Computer aided formulation development
- 1. COMPUTER - AIDED FORMULATION DEVELOPMENT PREPARED BY – Ms. SHRUTI TYAGI M. Pharm: Pharmaceutics Lecturer in Pharmacy (B.S. Anangpuria Institute of Pharmacy)
- 2. POINTS TO BE CONSIDERED - • Concept of optimization. • Parameters of optimization, Factorial design. • Use of computers in optimization. • Optimization of various Drug products and pharmaceutical processes. • Legal Protection of Innovative Uses of Computers in R&D. • Ethics of Computing in Pharmaceutical Research. • Computers in Market analysis.
- 3. Concept of optimization Optimization has been defined as the implementation of schematic approaches to achieve the best combination of product and/or process characteristics under a given set of conditions. Design and development of drug formulation or pharmaceutical process usually involves several variables. The input variables, which are directly under control of the product development scientist, are known as INDEPENDENT VARIABLES e.g., compressional force, excipient amount, mixing time etc.(such variables are either QUALITATIVE or QUANTITATIVE). The input variables, which are directly dependent upon the independent variables, are known as DEPENDENT VARIABLES e.g., hardness, disintegration time, dissolution time etc.
- 4. Parameters of optimization PROBLEM TYPE Constrained Unconstrained VARIABLES Independent Dependent
- 5. EXAMPLES OF PARAMETERS OF OPTIMIZATION 1. Problem Types Constrained: Making hardest tablet which disintegrates within 20 min Unconstrained: Making hardest tablet 2.Variables Independent: Mixing time for a given process step, Granulating time Dependent: Particle size of vesicles, hardness of the tablet
- 6. TYPES OF EXPERIMENTAL DESIGNS • Completely randomized designs. • Randomized block designs. • Factorial designs - 1. Full factorial designs 2. Fractional factorial designs • Response surface designs. • Central composite designs. • Box- Behnken designs. • Three level full factorial designs.
- 7. These designs compare the values of a response variable based on different levels of that primary factor. Example if there are 3 levels of primary factor with each level to be run 2 times then there are 6 factorial possible run sequence. 1. Completely randomized designs- A DIAGRAMATIC REPRESENTATION OF COMPLETELY RANDOMIZED DESIGN.
- 8. 2. Randomized block designs- For this type of design there is one factor or variable that is of primary interest ( to control the non-significant factors , an important technique called blocking is used to reduce or eliminate the contribution of these factors to experimental errors). A DIAGRAMATIC REPRESENTATION OF RANDOMIZED DESIGN.
- 9. 3. Factorial Designs- These are the designs of choice for simultaneous determination of the effects of several factors and there interactions. Symbols to donate levels are- (1)- when both the variables are in low concentrations. (a)- one low variable and second high variable. (b)- one high variable and second low variable. (ab)- when both the variables are in high concentrations. For instance- factorial designs are optimal to determine the effect of pressure and lubricant on the hardness of tablet. Other example is, effect of disintegrant and lubricant concentration on tablet dissolution.
- 10. A) Full Factorial designs- used for small set of factors. B) Fractional designs- used to examine multiple factors efficiently with fewer runs than corresponding full factorial designs. Types of fractional factorial designs:- • Homogeneous fractional factorial designs- used when large number of factors must be screened. • Mixed level fractional factorial designs- used when variety of factors need to be evaluated for main effects and higher level interactions can be assumed to be negligible, objective is to generate a design for one variable, A, at 2 levels and another , X, at 3 levels, mixed and evaluated. • Box-Hunter design • Plackett- Burman design • Tiguchi • Latin- Square
- 12. 4. Response surface designs- This model has quadratic designs- γ = β0 + β1X1 + β2X2 +....... β11 (X1 ) 2 + β22 (X2 )2 Designs for fitting these type of models are known as response surface designs. If defects and yields are the outputs and the goal is to minimise defects and maximize yields. Most common designs generally used in this response surface designs are: •Central composite design •Box-Behnken design
- 13. A)Central composite designs- The central composite design contains embedded factorial or fractional factorial designs with center points that is augmented with group of star points, these always contain twice as many star points as there are factors in the designs. The star points represents new extreme value ( low and high) for each factor in the design.These are of three types- • Circumscribed design- cube points are at the corners of unit cube, star points are along the axis at or outside the cube, and center point at the origin. • Inscribed design- star points take the value of +1 and -1 and cube points lie in the interior of the cube. • Faced design-star points are on the faces of cube.
- 15. B) Box- Behnken design- Uses just three levels of each factor, in this design the treatment combinations are at the midpoints of the edges of the process space and at the center. These designs are rotatable or near rotatable and require three levels of each factor.These designs are for three factors with circle points appearing at the origin and possibly repeated for several runs. It is an alternative to central composite design.
- 16. 5.Three level full factorial design- It is written as 3k factorial design. It means that k factors are considered each at three levels. These are usually referred to as low, intermediate and high values, which are usually expressed as 0, 1 and 2. The third level for a continuous factor facilitates investigation of a quadratic relationship between the response and each of the factors.
- 17. DESIGN MERIT LIMITATION FACTORIAL Efficient in estimating main effects and interactions. Reflection of curvature is not possible in a 2 level design, large number of experiments are required. FRACTIONAL FACTORIAL Suitable for large number of factor or factor levels. Effects can not be uniquely estimated, as are confounded with interaction terms, difficult to construct. PLACKET-BURMAN Suitable for very large number of factors,where even full factorial designs require a large number of experiments. Fixed designs in which runs are predetermined and are limited to ≤16 experiments. CENTRAL COMPOSITE Allows the work to proceed in stages. Difficult to practice with fractional values of α
- 18. Use of computers in optimization Now a days, computer use is considered almost indispensable in the design and optimization methods, as a great deal of intricate statistical and mathematical calculations are involved. The computer software have been used almost at every step during the entire optimization cycle ranging from selection of design, screening of factors, use of response surface designs, generation of the design matrix, plotting of 3D response surfaces and 2D contour plots, application of optimum search methods, interpretation of the results, and finally the validation of the methodology. Some important computer softwares used in optimization are as follows:- • Design expert • MINITAB • JMP • MATREX • CornerstoneTM • STATISTICA • NEMROD@
- 19. Optimization of various Drug products and pharmaceutical processes Liquid Formulations:- There are several reports on optimizations viz. emulsions, solutions, suspensions, lotions, etc. Amongst the ophthalmic and parentral formulations, solubility, chemical stability and viscosity have been optimized by varying the formulation composition. Emulsions, microemulsions, solutions, lotions or suspensions have been optimized for responses as turbidity, cloud point, physical stability, preservative efficacy etc., primarily by altering the levels of the ingredients. The Factorial design and Central composite design have been utilised as the experimental designs, with the number of independent variables ranging between 2 to 8 and responses between 1 and 5.
- 20. S.NO. TYPE DRUG DESIGN INPUT VARIABLES RESPONSE VARIABLES 1. Syrup Acetaminophen RSM 4 2 2. Emulsion Oxybenzone SMD 3 3 3. Lotion Erythromycin CCD 3 1 4. Suspension Rifampicin FD 4 5 5. Oral solution Lamivudine CCD 5 2 6. Microemulsion Retinol SMD 4 1 7. Ophthalmic formulation Enalkrien FD 3 1 8. Parenteral nutrition Nutrient mixtures PBD 5 1 9. Solution Diazepam SMD 3 1 Optimization reports on liquid dosage forms RSM-Response surface methodology, SMD- Simplex mixture design, CCD- Central composite design, FD- Factorial design, PBD- Placket-Burman design.
- 21. The various novel and innovative uses of computers plays a vital role in drug formulation and development, these uses of computers in the research and development sector can be protected legally through intellectual property rights. Intellectual property rights seek to protect knowledge derived from research and development especially by firms involved in collaborations with others to ensure that the knowledge is not expropriated by their potential partners. The lack of intellectual property rights reduces the bargaining power of collaboration partners and increase costs of information for such partners. The existence of protective mechanisms over intellectual assets is essential to enhance the competitiveness of organisations especially those working on R&D related issues as well as to attract potential investors. Legal Protection of Innovative Uses of Computers in Research and Development
- 22. Ethics of Computing in Pharmaceutical Research Computer ethics is a part of practical philosophy concerned with how computing professionals should make decisions regarding professional and social conduct. Margaret Anne Pierce, a professor in the Department of Mathematics and Computers at Georgia Southern University has categorized the ethical decisions related to computer technology and usage into three primary influences: • The individual's own personal code. • Any informal code of ethical conduct that exists in the work place. • Exposure to formal codes of ethics. Privacy is one of the major issues that has emerged since the internet has become part of many aspects of daily life. Internet users hand over personal information in order to sign up or register for services without realizing that they are potentially setting themselves up for invasions of privacy.
- 23. Identifying issues Identifying ethical issues as they arise, as well as defining how to deal with them, has traditionally been problematic. In solving problems relating to ethical issues, Michael Davis proposed a unique problem-solving method. In Davis's model, the ethical problem is stated, facts are checked, and a list of options is generated by considering relevant factors relating to the problem. The actual action taken is influenced by specific ethical standards. Ethical standards Various national and international professional societies and organizations have produced code of ethics documents to give basic behavioral guidelines to computing professionals and users. They include: 1.Association for Computing Machinery ACM Code of Ethics and Professional Conduct
- 24. 2. Australian Computer Society • ACS Code of Ethics • ACS Code of Professional Conduct 3. British Computer Society • BCS Code of Conduct • Code of Good Practice (retired May 2011) • Computer Ethics Institute • Ten Commandments of Computer Ethics marri 4. IEEE • IEEE Code of Ethics • IEEE Code of Conduct 5. League of Professional System Administrators • The System Administrators' Code of Ethics
- 25. Computers in Market analysis A market analysis studies the attractiveness and the dynamics of a special market within a special industry. It is part of the industry analysis and thus in turn of the global environmental analysis. Through all of these analyses, the strengths, weaknesses, opportunities and threats (SWOT) of a company can be identified. Finally, with the help of a SWOT analysis, adequate business strategies of a company will be defined. The market analysis is also known as a documented investigation of a market that is used to inform a firm's planning activities, particularly around decisions of inventory, purchase, work force expansion/contraction, facility expansion, purchases of capital equipment, promotional activities, and many other aspects of a company.
- 26. References 1. Bhupinder Singh, R.K.Gupta and Naveen Ahuja, “Computer assisted optimization of pharmaceutical formulations and processes”, page no. 273-318. 2. Nazura Abdul Manap, Rohimi Bin Shapiee, Pardis Moslemzedah Tehrani and Ahmad Azam bin Mohd. Shariff, “Protecting R&D Inventions through Intellectual Property Rights”: Journal of Intellectual Property Rights:Vol 21, March 2016, pp 110-116. 3. Pharmaceutical Optimization by G.T.Kulkarni.
- 27. THANK YOU