Design of Experiment ppt by Ganesh Asabe

Factorial Design , Composite Design, Mixture Design, Response Surface Methodology.

1. Design of Experiments(DoE): Factorial designs, Composite designs, Mixture designs, Response surface methodology PRESENTED BY GANESH PATIL M.S. PHARMACEUTICS SUBJECT CODE : GE 611

2. Contents

3. Design of experiments (DoE) Design of experiments (DOE) is  a systematic method to determine the relationship between factors affecting a process and the output of that process . This information is needed to manage process inputs in order to optimize the output. DoE – Powerful data collection and analysis tool of experiments Example : Binder – too much of binder – higher disintegration time – affect dissolution rate Effect of concentration of suspending agent in suspension. Effect of concentration of sweetening agents

4. PROCESS IN RELATION TO DoE: Variables that are difficult or impossible to control Eg : equipment performance,environment,operator, etc. NOISE VARIABLES

5. DoE Terminology FACTOR (INPUT, VARIABLE): Independent variable. This is what we control and change in experiment. It is referred as x1,x2,x3,… or A,B,C, Formulation : concentration of binder, disintegrant, lubricant etc. Process: blender RPM, blender occupancy, blending time FACTOR SETTING OR LEVEL : a particular value for a factor Concentration of PVP – 15 mg/tablet or 2.0%w/w Blender rpm : 20,25,30 Blending time : 10 min,15min,20min K : number of factors or variables used in a particular study RESPONSE : it is the outcome of an experiment. It is measured and not controlled like factors . It is referred as y1, y2. Dissolution profile- dissolution at 45 min time point , disintegration time Blend uniformity ,tablet hardness etc.

6. FACTORIAL DESIGNS

7. Thus, combinations of ( i ) lactose, acacia and Primojel, (ii) lactose, acacia and potato starch and (iii) lactose, PVP and potato starch are the best combinations of diluent, binder and disintegrant and hence these combinations are recommended for formulation development of Olmesartan tablets giving rapid and higher dissolution of Olmesartan. Case study

8. SELECTION OF PROCESS VARIABLES (FACTORS) DETERMINE SUITABLE EXPERIMENTAL DESIGN SELECTION OF AN EXPERIMENTAL DESIGN EXECUTION OF THE DESIGN CONDUCT EXPERIMENTS AND COLLECT DATA ANALYZE DATA AND FEED INTO THE DOE SOFTWARE INTERPRET THE RESULTS AND VERIFY RESULTS & CONDUCT ADDITIONAL EXPERIMENTS AS REQUIRED SETTING A SOLID OBJECTIVE KEY STEPS FOR EXPERIMENTAL DESIGN

9. Carbamazepine tablet formulation optimization: Ingredients Role in the formulation Mg/tab comments carbamazepine Active pharmaceutical ingredient 200.00 - Microcrystalline cellulose Diluent 135.00 Concentration not very critical, however can impact cost Povidone Binder 15.00 Concentration can impact dissolution Croscarmellose sodium Superdisintegrant 10.00 Colloidal silicon dioxide Glidant 5.00 - Magnesium stearate Lubricant 5.00 Concentration can impact dissolution Total tablet weight 400.00

10. Central composite design The center points are augmented with a group of axial points called star points. Most commonly used for optimization as it uses 5 levels. The number of experiments to perform in a centered composite design is determined by the following formula when the factorial design is full:   N = 2 k +2k+N . Center points - experimental runs where your X's are set halfway between (i.e., in the center of) the low and high settings . Star points  - new extreme values (low and high) for each factor in the design .

11. MIXTURE DESIGN Mixture experiment is applied when the overall amount of a composition is defined. Their scope is to rationalize the use of each constituent and its proportion in the formulation. Mixture Design can be powerful tool for optimizing the proportions of ingredients in a mixture to achieve a desired response

12. RESPONSE SURFACE METHODOLOGY Response surface methodology  is a statistical tool designated to model the data set and optimize the  response  variable within the specified ranges of the independent factors Typically RSM is used when curvature effects are observed and significant. Best model for determining curvature effects is 3 level factorial, however it leads to many runs and therefore 2 level factorial design with center points is used.

13. 3D and contour response surface plots of the recorded response drug loading (Y2) (A) Effects of chitosan concentration and Tween 80 concentration  10.36468/pharmaceutical-sciences.517 DOI:

14. (B) effects of chitosan concentration and Eudragit RS100 concentration (C) effects of Eudragit RS100 concentration and Tween 80 concentration

15. CONCLUSION : DoE is a powerful tool for designing experiments and analyzing the results. It provides a systematic approach to experimentation, saving time, resources, and improving product and process quality. By identifying the optimal levels of factors, it can lead to better decision-making and improved performance. Maximize process knowledge, with the minimum use of resource and accurate information, in the most efficient way possible. Identify factor interactions. Characterize the relative significance of each factor. Allow for the prediction of the process behavior within the design space. Establish a solid cause and effect relationship between CPPs and CQAs. Make the product or process more robust.

16. Martins Fukuda1 , Camila Francini Fidelis Pinto1 , Camila dos Santos Moreira1 , Alessandro Morais Saviano1 , Felipe Rebello Lourenço1, “Design of Experiments (DoE) applied to Pharmaceutical and Analytical Quality by Design ( QbD )” Stavros N. Politis , Paolo Colombo, Gaia Colombo & Dimitrios M. Rekkas “Design of experiments (DoE) in pharmaceutical development” M. A Kassem, Khaled Shaboury and A. I Mohamed “Application of Central Composite Design for the Development and Evaluation of Chitosan-based Colon Targeted Microspheres and in vitro Characterization” https://www.itl.nist.gov/div898/handbook/pri/section5/pri54.htm Vaddemukkala Yohan *1, Muneer Syed 1 , D.Srinivasarao 1 “ RESEARCH ARTICLE ON OPTIMIZATION OF OLMESARTAN TABLET FORMULATION BY 2 3 FACTORIAL DESIGN” REFERENCES