Implementation of QbD approach in RP-HPLC method optimization and validation for concurrent estimation of Deflazacort and Tamsulosin hydrochloride under ICH Q14 and Q2R2 framework

In the present work, a precise, accurate and selective stability-indicating RP-HPLC method has been developed and validated according to International Conference on Harmonization guidelines Q2-(R1) for the simultaneous quantitative determination of Tolterodine tartrate and Tamsulosin hydrochloride in bulk and its capsule formulation. The chromatographic separation was achieved on Hypersil octadecyl silane C18 (250 x 4.6mm, 5 μm) column at room temperature and mobile phase comprised of methanol: 0.05 M phosphate buffer, pH 7.0 in the ratio of 90:10 V/V. The flow rate of mobile phase was set at 1.0mL/min and compounds were monitored at 255nm using photodiode array detector. Tamsulosin hydrochloride and Tolterodine tartrate retention time were found to be 4.15±0.2 min and 8.42±0.2 min, respectively. The drug substances and products were subjected to acid hydrolysis, alkali hydrolysis, oxidative hydrolysis, photolytic and thermal degradation. The percent degradation of drugs was calculated in all stressed conditions. The analytical method validation parameters such as linearity, accuracy, precision, detection limits, quantitation limits and robustness indicate that drug substances and products were efficiently separated in present of their degradants and successfully applied for the routine analysis of Tolterodine tartrate and Tamsulosin hydrochloride in bulk and its capsule formulation in the quality control laboratory.

Reversed-phase high-performance liquid chromatography (RP-HPLC) and thin-layer chromatography (TLC) methods have been developed and validated for simultaneous estimation of tamsulosin hydrochloride and finasteride in bulk drug and in combined dosage forms. RP-HPLC separation was achieved on a Phenomenex C18 column using methanol/0.02 mol L-1 ammonium acetate buffer/triethylamine (79.9 + 20 + 0.1, V/V/V) (pH 9.2) as mobile phase. TLC separation was achieved on an aluminium-backed layer of silica gel 60 F254 using toluene/methanol/triethylamine (9 + 1.5 + 1, V/V/V) as eluent. Quantification was achieved with photodiode array (PDA) detection at 235 nm over the concentration range 0.5-16 and 1-50 μg mL-1 with mean recovery of 99.8 ± 0.9 and 100.0 ± 0.8% for tamsulosin hydrochloride and finasteride, respectively, by the RP-HPLC method. Quantification was achieved with UV detection at 270 nm over the concentration range 100-2000 ng per spot and 250-5000 ng per spot with mean recovery of 98.9 ± 0.9 and 99.6 ± 0.7 % for tamsulosin hydrochloride and finasteride, respectively, by the TLC method. Both methods are simple, precise, accurate and sensitive and are applicable to the simultaneous determination of tamsulosin hydrochloride and finasteride in bulk drug and in combined dosage forms.

In the present study, magnetite nanoparticles Fe 3 O 4 modified with Cetyltrimethylammonium bromide (CTAB) was successfully prepared and their application as a sorbent in the magnetic-dispersive solid phase extraction(M-dSPE)mode to preconcentration and determination of Tamsulosinhydrochloride (TMS) in human plasma was investigated by coupling with high performance liquid chromatography-ultraviolet detection (HPLC-UV).The influence of sorbent amount, pH of sample solution, extraction and desorption conditions were studied. The maximum adsorption capacity, and qmax, was obtained from Langmuir’s model.The structure, morphology and magnetic properties of adsorbent were characterized using scanning electron microscopy (SEM). Introduction: TMSbelongs to a class of drug called alpha-1(α 1 ) adrenergic receptor antagonists. Since TMS is widely used as an effective α 1 blocker, the development and validation of analytical methods for its determination in biological fluids are essential. Many of these methods are however, expensive,toxic, requiring a derivatization step and specific solvent extraction. Based on magnetite nano Fe 3 O 4 , a simple, fast and inexpensive, nontoxic M-dSPE method was established. Methods and Results: First the Fe 3 O 4 nanoparticles were synthesized via co-precipitation.Then Fe 3 O 4 (3mg) and CTAB 0.02- 4 mL of 0.1 %(w/v) were dispersed into phosphate buffer(pH=7.0) and added to the sample solution.The suspension was vigorously shaken to reach adsorption equilibrium, and the sorbent was subsequently isolated with a strong magnet. After that, the sorbent was eluted with buffer solution of pH 10.0 (100 µL) as the eluent solvent .Finally, the eluate was isolated from the sorbent by a strong magnet, and the supernatant was filtered and 20 μL of filtrate was injected into the HPLC-UV system for analysis in triplicate for each concentration. Conclusions: In this work a magnetite nanoFe 3 O 4 - based M-dSPE clean up combined with HPLC-UV developed as a new approach for the efficient determination of trace amount of TMS in plasma samples.This method provided effectively clean extracts and removed interfering peaks from the plasma. Furthermore this method was very fast,convenient,cost effective, nontoxic and with a very low consumption of solvent. Key words: Magnetite Nano Fe 3 O 4 , TMS, Human Plasma,M-dSPE.

A novel stability-indicating RP-HPLC method was developed and validated for simultaneous determination of Solifenacin Succinate & Tamsulosin Hydrochloride and its impurities in tablet dosage form. The method was developed using L1 column with gradient using the mobile phase consist of solvent-A (pH = 6.6, phosphate buffer + 0.5% Triethylamine) and solvent-B (90% Acetonitrile). The eluted compounds were monitored at 225 nm. Solifenacin Succinate & Tamsulosin Hydrochloride was subjected to oxidative, acid, base, hydrolytic, thermal and photolytic stress conditions. The developed method was validated as per ICH guidelines with respect to specificity, linearity, limit of detection, limit of quantitation, accuracy, precision and robustness. The limit of quantification results was ranged from 0.135 - 0.221 μg/mL for Solifenacin Succinate impurities and 0.043 - 0.090 μg/mL for Tamsulosin Hydrochloride impurities. This method is suitable for the estimation of impurities and assay of Solifenacin Succinate & Tamsulosin Hydrochloride in tablets dosage form.

We proposed an integrated bioanalytical method development and validation approach: (1) method screening based on analyte's physicochemical properties and metabolism information to determine the most appropriate extraction/analysis conditions; (2) preliminary stability evaluation using both quality control and incurred samples to establish sample collection, storage and processing conditions; (3) mock validation to examine method accuracy and precision and incurred sample reproducibility; and (4) method validation to confirm the results obtained during method development. This integrated approach was applied to the determination of compound I in rat plasma and compound II in rat and dog plasma. The effectiveness of the approach was demonstrated by the superior quality of three method validations: (1) a zero run failure rate; (2) >93% of quality control results within 10% of nominal values; and (3) 99% incurred sample within 9.2% of the original values. In addition, rat and dog plasma methods for compound II were successfully applied to analyze more than 900 plasma samples obtained from Investigational New Drug (IND) toxicology studies in rats and dogs with near perfect results: (1) a zero run failure rate; (2) excellent accuracy and precision for standards and quality controls; and (3) 98% incurred samples within 15% of the original values.

Bioanalytical method development and validation using incurred samples—Simultaneous quantitation of ramipril and ramiprilat in human EDTA plasma by LC–MS/MS

HPLC method development and validation plays an important role in the discovery, manufacturing, development of pharmaceutical products. HPLC methods are able to separate, detect and quantify various drugs their related substances, degraded products and impurities that may be introduced during the synthesis of drug substance. Here in this review various strategies for method development and validation on HPLC are well described. Along with this systematic approach for method validation is also described. Method validation establishes the performance characteristics and limitations of the developed method. Optimization of chromatographic conditions includes fixation of parameters like mobile phase, stationary phase, detection wavelength, elution mode that must affords to system suitability as well as stability of drugs, degradants, impurities. Force degradation studies helpful in the development and validation of stability indicating assay. They also demonstrates the specificity while developing stability indicating assay.

Drug-eluting stents have attracted significant attention in the medical community and pharmaceutical industry due to their proven success in significantly reducing restenosis. Abbott Laboratories is developing a drug-eluting stent coated with zotarolimus and swine was recently used as an animal model for the pre-clinical study of stent implantation. In this article, we present a detailed experimental design and results for the validation and sample analysis of zotarolimus drug concentration in stented swine artery samples. Introduction of tissue quality control (QC) samples allows evaluation of the entire analytical process as well as the stability of the drug in both original tissue and homogenized tissue samples. In addition, a novel approach using 100% swine blood as the homogenization solution was developed for the consistency of the liquid-liquid extraction recovery and stability of the zotarolimus in tissue homogenates. Standards were prepared by spiking zotarolimus working solution in swine blood and tissue QC samples were used along with the artery samples during the sample analysis. The linear dynamic range of blood standard samples is from 0.61 to 333.20 ng/mL to accommodate the predicted artery homogenate concentrations. Overall tissue QC %CV during the method validation was from 4.4% to 8.6%. The overall %bias of tissue QC samples during the method validation was from -7.3% to 16.6%. The method was successfully applied for the analysis of swine artery samples. A similar approach for method validation and sample analysis has been successfully applied for the analysis of swine myocardium, kidney and liver tissue samples.

<p class="abstract">Two hydrophilic interaction liquid chromatography (HILIC) methods for simultaneous determination of the major alkaloids (morphine, codeine, thebaine, oripavine, papaverine and noscapine) in opium poppy straw (<em>Papaver somniferum</em> L., Papaveraceae) were developed.</p><p class="abstract">The chromatographic behavior of target alkaloids was investigated on two different HILIC stationary phases: bare silica (Si-HILIC) and zwitterionic (ZIC-HILIC). Systematic optimization of the methods was carried out by use of chemometrics. A full factorial design of the experiments was utilized for assessment of the influence of acetonitrile share, ionic strength and the pH value of the mobile phase buffer on several chromatographic responses. The central composite circumscribed design of experiments was used for the robustness testing during the method validation.</p><p class="abstract">The separation of the alkaloids was obtained within close retention window on both columns with optimized gradient elution. The ZIC-HILIC method had advantage over Si-HILIC method in terms of sensitivity, robustness and cost. This method was found suitable for determination of the morphinane alkaloids from poppy straw.</p>

Aim and Study Design: Aims: The current research paper describes the RP-HPLC Method for estimation of Olmesartan Medoxomil, Telmisartan, and Hydrochlorothiazide and implements the role of QbD for Data Analysis
 Study design: Mentioned study is simple, rapid, economical, accurate, and robust RP-HPLC Method for Olmesartan Medoxomil, Telmisartan, and Hydrochlorothiazide and implementing QbD Approach for Data Analysis.
 Place and Duration of Study: The present study was carried out at Smt. S. M. Shah Pharmacy College, Mahemdabad, Gujarat, India from October 2019 to February 2020.
 Methodology: The separation was done on Hypersil ODS C18 column with dimensions (250mm x 4.6ID, Particle size: 5 microns) and Methanol: 0.02M potassium dihydrogen phosphate buffer (60:40%v/v) pH 3 used as mobile phase. The flow rate was 1.2ml/min; detection at 254nm. QbD approach was applied for data analysis. The method was validated according to ICH guidelines.
 Results: The RP-HPLC method was developed and validated for Linearity and Range through the QbD approach. Factorial Design was developed through Design Expert Software for estimation of Telmisartan, Olmesartan Medoxomil, and Hydrochlorothiazide. 27 experiments were constructed and its effect was seen on Resolution, Tailing factor, and Retention Time.
 Conclusion: It was clear that the proposed method was suitable for the QbD approach and identification and validation approaches. This process helps in the proper understanding of the parameters and less amount of time for the development cycle of the analytical method.

Critical analysis of several analytical method validation strategies in the framework of the fit for purpose concept

A rapid and sensitive reverse phase RP-HPLC method is proposed for the estimation of tamsulosin hydrochloride in tablets. Tamsulosin hydrochloride was chromatographed on a reverse phase C18 column with a mobile phase consisting of acetonitrile and water in the ratio of 50:50 v/v. The mobile phase was pumped at a flow rate of 1.5 ml/min. The eluents were monitored at 214 nm. The retention time of the drug was 1.7 min. With this method, linearity was observed between area under curve and concentration of tamsulosin hydrochloride in the injected solution, in the range of 5 to 100 μg/ml. The method was found to be applicable for analysis of the drug in tablets. The results were validated statistically.

Accurate estimation of forest aboveground biomass is essential for the assessment of regional carbon cycle and the climate change in the terrestrial ecosystem. Currently, ensemble learning algorithms and cross-validation methods have been widely applied to estimate regional forest Above Ground Biomass (AGB). However, the effects of ensemble learning algorithms, validation methods, and their interactions on forest AGB estimation were rarely investigated. Based on Landsat 8 Operational Land Imager (OLI) imagery, Airborne Laser Scanning (ALS) data and China’s National Forest Continuous Inventory data, this study explored the effects of five ensemble learning algorithms, including Simple Averaging (SA), Weighted Averaging (WA), Stacked Generalization (SG), Random Forest (RF) and Extreme Gradient Boosting (XGBoost), and two validation approaches (i.e. 10-fold and leave-one-out cross-validation) on the AGB estimation of the Natural Secondary Forests (NSFs) in northeast China. The results revealed that the ensemble learning algorithms that combine heterogenous-based models (i.e. SA, WA, SG) generally produced higher accuracy than the base models (i.e. Decision Tree (DT), K-Nearest Neighbor (KNN), Support Vector Regression (SVR), Convolutional Neural Network (CNN)). Among all ensemble learning algorithms, the SG algorithm has the highest accuracy whereas the XGBoost algorithm has the lowest accuracy. Although prediction models considerably impact the accuracy of AGB estimation, the validation approach also plays a non-negligible role in AGB estimation. The leave-one-out cross-validation produced much higher accuracy than the 10-fold cross-validation using the same prediction model and tends to generate over-optimistic AGB estimates compared to 10-fold cross-validation, especially for the averaging and stacking ensemble learning algorithms (i.e. SA, WA, SG). This study highlights the potential challenges of applying a leave-one-out cross-validation approach and provides a scientific foundation for the feasibility of different ensemble learning algorithms and cross-validation approaches for accurate AGB estimation.

The aim of the study was to evaluate prediction methods, validation approaches and pseudo-phenotypes for the prediction of the genomic breeding values of feed efficiency related traits in Nellore cattle. It used the phenotypic and genotypic information of 4,329 and 3,594 animals, respectively, which were tested for residual feed intake (RFI), dry matter intake (DMI), feed efficiency (FE), feed conversion ratio (FCR), residual body weight gain (RG), and residual intake and body weight gain (RIG). Six prediction methods were used: ssGBLUP, BayesA, BayesB, BayesCπ, BLASSO, and BayesR. Three validation approaches were used: 1) random: where the data was randomly divided into ten subsets and the validation was done in each subset at a time; 2) age: the division into the training (2010 to 2016) and validation population (2017) were based on the year of birth; 3) genetic breeding value (EBV) accuracy: the data was split in the training population being animals with accuracy above 0.45; and validation population those below 0.45. We checked the accuracy and bias of genomic value (GEBV). The results showed that the GEBV accuracy was the highest when the prediction is obtained with ssGBLUP (0.05 to 0.31) (Figure 1). The low heritability obtained, mainly for FE (0.07 ± 0.03) and FCR (0.09 ± 0.03), limited the GEBVs accuracy, which ranged from low to moderate. The regression coefficient estimates were close to 1, and similar between the prediction methods, validation approaches, and pseudo-phenotypes. The cross-validation presented the most accurate predictions ranging from 0.07 to 0.037. The prediction accuracy was higher for phenotype adjusted for fixed effects than for EBV and EBV deregressed (30.0 and 34.3%, respectively). Genomic prediction can provide a reliable estimate of genomic breeding values for RFI, DMI, RG and RGI, as to even say that those traits may have higher genetic gain than FE and FCR.

The excessive and continuously growing interest in the simultaneous determination of poppy alkaloids imposes the development and optimization of convenient high-throughput methods for the assessment of the qualitative and quantitative profile of alkaloids in poppy straw. Systematic optimization of two chromatographic methods (gas chromatography (GC)/flame ionization detector (FID)/mass spectrometry (MS) and reversed-phase (RP)-high-performance liquid chromatography (HPLC)/diode array detector (DAD)) for the separation of alkaloids from Papaver somniferum L. (Papaveraceae) was carried out. The effects of various conditions on the predefined chromatographic descriptors were investigated using chemometrics. A full factorial linear design of experiments for determining the relationship between chromatographic conditions and the retention behavior of the analytes was used. Central composite circumscribed design was utilized for the final method optimization. By conducting the optimization of the methods in very rational manner, a great deal of excessive and unproductive laboratory research work was avoided. The developed chromatographic methods were validated and compared in line with the resolving power, sensitivity, accuracy, speed, cost, ecological aspects, and compatibility with the poppy straw extraction procedure. The separation of the opium alkaloids using the GC/FID/MS method was achieved within 10 min, avoiding any derivatization step. This method has a stronger resolving power, shorter analysis time, better cost/effectiveness factor than the RP-HPLC/DAD method and is in line with the "green trend" of the analysis. The RP-HPLC/DAD method on the other hand displayed better sensitivity for all tested alkaloids. The proposed methods provide both fast screening and an accurate content assessment of the six alkaloids in the poppy samples obtained from the selection program of Papaver strains.