HPLC Method Development and Validation for Estimation of Fluticasone Furoate & Vilanterol Trifenatate in Bulk and Dosage Form by Using Quality by Design Approach

QbD principles proactively build quality into analytical methods by understanding component interactions through systematic testing. Robustness and ruggedness are crucial early in HPLC method development under QbD.¹ Fluticasone furoate and Vilanterol trifenatate are two active pharmaceutical ingredients commonly co-formulated for the treatment of respiratory conditions such as asthma and chronic obstructive pulmonary disease (COPD). Accurate and reliable analytical methods are crucial for their quality control in both bulk drug substances and pharmaceutical dosage forms. High-Performance Liquid Chromatography (HPLC) is a widely utilized technique in pharmaceutical analysis due to its sensitivity, selectivity, and versatility. Traditionally, HPLC method development has relied on empirical approaches, which can be time-consuming and may not always lead to robust methods. In recent years, the Quality by Design (QbD) approach, as advocated by regulatory bodies like the International Conference on Harmonisation (ICH), has gained significant traction in pharmaceutical development, including analytical methods. QbD emphasizes a systematic, risk-based approach to method development, focusing on understanding and controlling critical parameters to ensure predefined quality attributes are met consistently. This paradigm shift from "quality by testing" to "quality by design" leads to more robust, reliable, and efficient analytical methods. The core elements of QbD in analytical methods include defining the Analytical Target Profile (ATP), identifying Critical Quality Attributes (CQAs), understanding Critical Process Parameters (CPPs), conducting comprehensive Risk Assessment, employing systematic Method Design (including Design of Experiments (DoE)), and establishing a robust Control Strategy. The ATP defines the measurement goal and performance criteria, guiding the entire method development process. CQAs are the key response variables directly linked to the quality of the chromatogram, such as resolution, peak shape, and retention time. CPPs are the method parameters whose variability can impact the CQAs, necessitating their monitoring and control. Risk assessment tools, like Ishikawa diagrams and FMEA, help identify potential method variables and attributes that could affect method performance. Method design, often incorporating DoE (such as Box-Behnken design or factorial design), allows for the multivariate analysis of CPPs and their interactions, leading to a comprehensive understanding of the method's behaviour and the establishment of a Design Space (DS) where the method remains robust. Finally, a robust Control Strategy ensures the method consistently meets its predefined objectives throughout its lifecycle. This research article aims to develop and validate a novel, sensitive, and robust HPLC method for the simultaneous estimation of Fluticasone furoate and Vilanterol trifenatate in bulk and pharmaceutical dosage forms, incorporating the principles of the QbD approach. By systematically applying QbD elements, including defining ATP, identifying CQAs, performing risk assessment, utilizing DoE for method optimization, and establishing a robust control strategy, this study seeks to achieve a highly reliable and validated analytical method that ensures the quality and safety of these crucial pharmaceutical products.

Elements of QbD in Analytical Methods

1.2.1. Analytical Target Profile (ATP): ATP defines the measurement goal (analyte, performance criteria like accuracy, precision, range) guiding method selection for optimal selectivity, efficiency, and reproducibility. For HPLC, initial parameters (column, pH, modifier) are evaluated before defining Quality Target Product Profile (QTPP) and Critical Quality Attributes (CQAs).²

1.2.2. Critical Quality Attribute (CQA): CQAs are essential physical, chemical, biological, or microbiological properties within acceptable limits to ensure product quality. In analysis, CQAs are key response variables linked to chromatogram quality, categorized as "aim to have" or "must have" (e.g., resolution ≥ 1.8/1.5). Examples include resolution (Rs), run time, efficiency, resilience, and the separation criterion (S). S, while correlated with Rs, offers simpler calculation and lower uncertainty.³

1.2.3. Critical Process Parameters (CPP): CPPs are parameters whose variability impacts CQAs and thus require monitoring/control to ensure desired quality in both product and analytical methods. Parameters are unclassified, critical (affecting ATP compliance), or non-critical. Development aims to classify unclassified parameters; otherwise, they need fixed values or narrow ranges. Design Space (DS) represents a theoretical robustness zone where CQA levels remain stable. Defining an analytical DS involves simultaneously studying CPPs (operating factors like gradient time in chromatography) identified through risk analysis.^4,5

1.2.4. Risk Assessment: ICH Q9 outlines risk assessment as identification, analysis, and evaluation of potential method variables (PMVs) and attributes (PMAs) related to man, material, machine, method, environment, and measurement. Tools like Ishikawa diagrams aid in this. Risk assessment, using tools like FMEA (Risk Priority Number = Probability × Severity × Detectability), identifies critical factors affecting CQAs, guiding further studies.⁶

1.3. Method Design: Method design involves planning experimental conditions and resource availability, considering regional factors and instrument feasibility. For HPLC, scouting experiments explore parameters (pH, temperature, columns, buffers). Software aids in predicting chromatographic condition effects, optimizing resolution and run time cost-effectively. Method design includes selecting appropriate analytical techniques (e.g., HPLC-PDA for impurities) and should align with standardized approaches for seamless method transfer. Method Development Strategy (MDS), including Design of Experiments (DoE), facilitates risk assessment and control strategies. DoE enables multivariate analysis of parameters (e.g., HPLC wavelength, flow rate) on method performance.⁷

1.3.1. Design of Experiment (DoE): DoE involves defining factors and responses, creating a design model, evaluating it, and interpreting results for decision-making. DoE software aids Analytical Method Development (AMD). Unlike single-factor studies, DoE enables multivariate analysis to understand parameter impacts (e.g., HPLC conditions on retention, resolution). Software can generate best-fit equations and define design space. Analyst training in basic statistics is needed. Depending on complexity, full factorial designs can be used. DoE, a more efficient alternative to OFAT, maximizes information from data, saving resources and time by identifying critical factors, optimal conditions, and interactions.⁸

1.3.2. Factorial Design: Factorial designs simultaneously assess the effects of multiple factors and their interactions on experimental results. Key terms include: Factor (assigned variable), Levels (factor values), Effects (response change due to factor variation), and Interaction (lack of additive factor effects).⁹

1.3.3. Box Behnken Design: Box-Behnken designs are efficient three-level second-order designs, particularly for a small number of factors, requiring fewer runs compared to central composite designs in some cases.¹⁰

1.4. Control Strategy (CS): A control strategy is a planned set of controls ensuring process performance and product quality in a dynamic pharmaceutical environment with evolving standards. It includes continuous measurement using PAT tools. For analytical methods, CS manages input factors to meet system-suitability criteria and performance objectives established during validation. System suitability tests, potentially guided by Quality Risk Assessment (QRA), can be the primary control element, identifying failure modes and preventing erroneous results.^11,12

1.5. Analytical Chemistry: Analytical chemistry measures chemical composition and develops/improves analytical methods for qualitative (identifying components) and quantitative (determining amounts) analysis. Modern methods are sensitive, requiring small samples. Drug analysis covers bulk drugs, intermediates, research products, formulations, impurities, degradation products, and biological samples, contributing to drug efficacy, safety, and economy. Methods are classified as classical (separation followed by qualitative tests or gravimetric/titrimetric quantification) and instrumental (using scientific instruments).¹³

1.5.1. Classical Methods: These involve separation (precipitation, extraction, distillation) followed by qualitative identification (color, odor, melting/boiling points) or quantitative analysis (gravimetric or titrimetric measurements).¹⁴

1.5.2. Instrumental Methods: Instrumental methods utilize sophisticated instruments for analyte investigation, offering high sensitivity. Examples include separation techniques (HPLC, TLC, GC), spectroscopic methods (UV-Vis, MS, NMR), bioassay techniques, and electroanalytical techniques.¹⁵

1.5.3. Factors Affecting the Choice of Analytical Methods: Method selection depends on analysis type, analyte nature, potential interferences, available instruments, concentration range, required accuracy, and analysis time.¹⁶

1.5.4. Classification of Analytical Chemistry: Analytical chemistry is broadly divided into qualitative analysis (identifying components) and quantitative analysis (determining their amounts).¹⁷

1.6. UV-Visible Spectrophotometer: UV-Vis spectroscopy measures UV (190-380 nm) or visible (380-800 nm) light absorption by substances in solution, widely used in pharmaceutical analysis. Absorption occurs when light energy matches electronic and associated vibrational/rotational transitions (σ→σ∗,π→π∗,n→π∗,n→σ∗). Quantitative analysis follows Beer-Lambert's law (A=abc).¹⁸

1.6.1. Instrumentation of UV-Visible Spectrophotometer: Key components include light sources (deuterium, tungsten lamps), monochromator (diffraction grating), sample cell (quartz/glass cuvette), detector (photomultiplier tube, photodiode), and signal processor/readout.¹⁹

1.6.2. Methods of Multicomponent Analysis Using UV-Visible Spectrophotometer: Various techniques exist for analyzing multicomponent formulations, including simultaneous equation, area under curve, multicomponent mode, absorption ratio (Q-analysis), derivative spectroscopy, absorbance correction, difference spectroscopy, and single/double-point standardization.²⁰

Chromatography:

Chromatography separates mixture components based on their distribution between stationary and mobile phases, influenced by interactions like hydrogen bonding, van der Waals forces, electrostatic forces, hydrophobic forces, or particle size (e.g., size exclusion). Common modes include normal phase, reversed phase, ion chromatography, ion-exchange, affinity, and size exclusion. Reversed phase chromatography, popular for non-ionic small molecules, uses non-polar stationary phases and polar solvents. Retention in reversed phase is influenced by hydrophobicity and carbon chain length. Normal phase chromatography employs polar stationary phases and non-aqueous mobile phases, with separation based on interactions with polar silanol groups. HPLC is a high-speed form of column chromatography using high pressure to enhance separation efficiency with microparticulate packings. An HPLC system comprises a solvent reservoir, high-pressure pump, injector, column, and detector. Its importance in pharmaceutical analysis includes identification, quantification, and purity testing. Method development in HPLC often starts with reversed phase and considers stationary phase, mobile phase, and detector selection. Optimization involves adjusting parameters like flow rate, mobile/stationary phase composition, temperature, detection wavelength, and pH, often employing manual or automated approaches to enhance resolution, peak shape, and other analytical criteria.^21,22

Method Validation:

Method validation confirms that an analytical method consistently produces the desired result, ensuring identity, quality, purity, and potency. It's a one-time process after method development, considering all method variables. Key parameters include specificity, system suitability, precision (repeatability, intermediate precision, reproducibility), accuracy, linearity, range, limit of detection (LOD), limit of quantitation (LOQ), and robustness. System suitability assesses system performance using parameters like relative retention, theoretical plates, capacity factor, resolution, and peak asymmetry. Precision measures the agreement of multiple test results. Accuracy is the agreement between test results and the true value. Linearity verifies proportional analyte response to concentration. Range is the concentration interval with acceptable accuracy, linearity, and precision. LOD is the lowest detectable amount, while LOQ is the lowest quantifiable amount. Robustness indicates the method's resilience to small variations in method parameters.^23,24

6. MATERIALS AND INSTRUMENTS

6.1 MATERIALS:

6.1.1 API and marketed formulation

Table No. 3 Procurement of Drug Samples- I

6.1.2 Reagents

Table No. 3 Procurement of Drug Samples- II

6.2 Instruments:

Table No. 4 List of Reagents Used

Table No.  5 List of Instruments used

Experimental Work

7.1. Preliminary Characterization: Drug identity was confirmed by assessing color, odor, appearance (7.1.1) against standards and determining melting points (7.1.2) via the open capillary method. Solubility (7.1.3) was tested in methanol, ethanol, and water.

7.2. Selection of Analytical Wavelength:

7.2.1. Ultraviolet (UV) Spectroscopy: UV spectra of Fluticasone furoate and Vilanterol trifenatate in methanol were overlaid (200-400 nm). Analytical wavelengths selected were approximately 239 nm for Fluticasone furoate and 226 nm for Vilanterol trifenatate.

7.2.2. High Performance Liquid Chromatography (HPLC):

Selection of mobile phase

Fluticasone furoate and Vilanterol trifenatate were introduced into the HPLC system and analysed using various solvent mixtures to identify the optimal chromatographic conditions. According to a study, a mobile phase consisting of methanol: acetonitrile: phosphate buffer of pH 7 (60:20:20 % v/v) with a Water BEH X Bridge C18 column (250 mm × 4.6 mm, 5 μm) as the stationary phase, at a flow rate of 1 mL/min and a column temperature of 40°C, provided satisfactory separation. The detection wavelength was set at 280 nm. This isocratic elution method resulted in well-resolved peaks for both Fluticasone furoate and Vilanterol trifenatate with retention times of 4.232 and 3.539 minutes, respectively.

Table no. 06 Chromatographic condition (HPLC) Details used during method development

Table no. 07 Result of different trials

Fig. no. 10 Chromatogram of Trial 4

Table no. 11 Chromatogram of Trial 4