Vipul Patel/ Pharmaceutics and Pharmaceutical Technology FACTORIAL DESIGN DEPARTMENT OF PHARMACEUTICS AND PHARMACEUTICAL TECHNOLOGY, L.M.COLLEGE OF PHARMACY, AHMEDABAD. Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

Vipul Patel/ Pharmaceutics and Pharmaceutical Technology Research Process: Require intelligence planning and approach. Man Material Money Time Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

Research scientist Against the Person who Invest in Stock Market,.,. Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

What happening With Trial And Error Method Traditional Trend Randomized fashion of research Required More number of trials.., Take more time Cant predict the extension… i.e. cant say what happen if such change are made within that particular system. www.parasshah.weebly.com

e.g. In process of Extrusion Spheronization, Three attributes… No of trials are more.,.,. e.g. In process of Extrusion Spheronization, Three attributes… Binder (%) Granulation time (Min) Spheronization speed (RPM) Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

Vipul Patel/ Pharmaceutics and Pharmaceutical Technology Wastage of … Man Money Material Time And still for output ??? We are not sure !! Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

Is there Any alternative?? Optimization Designing experiments to yield the most information from the fewest runs Reduce the number of trial to minimum but in logical manner Carry out research in systematic way Identify the characteristic you want in your product Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

Factorial design Fractional Factorial design Simplex lattice design Various technique for optimization., Factorial design Fractional Factorial design Simplex lattice design Plackett-burman design Central composite design Constrained mixture design Box Behnken design Face centered cubic design (FCC) Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

FACTORIAL DESIGN Basic Terminology: In scientific language those attributes are called as variables.. Independent variables Conc. Of Polymer, Agitation Speed Binder (%), Granulation time Dependent variables Friability, hardness Pharmacological activity Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

Independent variable: Significant variable More important.. Go on changing level.. E.g. Polymer Conc, Granulation time Insignificant variable Not that much importance you can keep it at constant level also.. E.g. Effect of lubricant on floating tablet Independent variable may positive or negative result on to the dependent variable Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

Dependent variable Also Known as Response variable. Its output of our experiment. Not limit for dependent variable. This variable depends on independent variable. Keep as many as you wish. e.g. Angle of repose, Disintegration time, Friability, Hardness. Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

Vipul Patel/ Pharmaceutics and Pharmaceutical Technology LEVEL What is level?? Level of factor are the values or designations assigned to the factors. In General Factor and Level are keep below 3. No of trial depend upon... No of independent variable No of level So choosing the independent variable and no of level that is the crucial step in optimization… Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

Full factorial design at 2 levels: (Solubility of drug in Mixed Micelles) Factor Associated variable Lower level(coded -1) Upper level(coded +1) Conc. Of Bile salts X1 0.075 0.125 Lecithin-Cholate Molar ratio X2 0.6:1 1.4:1 Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

2^2 Full Factorial design : Solubility of drug in Mixed Micelles) No. X1 X2 Conc. Of Bile salts Lecithin-Cholate Molar ratio Solubility (mg/ml) 1 -1 0.075 0.6:1 6.58 2 +1 0.125 10.18 3 1.4:1 9.41 4 14.15 Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

First order or additive linear model: Y= 10.40 + 2.08 X1 + 1.92 X2 Complete model: Y= 10.40 + 2.08 X1 + 1.92 X2 + 0.28 X1X2 Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

Full factorial design for 3 factors(2^3) Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

Formulation of an oral solution: Factor Associated variable Lower level (coded -1) Upper level (coded +1) Polysorbate 80(%) X1 3.7 4.3 Propylene glycol(%) X2 17 23 Sucrose invert medium(%) X3 49 61 Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

2^3 full factorial design: No. X1 X2 X3 Polysorbate 80(%) Propylene glycol(%) Sucrose(ml) Turbidity y(ppm) 1 -1 3.7 17 49 3.1 2 +1 4.3 2.8 3 23 3.9 4 5 61 6.0 6 3.4 7 3.5 8 1.8 Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

Complete synergistic model: Y= 3.45 -0.675 X1 – 0.375 X2 + 0.225 X3 + 0.05 X1X2 - 0.4 X1X3 – 0.65 X2X3 + 0.175 X1X2X3 Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

GELLAN GUM-ALGINATE BEADS 32 FULL FACTORIAL DESIGN Why 3 level factorial design??? Independent Factors Levels -1 +1 X1: Gellan gum Concentration 1.5 2 2.5 X2: Sodium alginate Concentration 0.5 1 Percentage entrapment efficiency (Y1), swelling ratio (Y2) and T90 (time taken for 90% drug to be released) (Y3) was selected as dependant factors Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

Design matrix for 32 full factorial design Run Coded value Uncoded value Responses Batch code X1 X2 Gellan gum conc. Sodium alginate Conc. Entrapment efficiency swelling ratio T90 S1 -1 1.5 0.5 91.84 4.65 5.2 S2 2 93.1 5.92 7.5 S3 1 2.5 96.44 6.34 9.4 S4 94.18 5.39 S5 96.83 6.28 8.2 S6 98.09 6.85 9.1 S7 98.4 5.38 7.3 S8 99.79 6.54 9.5 S9 99.68 7.56 11.1 Design matrix for 32 full factorial design Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

The polynomial equations for three responses are shown below: Y1= 96.48+1.63X1+2.75X2-0.83X1X2 Y2= 6.15+0.83X1+0.50X2 Y3= 7.50+1.98X1+0.96X2+0.83X22   Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

Contour Plot: It’s a graphical representation of results. From the Full model equation, eliminate insignificant terms gives refined equation or reduced equation. This refined equation or Full equation is transferred in form of graphs. That is known as contour plot or response surface methodology plot. Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

Vipul Patel/ Pharmaceutics and Pharmaceutical Technology Run Coded value Uncoded value Responses Batch code X1 X2 Y1 Y2 Y3 S1 -1 1.5 0.5 91.84 4.65 5.2 S2 2 93.1 5.92 7.5 S3 1 2.5 96.44 6.34 9.4 S4 94.18 5.39 S5 96.83 6.28 8.2 S6 98.09 6.85 9.1 S7 98.4 5.38 7.3 S8 99.79 6.54 9.5 S9 99.68 7.56 11.1 99 98 97 93 94 95 96 10 9 8 7. 6 7 6.5 6 5.5 5 Y3 Y2 Y1 Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

Advantages of Factorial designs: Maximum efficiency in estimating main effects. Identification of interaction. Conclusions apply to a wide range of conditions. Maximum use of the data. Saves time and money. Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

References Gareth A. Lewis, Didier Mathieu, Roger Phan-Tan-Luu. Pharmaceutical Experimental Design. Marcel Dekker 1999. Sanford Bolton, Charles Bon. Pharmaceutical statistics, Practical and Clinical applications. Drugs and Pharmaceutical Sciences Vol-135. Pritesh C. Mistry. Development Of Gellan Gum Alginate Bead of Aceclofenac, 2006; LMCP THESIS. Vipul Patel/ Pharmaceutics and Pharmaceutical Technology

Vipul Patel/ Pharmaceutics and Pharmaceutical Technology Many THANKS for YOUR Attention Dziękuję dhanya-waad Дякую go raibh maith agat bedankt tesekkürle Merci Thank yu köszi tack så mycket mange tak Thank you faleminderit hvala Danke díky kiitos takk Obrigada Mulţumesc nandri Ευχαριστώ anugurihiitosumi Many Thanks for Your Attention Grazie תודה dhanya-waad Muchas gracias köszönöm tack děkuji vam ačiû Terima Kasih Спасибо شكرًا salamat Vipul Patel/ Pharmaceutics and Pharmaceutical Technology