|Year : 2021 | Volume
| Issue : 4 | Page : 360-366
Analytical quality by design based systematic development and optimization of a sensitive bioanalytical method for estimation cinacalcet HCl in rabbit serum
Sudhanshu Bhusan Routray1, Chinam Niranjan Patra1, Suryakanta Swain2, Bikash Ranjan Jena3
1 Department of Pharmaceutics, Roland Institute of Pharmaceutical Sciences, Affiliated to Biju Patnaik University of Technology, Rourkela, Odisha, India
2 Department of Pharmacy, School of Health Sciences, The Assam Kaziranga University, Koraikhowa, Jorhat, Assam, India
3 Department of Pharmacy, School of Pharmacy and Life Sciences, Centurion University of Technology and Management, Bhubaneswar, Odisha, India
|Date of Submission||05-Oct-2021|
|Date of Decision||20-Nov-2021|
|Date of Acceptance||24-Nov-2021|
|Date of Web Publication||04-Mar-2022|
Dr. Chinam Niranjan Patra
Department of Pharmaceutics, Roland Institute of Pharmaceutical Sciences, Affiliated to Biju Patnaik University of Technology, Rourkela - 760 010, Odisha
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Context: There is no straightforward method for estimating cinacalcet HCl in biological materials such as serum exists. As a result, the goal of this research is to develop a simple quality by design (QbD) enabled reverse phase-Ultra-Fast Liquid Chromatography (RP-UFLC) model for analyzing cinacalcet HCl in serum. Aim: The current study envisages the development and validation of an isocratic simple, precise, and rapid QbD enabled RP-UFLC method for the quantification of cinacalcet HCl in both solution form and blood samples. Subjects and Methods: The optimum conditions were outlined, selecting three influential factors (CMPs) i.e., mobile phase composition, flow rate, and injection volume. Systematic optimization was performed by 32-Box Benkhen experimental design using response surface methodology. The selected variables are further assessed for observed responses Critical Analytical attributes, i.e., peak area, retention time (Rt), USP Plate count. The optimized method used a chromatographic C18 (100 mm × 4.6 mm i.d) column with mobile phase (acetonitrile and Tetrabutyl Ammonium Hydrogen Sulphate [TBSH]) in the ratio of 1:1, with a flow rate of 1 mL/min with UV at λmax 223 nm. The developed method was found to be specific for cinacalcet HCl, enduring no interference of peaks with an overall analytical Rt of 4.3 min. Results: The Accuracy reported as % recovery was found to be 96.83%–101.32% and 95.18%–102.49% respectively. Inter-day precision (reproducibility) and intra-day precision (repeatability) were found to be 0.22–1.19 standard deviation (SD) and 0.14–2.12 SD respectively. The calibration curve was found to be linear with a regression equation Y = 195.8x + 21852, with R2 0.999 over a concentration range from 100 to 100,000 ng/mL. Conclusion: The required detection and quantitation limits (Limit of Detection and Limit of Quantitation) values were obtained within the acceptance limit based on S/N ratio which indicates the method was sensitive and rapidity of the method. Further, the developed QbD enabled UFLC method was approved and effectively entreated the blood tests to study the pharmacokinetic parameters which indicate a robust, accurate cost-effective method intended for quality control tool for routine systematic analysis in research labs.
Keywords: Cinacalcet HCl, design of experiment, pharmacokinetic study, serum samples, ultra-fast liquid chromatography, validation
|How to cite this article:|
Routray SB, Patra CN, Swain S, Jena BR. Analytical quality by design based systematic development and optimization of a sensitive bioanalytical method for estimation cinacalcet HCl in rabbit serum. J Pharm Bioall Sci 2021;13:360-6
|How to cite this URL:|
Routray SB, Patra CN, Swain S, Jena BR. Analytical quality by design based systematic development and optimization of a sensitive bioanalytical method for estimation cinacalcet HCl in rabbit serum. J Pharm Bioall Sci [serial online] 2021 [cited 2022 Aug 8];13:360-6. Available from: https://www.jpbsonline.org/text.asp?2021/13/4/360/339090
| Introduction|| |
Cinacalcet HCl, is chemically known as N-[1-(R)-(-)-(1-naphthyl) ethyl]-3-[3-(trifluoromethyl)-phenyl]-1-amino propane hydrochloride. It is primarily used to treat hyperparathyroidism (secondary) in individuals on hemo or peritoneal dialysis who have chronic kidney disease. [Figure 1] shows the chemical structure of cinacalcet HCl. It is also used to treat hypercalcemia in those who have parathyroid cancer. The main regulator of parathyroid hormone (PTH) secretion is the parathyroid gland's primary cell (PTH). Cinacalcet HCl reduces hormone levels directly by raising the sensitivity of calcium detecting receptors to extracellular calcium activation, which inhibits PTH release., The fall in PTH is accompanied by a decrease in serum calcium levels. It is widely distributed, and hepatically metabolized. It is plasma protein bound (93%–97%) with a long elimination half-life (30–40 h). In patients with moderate and severe hepatic impairment, the half-life of cinacalcet HCl is increased by 33% and 70%, respectively.
Yang et al., 2012 established a HPLC-MS/MS approach to measure the cinacalcet HCl (human plasma). Thomson et al., 2018 used reverse phase high performance liquid chromatography (HPLC) to investigate the stability of cinacalcet oral suspension, utilizing mobile phase A of deionized water with 0.1% trifluoroacetic acid (TFA) and mobile Phase B of acetonitrile with 0.1% TFA. Reddy et al., 2018 developed a GCMS method for determining the concentration of 3-(Trifluoromethyl)-cinnamaldehyde in the cinacalcet HCl. Darwish et al. (2012) developed a spectrophotometric approach for determining cinacalcet HCl in tablets. It was observed that no straightforward method for estimating cinacalcet HCl in biological materials such as serum exists. As a result, the goal of this research is to develop a simple quality by design (QbD) enabled reverse phase-Ultra-Fast Liquid Chromatography (RP-UFLC) model for analyzing cinacalcet HCl in serum. In addition to this, the drug has been thoroughly recognized by reverse phase HPLC methods for quantifying drug samples bio-analytically. A simple, sensitive, precise, accurate, specific, robust RP-UFLC method was developed by QbD approach to estimate bulk drugs and formulations.
| Subjects and Methods|| |
RACHEM labs Ltd, Hyderabad, provided Cinacalcet HCl as a free sample. E. Merck Private Limited in Mumbai supplied acetonitrile and TBSH. All of the other solvents were of analytical Reagent grade.
Equipment and chromatographic conditions
Cinacalcet HCl was analyzed using a simple, rapid, and accurate reverse phase ultra-fast liquid chromatographic technique. At a flow rate of 1 mL/min, chromatography was carried out on a 250 mm 4.6 mm i. d., 5 m particle, C18 column with a 50:50 (v/v) acetonitrile: Tetrabutyl Ammonium Hydrogen Sulphate (TBHS-10 millimolar) mobile phase and detection at 223 nm using a Photo Diode Array Detector.
The Design Expert (Ver. 12, Stat-Ease, Minepolis, USA) was employed for screening with method optimization for evaluation of CPPs through various experimental runs. The calculations for the analysis of the regression equation and its ANOVA were done by Microsoft Excel 2019 (Microsoft, USA).
Standard curve of cinacalcet HCl in mobile phase
Cinacalcet HCl, 10 mg, was precisely weighed and put to a 10 mL volumetric flask. To make a 1000 g/mL standard stock solution, Cinacalcet HCl was dissolved in the mobile phase. Cinacalcet HCl calibration standards were created at nine levels by properly mixing and diluting with mobile phase to achieve a concentration range of 100 ng/mL-100,000 ng/mL The calibration graph is drawn by plotting peak regions against corresponding concentrations.
Method development using Box–Behnken design
QbD usually delivers assistance to develop robust based methods with pertinency in drug substance analysis, degradation products, and other metabolites. Box–Behnken experimental design (BBD) was employed to compute independent variables (CMPs) and their capable effects upon, the three distinct critical analytical attributes (CAAs) like peak area, retention time (Rt), and USP plate count., The focal, interactions, and quadratic effects upon the influential critical variables such as mobile phase ratio, flow rate, and injection volume upon the dependent variables like peak area (Y1), Rt (Y2), and USP plate count (Y3), are analyzed with total 17 experimental runs., The Graphical and statistical chromatographic BBD includes basically the qualitative polynomial equations, 2-D, 3-D counter plot illustrations under the principle of Response surface methodology (RSM). It is explicit that the utilization of this 32 Box–Behnken design with RSM is an adaptable practice to reduce the total experimental runs to obtain sustainable, robust analysis requisite for the method development. The present article fruitfully reveals the analytical QbD (AQbD) approach's efficiency in enhancing the RP-UFLC bioanalytical method for the analysis with an improved understanding of the critical factor-response relationship for augmenting the method performance. As DoE is widely accepted as a scientifically-sound and legitimate paradigm, it possesses effective implementation strategies.
The trail runs aids in the construct of an arithmetical model involving the comprehensive analysis of critical factors. Similarly, the 17 experimental runs with three critical factors and its associated responses 32-BBD experimental design are enlisted in [Table 1]. The design matrix of all the encoded critical factors (independent variables i.e., % organic phase and flow rate, injection volume) and its associated observed responses (CAAs) are enlisted in [Table 2].
|Table 1: Design matrix as per Box-Benkhen design for optimization of Bioanalytical method|
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|Table 2: Optimization of chromatographic method using 32 Box-Behnken design|
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After interpretation of BBD, the calculated responses (Y1), (Y2), and (Y3) of dependent variables (CAAs) are represented as below equations Eq.(1), (2) (3) respectively.
Peak Area (Y1) =+2.385E + 05-15051.87A-82048.75B-44340.13C-48487.50AB + 62310.75AC
+1.267E + 05BC-85106.88A2+6490.37B2-23785.87C2 (1)
Rt (Y2) =+4.12-1.93A-0.2291B-00.0676C-0.2910AB + 0.0420AC-0.1622BC-0.3968A2-0.4600B2-0.6090C2 (2)
USP Plate count (Y3) =+4376.00-42240.13A-15117.13B + 4756.00C + 16186.50AB-4035.2 AC-6320.75BC + 7097.25A2+13003.25B2-570.50C2 (3)
Optimization of chromatographic method using response surface methodology
After selecting optimal chromatographic conditions, the Box–Behnken Design (BBD) with RSM, was executed through principles of ANOVA for method performance within the specified design space., The multivariate linear regression analysis performed the data optimization analysis to screen out the tentative responses 2-D counter and 3-D response surface plots. The experimental results or solutions from graphical optimization (experimental run 16) indicate that Organic phase composition (50% V/V), flow rate (1 mL/min) with injection volume (20 μl) are the most influential variables for method optimization affecting the CAAs, which explicate final obtained responses, i.e., Peak Area (258476.0050 cm2), Rt 4.304, with USP plate count 4498. The influence and interactions of critical factors i.e., % mobile phase, flow rate, and injection volume upon the obtained responses, are depicted in [Figure 2]. After optimization of the method the results of the (P < 0.05), f-value and lack of fit statistics with post prediction, confirmation data through principles of ANOVA using Box–Behnken design are demonstrated in [Table 3].
|Figure 2: Schematic diagram indicating Schematic diagram indicating 2-D surface contour plot analysis of peak area (Y1) response (a), Retention time (Y2) response (b), USP plate count (Y3) (c); 3-D surface contour plot analysis of peak area (Y1) response (d), Retention time (Y2) response (e), USP plate count (Y3) response|
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|Table 3: ANOVA and its significance value with respect to quadratic model post prediction and confirmation data|
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Analytical method validation proves that an analytical method that affords analytical results is acceptable for the envisioned practice. As per International; Conference on Harmonization (ICH) recommended guidelines, and the drug was subjected to various validation parameters like linearity, precision (system, intra and interday), accuracy, limit of detection (LOD), and limit of quantitation (LOQ), etc.
The precision of assay procedure was proven by performing six independent assays on a sample of cinacalcet HCl at 10 μg/mL and from the 6 samples, we selected one sample for system precision.
Spiking analysis was used to conduct the recovery research. The accuracy of the assay method was tested at three concentration levels (80, 100, and 120%). At each concentration level, triplicate preparation was done during the study.
Forced degradation study
The results of a forced degradation (FD) test of cinacalcet HCl were an indication of the procedure's stability. UV radiation (conducted as specified in ICH Q1B), heat (80°C), acid hydrolysis (0.1N HCl), alkaline hydrolysis (0.1N NaOH), and oxidation were all used in the degradation investigation (3% H2O2). All of the degradation tests lasted 30 min.,
Standard curve of cinacalcet HCl in mobile phase
The cinacalcet HCl obeyed linearity in the mobile phase in the concentration range of 100-100,000 ng/mL with regression equation Y = 195.8x + 25309 and high correlation coefficient of 0.999 [Figure 3]. Similarly, the representative data of linearity studies are enlisted in [Table 4].
Ultra-fast liquid chromatography assay of cinacalcet HCl
For the determination of cinacalcet HCl, UFLC with UV detection was used as a simple, fast, and effective separation approach. The best results were obtained using a 1:1 (v/v) acetonitrile:Tetrabutyl Ammonium Hydrogen Sulfate (TBHS-10 millimolar) mixture, which allowed for optimal drug separation using a C18 Analytical column at 1.0 ml/min flow rate. Cinacalcet HCl was eluted with a 4.3-min Rt. The selectivity of the assay was further demonstrated by its capacity to extract the drug from serum samples without interference from any endogenous material, with good separation and clarity of their peaks, using the chromatographic parameters indicated above. This is clearly indicated from [Figure 4]. The Rt of drug determined as 4.3 min.
Preparation of standard curve of cinacalcet HCl in serum
In an Eppendorf tube, blood (2 mL) was collected from the ear vein of an albino rabbit weighing 1.5–2 kg. To aid blood coagulation, these blood samples were stored for 30 min. In a cooling centrifuge (4°C), it was centrifuged for 20 min at 5000 rpm. For the investigation, approximately 1–1.5 mL of serum was isolated. The serum was then divided into 9 microcentrifuge tubes, each containing 100 μL of serum. Previously, the medication was diluted with acetonitrile to achieve various concentrations (100, 200, 500, 1000, 5000, 10,000, 20,000, 50,000, 100,000 ng/mL). Each concentration received 100 μL of drug solution, which was vortexed for 10 min. After that, each sample received 1 mL of ethyl acetate and was vortexed for 10 min. Then, for the next ten min, it was kept undisturbed. In a water bath, 0.5 mL of the supernatant layer was collected and dried at 70 ± 5°C for complete evaporation of ethyl acetate. 1 mL of mobile phase was used to rehydrate the dried samples. Without the medication solution, a blank serum sample was also created. A total of 20 μL of solution were injected into the UFLC. The drug concentration was put on the x-axis and the peak area was plotted on the y-axis in a standard graph [Figure 5]. The chromatogram of cinacalcet HCl is shown in [Figure 6] (Approval no 88 by IAEC of RIPS with Regd no 926/PO/ac/06/CPCSEA).
| Results and Discussion|| |
The system is repeatedly linked to numerous checks of a sample; the precision of a procedure is the level of assurance between individual test outputs.
The precision of the system ensures that the analytical system is in good operating status. The acceptance Criteria after 6 injections of standard preparation, the % relative SD (RSD) of the area response for cinacalcet HCl peak should be Neural machine translation (NMT) 2.0%. Data interpretation indicates that the (% RSD) as shown in the table indicates that the area response is constant [Table 5].
|Table 5: Standard injections of cinacalcet HCl peak response by system precision test|
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The precision of a method indicates whether or not a system produces accurate findings for a specific substance. The required acceptance criteria: NMT 2.0% should be the percentage RSD determined from 6 determinations. Similarly, the systematic procedure appears to be precise based on the provided data in [Table 6].
The accuracy of an analytical method is the closeness of test results performed. The recovery studies are performed (80%–120%), and the results are in the acceptance range, i.e., 98%–102% as demonstrated in [Table 7].
Limit of detection and limit of quantitation
The LOD and LOQ of the current studies were evaluated from the baseline noise of Cinacalcet HCl through findings of calculated signals of samples with known concentrations of analyte with that of the blank by (signal-to-noise) S/N ratio 3:1 (LOD) and 10:1 (LOQ) as per ICHQ2B guidelines. The calculated values of LOD and LOQ were obtained as 3193.66 and 9677.77 ng/mL respectively obtained from slope of calibration curve.
Specificity is the capability to evaluate the analyte explicitly in the occurrence of components, i.e., degradants, matrix, which may be anticipated to be present. The results established that there is no interference was detected from the mixture of excipients.
Forced degradation study
The drug was subjected to various stress conditions as per the recommendations of ICH guidelines ICHQ2R1., The cinacalcet HCl was tested under stress at a concentration of 10 μg/mL. Acidic hydrolysis, alkaline hydrolysis, oxidative degradation, thermal degradation, and UV radiation are all applied to the drug. Cinacalcet HCl has consistently showed <1%degradation, indicating that the drug was stable. The representative data of % degradation from acid, base, thermal and photolytic studies are demonstrated in [Table 8].
|Table 8: Forced degradation data of cinacalcet HCl in analytical ultra-fast liquid chromatography method|
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| Conclusion|| |
An accurate, precise, sensitive, stability-indicating QbD based RP-UFLC method has been developed and validated to estimate Cinacalcet HCl in bulk drugs and its pharmaceutical formulations with the aid of Box-Behnken experimental design. By implementing the DoE paradigm, Box–Behnken statistical design can evaluate the independent variables (CMPs) concurrently with adding up common interactions between the critical factors to optimize experimental conditions. It is explicit that the utilization of this Box–Behnken design with RSM is an adaptable practice to reduce the total experimental runs to obtain sustainable, robust analysis requisite for the method development. The present article fruitfully reveals the AQbD approach's efficiency in enhancing the RP-UFLC bioanalytical method for the analysis with an improved understanding of the critical factor-response relationship for augmenting the method performance. As DoE is widely accepted as a scientifically-sound and legitimate paradigm, it possesses effective implementation strategies. The overall FD studies practicing the AQbD approach for estimating Cinacalcet HCl in rabbit serum ensured a systematic, holistic method that is precise, robust, and stability-indicating. The technique also found practical application to the quality control labs for routine analysis. Optimizing the RP-UFLC strategy for Cinacalcet HCl can create the highest intense data, afford regulatory flexibility, and boost efficiency within a short time as per ICH Q8 (R2) and FDA perspectives. The optimized conditions by the anticipated method's AQbD established that the proposed study was cost-effective, more robust, and stable signifying. Therefore, the developed method can be implemented for the routine analysis of Cinacalcet HCl in bulk and pharmaceutical formulations.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7], [Table 8]