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@#In this paper, the uncertainties of correction factors of fluconazole impurities determined by HPLC standard curve method were evaluated, and the main common factors affecting the accuracy of standard curve method were found, so as to improve the accuracy of the method.In this study, the corresponding fitting lines of fluconazole and its impurities A, B, C, D, F and I were established respectively, and the ratio of the slope of fitting lines of each impurity and its corresponding principal component was calculated as the correction factor of the impurity.Then on the basis of GUM method, the uncertainty of each impurity correction factor determined by standard curve method was evaluated according to the established uncertainty evaluation scheme of correction factor determination process.The correction factor and uncertainty of fluconazole impurities A, B, C, D, F and I were 1.068 ± 0.046, 0.102 ± 0.005, 0.0582 ± 0.0031, 1.382 ± 0.121, 0.802 ± 0.067 and 1.383 ± 0.119, respectively, and the coverage factor k was 2.Finally, the contribution rate of each uncertainty component was calculated.In the relative combined standard uncertainties urel(f) of fluconazole impurities A, B, C, D, F and I correction factors, the sum of contribution rate of slope uncertainty urel(K) of the linear equation of principal component and its impurity is more than 85%; in the slope uncertainties urel(K) of linear equation, the contribution rates of uncertainties of solution concentration in 8 of 12 data groups are more than 80%, and the contribution rates of uncertainties introduced by reference substance content in solution concentration are about 80%.It can be seen that the preparation of linear solution concentration is the most influential factor in the determination of impurity correction factor by standard curve method, followed by the linear fitting process.In the preparation process of linear solution concentration, the purity of reference substance is the most influential factor, followed by weighing and pipetting times.The conclusion can help the experimenters to better formulate experimental plans and ensure the accuracy of the results when doing similar work.
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@#To improve the standard of quality control of tazobactam and its preparations in China, national reference standard of tazobactam impurity A was developed. After tazobactam impurity A was synthesized, its structure was validated by infrared (IR), mass spectrometry (MS) and nuclear magnetic resonance (NMR), and its content uniformity and short-term stability were measured and investigated. Then, water content and residue on ignition of impurity A were determined, and its purity was determined using high performance liquid chromatography (HPLC) with 10 mmol/L ammonium acetate solution-acetonitrile (98∶2) as the mobile phase. Mass balance method was used to determine the content of the first batch of tazobactam impurity A national standard substance. Meanwhile, nuclear magnetic quantitative method was used to calculate the content, which was mutually verified with the mass balance method. The developed reference material of tazobactam impurity A is consistent with the maximum degradation impurity in tazobactam system applicability solution and the reference material of tazobactam related substance A contained in USP41. Within the 95% confidence range, the ratio of inter- and intra-bottle variance of impurity A after separation was 0.61 (< F0.05(11,12)), proving that the uniformity was satisfying. The contents of organic impurity, water content and inorganic impurity in impurity A were 0.90%, 1.24% and 0.25%, respectively. The content of impurity A was determined to be 97.6% by mass balance method, which was basically consistent with the result of nuclear magnetic quantitative method (97.1%). Under the condition of 25 °C, the area normalized purity of impurity A was 99.1% at 0, 3, 5 and 10 days, proving that the sample was stable at room temperature for 10 days. Finally the first batch of national standard substance of tazobactam impurity A was established successfully.
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Objective:To evaluate the antimicrobial effectiveness of lomefloxacin hydrochloride eye drops from 13 domestic manu-facturers. Methods:The antimicrobial effectiveness of lomefloxacin hydrochloride eye drops was tested based on the antimicrobial ef-fectiveness testing in Chinese Pharmacopoeia(2015 edition,volume 4). Results:The samples from 5 manufacturers could reach level A,those from 3 manufacturers were at level B, and those from 5 manufacturers did not comply with the specification. Conclusion:Some problems exist in the usage of antimicrobial agents in lomefloxacin hydrochloride eye drops from some Chinese manufacturers,and these manufacturers should optimize the type and concentration of antimicrobial agents according to the requirements of Chinese Phar-macopoeia combined with the corresponding prescriptions under the principle of minimum concentration while best effect.
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The molecular descriptors of impurities with known structure in cefdinir were calculated, selected and associated with the chromatographic retention behavior to establish a model. This quantitative structure retention relationships (QSRR) model for the related substances of cefdinir was established under specific chromatographic condition and verified by other impurities. 12 molecular descriptors were used to establish the QSRR model, F_AFRBWF, Blbn_J, SsCH3, SssCH2, SsNH2, SssNH, SssS, SHdCH2, EEM_AFc, EEM_AFpl, EEM_XFpl and Pi_MaxQ. The relativity between true values and predictions in QSRR of cefdinir is R2 = 0.9836 (n = 18), ΔRRT is no more than 0.154, as 10.17% in RRT. The results indicate that the QSRR model for the related substances of cefdinir can be used to evaluate the analysis methods for related substances and predict the chromatographic behavior of new impurities, which will provide a new way for the evaluation of the effectiveness for drug quality control.
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The near infrared ( NIR ) spectra of 76 batches of the amoxicillin capsules from different manufacturers and their corresponding content powder without capsules cell were used to find some quantitative indicators to evaluate whether the piecewise direct standardization ( PDS ) algorithm succeeded in NIR quantitative model updating. 54 batches were used to construct the NIR quantitative model for capsule preparation. All the NIR spectra of amoxicillin capsules were divided into five classes by cluster analysis, and each class can be regarded as a homology sample set. The average spectrum for each homology sample set was calculated. Ten to Fifteen spectra were selected from each homology sample set as the corresponding master spectra of the PDS algorithm to correct all the NIR spectra of the amoxicillin content powder respectively. Then the corrected spectra were predicted by the constructed NIR quantitative model for amoxicillin capsules. The prediction error for each corrected powder spectrum, and the correlation coefficient between each corrected powder spectrum and the average spectrum of the corresponding homolog sample set which the PDS master spectra came from, were calculated. Finally, the relationship between the prediction error and its corresponding correlation coefficient were studied. It was found that the correction results correlated closely with the selected master spectra set in PDS algorithm. The bigger the correlation coefficient ( r) , the better the correction results. In general, when r is less than 99%, it can be judged that the PDS correction is failed. At this condition, the prediction error is often more than 5%. Therefore, the correlation coefficient between the corrected spectrum and its corresponding average spectrum of the homology sample set can be used as an indicator to evaluate the efficiency of the PDS correction.
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Abstract: Construction of a successful near infrared analysis model is a complex task. It spends a lot of manpower and material resources, and is restricted by sample collection and model optimization. So it is important to study on the extended application of the existing near infrared (NIR) models. In this paper, cephradine capsules universal quantitative model was used as an example to study on the feasibility of its extended application. Slope/bias correction and piecewise direct standardization correction methods were used to make the universal model to fit to predict the intermediates in manufacturing processes of cephradine capsules, such as the content of powder blend or granules. The results showed that the corrected NIR universal quantitative model can be used for process control although the results of the model correction by slope/bias or piecewise direct standardization were not as good as that of model updating. And it also indicated that the model corrected by slope/bias is better than that by piecewise direct standardization. Model correction provided a new application for NIR universal models in process control.
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A near infrared (NIR) method for the detection of illegal addition of sildenafil citrate in capsules of Chinese traditional medicine was constructed. The diffuse reflectance near infrared spectra were recorded using integrated sphere and fiber optics respectively. Using the spectra of the sildenafil citrate standard as Reference spectra, the threshold of the correlation coefficient was set up based on the minimum effective concentration of the sildenafil citrate. By comparing the threshold with the correlation coefficient between the tested spectra and the Reference spectra in the selected spectral range, the tested sample contains sildenafil citrate is determined. For the integrated sphere method, the spectral range of 6070-5800 cm~(-1) and 4170-4070 cm~(-1) were selected, and 70% was set as threshold. For the fiber method, 6070-5800 cm~(-1) and 65% were used. 79 and 247 batches of the Chinese traditional medicines contained sildenafil citrate collected from the Chinese market were used to validate the two methods separately. The accuracy of the integrated sphere method was 91.14%, and that of f iber method was 87.45%.