Quality by Design Application of Pharmaceutical QbD for Enhancement of the Solubility and Dissolution of a Class II BCS Drug using Polymeric Surfactants and Crystallization Inhibitors: Development of Controlled-Release Tablets

Page  2 1 inroduction 1.1 TPQP 1.2 CQAs 1.3 CPP 1.4 Design Space 1.5 control strategy (or normal operating ranges) 1.6 DOE 1.7 Felodipine 2 Methods 2.1 Identification of Material Attributes of Excipients Used for the Preparation of FSMs 2.2 Preparation of FSMs with the Selected Variables Using Box–Behnken Design 2.3 Evaluation of FSMs Prepared Using Box–Behnken Design 2.4 Development of Design Space of FSMs Having Optimum Quality 2.5 Determination of Control Strategy of the Optimized FSMs 2.6 Thermal Analysis of the Optimized FSM 2.7 Preparation of the CR Tablets Containing the Optimized In Situ-Formed FSM 3 conclusion

Page  3 1 inroduction QbD is concerned with the achievement of certain predictable quality with desired and predetermined specifications through relating the critical material attributes and critical process parameters (CPP) to the critical quality attributes (CQAs) of drug product. It uses multivariate experiments to understand product and process to establish a design space through design of experiments (DOE).

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Page  TPQP The target product quality profile a quantitative surrogate for aspects of clinical safety and efficacy that can be used to design and optimize a formulation and manufacturing process. It should include quantitative targets for impurities and stability, release profiles (dissolution) other product specific performance requirements.

Page  CQAs Critical Quality Attributes physical, chemical, biological or microbiological properties or characteristics that should be within an appropriate limit, range, or distribution to ensure the desired product quality.

Page  CPP critical process parameter any measurable input (input material attribute or operating parameter) or output (process state variable or output material attribute) of a process step that must be controlled to achieve the desired product quality and process consistency.

Page  8 For a given unit operation, there are four categories of parameters and attributes & input material attributes & output material attributes & input operating parameters & output process state conditions

Page  Design Space “The multidimensional combination and interaction of input variables (e.g., material attributes) and process parameters that have been demonstrated to provide assurance of quality.”

Page  10 Working within the design space is not considered as a change and nearly gives the desired product quality of the optimum CQAs. However, movement out of the design space is considered to be a change and gives a pharmaceutical product of low quality. Submission of a design space to FDA is a pathway obtaining the ability to operate within that design space without further regulatory approval. A design space is a way to represent the process understanding that has been established. The benefits of having a design space are clear; one challenge to the effective use of a design space is the cost of establishing it.

Page  control strategy (or normal operating ranges) the upper and/or lower limits for the critical material attributes and CPP between which the parameters are routinely controlled during production in order to assure reproducibility. The control space should be within the design space. If the control space is much smaller than the design space, the process is then considered robust. A control strategy may include input material controls, process controls and monitoring, design spaces around individual or multiple unit operations, and/or final product specifications used to ensure consistent quality.

Page  DOE DOE is an organized method to determine the relationship between the inputs(the raw material attributes and CPP ) and outputs ( the CQAs such as solubility and dissolution)of a process. Each unit operation has many input variables and CQAs, it is impossible to experimentally investigate all of them. Researchers have to use prior knowledge and risk management to identify critical input and output variables and process parameters to be investigated by DOE.

Page  Felodipine Felodipine is a model drug of the Biopharmaceutical Classification System (BCS) class II. It is used for treatment of chronic hypertension. Increasing the solubility of the sparingly water soluble drug and controlling its release rate from the product is critical during the development of a controlled-release (CR) tablet.

Page  14 2 Methods 2.1 Identification of Material Attributes of Excipients Used for the Preparation of FSMs Screening the Effect of Different Hydrophilic Carriers and Polymeric Surfactants on the Solubility of Felodipine Screening the Inhibitory Effects of Different Hydrophilic Carriers and Polymeric Surfactants on Crystallization of Felodipine from Supersaturated Solutions.

Page  Preparation of FSMs with the Selected Variables Using Box–Behnken Design Identify potential variables that can have an impact on the desired quality attribute of FSM Four methods of preparation could be used for preparing FSM. Preliminary studies were performed for selecting the appropriate method of manufacture. The mean solubility of the FSMs prepared using different techniques SE>PM ∼ SW ∼ cogrinding(arranged in descending order). Thus SE and PM techniques were selected to be the CPPs for development of FSM(PM technique was used for comparison).

Page  16 The physical properties of solid felodipine such as particle size (material attributes of drug) was considered as low-risk variables that had no impact on the CQAs of FSMs because felodipine was dissolved in ethyl alcohol when prepared as FSM using SE technique.

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Page  Design of Experiment. Box–Behnken statistical screening design was used to optimize and evaluate the effects of the material attributes and CPPs on the solubility and in vitro dissolution of FSMs.

Page  19 Y is the measured response associated with each factor level combination, b0 is an intercept, b1 to b33 are regression coefficients computed from the observed experimental values of Y, X1, X2, and X3 are the coded levels of independent variables. The terms X1X2 and X i 2 (i=1, 2, or 3) represent the interaction and quadratic terms, respectively.

Page  20 The potential CQAs of FSMs : maximum solubility, minimum crystallization from supersaturated solution and maximum dissolution rate of felodipine Preparation of FSMs.

Page  Evaluation of FSMs Prepared Using Box–Behnken Design Determination of Initial Maximum Solubility and Equilibrium Solubility (CQAs) of the Prepared FSMs in Distilled Water In Vitro Dissolution of Felodipine from the Prepared FSMs in 0.5% Sodium Lauryl Sulfate Solution.

Page  Development of Design Space of FSMs Having Optimum Quality The relationship between the process inputs (material attributes and process parameters) and CQAs were described in the design space. Design space was determined from the common region of successful operating ranges for multiple CQAs (Table I). The successful operating ranges for the maximum solubility (Y1), equilibrium solubility (Y2), and dissolution efficiency (Y3) DE60 (%) were ≥75 μg/mL, ≥45 μg/mL, and 75%≤Y3≤95%, respectively. It is expected that operation within the design space will result in a product possessing the desired CQAs.

Page  Determination of Control Strategy of the Optimized FSMs A control strategy is designed to ensure that a product of required quality will be produced consistently. The acceptable range of material attributes were determined based on design space.

Page  Thermal Analysis of the Optimized FSM 2.7 Preparation of the CR Tablets Containing the Optimized In Situ- Formed FSM

Page  25 3 conclusion The aim of this study was to apply quality by design (QbD) for pharmaceutical development of felodipine solid mixture (FSM) containing hydrophilic carriers and/or polymeric surfactants, for easier development of controlled-release tablets of felodipine. The material attributes, the process parameters (CPP), and the critical quality attributes of the FSMs were identified. Box–Behnken experimental design was applied to develop space design and determine the control space of FSMs that have maximum solubility, maximum dissolution, and ability to inhibit felodipine crystallization from supersaturated solution.

Page  26 Material attributes and CPP studied were the amount of hydroxypropyl methylcellulose (HPMC; X1), amount of polymeric surfactants Inutec®SP1 (X2), amount of Pluronic®F-127 (X3) and preparation techniques, physical mixture (PM) or solvent evaporation (SE; X4). The operating ranges, for robust development of FSM of desired quality, of Pluronic®, Inutec®SP1, HPMC, and preparation technique, are 49–50, 16–23, 83–100 mg, and SE, respectively.