Optimization and Validation for Simultaneous Estimation of Citicoline and Piracetam in bulk and tablet formulations using RP-HPLC method: Analytical quality by design approach

 

Ashu Mittal¹*, Shikha Parmar², Sadaf Jamal Gilani³, Syed Sarim Imam³, Mohamad Taleuzzaman³

¹KIET School of Pharmacy, Ghaziabad 201206, Uttar Pradesh, India

²H.R. Institute of Pharmacy, Ghaziabad-201206, Uttar Pradesh, India

³Glocal School of Pharmacy, Glocal University, Saharanpur-247121, Uttar Pradesh, India

*Corresponding Author E-mail: ashumittal1973@gmail.com

The present work describes a reversed phase high performance liquid chromatographic method for simultaneous estimation of Citicoline (CIT) and Piracetam (PIR) in bulk as well as tablet dosage forms. The estimation was carried out on a C₁₈ column using mobile mixture of acetonitrile and 10 mM disodium hydrogen phosphate buffer in the ratio of 10:90 (v/v) as a mobile phase. All analytes were detected by measuring the absorbance at 205 nm with flow rate of 1.0 ml/min. The total run time of the study was 16 min. for complete separation of both drugs. The elution was achieved at the retention times of 3.79 and 13.08 min for Citicoline, and Piracetam, respectively. The method was validated for accuracy, precision, linearity, specificity and sensitivity as per ICH norms. The calibration curves were found linear over the concentration ranges of 4- 40μg/mL for Citicoline and 5- 50μg/mL for Piracetam. From the validation study it was found that the method is specific, rapid, accurate and precise.

 

 

 

INTRODUCTION:

Citicoline (CIT- Fig. 1a), a psychostimulant, is chemicallycytidine-5’-{trihydrogendiphosphate} p’-[2-{trimethylammonio}ethyl] ester inner salt while, It plays an important role in cellular metabolism and readily absorbed in the gastrointestinal tract and widely distributed throughout the body, crosses the central nervous system (CNS). It activates biosynthesis of structural phospholipids, increases brain metabolism, and acts on the levels of different neurotransmitters.

 

It is an intermediate in the generation of phosphatidylcholine from choline [1-4]. Piracetam (PIR- Fig. 1b) is a nootropic drug in the racetams group, with chemicalname 2-oxo-1-pyrrolidine acetamide. It improves the function of the neurotransmitter acetylcholine via muscarinic cholinergic (ACh) receptors, which are implicated in memory processes. It increases cell membrane permeability and found to increase oxygen consumption in the brain. They exert their action by activating the biosynthesis of structural phospholipids in neuronal membrane. Both drugs are psychotherapeutic agents, used as psychostimulant, nootropic and neurotonics. These drugs increase cerebral metabolism and level of various neurotransmitters, including acetylcholine and dopamine, exerting its action by activating the biosynthesis of structural phospholipids in neuronal membrane. These drugs increase the blood flow and oxygen consumption in brain [5-8]. Literature survey revealed that there are several methods such as Spectrophotometric [9, 10]. HPLC [11-15] LC-MS/Ms [16] reported for the analysis of CIT and PIR either as an individual drug in pure, pharmaceutical forms or in combination with impurities as well as in biological fluids. But, there is no HPLC method reported for quantitative estimation of CIT and PIR in bulk as well tablet dosage form using analytical quality by design approach. Recently, holistic use of quality by design (QbD) approach in analytical method development, termed as analytical QbD (AQbD), has become quite popular in practice [17]. Based on the principles of design of experiments, AQbD helps in thorough understanding of the associated interaction(s) among the method variables [18] It involves optimization using experimental designs, modelization and optimum search through response surface methodology to embark upon the analytical design space, and postulating control strategy for continuous improvement [19]. The present work aims to provide a new method to develop mobile phase composition using the most relevant analytical quality by design methodology. The rational practice of design methodology in method development helps to establish a robust mobile phase composition. There are number of literature already reports the utility of experimental design methodology in LC analytical methods, such as the application of Box–Behnken design (BBD) for the optimization of mobile phase composition for drugs like amoxicillin trihydrate [20], lenalidomide [21], and risperidone [22] and combination drug Amlodipine and Valsartan [23] This validation study is defined by the process by which it is established, in laboratory by the performance characteristics of the method, which should meet the requirements for the intended analytical application [24]  This work describes the validation parameters stated by the ICH guidelines [25] to achieve an analytical method with acceptable characteristics of suitability, reliability and feasibility. Attempts were, therefore, made to develop a straight, rapid, sensitive, robust, effective and economic stability-indicating HPLC method employing AQbD approach for estimation of CIT and PIR in bulk drug and pharmaceutical formulations.

 

Figure 1(a-b): Chemical Srtructure of Citicoline and Piracetam

 

MATERIAL AND METHODS:

Chemicals and Reagents:

Citicoline and Piracetam pure drugs receved as gift sample from Olcare  lab, Wadhwan Gujrat and Akums Haridwar, respectively. LC grade acetonitrile, methanol (Merck, Darmstadt, Germany) and ultra distilled water were used for preparing mobile phases solutions. Phosphoric acid and sodium hydroxide used as buffer component were obtained from sigma. All chemicals and solvents were analytical reagent grade. Marketed tablets of CIT and PIR were purchased from pharmacy shop (NUTAM PLUS Piracetam 800 mg, Citicoline 500 mg)

 

Instrumentation:

The HPLC system used was Shimadzu LC-20AT pump, Rheodyne injector (20μL), SPD-20A UV detector and the system was controlled through Spinchrom CFR software (version 2.1.4.93). Analytical column used for this method was Gracesmart C18 (250 mm x 4.6 mm, 5μm). The mobile phase was vacuum-filtered through 0.2 μmSupor 200 membrane and degassed by ultrasonication for 10 min before use. The mobile phase flow rate was set at 1.0 ml/ min. All the standards and assay samples were filtered through 0.45 μmSupor 200 membrane before injection. After equilibration of column with the mobile phase indicated by a stable baseline, aliquots of sample (20 μL) were injected and the total run time was kept 10 min. The absorbances of the eluents were monitored at 205 nm a detection sensitivity of 0.1000 aufs.

 

Optimization

Based on the factor screening studies, selection of the optimized method performance was embarked upon for further method optimization. A box behnken design (BBD) was employed for optimization of the chosen, namely flow rate (X₁) and pH (X₂), and methanol concentration (X₃) studied at three different equidistant levels, that is, low (-1), intermediate (0) and high (+1) levels. Table-1 summarizes a design matrix account of 17 experimental runs as per BBD including a total of five centre point experimental runs. A standard concentration of sample was used for all the experimental runs, which were analyzed, namely peak area and retention time of CIT and PIR respectively. The search for optimum chromatographic condition was carried out to obtain efficient method performance by numerical optimization using the desirability function by ‘trading-off’ of various acceptance criteria, that is, minimization of retention time, and maximization of peak area. On the heels of numerical optimization, the graphical optimization was also carried out to embark upon the optimal analytical design space region depicting the location of the optimized solution.

 

Table 1: Box Behnken Design Matrix for Screening of Method Variables and Process Parameters with their actual and predicted value

	A	B	C	X1		X2		X3		X4
Run	ml/min)		(%)	Actual Value	Predicted value	Actual Value	Predicted value	Actual Value	Predicted value	Actual Value	Predicted value
1	1	3	40	3.57	3.63	585654	5851765	11.81	11.72	725467	718167
2	1.2	3	55	4.11	4.07	423121	4249234	12.88	12.83	556776	554665
3	1.2	3.5	40	4.51	4.53	380652	3804652	13.43	13.40	503453	509556
4	1	3	40	3.72	3.63	585440	5851532	11.65	11.72	724123	718128
5	1	3.5	25	3.07	3.02	398765	3979457	11.13	11.17	524521	530145
6	1	3.5	55	3.58	3.60	456543	4550822	12.38	12.47	607654	603823
7	0.8	3.5	40	3.12	3.14	449768	4525134	10.51	10.42	587656	579945
8	1	2.5	55	2.83	2.88	491543	4924451	10.65	10.61	623456	617921
9	1	3	40	3.61	3.63	584276	5851098	11.71	11.72	704576	718145
10	1.2	3	25	3.51	3.54	461355	4625065	11.43	11.43	576433	564843
11	1.2	2.5	40	3.38	3.37	535143	5324067	10.68	10.77	645461	653333
12	0.8	3	55	3.21	3.18	478327	4772934	10.51	10.52	567432	579188
13	0.8	3	25	2.61	2.65	391243	3894131	8.43	8.48	325643	327834
14	0.8	2.5	40	2.98	2.96	439178	4394875	8.45	8.49	376543	370563
15	1	2.5	25	2.42	2.40	497865	4994237	8.55	8.47	446532	450456

A:- flow rate; B:- pH; C:- Methanol %; X₁:-Rt of CIT in min; X₂:- Area of CIT; X₃:- Rt of PIR in min; X₄:- Area of PIR.

 

Standards Preparation:

The standard stock solutions of CIT and PIR were prepared by dissolving 40 mg of CIT and 50 mg of PIR in 100 mL of HPLC grade water to get stock solution. From these resulting solutions, further serial dilutions were prepared in mobile phase for constructing calibration curves.

 

Sample Solutions Preparation:

For sample solution preparation, 20 tablets of CT and PM (NUTAM PLUS; Piracetam 800 mg, Citicoline 500 mg) were weighed and crushed to obtain fine powder. An accurately weighed tablet powder equivalent to about 32 mg of PIR and 20mg of CIT were transferred to the 25 mL volumetric flask. 10 mL of HPLC grade water was added and sonicated for 10 min. The volume was made up to the mark to give stock solution. The sample was filtered through membrane filter to remove the impurities. From the above solution 1 mL sample was transferred into 10 mL volumetric flask and made up to mark with mobile phase. Similarly from the standard stock solution, 1mL sample was transferred to 10 mL volumetric flask and diluted with mobile phase to get desired concentration for analysis.

 

Method Validation:

Method validation was carried in accordance to the International Conference on Harmonization (ICH) guidelines for validation of analytical procedures. The assay was validated with respect to linearity, precision, accuracy, sensitivity and robustness.

 

Accuracy/Recovery:

Accuracy of the developed method was confirmed by performing a recovery study as per ICH norms at five different concentration levels (80%, 90%, 100%, 110%, 120%) by replicate analysis (n= 5). Standard drugs were added to a pre-analyzed sample solution and chromatograms were recorded. The percent of standard drugs recovered were calculated.

 

Precision:

The precision of the method was determined by repeatability, intermediate precision (intra-day, inter-day) and was expressed as % relative standard deviation (%R.S.D.). Intra- day precision was determined by performing analysis of triplicate injections of three different concentrations of combination on the same day at different time intervals and on three different days for Inter-day precision.

 

Linearity:

Calibration curves were obtained from injecting the six sets of nine serial dilutions of mixed standard stock solution of CIT and PIR. The linearity was determined for CIT and PIR separately by plotting a calibration graph of peak area of drug against their respective concentration.

Sensitivity:

Sensitivity of the method was determined by means of the detection limit (LOD) and quantification limit (LOQ).Calculations for LOD and LOQ were based on the standard deviation of the Y-intercepts of the six calibration curves (σ) and the average slope of the six calibration curve (S), using the equation LOD= 3.3×σ/S and the equation LOQ= 10×σ/S.

 

Robustness:

Robustness of the method was evaluated by the analysis of solution under varying experimental conditions such as pH of the mobile phase and flow rate. The flow rate was varied ±0.02 mL/ in (2%) and pH of the mobile phase was changed ±0.12 units (2%). Their effects on the retention time, and peak area were studied.

 

RESULT AND DISCUSSION:

Optimization data analysis and response surface maping:

A somewhat twisted 3D-response surface plot was observed for CAA, that is, peak area, as shown in Figure (2a-f). The Figure (2a-c) depicted the effect of flow rate, methanol % and pH on retention time of CIT. the increase in flow rate leads to increase in the Rt of CIT gradually, whereas pH does not have the significant effect on the Rt. The methanol concentration shows that as the concentration increases the retention time also increase up to intermediate level. After that the retention time decreases as concentration increases. In Figure (2d-f) shows the effect of independent factors on area of CIT. the dome shaped image shows as the methanol concentration increases the area of CIT also increases. The increase in area up to intermediate level of methanol after that it decreases. The increase in pH level decreases the area of CIT. The flow rate having significant effect on the area of CIT. The search for optimum solution was carried out by numerical optimization by ‘trading off’ various CAAs to attain the desired goals, that is, maximization of peak area and theoretical plates, and minimization of retention time and peak tailing to obtain desirability function close to 1. The optimized solution showed mobile phase composition containing mixture of acetonitrile:10mM phosphate buffer (90:10) and flow rate of 1 mL/min with desirability of 1.0. The optimization data analysis was carried out by selecting the second-order quadratic polynomial model for detecting the main and interaction effects both. Table 2 illustrates the coefficients of the second-order quadratic polynomial model along with ANOVA parameters. The coefficient analysis was performed by analyzing the different model. Figure 4 quantitatively compared the resultant experimental values of the responses with that of the predicted values. The graphical optimization also yielded the optimum solution demarcated within the analytical design space.

 

Figure 2(a-f): 3D-response surface plots showing the influence of independent variables on peak area and retention time for piracetam

 

Figure 3(a-f): 3D-response surface plots showing the influence of independent variables on peak area and retention time for Citicoline

 

Figure 4. Linear correlation plots between actual and predicted values for various responses.

Table 2: Summary of results of regression analysis for all responses

 

Validation Parameter:

Linearity:

The range of a method may be defined as the interval between upper and lower limits of quantization to which the method produces test results that are proportional to the analyte concentration. The calibration plot was linear over the concentration range investigated as shown in Table 3. The regression equation for PIR and CIT were found to be Y = 79340X – 26409 and Y= 57622X + 51242, respectively. The correlation coefficients for both the drugs were found to be closer to unity. There were no significant differences between the slopes of calibration plots constructed on different days.

 

Accuracy:

The recovery of the method was 99.39–100.6 % for CIT and 99.49-101.29 for PIR, respectively and after spiking a previously analyzed test solution with additional drug standard. The values of recovery and RSD are shown in the Table-4 and 5. The lower RSD value indicates the proposed method is accurate.

 

Table 3: Statistical parameters of developed method

 

Table 4: Data for % recovery of Citicoline

 

Table 5: Data for % recovery of Piracetam

 

Precision:

The precision of both the drugs were assessed by assay at different time intervals in the same day (intra-day precision) and by repetition for three different day’s inter-day precision as per ICH guidelines. The developed method showed good precision and %RSD for intra-day and inter-day precision were very low, which were less than 2% limit. The precision data are summarized in Table 6.

 

Table 6: Data for Precision of Citicoline and Piracetam

 

LOD and LOQ:

The limit of detection (LOD) and limit of quantization (LOQ) were determined from slope (S) of the linearity plot and standard deviation of the response to the blank sample (s), by formula LOD. The method observed LOD and LOQ value of 0.14 mg/ ml and 0.45 mg/ml for CIT and 0.21mg/ml and 0.65 mg PIR respectively. Table 3 indicated that the developed method had higher sensitivity to the mobile phase composition.

 

 

 

Selectivity:

The selectivity of the proposed method was assessed by analyzing the mean percentage recovery and %RSD from different replicates having known fixed concentrations. The recovery of the CIT and PIR were found to be more than 99.0% which shows that the method is highly selective. The chromatograms (Figure 5 and 6) of both standard and test sample showed that there is not much variation in the retention time of both drugs. None of the impurities interfere with peaks and so it indicates the method was found to be specific and selective.

 

Figure 5. HPLC standard chromatograms of Standard Citicoline and piracetam.

 

Figure 6. HPLC standard chromatograms of marketed formulation of Citicoline and Piracetam.

 

 

Robustness:

The robustness of the PIR and CIT was tested using the so-called ‘one factor at a time’ method. The factors evaluated were mobile phase composition, flow rate, and pH. There was no significant change in the RT and area of both drugs, when these conditions were varied as described in the experimental section. The low value of the RSD indicates the method is robust. These system-suitability tests aid checking of the method to ensure the HPLC system and procedure are capable of providing data of acceptable quality. It can therefore be concluded that the method gives consistent results if mobile phase pH, composition, and flow rate vary slightly.

 

Assay:

The validated method was used to estimate the total drug content of commercially available brand of CIT and PIR tablets. Satisfactory results were obtained. Recovery of CIT and PIR from combination tablet (Nutam Plus) were 99.14% (RSD 0.34%) and 100.21% (RSD 0.22%), respectively, i.e. agreement with the label claims was good (Table 3). The results of the assay indicated the method is selective for the analysis of both drugs without interference from the excipients present.

 

CONCLUSION:

A simple, sensitive and economical RP-HPLC method has been successfully developed employing the systematic QbD-based approach for quantification of CIT and PIR in bulk as well as in tablet formulations. The screening and optimization studies employing experimental designs finally embarked upon the selection of optimized condition for optimization and validation.  The validation study corroborated excellent linearity, accuracy, precision, specificity and robustness. Further, the experimentally observed values of LOD and LOQ of both drugs were found to be quite lower. The method demonstrated high degree of practical utility for estimation of CIT and PIR in pharmaceutical dosage forms.

 

REFERENCES:

1.     Wurtman RJ, Regan M, Ulus I, Yu L. Effect of oral CDP-choline on plasma choline and uridine levels in humans. Biochem Pharmacol 2000; 60(7):989-92.

2.     Rao AM, Hatcher JF, Dempsey RJ. CDP-choline: Neuroprotection in transient forebrain ischemia of gerbils. J Neurosci Res 1999; 58 (5):697‑705.

3.     Neil MJ, editor. The Merck Index- and Encyclopedia of Chemicals Drugs and Biological. 13^th edition. New Jersey: Merck and Co.; 2001. p. 388, 1290.

4.     Manutosh A, Jain Ak, Navneet G, Stability Indicating Reversed Phase-High Performance Liquid Chromatography Method Development And Validation For Simultaneous Determination Of Related Substances Of Citicoline And Piracetam In Pharmaceutical Dosage Form, Asian J Pharm Clin Res,  9, 2, 2016, 292-297.

5.     Skondia V and Kabes J. Piracetam in alcoholic psychoses: a double-blind, crossover, placebo Controlled study. The Journal of international medical research, 1985; 13(3): 185–7.

6.     Buranji I, Skocilic Z, and Kozaric-Kovacic. Cognitive function in alcoholics in a double blind study of piracetam. Lijecnickivjesnik, 1990; 112(3–4): 111–4.

7.     Kalmar. Adjuvant therapy with parenteral piracetam in alcohol withdrawal delirium. Orvosihetilap, 2003; 144(19): 927–30.

8.     Dencker SJ, Wilhelmson G, Carlsson E and Bereen. Piracetam and chlormethiazole in acute alcohol withdrawal: a controlled clinical trial. The Journal of international medical research. 1978; 6(5): 395–400.

9.     Surani S, Kimbahune R, Kabra P, Urmila GH, Spectrophotometric determination of Citicoline sodium in pure form and pharmaceutical formulation, Der Pharmacia Lettre, 2(5), 2010, 353-7.

10.  Sanjay S. Ritu K. Prachi K., and Urmila G.H., Spectrophotometric determination of citicoline sodium in pure form and pharmaceutical formulation, Der Pharmacia Lettre, 2010, 2(5), 353-357.

11.  Patel JA, Panigrahi B, Patel CN, Ramaligen B, ModhK, Stress degradation studies on Citicoline sodium and development of validated stability indicating HPLC assay, Journal of Pharmacy Research, 3(2), 2011, 150-4.

12.  Bindaiya SK, Sahu K, Bhidare M, Karthikeyan C, Moorthy NSHN, Mehta F, Development and validation of RP-HPLC method for determination of Citicoline monosodium in human plasma, Latin American Journal of Pharmacy, 30(4),2011, 794-800.

13.  Kolla T, Vijayabaskaran M, Latha ST, Method development and validation of RP-HPLC for simultaneous estimation of Citicoline and Piracetam in tablet dosage form, International Journal of Pharm Tech Research, 3(3), 2011,1311-3.

14.  Raga Pravallika E, Prashanthi D and ISMAIL Y, Method Development and Validation of RP-HPLC for Simultaneous Estimation of Citicoline and Piracetam in Tablet Dosage Form. International Journal of Chemical and Pharmaceutical Sciences 2012, 3 (2), 76-79.

15.  Curticapean A, Imre SJ, New validated method for Piracetam HPLC determination in Human Plasma, Journal of Biophysical and Biochemical Method, 69(3), 2007 Jan, 273-81.

16.  Wang X, Zhu J, Xu R, Yang X, Wu H, Lin D, Determination of Piracetam in rat plasma by LC-MS/MS and its application to pharmacokinetics, Biomedical Chromatography, 24(10),2010, 1108-12.

17.  Monks, K., Molnar, I., Rieger, H.J., Bogati, B., Szabo, E.; Quality by design: multidimensional exploration of the design space in high performance liquid chromatography method development for better robustness before validation; Journal of Chromatography A, (2011); 1232: 218–230.

18.  Nethercote, P., Ermer, J.; Quality by design for analytical methods: implications for method validation and transfer; Pharmaceutical Technology, (2012); 36: 74–79.

19.  Lionberger, R.A., Lee, S.L., Lee, L., Raw, A., Yu, L.X.; Quality by design: concepts for ANDAs; AAPS Journal, (2008); 10: 268–276.

20.  S. Beg, K. Kohli, S. Swain and M. S. Hasnain, J. Liq. Chromatogr. Relat. Technol., 2012, 35, 393–406.

21.  M. S. Hasnain, S. Rao, M. K. Singh, N. Vig, A. Gupta, A. Ansari, P. Sen, P. Joshi and S. Ali Ansari, Analyst, 2013, 138, 1581–1588.

22.  Syed Sarim Imam, Mohammed Aqil, Mohammed Akhtar, Yasmin Sultana, and Asgar Ali Optimization of mobile phase by 3²-mixture design for the validation and quantification of risperidone in bulk and pharmaceutical formulations using RP-HPLC, Anal. Methods, 2014, 6, 282–288

23.  Mittal A, Imam SS, Parmar S, Gilani SJ and Taleuzzaman M. Design of Experiment based Optimized RP-HPLC Method for Simultaneous Estimation of Amlodipine and Valsartan in Bulk and Tablet Formulations. Austin J Anal Pharm Chem. 2015; 2(6): 1057.

24.  Food and Drug Administration, 1987, Guidelines on General Principles of Process Validation, http://www.fda.gov/cdrh/ ode/425.pdf.

25.  ICH (Q2R1), Draft Guidelines on Validation of Analytical Procedures: Text and Methodology, IFPMA, Switzerland, 1995.

 

 

Received on 17.03.2017         Modified on 25.03.2017

Accepted on 11.04.2017         © AJRC All right reserved