Factorial Design Basics Of Factorial Design

1. FACTORIAL
DESIGN
Presented by: Priyanka Dinkar
Tambe.
F. Y. M. Pharm (Pharmaceutics).
Roll No: PH113.
P.E.S Modern College Of
Pharmacy
Guided By : Assist. Professor
A. G.Purohit Mam.
Department Of Pharmaceutics.
Date:23/10/2018
P. E. S. Modern College Of Pharmacy Nigdi, Pune.
Semester -1 Seminar.

2. CONTENTS:
 1. Optimization Techniques.
 2. Factorial Design definition.
 3. Types Of Factorial Design.
 4. Basics Of Factorial Design .
 5. Characteristics Of Factorial Design.
 6. Factorial Design Testing .
 7. Factorial Design Advantages .
 8. Factorial Design Disadvantages.
 9. Factorial Design Applications.
 10. Reference

3. Optimization Techniques:
 Optimization is choosing the best element from
some set of available alternative.
 According to the Merriam Webster Dictionary
Optimization means "an act, process or methodology
of making something as fully perfect, functional or
effective as possible.
 In the mathematical procedures"It means to
optimize to make as much perfect as possible.It is
the process of obtaining optimum formulation.It
means to optimize something, or use something at it
best , finding a perfect effective or functional answer.

4.  Formulation development is process of selection of
components and processing. Aim of optimization is
to understand formulation and target processing
parameters and formulation ingredients.It is used for
quality selection.
 Many a times finding the correct answer is not a
simple and straight forward in such cases using an
Optimization procedure for best compromise is the
smarter way to solve the problem.

5.  In Pharmacy word " Optimization"is found in the
literature referring to any study of formula.In
development of projects , pharmacist generally
experiments by a series of logical steps, carefully
controlling the variables and changing one at a time
until satisfactory results are obtained.This is now
optimization done in pharmaceutical industry.
 Optimization is defined as follow It is the process of
finding the best way of using the existing resources
while taking in to account all the factors that influence
decision in any experiment..

6. Factorial Design Definition:
 Factorial experiment is an experiment whose
design consist of two or more factor each with
different possible values or levels.
 Factorial Design technique introduced by fisher in
1926.
 Factorial design applied in optimization techniques.

7. Types Of Factorial Design:
 There are two types of factorial designs.
1. Full Factorial Design .
2. Fractional Factorial Design.
 Full Factorial Design:
A design in which every setting of every factor appears with setting of every
other factor is full factorial design.
Simplest design to create ,but extremely inefficient.
If there is k factor, each at Z level, a full FD has Zk.
 Number of runs (N)
N=y x
where , y=number of levels, x= number of factors E.g. 3
Factors, 2 levels each 23
=8

8.  Factors: Factors can be quantitative (numerical
number) or they are qualitative .
 Factorial design depends on independent variables
for development new formulation .
 Factorial design also depends on levels as well as
coding.

9.  Factorial Design: 22 , 23 , 32 , 33
22 FD= 2 Factors, 2 Levels=4 runs.
23 FD= 3 Factors, 2 Levels=8 runs.
32 FD= 2 factors, 3 Levels=9 runs .
33 FD =3 Factors, 3 Levels=27 runs

10.  Two Levels Full FD:
2 Factors: X1 and X1 (Independent variables)
2 levels : Low and High
Coding : (-1),(+1)
 Three level Full FD:
In three level factorial design,
3 factors: X1 , X 2and X3.
3 levels are use,
1) low(-1)
2) intermediate (0)
3) high (+1)

11.  Fraction Factorial Design :
In full FD, as a number of factor or level
increases ,the number of experiment required
exceeds to unmanageable levels.
In such cases , the number of experiment can be
reduced systematically and resulting design is
called as Fractional Factorial Design (FFD).
Applied if no of factor are more than 5.
Levels combinations are chosen to provide
sufficient information to determine the factor effect.

12.  Types of Fractional Factorial Design:
1. Homogeneous Fractional
2. Mixed level fractional
3. Plackett – Burman
Homogenous fractional:
Useful when large number of factors must be screened.
Mixed level Fractional
Useful when variety of factors need to be evaluated for main
effects and higher level interactions can be assumed to be
negligible.

13. Plackett- Burman:
It is a popular class of screening design.
These designs are very efficient screening designs
when only the main effects are of interest.
These are useful for detecting large main effects
economically, assuming all interactions are negligible
when compared with important main effects.

14. Basics Of Factorial Design:
 Factorial designs are most efficient for the
experiments involve the study of the effects of two or
more factors.
 By a factorial design , we mean that in each
complete trial or replication of the experiment all
possible combination of the levels of the factors are
investigated.
 When Factors are arranged in a factorial design,
they are often said to be crossed.

15. Characteristics Of Factorial
Design:
 The treatment must be amenable to being
administered in combination without changing
dosage in the presence of each other treatment.
 It must be acceptable not administer the individual
treatment (I.e. placebo is ethical ) or administer them
at lower doses if that will be required for the
combination.
 It must be genuinely interested in learning about
treatment combination require for the factorial design
.
 The therapeutic question must be chosen

16. Factorial Design Testing:
In chromatographic condition responses can be
1. Efficiency.
2. Retention Factor.
3. Asymmetry.
4. Retention Time.
5. Resolution.

17. Example:
 In this example resolution is considered as
response.No Factors Low
level
High level
1 Temp(x1 ) 30 50
2 % Ethanol (X2 ) 55 60
3 Flow Rate Of
Mobile Phase
0.1 0.2

18. Experiments for a 23 Factorial
Design:
No X1 X2 X3
1 -1 -1 -1
2 -1 1 -1
3 1 -1 -1
4 1 1 -1
5 -1 -1 1
6 -1 1 1
7 1 -1 1
8 1 1 1

19. Data analysis for 23 :
Temp % Ethanol Flow rate Resolution
30 55 0.1 2.4
50 55 0.1 1.8
30 60 0.1 1.9
50 60 0.1 1.4
30 55 0.2 2.4
50 55 0.2 1.8
30 60 0.2 1.6
50 60 0.2 1.1

20. Advantages:
 Its easier to study the combined effect of two or
more factors simultaneously and analyze their
interrelationships.
 It has a wide range of factor combination are used.
 It saves time.
 It permits the evaluation of interaction effects.

21. Disadvantages:
 Its complex when several factors are involved
simultaneously.
 Wasting of time and experimental material.
 Increase in factor size leads to increase in block size
which increase the chance of error.

22. Applications of Factorial
Design:

23. Software Used:
 Design Expert 7.1.3
 SYSTAT sigma Stat 3.11
 CYTEL East 3.1
 Minitab
 Matrex
 Omega
 Compact 21-Apr-15 O

24. Reference:
 Textbook Of Industrial Pharmacy by Shobha Rani
Hiremath page no 158-168.
 Fractional factorial designs that maximize the
probability of identifying the important factors.
Article in International Journal of Industrial and Systems
Engineering · January 2009.

25. Reference:
 full factorial design for optimization, development and
validation of HPLC method to determine valsartan in
nanoparticles by Lalit Kumar , M sreenivasa Reddy.
Department of pharmaceutics Manipal college of
pharmacy.
 Factorial Design considerations by Stephanie
Green,ping_ Tuesday Liu from journal of clinical
oncology .An American society.

26. THANKS YOU