This document discusses various optimization techniques used in pharmaceutical formulation and processing. It begins by defining optimization as making something as perfect or functional as possible. It describes the key parameters in optimization problems including independent and dependent variables as well as constrained and unconstrained problems. The document then explains several statistical design approaches to optimization including evolutionary operation, simplex method, and search methods. It provides examples of how these techniques are applied and the general steps involved in using a search method for optimization.

1. KARPAGAM COLLEGE OF PHARMACY
COIMBATORE-32
O P T I M I Z AT I O N T E C H N I Q U E I N
P H A R M A C E U T I C A L F O R M U L AT I O N A N D P R O C E S S I N G
P re s e n t e d B y,
N a v a n e e t h a k r i s h n a n . P
D e p a r t m e n t o f P h a r m a c e u t i c s
M . P h a r m S e m s t e r 1
1Department of Pharmaceutics

2. 2Department of Pharmaceutics
Contents
 Introduction
 Optimization Parameters
 Statistical Design
• Evolutionary Method
• Simplex Method
• Search Method
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INTRODUCTION
 Optimization is a Tool to quantitative a formulation that has been Quantitatively determined.
Optimization is not a screening Technique, it is useful in one qualitatively selects a formulation
 The word “OPTIMIZE” is defined as to make as Perfect or functional as possible.
 Optimization technique provides a both a depth of understanding and ability to explore and
defined a ranges for formulation and processing parameter
 It helps for the pharmaceutical scientist to understand the theoretical formulation and target
processing parameter
 The term “OPTIMIZATION” is used in pharmacy relative to formulation and processing.
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4. 4Department of Pharmaceutics
K a r p a g a m C o l l e g e o f P h a r m a c y, C o i m b a t o r e - 3 2
Optimization Parameters
Problem Types Variable Types
Constraints Dependent
variables
Independent
variables
Unconstraint

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Problem Types
Constraints:
 The Constrain optimization problem are restricted one
 It placed on the system by physical limitation (example Economic restriction)
 In other hand Constraints problem, one can make hardest tablet but it must disintegration in
less than 15 min.
 Constraints optimization problems only exist because formulators always wish to place
restriction in formulation, assume the hardest tablets would posses a low compression and
ejection force and faster disintegration and dissolution rate.
Unconstraint:
 In the Unconstraint optimization problem, there is no restriction for a pharmaceutical system.
 One can prepare most harder tablet as possible.
 Unconstraint optimization problem is almost not exist.

6. 6Department of Pharmaceutics
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Variables
 There are two types in variables
Independent Variables:
 The Independent variables are the formulation and process variables directly under the
control of formulation
Examples : Dilution ratio, Compression force , Binder and Lubricant Level etc.,
Dependent Variables:
 Dependent Variables are the response or the characteristic of the in-progress material
or resulting drug delivery system. These are the direct result of any change in
formulation.
Example : Disintegration time, Hardness, Dissolution rate etc.,

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Statistical Design
 It is widely used for optimization, It may be divided into two general category
1. First type is Evolutionary Operation and Simplex Method
2. Second type is Classic Mathematical and Search Method
 For the second type is require relation between any independent variables and one or
more independent variable be known
 To obtain a necessary relationship there are two possible approaches the theoretical and
the empirical
 If the formulation knows a theoretical equation for the formulation properties, it does
not require a experiment

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Evolutionary Operation (EVOP):
 One of the most widely used methods of experimental optimization in fields other than
pharmaceutical technology is evolutionary operation (EVOP).
 This technique is suited for production situation.
 The basic production procedure is allowed to evolve the optimum by planning and and
constant a repeatation.
 The process procedure for a products that meets all specifications and generates
information on product improvement.
 By this method experiment makes a very small changes in the formulation and process
but it makes it so many times (i.e repeats the experiment so many times) and the
experiment determine the product improvement. In case of the optimum product were
obtained then experiment further doesn’t proceed.
 In industry these process are run over and over again.

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Simplex method :
 Simplex method are used in the analytical methods (a continuous flow analyzer).
 A simplex is geometric method in which it is represented as triangle based on two factor
or independent variables.
 Once the Simplex has been determined then its successive calculation of comparing a
magnitude of response.
 Example:
• Two reagent required in the analysis reaction.
• The initial simplex represented by lowest triangle.
• Vertices represented by spectrophotometric response.
• Since the worst response is 0.25
• The better response by moving away from the worst response.
• Optimum response is 0.721

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11. 11Department of Pharmaceutics
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Search method :
 The search method also applied in pharmaceutical system.
 It makes a five independent variables into account and it is computer assisted
 The preson unfamiliar with maths and computer could not carry out a optimisation study
 Example:
In this system also Tablet formulation was selected
The five independent variables are selected they are :
• Diluent ratio
• Compressional force
• Nisintegration level
• Binder level
• lubricant level

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The Dependent variables:
Disintegration Time
Hardness
Dissolution
Friability
Weight Uniformity
Thickness
Porosity
Mean pore diameter
 The Experimental design used showed in the table 1.
 The fact thet there are five independent variables dicates that a total of 27 experiment
or formulation be prepared.
 This design known as a Five factors.
 The first 16 formulation represent a half factorial design for five factors at two levels,
resulting in ½ * 25 = 16 trials.

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 The two levels are represented by +1 and -1 analogue to the high and low values in any
two level factorial design.

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Steps in Search method:
• Select a system
• Select a variable
• Perform the experiment
• Submit a data for statistical analysis
• Set a specifications for feasibility program
• Select a constraints for grid search
• Evaluate

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Reference:
• Modern Pharmaceutics by Bankar, Fourth edition Page .No : 607 to 618.
• wikipedia.org

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