IJCRR - 14(18), September, 2022
Date of Publication: 24-Sep-2022
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Identification and Mitigation of Risks using Quality Risk Assessment Tools for Formulation Development of Pazopanib HCl Extrudates by using HME Technique: A Systematic QbD Approach
Author: Amit Gupta, Rashmi Dahima
Abstract:Introduction: Pharmaceutical development ensures to design a valued product and robust manufacturing process to consistently deliver intended performance. It is necessary to recognize that quality cannot be tested into drug products but it should be built in during formulation design and development. Pazopanib HCl is a protein kinase inhibitor molecule approved by USFDA and European agencies for the treatment of renal cell carcinoma (RCC) patients and other renal malignancies, but it has very poor aqueous solubility and drug release. Therefore, it is essential need to improve the solubility and in vitro dissolution characteristics. Objective/Aim: The main objective of this study was to prepare stable Pazopanib HCl extrudates (PZP-Ex) by using the Quality by Design (QbD) approach. Method: Pazopanib HCl extrudates (PZP-Ex) was manufactured using hot melt extrusion technique. Initially, the quality target product profile (QTPP) and critical quality attributes (CQAs) were identified, and then risk assessment was done using a heat map and failure mode and effect analysis (FMEA) approach. A full factorial design (FFD) was used to study the impact of two continuous variables i.e., level of polymer, milling speed and one categorical (milling screen type) factor on particle size distribution (PSD), disintegration time and dissolution of extrudates. Results: The significance (p) value for studied response variables i.e., percent retention on 40 mesh ASTM sieve (420 µ), disintegration time and percent drug release in 15 min were 0.006, 0.0243 and 0.0355 respectively from the actual by a predicted plot which signifies that the model is significant. The polymer-to-drug ratio has a significant impact on drug release and disintegration time of extrudates. Conclusion: Pazopanib HCl extrudates were successfully prepared by HME technique. Critical formulation and process parameters such as polymer to drug ratio, milling screen size and milling speed were optimized using FFD.
Keywords: CQAs, FMEA, Heatmap, QbD, QTPP, Risk management
In the 21st century, “Risk Management Principles” are most commonly and effectively employed in various areas of business operations such as finance, safety, public health including biological and pharmaceutical research domain.1 The main objective of pharmaceutical development is to design a quality product and its manufacturing process to deliver consistently the intended performance of the drug product.2
In past decade, the traditional quality by testing (QbT) approach was used to ensure the quality of drug products by checking it against the regulatory specifications.3 Quality by design (QbD) is described in ICH Q8, Q9 and Q10 guidance documents. QbD principles promote systematic, scientific knowledge-based development for continuous improvement of pharmaceutical drug products. The product or process knowledge, risk assessment and its management, quality management system (QMS) along with the use of process analytical technology (PAT) are tools for successful product development.4 Now a days, pharmaceutical industries are more focusing to develop and integrate the quality systems within organizations practices; hence, quality risk management is a valuable and main component of an effective quality system.5
Pazopanib HCl is a potent tyrosine kinase inhibitor that inhibits angiogenesis through the VEGFR receptor and blocks tumor growth. This drug molecule has been used in the treatment of renal cell carcinoma and other malignancies. It is a poorly water soluble and highly permeable class II drug of Biopharmaceutics Classification System (BCS). The recommended maximum daily dose of Pazopanib HCl is up to 800 mg, administered as 4 tablets of 200 mg strength.6 The goal of this study was to identify, ranking and mitigation of process associated risksto the drug product critical quality attributes(CQAs) during the development of Pazopanib HCl HME extrudates using QbD elements and risk management tools.7
It is hypothesized that HME polymer physicochemical properties will have a major impact on the qualities of drug extrudates, since the HME polymer is major component. The aim of the present study was to optimize polymer to drug ratio to get maximum miscibility and obtain a Pazopanib HCl extrudates (PZP-Ex) with faster disintegration time and drug release. The critical process parameters (CPPs) such as milling screen size and milling speed during extrudate preparation and its impact on extrudates PSD, disintegration, and dissolution time were also studied.
Commonly used material such as Affinisol HPMCas HME polymer and poloxamer 188 as plasticizer were used in current study. The outcomes from this study may provide a way forward to other researchers in developing HME extrudates with better compressibility and desired attributes, such as faster disintegration time and dissolution.
Materials and Methods
Pazopanib HCl active pharmaceutical ingredient was gifted from Sun Pharmaceutical Industries Ltd., Gurgaon, India. The cellulosic polymer Affinisol HPMC HME 15LV was donated by Dupont (Nutrition and Biosciences, USA). Other ingredients such as Poloxamer 188 were obtained from BASF Corporation (Mumbai, India). All other chemicals and solvents used in this study were of analytical grade.
QbD elements and risk assessment procedure
The main component of product development by QbD are quality target product profile (QTPP), critical quality attributes (CQAs),design of experiments (DoE), risk assessment and control strategy.8 Control strategy is generally defined based on the scientific knowledge gained during product development and experimentation, which establish the relationship between formulation and process variables that must be controlled to develop high quality product.9,10 Quality risk assessment process is utilized for identification, analysis, evaluation and mitigation of risks related to intermediate in process quality assurance (IPQA) and during production check quality assurance.11 A general process flow for quality risk assessment (QRA) are described in figure1.
Preparation of Pazopanib HCl HME Extrudates (PZP-Ex)
The Pazopanib HCl extrudates (PZP-Ex) was manufactured as per below mentioned formula in Table 1. Initially Affinisol HPMC 15 LV polymer, poloxamer 188 and pazopanib HCl drug were mixed in rapid mixer granulator for 5 minutes at slow impeller speed. Then prepared premix was extruded using a hot melt extruder instrument. Hot melt extrusion were carried out using co-rotating twin-screw extruder (Thermo-scientific) fitted with various screws containing kneading elements at 30° and 60 ° orientation. The feed rate of the premix material and the screw speed were kept constant at 2 g/min and 100 rpm respectively. The barrel temperature was kept as (100/180/180/180/180 °C) for different trials. The extrudates were kept at room temperature prior to milling operation. A Quadro Comil (Fitzpatrick) was operated at defined speed with forward knives fitted with suitable size screen to mill the extrudates. The 16 # ASTM (1204 µm) to 20 # ASTM (850 µm) powder fraction was collected and further used for disintegration and dissolution testing.
In heat map, the level of risk (low/medium/high) is assigned through colour. Risk coding is based on prior scientific knowledge including experimental outcomes and justification is provided for assigned risk in each cell considering severity. The green colour has been coded for low risk, yellow for medium risk and red for high risk.12
Failure mode and effect analysis (FMEA)
FMEA is an exhaustive technique thatcan help us to determine the potential failure modes and its causes, potential failure effects, severity rank of the failure effect, occurrence rank of the failure, current detection mode and its failure rate. Hence, risk assigned in heat map and FMEA shall be mitigated based on the scientific rationale and through execution of experiments.13 Refer below tables for risk level, RPN range, colour criteria and scoring criteria for failure mode and risk analysis (Table 2, 3).
DoE approach was employed for systematic optimization of formulation and process variables during Pazopanib HCl extrudates (PZP-Ex) preparation. A full factorial design (FFD) was selected with three factors and two levels (low and high) as shown in Table 4. The polymer-to-drug ratio and milling speed are continuous variables and evaluated at the ratio of 0.5:1 to 2:1 and 1200 -2400 rpm respectively. Whereas, milling screen size is a categorical factor and studied the impact of 40G and 50G milling screens on granule characteristics, disintegration time and percent drug release.
QbD elements and risk assessment procedure
Based on the clinical and pharmacokinetic characteristics as well as the physicochemical characteristics requirements, QTPP and CQAs elements were defined to guide the development of Pazopanib HCl extrudates by HME technique (Table 5).
Preparation of pazopanib HCl HME Extrudates (PZP-Ex)
Pazopanib HCl extrudates were manufactured using hot melt extrusion technique, which are having unit operations such as sifting, mixing, extrusion and milling. Process map are described in below figure (figure 2).
Heat map is a systematic approach employed to understand and prioritize the risk elements. In order to evaluate the impact of each variable on DPCQAs, risk coding is done.
In heat map (Table 6), variable location, parameter location and drug product CQAs is listed in the header row. For each variable, the cell is filled with designated colour for the assigned risk and justification updated. The justification is provided based on the severity.
Failure mode and effect analysis (FMEA)
Failure mode and effects analysis is a structured and systematic process to identify potential possible failures in drug product. Initial FMEA for manufacturing process of pazopanib HCl extrudates are summarized in Table 7.
Based on the initial risk assessment for formulation components, experimental trials were conducted to evaluate the risk of processing steps. The experimental trial matrix and trial outcomes are depicted in table 8. All statistical analysis has been carried out using JMP Software (by SAS, version 16).
The particle size distribution of extrudates was carried out using a sieve shaker and percent retention on 40 mesh sieve size was calculated. The 16 # ASTM (1204 µm) to 20 # ASTM (850 µm) extrudates fraction was collected and further used for disintegration and dissolution testing. The disintegration time is also an important in-process material attribute and were carried out in water (n=6) at 37±20C with a sinker using disintegration test apparatus.A disintegration test of 16-20 # fraction extrudates material was carried out by holding the material in 40# stainless steel sinker. The percent drug release at 15 min time point in pH 6.8 phosphate buffer, 900 ml, type I (basket)was carried out and samples were analyzed using the validated HPLC method.
Statistical Outcomes of Experimental Trials
The DoE trials with responses were analyzed in JMP software (version 16.0) through “fit Model” approach. Based on the ANOVA and regression analysis, p value and R square value were observed from the “Actual predicted plot” for each response and recorded in table 9.
The sorted parameters (Table 10) and prediction profiler (Figure 3) indicated the impact of polymer-to-drug ratio level, milling screen and milling speed and its interaction terms on extrudates characteristics such as particle size distribution, disintegration time and dissolution. The sorted parameters for each term are summarized below:
Impact of polymer to drug ratio: Based on the sorted parameters and prediction profiler (figure 3) it can be concluded that polymer level has significant impact on studied responses and p value was found < 0.05. At optimum polymer to drug ratio (1:1), model predicted the % retention on 40#, DT and dissolution at 15 mins about 38.1%, 99 secs (1 min 39 secs) and 81.3% respectively.
Impact of milling screen size: Based on the p value from the sorted parameter results as shown above in the table 10, milling screen size has significant impact on all the studied responses. As per the prediction profiler, 40G screen size has obtained the finer granules in comparison to the 50G obtained granules.
Impact of milling speed: Based on the sorted parameters it can be concluded that milling speed has no significant impact on studied responses and p value was found > 0.05. However, from prediction profiler it was observed that% drug release decreased by decreasing the milling rpm. This might be due to slight less fine formation at lower milling speed.
Failure mode and effect analysis (FMEA)-Updated:
FMEA was updated based on DoE optimization studies results and risk was reduced to low from high or medium risk.
In 2007, Food and Drug Administration (FDA) published guidance on defining a target product profile (TPP). The TPP provides a written statement of the overall intent of drug development program.14 QTPP and CQAs were discussed initially to design and development of Pazopanib HCl extrudates (PZP-Ex). Process map was defined for preparation of extrudates using HME technique. Initially risk was identified for the formula and process variables using risk assessment tools i.e., heat map and FMEA. The assigned risk for each unit operations were mitigated for medium and high risks process steps based on the scientific knowledge gained during the product development and through experimental trials.
In the present study, full factorial design was used for the optimization of formula and process variables and total of 10 experimental trials were executed. The DoE trials with responses were analysed in JMP software (version 16.0) through “fit Model” approach. The p-value signifies whether the model is significant or not. The p value was observed less than 0.05 for all the studied response variables i.e., percent retention on 40 # ASTM sieve, disintegration time and percent drug release in 15 min hence model was significant.
The sorted parameters and p-value are summarized for the study's responses (Table 10). The % dissolution was directly proportional to the polymer level and this might be due to the fact that a higher polymer-to-drug ratio will convert the crystalline drug into an amorphous solid dispersion state. Milling screen size may impact on extrudates granulometry due to aperture size differences between 40G and 50G mesh. 40G screen has small apertures in comparison to 50G screen. Disintegration time is likely to be impacted by the ratio of coarse to fine granules, hence 40G obtained granules show faster disintegration and percent drug release.
In this study, the impact of input variables on studied responses for prepared Pazopanib HCl extrudates by HME technique were successfully optimized. The Pazopanib HCl API was embedded in Affinisol HPMC polymer along with using Poloxamer 188 as a plasticizer. The main goal to carry out risk assessment for Pazopanib HCl extrudates are to reduce the process variations, probability failure rate and manufacturing process defects, thereby obtaining robust unit operations and enhancing manufacturing efficiencies. The polymer-to-drug ratio has a significant impact on drug release and disintegration time of extrudates. The key elements of pharmaceutical QbD were included i.e., QTPP, process design and understanding, CQAs, prior scientific knowledge, risk elements (Heat map and FMEA), DoE screening, and control strategy. Based on the DoE screening study, critical process parameters such as polymer-to-drug ratio, milling screen size and milling speed were optimized and proposed as 2:1, 40G and 1800 rpm respectively.
Acknowledgment: Authors are thankful to BASF, India and Dupont for providing excipients as gift sample. The authors are also grateful to authors/publishers of referenced articles, books and journals.
Source of funding: Nil
Conflict of interest: We declare that we do not have any conflict of interest.
Gupta A conceptualized the research work. Also performed experimentation and analysis.
Dahima R performed the statistical data interpretation and contributed to the manuscript writing.
Abbreviations: ANOVA: analysis of variance; BCS: biopharmaceutics classification system; CPPs: critical process parameters; CQAs: critical quality attributes; DoE: design of experiments; DPCQA: during production check quality assurance; FDA: food and drug administration; FFD: full factorial design; FMEA: failure mode and effect analysis; HME: hot melt extrusion HPLC: high-performance liquid chromatography; ICH: international council for harmonization of technical requirements for pharmaceuticals for human use; IPQA: in-process quality assurance; NSAID: non-steroidal anti-inflammatory drug; PAT: process analytical technology; Pazopanib HCl Extrudates: PZP-Ex; QbD: Quality by design; QbT: quality by testing; QRA: quality risk assessment; QTPP: quality target product profile; TPP: target product profile
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