15
-►
Years* GMP = Good Manufacturing Practice

DESIGN OF EXPERIMENTS
The term experiment is defined as the systemic procedure carried out under controlled
conditions in order to discover an unknown effect, to test or establish a hypothesis, or to
illustrate unknown effect.
Design of experiment (DOE) has proven to be an effective tool for formulation scientist
throughout the many stages of the formulation process.
The word optimize is defined as, making as perfect, effective or functional as possible.
Optimization may be interpreted as to find out the value of controllable independent
variable, that gives the most desired value of dependent variables.
The application of formulation optimization techniques is relatively new to the practice of
pharmacy when used intelligently, with the common sense; these “statistical” methods will
broaden the perspective of the formulation process.
11

ADVANTAGES
A High Level of Control
With experimental research groups, the
people conducting the research have a very
high level of control over their variables.
Clear Cut Conclusions
Since there is such a high level of control,
and only one specific variable is being
tested at a time, the results are much more
relevant than some other forms of research.
Many Variations Can Be Utilized
There is a very wide variety of this type of
research. Each can provide different
benefits, depending on what is being
explored. The investigator has the ability to
tailor make the experiment for their own
unique situation, while still remaining in
the validity of the experimental research
design.
DISADVANTAGES
Largely Subject To Human Errors
This is especially true when it comes to
research and experiments. Any form of
error, whether a systematic (error with the
experiment) or random error (uncontrolled
or unpredictable), or human errors such as
revealing who the control group is, they
can all completely destroy the validity of
the experiment.
Can Create Artificial Situations
By having such deep control over the
variables being tested, it is very possible
that the data can be skewed or corrupted to
fit whatever outcome the researcher needs.
This is especially true if it is being done
for a business or market study.
Can Take An Extensive Amount of Time
To Do Full Research With experimental
testing individual experiments have to be
done in order to fully research each
variable.
12

IDEAL CHARACTERISTICS OF DRUG
DELIVERY
Ideal drug delivery should,
Control the drug release i.e. Novel Drug Delivery System
Increase the absorption of an insoluble APIs
Reduce the APIs toxicity
Improve the drug release profile
Create truly best-in-class products
Reduce price
The ability to target
13

Terms used in Design of Experiments
Variables
These are the measurements, values, which are characteristics of the
data.
There are two types of variables; dependent variables and
independent variables. Independent variables (X) are set in advance,
which are not influenced by any other values
e.g., Lubricants concentration of polymer, influenced by the
independent variables e.g., hardness, dissolution rate etc.
14

Factor
 Factors are nothing but the independent variables are assigned value
such as concentration, temperature, lubricant agent, drug to polymer
ratio, polymer to polymer ratio or polymer grade.
A factor can be qualitative of quantitative.
A quantitative factor has a numerical value to it for e.g.
Concentration (1%, 2% ...so on), drug to polymer ratio (1:1, 1:2 ...etc.).
Qualitative factors are the factors, which are not numerical value for
e.g., the polymer grade, humidity condition, type of equipment, etc.
These are discrete in nature.
15

Levels
The levels of a factor are the values or designation assigned to the
factor. For e.g., in concentration (factor) 1% will be one level, while
2% will be another level.
Two different plasticizers are levels for grade factor. Usually levels
are indicated as low, middle or high level.
Normally for ease of calculation the numeric and discrete levels are
converted to -1 (low level) and +1 (high level).
The general formula for this conversion is,
Level = X – Average of two levels / Half the difference of levels.
Where ‘X’ is the numeric value.
16

Response
These are nothing but the dependent variables which are dependent
the independent variables, generally response indicates the outcome of
the experiment.
Response is mostly interpreted as the outcome of an experiment.
It is the effect, which we are going to evaluate i.e. disintegration
time, duration of buoyancy etc.
Effect
The effect of a factor is the change in response caused by varying
the levels of the factor.
This describes the relationship between various factors and levels.
17

Interaction
Interaction is also similar to effect, which gives overall effect of two
or more variables (factors) on a response.
For e.g., the combined effect of lubricants (factor) and glidants
(factor) on hardness (response) of a tablet.
In the trial and error method, a lot of formulations have to be
prepared to get a conclusion, which involves lots of money, time and
energy.
These can be minimized by the use of optimization technique.
18

Response Surface Methodology (RSM)
Response surface methodology (RSM) is an experimental strategy
that was developed in the 1950’s.
RSM is comprised of a group of mathematical and statistical
techniques that are based on fitting experimental data generated from
studies established using an experimental design to empirical models
and that are subsequently used to define a relationship between the
responses observed and the independent input variables.
RSM is able to define the effect of independent variables alone and
in combination with the manufacturing processes under investigation.
19

Choice of Response Surface Design
Central Composite Design (CCD)
A CCD was originally presented by Box and Wilson and is based on a
factorial design with additional points to estimate the curvature of that
design.
CCD encompasses a full factorial or fractional factorial approach
which can be represented, as shown in fig: below, as the eight corners
of a cube.
There are the six points, known as the axial or star points, located in
the centre of each face of the cube with a final point located in the
middle of the cube that is known as the centre point.
The axial points are experimental runs where all but one of the factors
to be investigated is set at the intermediate level under consideration.
The axial points are all eqi-distance from the centre point and are
denoted using the symbol, alpha (α).
The factors under consideration are usually investigated at five
different levels and are always represented by coded values viz., -α, -1,
0, +1 and +α. 20

Fig: Schematic diagram representing the levels studied in a Central Composite Design
21

Box – Behnken Design (BBD)
The BBD describes a class of second order designs based on a three
level incomplete factorial approach which are also represented as coded
values viz., -1, 0 and +1.
In this design approach, the treatment combinations are located at the
midpoint(s) of the edge of the process space and at the center, as
represented in fig: below
Figure : Schematic diagram representing the levels studied in a Box – Behnken Design 22

The number of experiments for Box – Behnken Designs can be
calculated using equation.
N= 2k (k-1) + C0
Where,
N = the number of experiments
K = the factor number
C0 = the replicate number of the central point
Doehlert Design
It is an experimental design approach in which different factors can
be studied levels simultaneously.
This aspect of the Doehlert design is an important characteristic
when using some inputs variables that may be subject to restrictions
such as for example cost or experimental constraints (limited amounts
of raw material or limited amount of time available) thereby making it
a practical and economic alternative to other, second order
experimental design approaches. 23

This design describes a circular domain of two input variables, a
spherical domain for three input variables are to be investigated and
which highlights the uniformity of the input variables to be studied in
the experimental domain.
The number of experiments required for a Doehlert design is
determined by using equation,
N = k2 + k + C0
Where,
N = the number of experiments
K = the factor number
C0 = the replicate number of the central point
24

SOFTWARE FOR DESIGN OF EXPERIMENTS
Many commercial software packages are available which are either
dedicated to experimental design alone or are of a more general
statistical type.
Software’s dedicated to experimental designs
DESIGN EXPERT
ECHIP
MULTI – SIMPLEX
NEMRODW
Software for General Statistical Nature
SAS
MINITAB
Newly available
SIGMA TECHNOLOGIES 25

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