TY - JOUR
AU - Mutalik, Srinivas
AB - Abstract A stability-indicating reverse phase high-performance liquid chromatography method was developed and validated for simultaneous quantification of apremilast (APL) and betamethasone dipropionate (BD) in bulk as well as drug loaded microsponges. Various mobile phase systems were screened to check the system suitability followed by force degradation analysis to determine APL and BD stability under varying stress conditions. A central composite design model was used to optimize the column temperature and flow rate using Design Expert® (9.0.1). One factor at a time approach with five independent factors were used to validate the robustness of the method. Finally, APL and BD were precisely and accurately quantified from drug loaded microsponges using the validated method. A favorable separation of APL and BD was obtained on a Phenomenex® Luna C18 column using a mixture of 50 mM phosphate buffer containing 0.1% triethylamine (pH 6.1) and acetonitrile (60:40%v/v) as mobile phase. Both the drugs were found to be stable when exposed to stressors such as heat-, light-, alkali-, acid- and peroxide-induced degradation. The calibration curves were found to be linear with appreciable limit of detection and limit of quantification. Recovery and percentage relative standard deviation of peak areas for APL and BD were found to be < 2.0% and 99–100% in bulk drug solution and <2.0% and 99–103% in microsponge formulation, respectively. Statistical analysis using analysis of variance indicated that the model was significant (P < 0.001). Hence, the developed method can be effectively used to quantify APL and BD, both in bulk as well as microsponge formulations. Introduction In pharmaceutical sciences, nanotechnology has become a vital component that finds numerous applications in drug delivery systems by improving the biological activity of drugs (1). With the support of nanotechnology, drug delivery to the targeted site is potentiated in a competent way. Although microsponge formulation is a neoteric technology, it has shown greater advancements in topically applied formulations by providing sustained release of drugs on skin (2, 3). The main advantage of using microsponge formulation is that not only will it reduce the local adverse effects but also will enhance the efficacy of topical agents. The size of the microsponges should range between 5 and 300 μm as the particle size is the most vital feature for topical application. Increase in size beyond 300 μm will hinder the passage through stratum corneum. Microsponges allow the drug to be present on epidermis for a longer period of time. Therefore, it is beneficial as a delivery system for dermal application (4, 5). Apremilast (APL; N-[2-[(1S)-1-(3-ethoxy-4-methoxyphenyl)-2-(methylsulfonyl)ethyl]-2,3-dihydro-1,3-dioxo-1H-isoindol-4-yl]acetamide) is a phosphodiesterase 4 (PDE4) inhibitor, which is effective in the treatment of plaque psoriasis (6, 7). It works on the mechanism of inhibition of PDE4 enzymes which in turn inhibits the production of pro-inflammatory mediators like TNF-α, interferon-γ and IL-23, and increases anti-inflammatory mediator production such as IL-10 (8). Betamethasone (BD) is a potent topical corticosteroid, which is also used as an anti-inflammatory agent and for the treatment of several skin disorders, allergies and other diseases occurring due to glucocorticoid deficiency (9, 10). The combination of BD and APL can be used for the treatment of skin inflammation, psoriasis and other skin diseases (11). APL is generally administered by the oral route, while BD is available as topical formulations (12, 13). Previously, a few nano-carrier based formulations such as emulgel (14), nanoparticles (15–17) and nano-structured lipid carriers (NLCs) (18, 19) have been reported for APL and BD albeit individually, which showed higher deposition in skin with no skin irritation indicating that nanoformulations of these drugs are safe and effective for the treatment of psoriasis. However, we would be the first to report the application of these drugs as a combination therapy using microsponge-based topical formulation. As analytical methodology imparts an important role in the evaluation of optimized formulations, it is essential to develop an accurate, precise and valid analytical method for the evaluation of topical preparations (20, 21). The optimization of chromatographic method is often complex; therefore, such separations must be assessed by means of a quality by design (QbD) methodology. By using design-of-experiments (DoE), the optimal experimental conditions are obtained with quality assurance paving the way for a systematic approach in the development of a suitable method by incorporating multi-dimensional combinations and interactions between input variables and parameters (22). Previous reports have acknowledged the use of a DoE-based approach for the estimation of APL and BD albeit individually in bulk drug or formulations. Several analytical methods such as ultraviolet (UV) (23, 24), high-performance liquid chromatography (HPLC; 25–28), liquid chromatography–mass spectrometry (LC–MS/MS) (29, 30) have been reported. Quite a few methods have described the use of chromatographic methods for the simultaneous estimation of BD in combination with other drugs (31–34). To date, there are no reports on a suitable analytical method for simultaneous estimation of APL and BD. In addition, we would be the first to report the potential of this combination as a microsponge-based topical formulation. Hence, this study focusses on the development of a simultaneous reversed-phase HPLC (RP-HPLC) method for quantification of APL and BD through UV detection with acceptable precision, accuracy and simplicity and validation of the developed method as per (ICH) Q2 R1 guidelines (35). A central composite design (CCD) was used for optimization of the chromatographic method. There are two major tools which are used for optimization of an analytical method namely: (i) Statistical parameter evaluation and (ii) experimental design. It is advantageous to identify and to evaluate most essential parameter with a minimum number of runs. The selection of the parameter levels through trial and error experiment is a time consuming process. Therefore, we selected a CCD model to determine the best experimental conditions in RP-HPLC. There were three steps for the optimization of HPLC method: (1) preliminary experiments to choose essential requirements of the method, (2) screening to select important variables, (3) response surfacing to locate the optimal point. During the optimization steps, retention time, peak resolution, tailing factor and HETP responses were screened in order to minimize the analysis time and maximize the peak resolution of the developed method. To check the stability of both the drugs, a force degradation study was also performed by exposing the drugs to varying stress agents to estimate the drug (s) among degraded products with high tenacity and specificity. In addition, the optimized and validated method can be applied to simultaneously quantify APL and BD in bulk and in microsponge formulation and can also be used further in estimating percent drug content, entrapment efficiency and drug release studies. Materials and Methods Material and reagents APL and BD were generously gifted by Glenmark Pharmaceuticals (Mumbai, India) and Sun Pharma Pvt Ltd (Gurugram, India), respectively. Triethylamine (TEA) (purity ≥ 99%) was procured from Merck Ltd (Mumbai, India), Potassium dihydrogen orthophosphate (KH2PO4) (purity ≥ 99%) and sodium hydroxide (NaOH) were obtained from Sigma Aldrich (Bangalore, India). Hydrogen peroxide (H2O2; 35% AR) and hydrochloric acid (HCl; 35% pure) were obtained from Loba Chemie Pvt Ltd (Mumbai, India) and Hi-Media Labs Pvt Ltd (Mumbai, India), respectively. Milli-Q water was obtained from a Millipore Direct-Q® 3 water purification system (Millipore Corporation, Billerica, MA, USA), while acetonitrile (ACN) of HPLC grade (purity: min 99.8%) was obtained from Lab Scan Pvt Ltd (Bangalore, India). Instrumentation and apparatus HPLC system with model no. LC-2010CHT bearing a serial no. C21255111757-LP was configured with quaternary low-pressure gradient pumps, Photo-Diode Array (PDA) and UV detector (SPD-M-20A). An inbuilt degasser unit, auto sampler and column oven was equipped within the HPLC system (Shimadzu Corporation, Kyoto, Japan) and was used for analysis. Data and batch processing, monitoring and acquisition were performed with LC solution 5.57 system control software. The prepared mobile phase was filtered through a membrane filter (pore size 0.22 μ) using a glass vacuum filtration assembly (Millipore) and degassed using an ultrasonic bath (Equitron, Medica Instruments Mfg. Co., Mumbai, India). The membrane filter was obtained from Pall Pvt Ltd (Bangalore, India) The pH of buffer solutions was measured using a pH meter (pH 510, Eutech Instruments, Thermofisher Scientific, Bangalore, India) equipped with a glass electrode (Van London Co., USA). Analytical methods for estimation of APL and BD Using UV spectroscopy Standard stock solutions (1 mg/mL) of both the drugs (APL and BD) were prepared individually and diluted to obtain 10 μg/mL concentration. The spectrum of the individual solution was obtained by scanning the solution using a UV spectrophotometer (Shimadzu Corporation, Kyoto, Japan) in the wavelength range of 200–400 nm. Individually, APL showed maximum absorption at wavelength (λmax) 230 nm, whereas BD showed maximum absorption at wavelength (λmax) 242 nm. The same stock solution (10 μg/mL) of both drugs were mixed in 1:1 ratio and scanned to obtain the single detection wavelength. Both the drugs in 1:1 ratio showed maximum absorption at 233 nm, where the absorptivity difference between the two components were as large as possible. Hence, this wavelength was selected for the proposed method. Using HPLC Primarily, various mobile phases were screened with respect to pH and composition of mobile phase, to optimize the chromatographic separation of APL and BD. Several isocratic and gradient methods were trialed to get the best possible responses for different chromatographic parameters like retention time (Rt), peak area, tailing factor (Tf) and theoretical plate count (NTP) to check the system suitability. Optimum separation of APL and BD was obtained by an isocratic method involving a mobile phase mixture comprising of 50 mM potassium dihydrogen orthophosphate solution with 0.1% v/v TEA (pH 6.1 ± 0.05) and acetonitrile in the ratio of 60:40 as mobile phase. A Phenomenex® Luna C18 column (250 × 4.6 mm i.d., 5 μm particle size, 100 Å) was used as the stationary phase. Then, after selecting the ratio and composition of the mobile phase, the chromatographic condition was set at 20 μL injection volume with 1.0 mL/min flow rate at 40°C column temperature with a run time of 30 min. The autosampler temperature was maintained at 5°C with a detection wavelength of 233 nm. Preparation of standard solutions The primary stock solutions of APL and BD were prepared separately to obtain a concentration of 1 mg/mL (1,000 μg/mL) of APL and BD by accurately dissolving 10 mg of APL and BD separately in 10 mL of diluent (mixture of ACN and water, in 1:1 ratio). This mixture was then vortexed for 2 min. Working stock solutions with concentration ranging from 0.5 to 10 μg/mL were then prepared by appropriately diluting the primary stock solutions of APL and BD with diluent. Design-of-experiment aided method optimization In order to develop an optimum chromatographic method for the estimation of analyte (s), it is essential to identify and evaluate the critical parameters that result in favorable chromatographic separation. In the absence of an experimental design, a number of trials may be required to perform which is time consuming (36). Hence, it is imperative to perform initial experiments to identify the quintessential requirements of a chromatographic method, followed by application of a suitable model to determine the optimum chromatographic conditions. In this regard, DoE is a vital approach for method development as it provides information on how method parameters interact with each other, which can lead to an analytical procedure with robust ranges of operation (37). So far, there are no reports on simultaneous estimation of APL and BD by using DoE for a suitable analytical method development and validation in bulk and pharmaceutical formulation. Mobile phase optimization Keeping in mind the pKa of APL and BD, several mobile phase systems with different pH ranges were attempted viz., pH 6.1 potassium phosphate buffer, pH 5.5 sodium phosphate buffer and pH 3.0 trifluoroacetic acid in water (TFA; 0.03%). For the preparation of pH 6.1 potassium phosphate buffer, to a 50 mM potassium phosphate solution, triethyl amine (TEA; to get 0.1%) was added. For pH 5.5 sodium phosphate buffer preparation, 50 mM sodium phosphate solution was adjusted to pH 5.5 using dilute NaOH solution or orthophosphoric acid (OPA). For pH 3.0 trifluoroacetic acid in water preparation, 30 μL of TFA was added in 100 mL of water. Central composite design model for method optimization A CCD model was used for the optimization of the chromatographic method to assess the key effect of independent factors on the chromatographic properties of both the drugs (38–40). Design Expert® software (version 9.0.4.1; Stat-Ease, Inc. Minneapolis, MN) was used to deduce the CCD model. The effect of two method parameters, i.e., column temperature (A) and flow rate (B) at two different levels were selected to examine the response on Rt of APL (X1) and BD (X2), peak area of APL (X3) and BD (X4), Tf of APL (X5) and BD (X6), and NTP of APL (X7) and BD (X8). A total of 13 runs were carried out to optimize the method parameters based on the method responses. Method validation The optimized analytical method was validated as per ICH guidelines for the following parameters (35). System suitability This parameter was used to examine the appropriateness of the whole analytical background (including column, system, reagents and analysts). To perform system suitability check, the stock sample of APL and BD (1 μg/mL) was prepared and injected into HPLC for six times. Specificity Specificity is performed to identify the interference between diluent and placebo at the Rt of APL and BD peak. This was assessed by injecting the samples (placebo and diluent) in triplicates into HPLC. Linearity Linearity was assessed by preparing different concentrations of standard drug solution in the range of 0.05–10 μg/mL, which were injected in five sets and the linear calibration curve was obtained throughout the mentioned concentration range. Regression analysis was done on the peak area (y) vs. concentration (x). Limit of detection and limit of quantification The limit of detection (LOD) and the limit of quantification (LOQ) were determined utilizing the standard deviation of the responses and the slope. $$ \mathrm{LOD}=\frac{3.3\ x\ \sigma }{s}\ \mathrm{and}\ \mathrm{LOQ}=\frac{10\ x\ \sigma }{s} $$ where σ = smallest value of standard deviation in linearity range; s = slope of the linearity curve. Precision and accuracy Intra-day (same day) and inter-day (different day) precision was carried out by injecting 1 μg/mL concentration of APL or BD standard solutions, six times into HPLC. Accuracy was recognized by defining recovery (%) of APL and BD at three unique concentrations (80%, 100% and 120%) in triplicates. Robustness This parameter was performed to check the optimized method accuracy by altering the chromatographic factors: Flow rate (1.0 ± 0.2 mL/min), mobile phase ratio (60:40 ± 2%), column temperature (40 ± 2°C), injection volume (20 ± 2 μL) and detection wavelength (233 ± 2 nm). One-factor-at-a-time approach was utilized to yield a sum of 15 trials to distinguish any effects on responses, such as Rt, peak area, Tf and NTP. Sample solution stability To determine the sample solution stability, the 24-h old precision samples followed by freshly prepared samples were injected in triplicates into HPLC (41). Similarity index was calculated using following formula: $$ \mathrm{Similarity}\ \mathrm{index}=\frac{{\mathrm{Peak}\ \mathrm{area}}_{\mathrm{old}\ \mathrm{std}}\times{\mathrm{Amt}}_{\mathrm{new}\ \mathrm{std}}}{\mathrm{Average}\ {\mathrm{peak}\ \mathrm{area}}_{\mathrm{new}\ \mathrm{std}}\times{\mathrm{Amt}}_{\mathrm{old}\ \mathrm{std}}} $$ where |${\mathrm{peak}\ \mathrm{area}}_{\mathrm{old}\ \mathrm{std}}$| is sample after 24 h; |$\mathrm{Average}\ {\mathrm{peak}\ \mathrm{area}}_{\mathrm{new}\ \mathrm{std}}$| is peak area of freshly prepared sample; |${\mathrm{Amt}}_{\mathrm{old}\ \mathrm{std}}$| and |${\mathrm{Amt}}_{\mathrm{new}\ \mathrm{std}}$| are the amounts of old and new standards. Mobile phase stability Mobile phase stability was determined by eluting both APL and BD samples using 24-h old and freshly prepared mobile phase. Similarity index was calculated using following formula: $$\begin{equation*} \mathrm{Similarity}\ \mathrm{index}=\frac{\mathrm{Avg}.{\mathrm{peak}\ \mathrm{area}}_{\mathrm{old}\ \mathrm{mobile}\ \mathrm{phase}}\times{\mathrm{Amt}}_{\mathrm{fresh}\ \mathrm{mobile}\ \mathrm{phase}}}{\mathrm{Avg}.{\mathrm{peak}\ \mathrm{area}}_{\mathrm{fresh}\ \mathrm{mobile}\ \mathrm{phase}}\times{\mathrm{Amt}}_{\mathrm{old}\ \mathrm{mobile}\ \mathrm{phase}}} \end{equation*}$$ where |$\mathrm{Avg}.{\mathrm{peak}\ \mathrm{area}}_{\mathrm{old}\ \mathrm{mobile}\ \mathrm{phase}}$| and |$\mathrm{Avg}.{\mathrm{peak}\ \mathrm{area}}_{\mathrm{fresh}\ \mathrm{mobile}\ \mathrm{phase}}$| are peak area of APL and BD with old and freshly prepared mobile phase, respectively. |${\mathrm{Amt}}_{\mathrm{old}\ \mathrm{mobile}\ \mathrm{phase}}$| and |${\mathrm{Amt}}_{\mathrm{fresh}\ \mathrm{mobile}\ \mathrm{phase}}$|are the amount of APL and BD quantified with old and freshly prepared mobile phase, respectively. Assessment of stability of APL and BD by force degradation (stress testing) studies A stress testing study was performed by subjecting APL and BD to acid—induced (HCl) and alkaline—induced (NaOH) hydrolysis, oxidative (H2O2), thermal and photolytic degradation (42, 43). For determining the stability of both the drugs, stress testing studies were performed on 1 mg/mL standard stock solution of APL or BD in diluent. Acid hydrolysis using HCl Force degradation study by acid hydrolysis method was performed on a 1 mg/mL solution of both the drugs individually. Acid hydrolysis was conducted using two different molar concentrations of HCl (0.1 N and 1 N) (1, 37). Briefly, 3 mL of 0.1 N HCl and 1 N HCl was added to 1 mL of 1 mg/mL drug solution and the mixture was heated to 60°C for approximately 24 and 12 h, respectively. 0.1 N and 1 N NaOH were added to neutralize the resulting solution. Later, the sample was further diluted with the diluent and injected into HPLC for analysis. Alkaline hydrolysis using NaOH Alkali hydrolysis of APL or BD was carried out using two different molar concentrations of NaOH (0.1 N and 1 N). About 3 mL of 0.1 N NaOH and 1 N NaOH was added to 1 mL of 1 mg/mL of individual drug solution and the mixture was heated at 60°C for approximately for 24 and 12 h, respectively. 0.1 N and 1 N HCl were added to neutralize the resulting solution. The samples were further diluted with diluent and injected in HPLC. Oxidative degradation using hydrogen peroxide (H2O2) To 1 mg/mL concentration of APL or BD, 1 mL of 3% w/v solution of hydrogen peroxide solution was added and allowed to keep in dark for 24 h. The solution was then appropriately diluted and injected into HPLC for analysis. Photolytic degradation In this study, a solid sample (10 mg) was exposed to direct sunlight for 24 h (1, 37). The samples were then analyzed by HPLC with appropriate dilution. Thermal degradation The solid drug sample (10 mg) was kept in an oven at 60°C for 24 h (1, 37). The samples were then analyzed by HPLC after appropriate dilution. Simultaneous estimation of APL and BD in microsponge formulation Drug loading into microsponge Methyl methacrylate/glycol dimethacrylate cross polymer-based microsponge was accurately weighed (80 mg) and heated to warm in a small beaker. In warm Milli-Q water (3.5 times the weight of the microsponge), 5 mg of APL and 1.66 mg of BD were dissolved by mixing. The drug solution was mixed with warmed microsponge until all the solution was absorbed onto the microsponges. Then, the microsponges were dried overnight under vacuum at 40°C. In the same way, drugs were loaded two more times by layering method. Approximately, 15 mg of APL and 5 mg of BD were loaded into the microsponges (44, 45). Encapsulation efficiency of microsponges The assessment of percentage encapsulation efficiency of APL and BD in microsponge was done by direct method (46). The drug loaded microsponges were kept under stirring in the mobile phase for 24 h and after 24 h it was sonicated for 5 min. The sonicated solution was filtered through 0.45 μm membrane and drug was estimated using HPLC. The percentage encapsulation efficiency was determined by the formula: $$ \mathrm{Entrapment}\ \mathrm{Efficiency}\ \left(\%\right)=\frac{{\left[D\right]}_E}{{\left[D\right]}_T}\ x\ 100 $$ where [D]E is the amount of drugs (APL and BD) entrapped in microsponges; [D]T is the total amount of drug (APL and BD) loaded in the microsponges. Determination of accuracy for analysis of drugs in microsponge formulation Accuracy was determined at 80%, 100% and 120% spike level of APL and BD and, %recovery and %RSD were calculated. Results Mobile phase optimization With 0.03% TFA in water (pH 3.0) and ACN mixture using a gradient method at 0.8 mL/min flow rate (Figure 1b), APL peak was eluted at 2.3 min with plate count and Tf of 3,501 and 1.6, while BD peak was not eluted sodium phosphate buffer (50 mM pH 5.5) with 0.1% TEA and ACN mixture (60:40% v/v, 1 mL/min), did not elute either of the drugs (Figure 1c). Potassium phosphate buffer (50 mM, pH 6.1) with 0.1% TEA and ACN mixture in gradient method eluted APL and BD peaks at 17.35 and 12.74 min with plate count and Tf of 6,000 and 1.1, respectively (Figure 1d). At 55:45% v/v (Figure 1e) ratio, peaks were observed at 13.25 and 7.04 min with plate count and Tf of 4,500 and 1.5 in which BD peak shape was inappropriate. With 60:40% v/v ratio, APL and BD peaks were eluted at 14.01 and 7.38 min with plate count and Tf of 7,000 and 1.0 (Figure 1f). Figure 1 Open in new tabDownload slide Mobile phase optimization. Chromatogram obtained with (a) Diluent (50,50 ACN:water); (b) 0.03% TFA in water (pH 2.42) and 0.03% TFA in ACN, gradient method; (c) 50 mM sodium phosphate buffer + 0.1% TEA pH 5.5 and ACN at 60:40 v/v; (d) 50 mM potassium phosphate buffer + 0.1% TEA pH 6.1 and ACN, gradient method; (e) 50 mM potassium phosphate buffer + 0.1% TEA pH 6.1 and ACN at 55:45 v/v; (f) 50 mM potassium phosphate buffer + 0.1% TEA pH 6.1 and ACN at 60:40 v/v. Figure 1 Open in new tabDownload slide Mobile phase optimization. Chromatogram obtained with (a) Diluent (50,50 ACN:water); (b) 0.03% TFA in water (pH 2.42) and 0.03% TFA in ACN, gradient method; (c) 50 mM sodium phosphate buffer + 0.1% TEA pH 5.5 and ACN at 60:40 v/v; (d) 50 mM potassium phosphate buffer + 0.1% TEA pH 6.1 and ACN, gradient method; (e) 50 mM potassium phosphate buffer + 0.1% TEA pH 6.1 and ACN at 55:45 v/v; (f) 50 mM potassium phosphate buffer + 0.1% TEA pH 6.1 and ACN at 60:40 v/v. Method optimization using CCD A total of 13 trials were resulted based on the CCD design, the details of which are given in Table I. Quadratic responses having interaction values were obtained on using the selected model and demonstrated the effect of independent variables on the experimental responses. Polynomial coefficients of both APL and BD were well suited for the data and the R2 values ranged between 0.998 and 1.0 (P < 0.05 for all values). Figure 2 shows the perturbation plots obtained for APL and BD as per CCD model, demonstrating the effect of independent variables on the observed responses. Table I Experimental Conditions for CCD with Values of Observed Responses Run order . Independent variables . Responses . . A: Flow rate (mL/min) . B: Column Temp. (°C) . Rt . Peak Area . Tf . NTP . . . . X1 . X2 . X3 . X4 . X5 . X6 . X7 . X8 . 1 −1 0 7.98 16.02 114,602 233,694 0.90 0.92 2,530 1,356 2 −1 –1 10.29 20.9 138,723 284,766 1.01 1.07 1,691 833 3 0 0 8.29 16.46 111,990 226,572 1.24 1.20 7,933 8,181 4 0 0 8.20 16.25 109,482 228,773 1.25 1.22 7,696 7,791 5 0 0 8.12 16.03 112,111 227,114 1.27 1.22 7,575 7,619 6 –1 +1 6.24 12.17 95,718 193,913 1.10 1.08 2,432 2,860 7 0 –1 11.43 22.98 153,086 264,894 1.01 0.69 1,769 4,537 8 0 0 7.84 15.31 110,410 229,312 1.22 1.16 7,147 6,969 9 0 0 7.79 15.19 110,048 229,253 0.92 0.89 5,179 4,113 10 +1 0 7.81 14.65 117,738 244,973 1.22 1.06 3,573 3,274 11 0 +1 5.65 10.58 90,148 177,599 1.29 0.99 4,101 3,553 12 +1 –1 10.10 19.57 148,754 299,296 0.93 0.80 4,843 4,595 13 +1 +1 6.15 11.37 101,311 202,039 1.34 1.08 4,291 4,750 Run order . Independent variables . Responses . . A: Flow rate (mL/min) . B: Column Temp. (°C) . Rt . Peak Area . Tf . NTP . . . . X1 . X2 . X3 . X4 . X5 . X6 . X7 . X8 . 1 −1 0 7.98 16.02 114,602 233,694 0.90 0.92 2,530 1,356 2 −1 –1 10.29 20.9 138,723 284,766 1.01 1.07 1,691 833 3 0 0 8.29 16.46 111,990 226,572 1.24 1.20 7,933 8,181 4 0 0 8.20 16.25 109,482 228,773 1.25 1.22 7,696 7,791 5 0 0 8.12 16.03 112,111 227,114 1.27 1.22 7,575 7,619 6 –1 +1 6.24 12.17 95,718 193,913 1.10 1.08 2,432 2,860 7 0 –1 11.43 22.98 153,086 264,894 1.01 0.69 1,769 4,537 8 0 0 7.84 15.31 110,410 229,312 1.22 1.16 7,147 6,969 9 0 0 7.79 15.19 110,048 229,253 0.92 0.89 5,179 4,113 10 +1 0 7.81 14.65 117,738 244,973 1.22 1.06 3,573 3,274 11 0 +1 5.65 10.58 90,148 177,599 1.29 0.99 4,101 3,553 12 +1 –1 10.10 19.57 148,754 299,296 0.93 0.80 4,843 4,595 13 +1 +1 6.15 11.37 101,311 202,039 1.34 1.08 4,291 4,750 Note: −1 indicates lower level of factor (0.8 mL/min and 35°C for flow rate and column temperature), 0 indicates center level of factor (1.0 mL/min and 40°C for flow rate and column temperature) and + 1 indicates higher level of factor (1.2 mL/min and 45°C for flow rate and column temperature). X1 and X2: Rt of APL and BD; X3 and X4: peak area of APL and BD; X5 and X6: Tf of APL and BD; X7 and X8: NTP of APL and BD. Rt – retention time; Tf – tailing factor; NTP – number of theoretical plates. Open in new tab Table I Experimental Conditions for CCD with Values of Observed Responses Run order . Independent variables . Responses . . A: Flow rate (mL/min) . B: Column Temp. (°C) . Rt . Peak Area . Tf . NTP . . . . X1 . X2 . X3 . X4 . X5 . X6 . X7 . X8 . 1 −1 0 7.98 16.02 114,602 233,694 0.90 0.92 2,530 1,356 2 −1 –1 10.29 20.9 138,723 284,766 1.01 1.07 1,691 833 3 0 0 8.29 16.46 111,990 226,572 1.24 1.20 7,933 8,181 4 0 0 8.20 16.25 109,482 228,773 1.25 1.22 7,696 7,791 5 0 0 8.12 16.03 112,111 227,114 1.27 1.22 7,575 7,619 6 –1 +1 6.24 12.17 95,718 193,913 1.10 1.08 2,432 2,860 7 0 –1 11.43 22.98 153,086 264,894 1.01 0.69 1,769 4,537 8 0 0 7.84 15.31 110,410 229,312 1.22 1.16 7,147 6,969 9 0 0 7.79 15.19 110,048 229,253 0.92 0.89 5,179 4,113 10 +1 0 7.81 14.65 117,738 244,973 1.22 1.06 3,573 3,274 11 0 +1 5.65 10.58 90,148 177,599 1.29 0.99 4,101 3,553 12 +1 –1 10.10 19.57 148,754 299,296 0.93 0.80 4,843 4,595 13 +1 +1 6.15 11.37 101,311 202,039 1.34 1.08 4,291 4,750 Run order . Independent variables . Responses . . A: Flow rate (mL/min) . B: Column Temp. (°C) . Rt . Peak Area . Tf . NTP . . . . X1 . X2 . X3 . X4 . X5 . X6 . X7 . X8 . 1 −1 0 7.98 16.02 114,602 233,694 0.90 0.92 2,530 1,356 2 −1 –1 10.29 20.9 138,723 284,766 1.01 1.07 1,691 833 3 0 0 8.29 16.46 111,990 226,572 1.24 1.20 7,933 8,181 4 0 0 8.20 16.25 109,482 228,773 1.25 1.22 7,696 7,791 5 0 0 8.12 16.03 112,111 227,114 1.27 1.22 7,575 7,619 6 –1 +1 6.24 12.17 95,718 193,913 1.10 1.08 2,432 2,860 7 0 –1 11.43 22.98 153,086 264,894 1.01 0.69 1,769 4,537 8 0 0 7.84 15.31 110,410 229,312 1.22 1.16 7,147 6,969 9 0 0 7.79 15.19 110,048 229,253 0.92 0.89 5,179 4,113 10 +1 0 7.81 14.65 117,738 244,973 1.22 1.06 3,573 3,274 11 0 +1 5.65 10.58 90,148 177,599 1.29 0.99 4,101 3,553 12 +1 –1 10.10 19.57 148,754 299,296 0.93 0.80 4,843 4,595 13 +1 +1 6.15 11.37 101,311 202,039 1.34 1.08 4,291 4,750 Note: −1 indicates lower level of factor (0.8 mL/min and 35°C for flow rate and column temperature), 0 indicates center level of factor (1.0 mL/min and 40°C for flow rate and column temperature) and + 1 indicates higher level of factor (1.2 mL/min and 45°C for flow rate and column temperature). X1 and X2: Rt of APL and BD; X3 and X4: peak area of APL and BD; X5 and X6: Tf of APL and BD; X7 and X8: NTP of APL and BD. Rt – retention time; Tf – tailing factor; NTP – number of theoretical plates. Open in new tab Figure 2 Open in new tabDownload slide Perturbation plots. (a and b) peak area; (c and d) retention time (Rt), (e and f) tailing factor (Tf) and (g and h) theoretical plate count (NTP). Note: A, column temperature (°C); B, flow rate (mL/min); a, c, e and g represents responses for APL; b, d, f and h represents responses for BD. Figure 2 Open in new tabDownload slide Perturbation plots. (a and b) peak area; (c and d) retention time (Rt), (e and f) tailing factor (Tf) and (g and h) theoretical plate count (NTP). Note: A, column temperature (°C); B, flow rate (mL/min); a, c, e and g represents responses for APL; b, d, f and h represents responses for BD. Based on the results of analysis of variance (ANOVA), the equation obtained using column temperature (A) and flow rate (B) as independent factors with Rt of APL (X1) was: X1 = 15.85 – 0.51A – 4.31B + 0.13AB – 0.27A2 + 0.45B2 (1) Adjusted R2 value was observed to be 0.8637. On the other hand, the equation for Rt of BD (X2) was obtained as follows: X2 = 8.05 – 0.065A – 2.02B + 0.025AB – 0.082A2 + 0.24B2 (2) Statistic parameter of X2 revealed an adjusted R2 of 0.9897. Equations (3 and 4) demonstrated the response of peak area of APL (X3) and BD (X4). The statistic results revealed an adjusted R2 value of 0.8637 for APL and 0.9877 for BD. X3 = 2.340E+005 + 4825.49A – 38945.85B (3) X4 = 1.108E+005 + 2507.37A – 22428.79B – 1109.50AB + 3240.27A2 + 5959.28B2 (4) Equation (5) explains the correlation between response of Tf of APL and flow rate and column temperature. The statistical results showed an adjusted R2 value of 0.3399. X5 = 1.14 – 9.001E-003A + 0.089B + 0.068AB – 0.051A2 – 0.13B2 (5) Similarly, Equation (6) explains the response of Tf of BD on varying flow rate and column temperature. Results of ANOVA analysis revealed an adjusted R2 value of 0.3916. X6 = 1.13 + 0.077A + 0.11B (6) Equations (7 and 8) corresponded to the response of NTP of APL and BD. Statistical results indicated an acceptable value for adjusted R2. X7 = 6934.60 + 1045.56A + 98.80B – 468.00AB – 2289.92A2 – 1424.93B2 (7) X8 = 7160.60 + 810.75A + 435.87B – 323.25AB – 1974.30A2 – 2032.55B2 (8) Analytical method validation System suitability and specificity Validation results are presented in Table II. The percentage RSD of peak area, Tf and NTP were found to be < 2.0%, < 1.5% and >2,000, respectively. The chromatograms of diluent, placebo, drug solution (APL and BD) and microsponge formulation were compared (Figure 4). The chromatograms obtained with simultaneous estimation of APL and BD show no interference at the Rt of both the drugs when compared with the chromatograms of diluent and placebo. Table II Results of Validation Parameters System suitability . Parameters . Acceptance criteria . Observed . . . . . APL . BD . . RSD of peak area (n = 6) . RSD < 2.0% . 0.10 . 0.09 . . Tf . <1.5 . 1.05 . 1.14 . . N . >2,000 . 4,811 . 4,371 . Linear regression data Linearity (μg/mL); (n = 5) – 0.05–10 Slope 50.509 23.731 Y-intercept when X = 0 2359.6 994.84 P-value at 95% C.I. <0.0001 R 2 0.9998 Precision %RSD for intraday <2.0% 0.01 0.01 %RSD for interday <2.0% 0.02 0.01 Accuracy Initial conc. (μg/mL) Observed mean conc. (μg/mL); n = 3 Mean recovery (%) BD APL BD APL 800 ng/mL 799.51 806.62 99.94 100.83 1,000 ng/mL 973.39 901.93 97.34 90.19 1,200 ng/mL 1191.66 1193.46 99.30 99.93 LOD (ng/mL) – – 24.20 23.36 LOQ (ng/mL) 73.37 70.77 Robustness Flow rate, mobile phase ratio, column temperature, injection volume, detection wavelength RSD < 2% 1.132 1.192 Stability Sample solution (24 h) 0.97 0.96 Mobile phase (24 h) 0.99 1.01 System suitability . Parameters . Acceptance criteria . Observed . . . . . APL . BD . . RSD of peak area (n = 6) . RSD < 2.0% . 0.10 . 0.09 . . Tf . <1.5 . 1.05 . 1.14 . . N . >2,000 . 4,811 . 4,371 . Linear regression data Linearity (μg/mL); (n = 5) – 0.05–10 Slope 50.509 23.731 Y-intercept when X = 0 2359.6 994.84 P-value at 95% C.I. <0.0001 R 2 0.9998 Precision %RSD for intraday <2.0% 0.01 0.01 %RSD for interday <2.0% 0.02 0.01 Accuracy Initial conc. (μg/mL) Observed mean conc. (μg/mL); n = 3 Mean recovery (%) BD APL BD APL 800 ng/mL 799.51 806.62 99.94 100.83 1,000 ng/mL 973.39 901.93 97.34 90.19 1,200 ng/mL 1191.66 1193.46 99.30 99.93 LOD (ng/mL) – – 24.20 23.36 LOQ (ng/mL) 73.37 70.77 Robustness Flow rate, mobile phase ratio, column temperature, injection volume, detection wavelength RSD < 2% 1.132 1.192 Stability Sample solution (24 h) 0.97 0.96 Mobile phase (24 h) 0.99 1.01 Open in new tab Table II Results of Validation Parameters System suitability . Parameters . Acceptance criteria . Observed . . . . . APL . BD . . RSD of peak area (n = 6) . RSD < 2.0% . 0.10 . 0.09 . . Tf . <1.5 . 1.05 . 1.14 . . N . >2,000 . 4,811 . 4,371 . Linear regression data Linearity (μg/mL); (n = 5) – 0.05–10 Slope 50.509 23.731 Y-intercept when X = 0 2359.6 994.84 P-value at 95% C.I. <0.0001 R 2 0.9998 Precision %RSD for intraday <2.0% 0.01 0.01 %RSD for interday <2.0% 0.02 0.01 Accuracy Initial conc. (μg/mL) Observed mean conc. (μg/mL); n = 3 Mean recovery (%) BD APL BD APL 800 ng/mL 799.51 806.62 99.94 100.83 1,000 ng/mL 973.39 901.93 97.34 90.19 1,200 ng/mL 1191.66 1193.46 99.30 99.93 LOD (ng/mL) – – 24.20 23.36 LOQ (ng/mL) 73.37 70.77 Robustness Flow rate, mobile phase ratio, column temperature, injection volume, detection wavelength RSD < 2% 1.132 1.192 Stability Sample solution (24 h) 0.97 0.96 Mobile phase (24 h) 0.99 1.01 System suitability . Parameters . Acceptance criteria . Observed . . . . . APL . BD . . RSD of peak area (n = 6) . RSD < 2.0% . 0.10 . 0.09 . . Tf . <1.5 . 1.05 . 1.14 . . N . >2,000 . 4,811 . 4,371 . Linear regression data Linearity (μg/mL); (n = 5) – 0.05–10 Slope 50.509 23.731 Y-intercept when X = 0 2359.6 994.84 P-value at 95% C.I. <0.0001 R 2 0.9998 Precision %RSD for intraday <2.0% 0.01 0.01 %RSD for interday <2.0% 0.02 0.01 Accuracy Initial conc. (μg/mL) Observed mean conc. (μg/mL); n = 3 Mean recovery (%) BD APL BD APL 800 ng/mL 799.51 806.62 99.94 100.83 1,000 ng/mL 973.39 901.93 97.34 90.19 1,200 ng/mL 1191.66 1193.46 99.30 99.93 LOD (ng/mL) – – 24.20 23.36 LOQ (ng/mL) 73.37 70.77 Robustness Flow rate, mobile phase ratio, column temperature, injection volume, detection wavelength RSD < 2% 1.132 1.192 Stability Sample solution (24 h) 0.97 0.96 Mobile phase (24 h) 0.99 1.01 Open in new tab Linearity Plotting the mean peak area against the resultant concentrations indicated that the chromatographic method was linear over the proposed concentration range (0.05–10 μg/mL) for both APL and BD. The calibration curve yielded a linear equation with an R2 value of 0.9997 and 0.9998 for APL and BD, respectively. Limit of detection and limit of quantification For both APL and BD, LOD were calculated to be 24.20 and 23.36 ng/mL, respectively; whereas the LOQ values were found to be 73.34 and 70.77 ng/mL for BD and APL, respectively. Precision and accuracy The data for drug recovery (in percentage) at low (800 ng/mL), middle (1,000 ng/mL) and high (1,200 ng/mL) level concentrations ranged between 96 and 102%, and %RSD values were found to be <1, which was well within the accepted limits (Table II). The results of repeatability as well as precision (both inter- and intra-day) complied with the acceptable range, i.e., < 2% for RSD and Tf and not less than 2,000 for NTP. Robustness The effect of variation in several factors viz., flow rate, column temperature, mobile phase ratio, injection volume and detection wavelength were assessed for different responses such as peak area, Rt, Tf and NTP using one factor at a time (OFAT) approach. The results of the robustness testing are presented as percentage RSD (Table II). Altering the flow rate, i.e., 0.8 ± 0.2 mL/min the % RSD was found to be 1.54 and 0.75 for APL and BD, respectively. It showed a significant effect on the Rt of both the drugs. Similarly, when column temperature was changed ±2°C from 40°C, the observed % RSD were found to be 0.96 and 0.80 for APL and BD, respectively. The Rt of the drugs did not change however, deterioration of the peak shape was observed. When mobile phase ratio was changed, a slight shift in Rt was observed with % RSD values of 1.07 and 0.99 for APL and BD, respectively. On the other hand, when injection volume and detection wavelength were changed from 10 ± 2 μL and 233 ± 2 nm, the %RSD was found to be 1.33, 0.58 and 0.56, 1.76 for APL and BD, respectively, altering the injection volume showed significant changes in peak area of both drugs while change in detection wavelength did not show any considerable effect on the peak area. With respect to Tf and NTP, by varying the above five parameters resulted in insignificant changes and they were found well within the ICH limits (RSD < 2.0%). Sample solution and mobile phase stability The sample solution was stable for 24 h as indicated by the values for recovery (96–102%) and RSD (<2.0%). The results are shown in (Table II). Force degradation studies Table III shows the results of stress induced degradation studies. Force degradation studies are necessary as it demonstrates the specificity of stability-indicating methods. It can likewise be utilized to decide the degradation pathways and degraded products of both the drugs that could form during storage, and encourage formulation development. The force degradation study relies on the fact that the chemistry of active pharmaceutical ingredients and formulation of each compound is dissimilar (43, 44). Table III Results of Force Degradation Studies for APL and BD Stress type . Stress condition . % Degraded . %Recovered . Acid hydrolysis 0.1 N HCl, 60°C, 24 h 1 N HCl, 60°C, 12 h APL BD APL BD 7.10 17.90 1.29 8.87 92.90 82.10 98.71 91.13 Base hydrolysis 0.1 N NaOH, 60°C, 24 h 1 N NaOH, 60°C, 12 h 0.65 11.29 0.65 9.19 99.35 88.71 99.35 90.81 Oxidation 3% w/v H2O2, RT, 24 h 16.94 0.81 83.06 99.19 Photolysis Under direct sunlight, 24 h 17.2 18.6 82.8 81.4 Thermal Solid drug, 60°C, 24 h 13.4 2.0 86.6 98.0 Stress type . Stress condition . % Degraded . %Recovered . Acid hydrolysis 0.1 N HCl, 60°C, 24 h 1 N HCl, 60°C, 12 h APL BD APL BD 7.10 17.90 1.29 8.87 92.90 82.10 98.71 91.13 Base hydrolysis 0.1 N NaOH, 60°C, 24 h 1 N NaOH, 60°C, 12 h 0.65 11.29 0.65 9.19 99.35 88.71 99.35 90.81 Oxidation 3% w/v H2O2, RT, 24 h 16.94 0.81 83.06 99.19 Photolysis Under direct sunlight, 24 h 17.2 18.6 82.8 81.4 Thermal Solid drug, 60°C, 24 h 13.4 2.0 86.6 98.0 Open in new tab Table III Results of Force Degradation Studies for APL and BD Stress type . Stress condition . % Degraded . %Recovered . Acid hydrolysis 0.1 N HCl, 60°C, 24 h 1 N HCl, 60°C, 12 h APL BD APL BD 7.10 17.90 1.29 8.87 92.90 82.10 98.71 91.13 Base hydrolysis 0.1 N NaOH, 60°C, 24 h 1 N NaOH, 60°C, 12 h 0.65 11.29 0.65 9.19 99.35 88.71 99.35 90.81 Oxidation 3% w/v H2O2, RT, 24 h 16.94 0.81 83.06 99.19 Photolysis Under direct sunlight, 24 h 17.2 18.6 82.8 81.4 Thermal Solid drug, 60°C, 24 h 13.4 2.0 86.6 98.0 Stress type . Stress condition . % Degraded . %Recovered . Acid hydrolysis 0.1 N HCl, 60°C, 24 h 1 N HCl, 60°C, 12 h APL BD APL BD 7.10 17.90 1.29 8.87 92.90 82.10 98.71 91.13 Base hydrolysis 0.1 N NaOH, 60°C, 24 h 1 N NaOH, 60°C, 12 h 0.65 11.29 0.65 9.19 99.35 88.71 99.35 90.81 Oxidation 3% w/v H2O2, RT, 24 h 16.94 0.81 83.06 99.19 Photolysis Under direct sunlight, 24 h 17.2 18.6 82.8 81.4 Thermal Solid drug, 60°C, 24 h 13.4 2.0 86.6 98.0 Open in new tab Acid hydrolysis Lower (12 h) and higher exposure time (24 h) at lower and higher strengths of HCl, i.e., 0.1 N and 1 N HCl were used to carry out the degradation studies. After 24 h, 0.1 N HCl degraded APL and BD to a lower extent, i.e., 7.10% and 1.29%, respectively, depicted in (Figure 3i), while higher strength (1 N HCl) degraded APL and BD to a higher extent, i.e., 17.90% and 8.87% (Figure 3iii), respectively after 12 h. Figure 3 Open in new tabDownload slide Results of forced degradation studies for APL and BD. Chromatogram obtained with (i) Acid-induced hydrolysis (0.1 N HCl) – (A) sample, (B) blank; (ii) base-induced hydrolysis (0.1 N NaOH) – (A) sample, (B) blank; (iii) acid-induced hydrolysis (1 N HCl) – (A) sample, (B) blank; (iv) base-induced hydrolysis (1 N NaOH) – (A) sample, (B) blank; (v) oxidation-induced degradation – (A) sample, (B) blank; (vi) photolytic degradation – (A) sample, (B) blank; (vii) thermal degradation – (A) sample, (B) blank. Figure 3 Open in new tabDownload slide Results of forced degradation studies for APL and BD. Chromatogram obtained with (i) Acid-induced hydrolysis (0.1 N HCl) – (A) sample, (B) blank; (ii) base-induced hydrolysis (0.1 N NaOH) – (A) sample, (B) blank; (iii) acid-induced hydrolysis (1 N HCl) – (A) sample, (B) blank; (iv) base-induced hydrolysis (1 N NaOH) – (A) sample, (B) blank; (v) oxidation-induced degradation – (A) sample, (B) blank; (vi) photolytic degradation – (A) sample, (B) blank; (vii) thermal degradation – (A) sample, (B) blank. Alkali hydrolysis Lower strength of the base (0.1 N NaOH) at higher exposure time (24 h) degraded both the drugs to a negligible extent, i.e., 0.65 ± 0.01% (Figure 3ii). While 1 N NaOH degraded APL and BD to a higher extent, i.e., 11.30 ± 0.01% and 9.17 ± 0.02% at lower exposure time (12 h) (Figure 3iv), respectively. Oxidative degradation using hydrogen peroxide In oxidative reaction, lower strength of oxidative agent (3% H2O2) did not considerably degrade BD, i.e., only 0.81 ± 0.01% degradation was seen; however, considerable degradation of APL was observed, i.e., 16.96 ± 0.02%, depicted in Figure 3v. Photolytic and thermal degradation In photolytic degradation studies, degradation of both APL and BD were observed at 17.24 ± 0.06% and 18.64 ± 0.06% (Figure 3vi), whereas in thermal degradation studies APL degraded at higher extent, i.e., 13.43 ± 0.04% while only 2.06 ± 0.05% degradation of BD was observed (Figure 3vii). Application of optimized method Both the drugs were successfully loaded into microsponges by layering technique. APL and BD were analyzed without any interference from the formulation excipients, which was determined by overlapping the chromatograms of placebo and drug-loaded microsponges with a diluent chromatogram (Figure 4). Accuracy studies for extracted drug samples, the %RSD and recovery was found to be < 2% and 98–103% for both the drugs (Table IV). The total quantity of drug (drug content) present in the formulation was found to be 4.85 ± 0.01 and 14.19 ± 0.01 mg for BD and APL, respectively of the loaded drugs. The entrapment efficiency of the microsponge formulation was observed as 97.14 ± 0.03% and 94.62 ± 0.07% for BD and APL, respectively. Figure 4 Open in new tabDownload slide Overlay chromatograms. (A) diluent, (B) placebo microsponge, (C) standard APL and BD solution, (D) microsponges loaded with APL and BD. APL: apremilast. BD: betamethasone dipropionate. Figure 4 Open in new tabDownload slide Overlay chromatograms. (A) diluent, (B) placebo microsponge, (C) standard APL and BD solution, (D) microsponges loaded with APL and BD. APL: apremilast. BD: betamethasone dipropionate. Table IV Accuracy Data for Estimation of APL and BD in Microsponge Formulation Drug . Spike level (%) . Concentration (μg/mL) . Amount recovered (μg/mL) . %RSD . %Recovery . APL 80 4.8 4.75 0.46 99.11 100 6 5.94 0.57 99.02 120 7.2 7.14 0.34 99.30 BD 80 0.8 0.817 0.84 102.23 100 1 1.02 0.52 102.46 120 1.2 1.24 0.95 103.34 Drug . Spike level (%) . Concentration (μg/mL) . Amount recovered (μg/mL) . %RSD . %Recovery . APL 80 4.8 4.75 0.46 99.11 100 6 5.94 0.57 99.02 120 7.2 7.14 0.34 99.30 BD 80 0.8 0.817 0.84 102.23 100 1 1.02 0.52 102.46 120 1.2 1.24 0.95 103.34 Open in new tab Table IV Accuracy Data for Estimation of APL and BD in Microsponge Formulation Drug . Spike level (%) . Concentration (μg/mL) . Amount recovered (μg/mL) . %RSD . %Recovery . APL 80 4.8 4.75 0.46 99.11 100 6 5.94 0.57 99.02 120 7.2 7.14 0.34 99.30 BD 80 0.8 0.817 0.84 102.23 100 1 1.02 0.52 102.46 120 1.2 1.24 0.95 103.34 Drug . Spike level (%) . Concentration (μg/mL) . Amount recovered (μg/mL) . %RSD . %Recovery . APL 80 4.8 4.75 0.46 99.11 100 6 5.94 0.57 99.02 120 7.2 7.14 0.34 99.30 BD 80 0.8 0.817 0.84 102.23 100 1 1.02 0.52 102.46 120 1.2 1.24 0.95 103.34 Open in new tab Discussion Throughout the analytical method development, numerous trials with different mobile phases were engaged for the best separation of APL and BD. As the pH has a strong effect on the peak shape and elution of the component, mobile phase pH should be adjusted so as to allow complete ionization or unionization of drug. The pKa of APL is ~4.83, whereas BD has a pKa ~12.42 which indicates that BD is unaffected by pH changes in mobile phase (28, 31). Based on this, standard buffer solutions having different pH were evaluated, viz. pH 3.0 TFA buffer (0.03% in water), pH 6.1 potassium phosphate buffer and pH 5.5 sodium phosphate buffer. The method development was initiated using a mobile phase system comprising 0.03% TFA in water (pH 3.0). Being an acidic pH, both the drugs (APL and BD) retained at a lesser Rt, with poor peak resolution, Tf and lesser NTP which may be detrimental when estimation is performed in skin homogenates (47). For acidic drugs to be separated in neutral form, basic pH or weakly acidic pH is required. Therefore, we moved ahead with phosphate buffers of varying pH for better separation. In comparison to pH 3.0 TFA buffer, pH 6.1 potassium phosphate buffer yielded a better peak with respect to Rt, peak shape, Tf and NTP. As skin pH is 5.5, it was thought that elution of both the drugs must be better in pH 5.5 sodium phosphate buffer. However, no peak elution was observed at this pH. Therefore, we went ahead by making use of pH 6.1 potassium phosphate buffer (60%) and ACN (40%) as the mobile phase system which gave acceptable Rt for both APL and BD with good peak shape and optimum Tf and NTP. Therefore, 50 mM pH 6.1 potassium phosphate buffer with 0.1% TEA was selected as the aqueous phase. ACN was used as the organic phase as it possesses more organic nature than methanol and is expected to improve the tailing of the drugs. Currently, the DoE used for analytical method development, known as analytical DoE, has gained popularity and is much in use nowadays as it includes both screening and optimization to obtain the best method through response surface methodology with a logical spatial design, and suggesting strategies to continuously improve the outcomes (20, 27). Over the years, the use of DoE as an analytical approach to develop affordable and effective chromatographic methods for identification and quantification of analytes has been well documented (36, 38). Estimation of drug either alone or in combination, present in a pharmaceutical formulation or in bulk drugs using a DoE-aided methodology greatly helps in devising the formulation strategy (38). Hence, in the present study, we employed a DoE-based approach to develop and validate a RP-HPLC method to simultaneously quantify APL and BD, both in bulk drug as well as in microsponge formulations. In addition, DoE was utilized to optimize the analytical method (by employing column temperature and flow rate as factors and the resultant effect was observed on the responses such as Rt, peak area, Tf and NTP) to simultaneously estimate APL and BD from its combination system. From Equation (1), it is evident that a negative effect on Rt of APL was observed by varying the column temperature and flow rate. Both column temperature and flow rate significantly contributed to the negative effect indicating that increase in flow rate and column temperature decreased the Rt. From Equation (2), it was observed that, Rt of BD decreased considerably, on change in flow rate while no significant effect was observed by varying the column temperature as indicated by the ANOVA analysis. Similarly, Equations (3 and 4) indicates an increase in flow rate resulted in a decrease in peak area of APL and BD indicating a negative effect. On the other hand, an increase in column temperature had a positive effect on the peak area of BD, while no significant effect was seen on the peak area of APL. From Equation (5), it is evident that, and changes in flow rate had a significant positive effect on Tf of APL while no significant effect was observed on Tf of APL on varying column temperature. While Equation (6) showed a significant positive effect on Tf of BD by varying column temperature and flow rate. A significant positive effect was also observed on NTP of APL and BD by varying the column temperature indicated by Equations (7 and 8). Contrarily, no significant change was observed on NTP of both drugs on varying the flow rate. All these results indicate that at intermediary stages of flow rate and column temperature, i.e., 1.0 mL/min and 40°C, the results were found to be satisfactory with respect to peak area, Rt, Tf and NTP. Analysis of the model using ANOVA revealed the statistical significance of the model parameters. The model demonstrated a desirability value of 1 and numerical point prediction was used to select the optimized mobile phase parameters (1, 36). Overall, the chromatographic method was observed to be accurate and precise which was concluded from calibration curve, linearity, accuracy, precision, LOD and LOQ studies. This method was also found to be robust upon deliberately altering the method variables (flow rate, injection volume, detection wavelength, column temperature and mobile phase ratio), and the %RSD value of the responses was found to be acceptable as per ICH guidelines (<2.0%). Hence, the simultaneous estimation method that was developed in the present study was found to be appropriate in estimating APL and BD. Although in all the stress conditions both the drugs showed some extent of degradation, the magnitude was <20%, which is generally accepted limit as per ICH guidelines. Overall, exposure of both the drugs at varying stress conditions revealed greater than 80% drug recovery which indicates that both APL and BD were stable and showed minimal degradation in all stress conditions. The results for drug recovery and %RSD showed the exceptional precision and accuracy of the currently developed method in determining the microsponge content of APL and BD (45, 47). Therefore, the developed analytical method can be effectively used for the simultaneously quantifying APL and BD in bulk and microsponge formulation. Conclusion In the absence of a suitable chromatographic method for quantifying APL and BD simultaneously, the method developed, optimized and validated in the current study is unique for their quantification in bulk drugs and in microsponge formulations. Both APL and BD were stable when exposed to varying stress conditions. A DoE-based CCD model was found to be appropriate for the optimization of the chromatographic method for estimation of APL and BD. The optimized, validated and stable chromatographic method developed in the present study conforms to the acceptance criteria as per ICH requirements (48). The developed method can be extended to estimate the content of APL and BD in a variety of pharmaceutical formulations. Acknowledgements The authors are grateful to Glenmark Pharmaceuticals (Mumbai, India) and Sun Pharma (Gurugram, India) for providing the gift samples of active pharmaceutical ingredients. Authors are thankful to (1) Biotechnology Industry Research Assistance Council (BIRAC), Department of Biotechnology, Government of India, New Delhi and Indian Council of Medical Research (ICMR), Government of India, New Delhi (for providing Senior Research Fellowship to Ms Prashansha Mullick), (2) to Department of Science and Technology (DST), Government of India, New Delhi (for providing DST-INSPIRE fellowship to Ms Sadhana P Mutalik) and (3) to Manipal Academy of Higher Education, Manipal (for providing Postdoctoral Research Fellowship to Dr Abhijeet Pandey). The authors are also grateful to Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal for providing the facilities. Conflict of Interest Authors report no conflict of interest. Reference 1. 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TI - Simultaneous Estimation of Apremilast and Betamethasone Dipropionate in Microsponge-Based Topical Formulation using a Stability Indicating RP-HPLC Method: A Quality-by-Design Approach
JF - Journal of Chromatographic Science
DO - 10.1093/chromsci/bmab016
DA - 2021-02-23
UR - https://www.deepdyve.com/lp/oxford-university-press/simultaneous-estimation-of-apremilast-and-betamethasone-dipropionate-9wfS67EIIP
SP - 1
EP - 1
VL - Advance Article
IS - 
DP - DeepDyve
ER -