concept of optimization
- 1. 1 COMPUTER-AIDED FORMULATION DEVELOPMENT & CONCEPT OF OPTIMIZATION SUBMITTED BY SHUBHAM KOTNALA Department of Pharmaceutical Sciences BBAU Lucknow
- 2. CONTENTS 2 Introduction. Advantages. Concept and terms. Optimization Parameters. Design Of Experiments. Conclusion. References.
- 3. 3 Formulation and development is a process of selection of component and processing. Now days computer tools used in the formulation and development of pharmaceutical product. Various technique, such as design of experiment are implemented for optimization of formulation and processing parameter. Many times finding the correct answer is not simple and straight forward in such cases use of computer tools (optimization procedure) for best compromise is the smarter way to solve problem. INTRODUCTION
- 4. 4 The term Optimize is defined as to make perfect , effective, or functional as possible. It is the process of finding the best way of using the existing resources. While taking in to the account of all the factors that influences decisions in any experiment. Traditionally, optimization in pharmaceuticals refers to changing one variable at a time, so to obtain solution of a problematic formulation.
- 5. ADVANTAGES 5
- 6. BASIC CONCEPT OF OPTIMIZATION & TERMINOLOGY 6 Various terminology and concept associated with optimization :- 1.Variables. 2.Effect, Interaction & Confounding. 3.Code transformation. 4. Factor space. 5.Experimental design. 6.Response surface.
- 7. VARIABLES 7 Design and development of drug formulation or pharmaceutical process usually involve several variables. VARIBLES QUANTITATIVE (CAN BE ASSIGNED A NO.) Eg-AMOUNT OF DISINTEGRANT, QUALITATIVE (NOT ASSIGNED A NO. Eg- TYPE OF EMULGENT,POLYMER GRADE INPUT VARIABLES (INDEPENDENT VARIABLES) Eg- MIXING TIME, COMPRESSION FORCE DEPENDENT VARIABLES (RESPONSE VARIABLES)
- 8. 8 INDEPENDENT VARIABLES (INPUT VARIABLES) The independent variables, which influence the formulation characteristics or output of the process, are labeled as FACTORS. Values assigned to the factors are termed as LEVELS, e.g., 30°and 50°are the levels for the factor, temperature. The restrictions placed on the factor levels are known as CONSTRAINTS.
- 9. 9 DEPENDENT VARIABLES (RESPONSE VARIABLES) The characteristics of the finished drug product or the in-process material are known as dependent. Variables, e.g., drug release profile, friability, size of tablet granules, disintegration time, etc. These variables are the measured properties of the system to estimate the outcome of the experiment. These variables are the direct function(s) of any change(s) in the independent variables.
- 10. 10 Accordingly, a drug formulation (product) with respect to optimization techniques can be considered as a system, whose output (Y) is influenced by a set of controllable (X) and uncontrollable (U) input variables via a transfer function (T). The nomenclature of T depends upon the predictability of the output as an effect of change of the input variables. T System with controllable input variables (X), uncontrollable input variables (U), transfer function (T) & output variables (Y). X U Y
- 11. 11 If the output is totally unpredictable from the previous studies, T is termed as black box. The term, white box is used for a system with absolutely true predictability. While the term, gray box is used for moderate.
- 12. EFFECT INTERACTION &CONFOUNDING. 12 The magnitude of the change in response caused by varying the factor level(s) is termed as an EFFECT. The main effect is the effect of a factor averaged over all the levels of other factors. An INTERACTION is said to occur, when there is "lack of additivity of factor effects". An interaction may be said to take place when the effect of two or more factors is dependent on each other, e.g., effect of factor A depends on the level given to the factor B. The term orthogonality is used, if the estimated effects are due to the main factor of interest and are independent of interactions (Box et al., 1960; Bolton, 1990). Conversely, lack of orthogonality (or independence) is termed as CONFOUNDING or . The measure of the degree of confounding is known as resolution.
- 13. CODE TRANSFORMATION 13 The process of denoting a natural variable into a dimensionless coded variable Xi such that the central value of experimental domain is zero is known as coding or normalization. Various salient features of the transformation include: Depiction of effects and interaction using signs (+) or (-). Allocation of equal significance to each axis. Easier calculation of the coefficients. Easier calculation of the coefficient variances. Easier depiction of the response surfaces. Orthogonality of the effects.
- 14. 14 Generally, the various levels of a factor are designated as -1, 0 and +1, representing the lowest, intermediate (central) and the highest factor levels investigated, respectively. For instance, if starch, a disintegrating agent, is studied as a factor in the range of 5 to 10% (w/w), then codes -1 and +1 signify 5% and 10% concentrations, respectively. The code 0 would represent the central point at the mean of the two extremes, i.e., 7.5% w/w.
- 15. FACTOR SPACE 15 The dimensional space defined by the coded variables is known as factor space. The part of the factor space that is investigated experimentally for optimization is the experimental domain , Also known as the region of interest, it is enclosed by the upper and lower levels of the variables. The factor space covers the entire figure area and extends even beyond it, whereas the design space of the experimental domain is the square enclosed by X1 = ± 1, X2 = ± 1. In Fig. represent the factor space for two factors on a bi- dimensional (2-D) plane during a typical tablet compression process.
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- 17. Experimental Design 17 Conduct of an experiment and subsequent interpretation of its experimental outcome are the twin essential features of the general scientific methodology. This can be accomplished only if the experiments are carried out in a systematic way and the inferences are drawn accordingly. Runs or trials are the experiments conducted as per the selected experimental design. Primarily, the experimental (or statistical) designs are based on the principles of randomization (the manner of allocations of treatments to the experimental units), replication (the number of units employed for each treatment) and error control or local control (grouping of specific type of experiments to increase the precision).
- 18. RESPONSE SURFACE 18 Conduct of DoE trials, as per the chosen statistical design, yields a series of data on response variables explored. Such data can be suitably modeled to generate mathematical relationship between the independent variables and the dependent variable. Graphical depiction of the mathematical relationship is known as Response surface. A response surface plot is a 3-D graphical representation of a response plotted between two independent variables and one response variable. The use of 3-D response surface plots allows understanding of the behavior of the system by demonstrating the contribution of the independent variables.
- 19. DESIGN OF EXPERIMENT 19 Design of experiment :- Is a structure organized method used to determine the factor affecting to process and output of that process. Parsimony Principle:- some of factor are important ,while other factor are not important. Few variables are effective or other are not effective. Experimental design is an integral part of optimization technique. Those technique used in the formulation optimization.
- 21. DOE FOR FORMULATION & DEVELOPMENT 21 All pharmaceutical products are formulated to specific dosage form drugs to be effectively delivered to patient typical pharmaceutical dosage form include tablets, capsules, solution suspension, etc. Different dosage form required different technology usually present different technological challenge for formulation & development . Due to complex challenges, formulations scientist used effective methodology like as design of experiment and statistical analysis for formulation and development . Formulation scientist used this method for process optimization and process validation .
- 22. COMPUTER SOFTWARE 22 Software Silent feature Design Expert Powerful & compressive package used for optimizing pharmaceutical formulation and process Minitab Powerful DOE software for automated data analysis MS- Excel compatibility. Include almost all design of RSM. DOE PRO XL MS-Excel compatible DOE software for automated data analysis CARD Powerful DOE software for data analysis include graphics and help feature
- 23. CONCLUSION 23 Design of experiment & statistical analysis have been used in the formulation development. Using design of experiment formulation scientist evaluate the all formulation factors in systematically and timely manner to optimize the formulation and manufacturing process. When the pharmaceutical process and product are optimize by systematic approach then process validation & scale up can be efficient because of the robustness of the formulation and manufacturing process.
- 24. REFERENCES 24 Singh B, Gupta RK, Ahuja N. Computer-assisted optimization of pharmaceutical formulations and processes. Pharmaceutical Product Development (Ed. NK Jain), CBS Publishers, New Delhi. 2006:273-318. Cooper L. and Steinberg D., Introduction to methods of optimization, W.B.Saunders,Philadelphia, 1970, 1st Edition, 301- 305.