Development of a green HPLC method for the analysis of artesunate and amodiaquine impurities using Quality by Design.

Greening analytical methods has become of great interest in the field of pharmaceutical analysis to protect both the operators' health and the environment. In this work, an innovative methodology combining Quality-by-Design (QbD) and Green Chemistry principles was followed to develop a single, green and robust RP-HPLC method for the quantitative analysis of impurities of both artesunate and amodiaquine drugs. Ethanol was selected as the best ecofriendly alternative solvent in substitution to the commonly used organic solvents such as acetonitrile and methanol. To achieve method objectives, resolutions between the 10 peaks were chosen as critical method attributes (CMAs) to be optimized through QbD approach. Based on a quality risk assessment, pH, temperature, and gradient slope were then selected as critical method parameters (CMPs) and a three level full factorial design was used to model the CMAs as function of the CMPs. Response surface methodology associated to Monte Carlo simulations allowed to determine the method operable domain region (MODR), i.e., the multidimensional combination of CMPs where CMAs simultaneously satisfied specifications (Rs ≥ 1.5) with a probability at least equal to 95 %. Inside the MODR, the working point was chosen based on green criteria, involving a mobile phase composed of ethanol and 10 mM acetic acid only as pH modifier. The method was successfully validated for all impurities using accuracy profile methodology, which was fully compliant with the ICH Q2(R1) requirements. Finally, the method was applied to the analysis of amodiaquine and artesunate impurities in raw materials and formulations.

Quality of antiepileptic drugs in sub-Saharan Africa: A study in Gabon, Kenya, and Madagascar.

OBJECTIVE: Epilepsy is a major public health issue in low- and middle-income countries, where the availability and accessibility of quality treatment remain important issues, the severity of which may be aggravated by poor quality antiepileptic drugs (AEDs). The primary objective of this study was to measure the quality of AEDs in rural and urban areas in 3 African countries. METHODS: This cross-sectional study was carried out in Gabon, Kenya, and Madagascar. Both official and unofficial supply chains in urban and rural areas were investigated. Samples of oral AEDs were collected in areas where a patient could buy or obtain them. Pharmacological analytical procedures and Medicine Quality Assessment Reporting Guidelines were used to assess quality. RESULTS: In total, 102 batches, representing 3782 units of AEDs, were sampled. Overall, 32.3% of the tablets were of poor quality, but no significant difference was observed across sites: 26.5% in Gabon, 37.0% in Kenya, and 34.1% in Madagascar (P = .7). The highest proportions of substandard medications were found in the carbamazepine (38.7%; 95% confidence interval [CI] 21.8-57.8) and phenytoin (83.3%; 95% CI 35.8-99.5) batches, which were mainly flawed by their failure to dissolve. Sodium valproate was the AED with the poorest quality (32.1%; 95% CI 15.8-42.3). The phenobarbital (94.1%; 95% CI 80.3-99.2) and diazepam (100.0%) batches were of better quality. The prevalence of substandard quality medications increased in samples supplied by public facilities (odds ratio [OR] 9.9; 95% CI 1.2-84.1; P < .04) and manufacturers located in China (OR 119.8; 95% CI 8.7-1651.9; P < .001). The prevalence of AEDs of bad quality increased when they were stored improperly (OR 5.4; 95% CI 1.2-24.1; P < .03). SIGNIFICANCE: No counterfeiting was observed. However, inadequate AED storage conditions are likely to lead to ineffective and possibly dangerous AEDs, even when good-quality AEDs are initially imported.

Latency and persistence of diet volatile biomarkers in lamb fats.

Several studies have shown that volatile compounds are particularly well-suited for the authentication lamb diet by gas chromatography-mass spectrometry (GC-MS) analysis of adipose tissue. The aim of the present work was to use dynamic headspace-GC-MS to study the variations in the amounts of volatile diet tracers in perirenal fat (PRF) and caudal subcutaneous fat (CSCF) in lambs (n = 24) that were fed with concentrate and then allowed to graze for 0, 17, 51, or 85 days. Twenty-six volatile compounds were found to distinguish between the four diets (p < 0.05) in both PRF and CSCF. Of these diet tracers, 16 were found to be related to the pasture diet and increased at different rates according to the time spent at pasture (latency), while 10 were found in higher amounts in tissues of lambs fed with exclusive concentrate and exhibited different rates of clearance (persistence). Twenty-four of these discriminant compounds, including alkanes, ketones, terpenes, and 2,3-octanedione, were previously stated as pasture diet tracers in several earlier studies, suggesting their potential universality. All degrees of latency or persistence were exhibited by the pasture and concentrate diet tracers, respectively. A principal component analysis performed on ratios of selected diet tracers from both adipose tissues evidenced successful differentiation of the four feeding situations.

Authentication of meat products: determination of animal feeding by parallel GC-MS analysis of three adipose tissues.

Authentication of farm animal rearing conditions, especially the type of feeding, is a key issue in certification of meat quality and meat products. The purpose of this article was to analyze in parallel the volatile fraction of three adipose tissues excised from 16 lambs in order to authenticate two animal diets: pasture (n = 8) and concentrate (n = 8). On the basis of growth rate and anatomical location, three different lamb adipose tissues were analyzed: perirenal fat (PRF), caudal subcutaneous fat (CSCF), and heart fat (HF). An initial experiment was used to optimize the extraction of volatile compounds from the adipose tissues. Using a lipid liquid phase extraction, heating the ground tissue to 70 degrees C, was shown to be the best sample preparation mode before dynamic headspace-gas chromatography-mass spectrometry (DH-GC-MS) analysis to achieve a good representation of the starting material, while getting a good extraction and reproducibility. Next, the application of an instrumental drifts correction procedure to DH-GC-MS data enabled the identification of 130 volatile compounds that discriminate the two diets in one or several of the three tissues: 104 were found in PRF, 75 in CSCF, and 70 in HF. Forty-eight of these diet tracers, including 2,3-octanedione, toluene, terpenes, alkanes, alkenes, and ketones, had previously been identified as ruminant pasture-diet tracers and can be considered generic of this type of animal feeding. Moreover, 49 of the 130 compounds could identify diets in only one tissue, suggesting that complementary analysis of several tissues is superior for diet identification. Finally, multivariate discriminant analyses confirmed that the discrimination was improved when PRF, CSCF, and HF were considered simultaneously, even if HF contributed minimal information.