Analytical Quality by Design Based Systematic Development and Optimization of a Sensitive Bioanalytical Method for Estimation Cinacalcet HCl in Rabbit Serum.

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 R 2 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. Copyright:

INTRODUCTION

Cinacalcet HCl, is chemically known as N-[1-(R)-(-)-(1-naphthyl) ethyl]-3-[3-(trifluoromethyl)-phenyl]-1-amino propane hydrochloride.[1] It is primarily used to treat hyperparathyroidism (secondary) in individuals on hemo or peritoneal dialysis who have chronic kidney disease.[2] 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.[34] 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).[5] In patients with moderate and severe hepatic impairment, the half-life of cinacalcet HCl is increased by 33% and 70%, respectively.[6]

Figure 1

Chemical structure of cinacalcet HCl

Yang et al., 2012 established a HPLC-MS/MS approach to measure the cinacalcet HCl (human plasma).[7] 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.[8] 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.[9] It was observed that no straightforward method for estimating cinacalcet HCl in biological materials such as serum exists.[10] 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

Materials

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.

Statistical design

The Design Expert (Ver. 12, Stat-Ease, Minepolis, USA) was employed for screening with method optimization for evaluation of CPPs through various experimental runs.[11] 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.[12] 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.[1213] 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.[1415] 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

	Low level (−1)	High level (+1)
Independent variables
X1: Organic phase composition (percentage v/v)	30	70
X2: Flow rate (mL/min)	0.5	1.5
X3: Injection volume (μl)	10	30
Dependent variables (responses)
Y1: Peak area
Y2: Retention time
Y3: USP plate count

USP: United states pharmacopoeia

Table 2

Optimization of chromatographic method using 32 Box-Behnken design

Experimental runs	Organic phase composition (percentage V/V)	Flow rate (mL/min)	Injection volume (μL)	Peak area (cm2)	Rt (min)	USP plate count
1	30	1.5	20	107,458.00	5.873	1544
2	50	1.5	10	98,428.00	2.502	2605
3	50	1	20	236,574.00	4.124	3653
4	50	1	20	238,378.00	4.354	4896
5	30	1	30	162,902.00	5.106	12,840
6	50	0.5	10	509,141.00	3.964	13,918
7	50	1	20	229,029.00	3.823	3855
8	50	1.5	30	186,742.00	1.821	7058
9	50	1	20	230,263.00	4.014	4978
10	50	0.5	30	90,683.00	3.932	43,654
11	70	1	10	83,937.00	1.046	17,036
12	70	1.5	20	41,529.00	1.531	10,895
13	30	0.5	20	181,351.00	4.421	70,431
14	70	0.5	20	309,372.00	1.243	15,036
15	70	1	30	84,112.00	1.216	10,895
16	50	1	20	258,476.00	4.304	4498
17	30	1	10	187,654.00	5.104	2840

USP: United states pharmacopoeia

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.[1415] 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

Table 3

ANOVA and its significance value with respect to quadratic model post prediction and confirmation data

	Peak area cm2				Retention time (Minute)		USP plate count
Source	F		P		F	P	F	P
Model	7.03		0.0088		6.95	0.0091	5.51	0.0174
A-Mobile phase	0.6407		0.4498		54.56	0.0002	1.61	0.2449
B-Flow rate	19.04		0.0033		0.7661	0.4104	20.64	0.0027
C-injection volume	5.56		0.0505		0.0667	0.8036	2.04	0.1960
AB	3.32		0.1110		0.6179	0.4576	11.83	0.0108
AC	0.0549		0.8214		0.0129	0.9129	0.7353	0.4196
A²	10.78		0.0134		0.1921	0.6744	2.39	0.1657
B²	0.0627		0.8095		1.21	0.3079	8.04	0.0252
C²	0.8421		0.3893		1.63	0.2430	0.0155	0.9045
Lack of fit	45.79		0.0015*		2.85	0.0044*	572.08	0.0001*
Run 16 Response	Predicted Mean	Predicted Median	Observed Value	n	Sth Dev.	SE Pred.	95% PI low	95% PI high
Peak Area	238544.00	238544.00	258476.00	1	53186.96	58263.39	100772.97	376315.03
Retention Time	4.1238	4.1238	4.304	1	0.7403	0.811063	2.20594	6.04166
USP plate count	4376	4376	4498	1	9411.9	10310.2	-20003.8	28755.8

Significant levels, i.e., less than α value (0.05); *P. I: prediction interval, Std Dev: standard deviation, SE: standard error

Method validation

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.[16]

Precision

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.[16]

Accuracy

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.[16]

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.[1718]

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.

Figure 3

Standard chromatogram of cinacalcet HCl in mobile phase

Table 4

Linearity data of cinacalcet HCl

Concentration (ng/mL)	Peak area
100	75,940
200	93,734
500	55,923
1000	109,992
5000	992,229
10,000	1,916,834
20,000	3,907,652
50,000	10,249,141
100,000	19,408,238

HCl: Hydrochloride

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.

Figure 4

Calibration curve of cinacalcet HCl in mobile phase

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).

Figure 5

Calibration curve of cinacalcet HCl in rabbit serum

Figure 6

Standard chromatogram of cinacalcet HCl in rabbit serum

RESULTS AND DISCUSSION

Precision Study

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.[16]

System precision

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

Sample number	RT	Peak area	Mean±SD	Percentage RSD
1	4.3	2,215,528	2,228,654±12,813.04	0.574
2	4.3	2,232,857
3	4.3	2,227,809
4	4.3	2,215,077
5	4.3	2,248,001

RSD: Relative standard deviation, RT: Retention time, SD: Standard deviation, HCl: Hydrochloride

Method precision

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.

Table 6

Method precision data of cinacalcet HCl

Sample number	RT	Peak area	Mean±SD	Percentage RSD
1	4.3	2,216,834	2,168,690±22,524.4777	1.03
2	4.3	2,217,531
3	4.3	2,246,522
4	4.3	2,253,766
5	4.3	2,268,303
6	4.3	2,264,185

RSD: Relative standard deviation, RT: Retention time, SD: Standard deviation, HCl: Hydrochloride

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.

Table 7

Accuracy data of cinacalcet HCl

Sample number	Percentage of concentration level	RT	Peak area	Mean±SD	Percentage recovery
1	80	4.3	2,575,207	2,559,503±13,453.76	99.59
	80	4.3	2,568,607
	80	4.3	2,534,696
2	100	4.3	2,875,207	2,842,392±123,547.98	100
	100	4.3	2,837,280
	100	4.3	2,814,689
3	120	4.3	2,914,294	2,958,927±139,876.57	90.16
	120	4.3	2,963,542
	120	4.3	2,998,947

RSD: Relative standard deviation, RT: Retention time, SD: Standard deviation, HCl: Hydrochloride

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

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.

The drug was subjected to various stress conditions as per the recommendations of ICH guidelines ICHQ2R1.[1718] 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

Stress condition	RT	Initial area	Percentage initial degradation	Final area	Percentage final degradation
UV light	4.3	1,783,139	23.02	1,816,834	0.802
Heat (°C)	4.3	1,421,060	38.65	1,902,135	0.76
Acid hydrolysis	4.3	1,339,835	42.16	1,868,974	0.41
Alkaline hydrolysis	4.3	2,217,907	4.25	1,856,426	0.43
Oxidation	4.3	2,486,887	7.35	1,878,497	0.43

RT: Retention time, UV: Ultraviolet, HCl: Hydrochloride

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

Nil.

Conflicts of interest

There are no conflicts of interest.