Development Of Chromatographic Method Research Articles

Box-Behnken design in optimization of the green liquid chromatographic method for the quantification of Afatinib in drug product: AQbD approach

The aim of this research work was to quantitatively determine the tyrosine kinase inhibitor, Afatinib, in tablets using an eco-friendly chromatographic method. The development of a green liquid chromatographic method using analytical quality-by-design (AQbD) approach principles to estimate Afatinib via Box-Behnken design. A simple and effective green liquid chromatographic method was developed and validated. The analysis was done on the Zodiac C18 column by isocratic elution mode. Mobile phase composed of pH 3.0 potassium dihydrogen phosphate buffer and ethanol in the ratio of 65:35%V/V. The flow rate was set to 0.6 mL/min. with an injection volume of 10 µL and at detection wavelength of 254 nm. The optimized method was found to be specific, linear, precise, accurate, and robust. Established linearity in the range of 24.6 to 73.9 µg/mL. The developed method exhibited excellent greenness. Based on the greenness assessment tools, the analytical eco-score value of 94 and the pictograms of NEMI, Modified NEMI, GAPI, Complex GAPI, AGREE, and AGREE prep expressed the method’s greenness. Hence, the AQbD approach based green method and the validation data indicate that the method can be employed in routine analysis for the determination of Afatinib in pharmaceutical dosage form in quality control laboratory use.

Assisted Active Learning for Model-Based Method Development in Liquid Chromatography.

In recent decades, there has been a growing interest in fully automated methods for tackling complex optimization problems across various fields. Active learning (AL) and its variant, assisted active learning (AAL), incorporating guidance or assistance from external sources into the learning process, play key roles in this automation by enabling the autonomous selection of optimal experimental conditions to efficiently explore the problem space. These approaches are particularly valuable in situations wherein experimentation is costly or time-consuming. This study explores the application of AAL in model-based method development (MD) for liquid chromatography (LC) by using Bayesian statistics to incorporate historical data and analyte information for the generation of initial retention models. The process involves updating the model parameters based on new experiments, coupled with an active data selection method to choose the most informative experiment to run in a subsequent step. This iterative process balances model exploitation and experimental exploration until a satisfactory separation is achieved. The effectiveness of this approach is demonstrated via two practical examples, resulting in optimized separations in a limited number of experiments by optimizing the gradient slope. It is shown that the ability of AAL to leverage past knowledge and compound information to improve accuracy and reduce experimental runs offers a flexible alternative approach to fixed design methods.

A Quality by Design (QbD) driven gradient high performance liquid chromatography method development for the simultaneous estimation of dasatinib and nilotinib in lipid nanocarriers

Tyrosine kinase inhibitors (TKIs) are effective as a targeted treatment for chronic myeloid leukemia (CML), which can selectively suppress BCR-ABL1 kinase activity. CML therapy with TKIs combination has been supported by in-vitro, in-vivo, and patient-based data where the nilotinib-dasatinib co-administration has exerted superior anticancer efficacy with greater cellular uptake, less resistance to chemotherapy, and no additive adverse events encountered. Therefore, it is essential to develop a suitable analytical method for the simultaneous estimation of these drugs in the developed novel lipid nanocarriers like liposomes. Design of Experiment (DoE) has been implemented as a tool of QbD to systematically investigate the relation between the HPLC method attributes and analytical responses, i.e., chromatographic detection, quantification, and peak properties for dasatinib and nilotinib. An Ishikawa diagram is constructed to delineate possible influencing variables to the analytical performances. Afterward, 4 factors 2 level full factorial design (FFD) was employed to model and identify the main effects and interaction effects between the factors selected after the initial risk assessment. The suggested design space for optimized chromatographic conditions by QbD analysis is linear within the selected range of drug concentrations, accurate and precise, sensitive, and robust according to the ICH guidelines. The optimal method is comprised of a 1 mL/min flow rate of mobile phase (ACN and 20 mM KH2PO4 of pH 7.00) in gradient mode at 25 °C column temperature for 20 μL sample injection volume and detection wavelength fixed at 297 nm. Most importantly, this novel HPLC method is simple and selective enough to evaluate dasatinib and nilotinib content in the lipid nanocarriers.

Development and Validation of a Novel Stability-Indicating Reverse Phase High-Performance Liquid Chromatography Method for the Quantification of Capivasertib in Bulk Drug and Pharmaceutical Dosage Form

The quantification of capivasertib has been achieved using a Waters Symmetry column with UV detection at 260 nm through a novel stability-indicating reverse-phase high-performance liquid chromatography (RP-HPLC) method that has been established and verified. The analysis can be completed in just 5 minutes. The separation and collection of capivasertib occurred at a retention time of 3.3475 minutes. The concentration range of capivasertib was shown to be linear, ranging from 50 to 300 μg/mL. The regression equations for capivasertib were determined as y = 13485.85x + 1723.04. The detection limit for capivasertib was determined to be 0.6 μg/mL, while the quantification limits were established at 2.00 and 0.5000 μg/mL, respectively.

Development and optimization of high-performance extraction chromatography method for separation of rare earth elements

The effectiveness of commonly used extractants for chromatographic separation of rare earth elements (REEs) was compared. Columns loaded with similar molar concentrations of tributyl phosphate (TBP), di-(2-ethylhexyl) phosphoric acid (HDEHP), and N-Methyl-N, N, N-tri-octyl-ammonium chloride (Aliquat-336), with mineral acid as eluent were evaluated. Retention factors were determined, and separation efficiency was assessed based on the resolution data of the REEs acquired under the same elution conditions for each column. HDEHP demonstrated the best separation efficiency for the entire REE series (mean Rs = 2.76), followed by TBP (mean Rs = 1.52), while Aliquat-336 exhibited the lowest performance (mean Rs = 1.42). The HDEHP-coated column was then used to optimize the extraction chromatographic separation of the REEs. The primary challenge was to completely elute the heavy REEs (Tb – Lu) while maintaining adequate separation of the light REEs (La – Gd) within a reasonably short time. The stepwise gradient elution procedure improved the resolution between adjacent REEs, allowing the complete separation of the entire REE series within 25 minutes. Better separation efficiency for light REEs was achieved at higher column temperatures and a mobile phase flow rate of 1.5 mL/min in the tested domain of 20–60 °C, and 0.5–2.0 mL/min, respectively, resulting in plate heights (H) ranging from 0.011 to 0.027 mm.

Analytical QbD for the optimization of a multimode HPLC method for the investigation of hydrochlorothiazide, diltiazem and propranolol release from 3D printed formulation

Since 3D printing technology is an emerging field in pharmaceutical technology, the present study aimed at the development of a mixed-mode liquid chromatographic method for the separation and determination of hydrochlorothiazide, diltiazem, and propranolol to investigate their in-vitro release performance from 3D printed tablets. Due to the unique properties of the mixed-mode stationary phase, the three drugs were separated in less than 8 min under isocratic elution. Method development was accomplished following the Analytical Quality by Design principles and was evaluated using risk assessment and multivariate analysis. The influences of critical method parameters on critical method attributes (were screened using a 2-level fractional factorial design and subsequently optimized through a central composite design. The method operable design region was approved by the establishment of a robust zone using Monte Carlo simulation and capability analysis. The validation of the HPLC method was performed based on the total error concept. The relative bias was varied between ─ 11.6 % and 10.5 % and the RSD values for repeatability and intermediate precision were below 4.4 % in all cases. The limits of detection (LOD) ranged between 0.17 – 0.90 μg/mL and were adequate for the specific application. The developed method was successfully applied to the analysis of the studied drugs in in-vitro drug release samples obtained from 3D-printed tablets combining the above-mentioned active pharmaceutical ingredients (APIs).

Development and Validation of Ultra-Performance Liquid Chromatography (UPLC) Method for Simultaneous Quantification of Hydrochlorothiazide, Amlodipine Besylate, and Valsartan in Marketed Fixed-Dose Combination Tablet

Fixed-dose combination therapy is considered a practical approach in the treatment of various diseases, as it can simultaneously target different mechanisms of action that achieve the required therapeutic efficacy through a synergistic effect. A combination of hydrochlorothiazide (HTZ), amlodipine (AMD), and valsartan (VLS) has been created for the treatment of hypertension. Therefore, the aim of this study was to develop an optimized UPLC method for the simultaneous quantification of this combination. A DoE at a level of 32 was used to investigate the effects of column temperature (20, 30, and 40 °C) and formic acid concentration (0.05, 0.15, and 0.25%) on the retention time of each active pharmaceutical ingredient (API), the peak area, and the peak symmetry, as well as the resolution between HTZ-AMD and AMD-VLS peaks. The optimized analytical method was validated and used to extract the three APIs from the marketed product. The optimized analytical condition with a column temperature of 27.86 °C and a formic acid concentration of 0.172% showed good separation of the three APIs in 1.62 ± 0.006, 3.59 ± 0.002, and 3.94 ± 0.002 min for HTZ, AMD, and VST, respectively. The developed method was linear with the LOQ for a HTC, AMD, and VST of 0.028, 0.038, and 0.101 ppm, respectively. Moreover, the developed assay was sustainable and robust, with an RSD % of less than 2%. The application of this method in the extraction of HTZ, AMD, and VST from the Exforge® marketed product showed good separation with a measurable drug content of 23.5 ± 0.7, 9.68 ± 0.1, and 165.2 ± 5.2 mg compared to the label claims of 25/10/160 for HTZ, AMD, and VST, respectively.

Development of a high-performance liquid chromatography (HPLC) method for analysis of charantin in bitter gourd (Momordica charantia) fruits

Development of a high-performance liquid chromatography (HPLC) method for analysis of charantin in bitter gourd (Momordica charantia) fruits

Development of a liquid chromatographic method with a different selectivity for the quantification of eighteen phytocannabinoids in hemp

To quantify phytocannabinoids in hemp, liquid chromatography diode array detector (LC-DAD) methods are favored, but their selectivity depends on baseline separation of all phytocannabinoids and unknown compounds in an extract. Therefore, development of a LC-DAD method with a different selectivity has become highly desirable. Currently, most LC-DAD methods use the water/acetonitrile eluting system, while this study aimed to use the water/methanol eluting system. A systematic investigation of various chromatographic parameters on LC separation of eighteen phytocannabinoids, the maximum number that has been quantified in hemp so far, plus two potential internal standards, led to a four-step isocratic mobile phase that was able to baseline separate the twenty compounds with a significantly different eluting order from published methods. Although changes in the mobile phase composition caused baseline drifts, consequent difficulty in quantification was avoided through detection at wavelengths longer than 230 nm. Subsequently, the method was validated according to the ISO 17025 guidelines, calibrated between 0.04 and 50 µg/mL, and used to analyze phytocannabinoids in nine strains of hemp flowers that were extracted using methanol between 0.04 and 50 % (w/w). Extraction recovery was tracked in real-time by spiking one of the two potential internal standards, i.e., abnormal cannabidiol (ACBD), a cannabinoid not naturally present in hemp. Method selectivity was further assessed by electrospray ionization time-of-flight mass spectrometry (ESI/TOFMS), indicating minimum interferences. In addition, five untargeted/unknown phytocannabinoids were identified by ESI/TOFMS, including two structural isomers of Δ9-tetrahydrocannabinol (Δ9-THC), two structural isomers of Δ9-tetrahydrocannabinolic acid (Δ9-THCA), and one structural isomer of Δ9-THC acetate.

Evaluating the effectiveness of different household washing techniques for removal of insecticides from spinach and chickpea leaves by micellar liquid chromatography

In the past few decades, the employment of green analytical approaches in chromatographic method development has attracted the analytical separation community. The greenness of the developed method depends upon the toxicity of solvents and the amount of generated post-analysis waste generated. In this concern, micellar liquid chromatography (MLC) is a simple and rapid technique that generates very low toxic waste compared to traditional chromatographic pesticide detection methods. Here, MLC method has been validated and applied for the determination of monocrotofos (MCF), imidacloprid (ICP), dimethoate (DM) and profenofos (PFF) in spinach and chickpea leaves. The optimized mobile phase was 0.065 M SDS-2 % 1-propanol, 0.01 M NaH2PO4 buffered to pH 7. A C18 column was used for separation with a flow rate of 1 mL/min. The developed method has been validated following the guidelines of SANTE/11,312/2021 and ICH guidelines for; limit of quantification (0.05–0.20 mg/kg), linearity (r2> 0.997–0.999), precision (<6.3 %), accuracy (96.3 %–99.8 %) and robustness (<6) in real samples. ICP and MCF, apart from DM and PFF, were detected in the present work. After detecting insecticides in spinach and chickpea leaves both were washed with different household chemicals i.e. normal, lukewarm, common salt, lemon juice water and commercial ozonizer. Based on five washing techniques with insecticide concentration time intervals reduction rates were calculated for each washing treatment. The results show that lemon juice, common salt water, and ozonizer can be used as washing techniques for the reduction of superficial and systematic residues of ICP and MCF. Common salt and lemon juice water were better for washing over vinegar and potassium permanganate (KMnO4) as they enhance the colour of the green leafy vegetables and are available in every Indian kitchen. They can be easily used by lower socioeconomic classes who cannot afford KMnO4 and vinegar.

Development and Validation of High-Performance Thin Layer Chromatographic Method for Estimation of Acyclovir

Development and Validation of High-Performance Thin Layer Chromatographic Method for Estimation of Acyclovir

Development and validation of high-performance liquid chromatography method for the simultaneous quantification of rivastigmine hydrogen tartrate and asiaticoside co-loaded in niosomes: A Box–Behnken design approach

Rivastigmine hydrogen tartrate (RHT), a reversible cholinesterase inhibitor, is considered as the first-line therapy for mild to moderate Alzheimer’s disease. Asiaticoside (AS), a pentacyclic triterpenoid saponin, is well known as cognitive enhancer due to its antioxidant effect. Based on the hypothesis of their synergistic therapeutic potential, RHT and AS were co-encapsulated in niosomal formulation. A simple, precise, and accurate high-performance liquid chromatography method was developed for simultaneous quantitative analysis. The chromatographic parameters were optimized by Box-Behnken experimental design. The separation was performed on a reversed-phase Phenomenex C18 (150 mm × 4.6 mm, 5 μm) column at 30 °C under the UV detection of 210 nm. The optimized mobile phase consisted of a mixture of 20 mM potassium dihydrogen phosphate buffer (pH 2.6) and acetonitrile (72:28 % v/v) under the isocratic mode at the flow rate of 0.9 mL/min. The developed method was fully validated under the ICH guidelines and could be successfully applied for simultaneous quantitative analysis of RHT and AS in niosomal formulation.

A new chromatographic response function with automatically adapting weight factor for automated method development

A critical factor for automated method development in chromatography is the maximization or minimization of an objective function describing the quality (and speed) of the separation. In chromatography, this function is commonly referred to as a chromatographic response function (CRF). Many CRFs have previously been introduced, but many have unfavourable properties such as featuring multiple optima, insufficient discriminatory power, and a too strong dependence on the weight factors needed to balance resolution and time penalty components. To overcome these problems, the present study introduces a new type of CRF wherein the relative weight of the time penalty term is a self-adaptive function of the separation quality. The ability to unambiguously identify the optimal gradient settings of this newly proposed CRF is compared to that of some of the most frequently used CRFs in a study covering 100 randomly composed in silico samples. Doing so, the new CRF is found to flawlessly lead to the correct solution (=linear gradient parameters providing the highest resolution in the shortest potential time) in 100 % of the cases, while the most frequently used literature CRFs were off-target for about 50 to 60 % of the samples, even when considering the availability of spectral peak shape data. Some slight alterations to the proposed CRF are introduced and discussed as well.

Quality by design‐engineered reversed‐phase high‐performance liquid chromatography method development and validation for simultaneous estimation of neomycin sulfate and beclomethasone dipropionate in bulk and pharmaceutical dosage form

AbstractThe aim of this study was to develop and validate a robust reversed‐phase high‐performance liquid chromatography (RP‐HPLC) method for the simultaneous estimation of neomycin sulfate (NEO) and beclomethasone dipropionate (BECLO) in both bulk drug and pharmaceutical dosage forms. The analysis was conducted using the Box‐Behnken design. The separation of NEO and BECLO was conducted on a Phenomenex Luna C‐18 column (4.6 × 150 mm, 5 µm), employing a mobile phase comprising a mixture of methanol and trifluoroacetic acid in a ratio of 88:12% v/v. The separation was performed at a flow rate of 0.6 mL/min. NEO and BECLO were analyzed at a wavelength of 240 nm employing a photodiode array detector. The validation of the methodology followed the guidelines outlined in the International Council for Harmonization Q2 R (1). The validation process involved assessing critical parameters such as linearity, accuracy, system suitability, precision, and robustness. The results for each parameter were found to be within the acceptable range. The results indicate that the established RP‐HPLC method can effectively be employed for the routine analysis of NEO and BECLO in bulk drug and pharmaceutical dosage forms.

Enhancing LC×LC separations through multi-task Bayesian optimization

Method development in comprehensive two-dimensional liquid chromatography (LC×LC) is a challenging process. The interdependencies between the two dimensions and the possibility of incorporating complex gradient profiles, such as multi-segmented gradients or shifting gradients, make trial-and-error method development time-consuming and highly dependent on user experience. Retention modeling and Bayesian optimization (BO) have been proposed as solutions to mitigate these issues. However, both approaches have their strengths and weaknesses. On the one hand, retention modeling, which approximates true retention behavior, depends on effective peak tracking and accurate retention time and width predictions, which are increasingly challenging for complex samples and advanced gradient assemblies. On the other hand, Bayesian optimization may require many experiments when dealing with many adjustable parameters, as in LC×LC. Therefore, in this work, we investigate the use of multi-task Bayesian optimization (MTBO), a method that can combine information from both retention modeling and experimental measurements. The algorithm was first tested and compared with BO using a synthetic retention modeling test case, where it was shown that MTBO finds better optima with fewer method-development iterations than conventional BO. Next, the algorithm was tested on the optimization of a method for a pesticide sample and we found that the algorithm was able to improve upon the initial scanning experiments. Multi-task Bayesian optimization is a promising technique in situations where modeling retention is challenging, and the high number of adjustable parameters and/or limited optimization budget makes traditional Bayesian optimization impractical.

A bioanalytical assay for estimation of thymoquinone in rats cerebrospinal fluid and brain tissues of nasally administrated thymoquinone loaded lipo-polymeric nanoshells and its pharmacokinetic profiling

Thymoquinone (TH) has been one of the major phytochemical used in the treatment of cancers since long time, especially in the management of glioblastoma multiforme (GBM). The formulation of lipo-polymeric nanoshells (LPNs) and their nasal delivery are fascinating approaches for overcoming the drawbacks of low solubility and poor bioavailability of TH. Hence targeting LPNs to the brain requires a validated bioanalytical method for the assessment of TH concentration in Cerebrospinal fluid (CSF) and brain tissue homogenates (BTH). Therefore, the current work focuses on the development and validation of high-performance liquid chromatography (HPLC) method in CSF by employing nasal simulated fluid (NSF) as one of the major components of the mobile phase. The developed method was checked for linearity in the range of 0.05 to 1.6 μg/mL, having an r2 value of 0.999 with mean % recovery >95% and % RSD values below <2.0%. The developed method gave a clear separation of TH at 6.021 ± 0.17 min with an internal standard at 4.102 ± 0.09 min and a CSF spike at 2.170 ± 0.12 min. The developed method assisted in determining the in-vitro and in-vivo drug release study of LPNs, pharmacokinetic profiling, qualitative in-vivo brain uptake study, in-vitro cellular uptake, and generating stability data of formulated LPNs proposed for intranasal administration in rats.

Development and validation of a high-performance thin-layer chromatography method for detection of sibutramine in dietary supplements.

In the period between 1997 and 2010, sibutramine-containing drugs were widely prescribed for obesity and over-weight management. Due to safety concerns, in 2010 all medicines containing sibutramine were urgently withdrawn from the USA and European pharmaceutical market. Although sibutramine is no longer available in pharmaceutical products, there have been numerous reports of mislabeled weight-loss dietary supplements containing sibutramine.

Stability indicating high performance thin layer chromatography method development and validation for quantitative determination of tetracycline hydrochloride in tetracycline hydrochloride active pharmaceutical ingredient (API) and its dosage forms

Simple, quick, cost-effective, and environmentally friendly analytical methods for quality assurance and control roles for different medicines, including Tetrcyclines, are most significantly needed. Also, different thin layer chromatography (TLC)-based methods for tetracycline identification exist, but high performance thin layer chromatography methods based on modern state- of- the art equipment are still nonexistent. Thus, in this study, analytical method development and verification were done by high performance thin layer chromatography (HPTLC) (using an automated equipment model) using glass plates coated with silica gel 60 F254 after treating with 10% Na2EDTA. Validation was carried out according to International Council for Harmonization (ICH) guidelines. A mobile phase formed from ethyl acetate, acetonitrile, methanol, and 1% aqueous ammonia in the composition of 4.4:19.6:10:6 volume to volume ratio (V/V) was used. Rf value, percentage recoveries, linearity ranges, limit of detection (LOD), and limit of quantitation (LOQ) for the developed HPTLC method were 0.28, 100.83–106.25%, 160–560 ng/band (r2 values of 0.9999), 31.9 ng/band, and 96.7 ng/band, respectively. The results of the sample assays conducted using the new method and the United States Pharmacopoeia (USP) high performance liquid chromatography (HPLC) method were 91.59% to 108.3% and 90.83% to 102.85%, respectively. The F test for the aforementioned methods was 2.01, which is smaller than the tabulated F value of 5.05 with 5 degrees of freedom at a 95% confidence range, proving that the newly developed HPTLC and HPLC pharmacopoeial methods can be used interchangeably.The newly developed HPTLC method is easy, economical, specific, accurate, and roboust, thus it can be employed in a range of settings that require quality control and assurance activities of tetracycline hydrochloride (TC-HCl) in bulk and ointment dosage forms.

Development and Validation of High-Performance Thin Layer Chromatographic Method for Simultaneous Estimation of Curcumin and Artemisinin

Curcumin and Artemisinin are proposed to be formulated as combination therapy to expand the antimalarial effect in resistant and liable isolates. The present research work was to develop and validate a simple, accurate, precise, high-performance thin layer chromatographic method for simultaneous determination of Curcumin and Artemisinin. The chromatographic separation was carried out on a precoated silica gel aluminum plate, 20 × 20 cm, 100μm thickness, with a mixture of Hexane, Toluene and Ethyl acetate (6:1:3) as mobile phase UV detection was performed at 496nm. The Rf were 0.23 and 0.76 for Curcumin and Artemisinin, respectively. Calibration plots were linear over the concentration range 200-1000ng/band for both Curcumin and Artemisinin. The method was validated in accordance with ICH Q2(R1) guidelines for linearity, sensitivity accuracy, precision, and robustness. The percent recoveries in terms of accuracy for the synthetic mixture were found to be 99.8% to 100.0% and 99.94% to 100.4%, and the pooled percent relative standard deviation for repeatability and intermediate precision studies was found to be 0.015-0.042% and 0.008-0.070% for Curcumin and Artemisinin, respectively. A factorial design was used to optimize the chromatographic conditions for the robustness study. In conclusion, a novel, simple, accurate and reproducible HPTLC method was developed and could be applied for quality control testing of Curcumin and Artemisinin in synthetic mixture.

Robust high-performance thin-layer chromatography (HPTLC) method for stability assessment and simultaneous quantification of epigallocatechin-3-gallate and rosmarinic acid in lipid-based nanoparticles and biological matrices.

Skin cancer poses a significant health risk globally, necessitating effective and safe therapeutic interventions. Epigallocatechin-3-gallate (EGCG) from green tea and rosmarinic acid (RA) from herbs like rosemary offer promising anticancer properties. Combining these compounds may enhance their effectiveness, prompting the need for a reliable analytical method to quantify them. Herein, we present the development and validation of a high-performance thin-layer chromatography (HPTLC) method for concurrent quantification of EGCG and RA in lipid-based nanoparticles and biological samples. The method underwent optimisation through design of experiments (DoE), resulting in the establishment of robust chromatographic conditions. The separation process utilised aluminium HPTLC plates coated with silica gel 60 F254 as the stationary phase, with the mobile phase comprising ethyl acetate, toluene, formic acid, and methanol in a ratio of 4:4:1:1 v/v. The retention factor (Rf) values obtained were 0.38 for EGCG and 0.61 for RA. The method demonstrated linearity over a range of 100-500 ng/band for both compounds with excellent correlation coefficients. Limits of detection and quantification were determined, indicating high sensitivity. Precision evaluations revealed relative standard deviation below 2%, ensuring method reproducibility. Recovery assays in lipid-based nanoparticles, plasma, and urine samples demonstrated excellent recoveries (96.2%-102.1%). Forced degradation studies revealed minimal degradation under various stress conditions, with photolytic degradation showing the least impact. The developed HPTLC method offers a rapid, sensitive, and reliable approach for quantifying EGCG and RA, laying the groundwork for their further investigation as anticancer agents alone and in combination therapies.