Considerable inter- and intraspecific variation with respect to the quantity and composition of plant natural products exists. The processes that drive this variation remain largely unknown. Understanding which factors determine chemical diversity has the potential to shed light on plant defenses against herbivores and diseases and accelerate drug discovery. For centuries, Cinchona alkaloids were the primary treatment of malaria. Using Cinchona calisaya as a model, we generated genetic profiles of leaf samples from four plastid (trnL-F, matK, rps16 and ndhF) and one nuclear (ITS) DNA regions from twenty-two Cinchona calisaya stands sampled in the Yungas region of La Paz (Bolivia). Climatic and soil parameters were characterized and bark samples were analyzed for content of the four major alkaloids using HPLC-UV to explore the utility of evolutionary history (phylogeny) in determining variation within species of these compounds under natural conditions. A significant phylogenetic signal was found for the content of two out of four major Cinchona alkaloids (quinine and cinchonidine) and their total content. Climatic parameters, primarily driven by changing altitude, predicted 20.2% of the overall alkaloid variation, and geographical separation accounted for a further 9.7%. A clade of high alkaloid producing trees was identified that spanned a narrow range of altitudes, from 1,100 to 1,350 m. However, climate expressed by altitude was not a significant driver when accounting for phylogeny, suggesting that the chemical diversity is primarily driven by phylogeny. Comparisons of the relative effects of both environmental and genetic variability in determining plant chemical diversity have scarcely been performed at the genotypic level. In this study we demonstrate there is an essential need to do so if the extensive genotypic variation in plant biochemistry is to be fully understood.

Mimicking the human decision-making process is challenging. Especially, many process control situations during the manufacturing of pharmaceuticals are based on visual observations and related experience-based actions. The aim of the present work was to investigate the use of image analysis to classify the quality of coated tablets. Tablets with an increasing amount of coating solution were imaged by fast scanning using a conventional office scanner. A segmentation routine was implemented to the images, allowing the extraction of numeric image-based information from individual tablets. The image preprocessing was performed prior to utilization of four different classification techniques for the individual tablet images. The support vector machine (SVM) technique performed superior compared to a convolutional neural network (CNN) in relation to computational time, and this approach was also slightly better at classifying the tablets correctly. The fastest multivariate method was partial least squares (PLS) regression, but this method was hampered by the inferior classification accuracy of the tablets. Finally, it was possible to create a numerical threshold classification model with an accuracy comparable to the SVM approach, so it is evident that there exist multiple valid options for classifying coated tablets.

In this study, we present a dissolution test system that allows for the testing of dissolution of nano- and micrometer size materials under highly controlled atmospheric composition (O₂ and CO₂), temperature, and pH. The system enables dissolution testing in physiological simulant fluids (here low-calcium Gamble’s solution and phagolysosomal simulant fluid) and derivation of the temporal dissolution rates and reactivity of test materials. The system was validated considering the initial dissolution rates and dissolution profiles using eight different materials (γ-Al₂O₃, TiO₂ (NM-104 coated with Al₂O₃ and glycerin), ZnO (NM-110 and NM-113, uncoated; and NM-111 coated with triethoxycaprylsilane), SiO₂ (NM-200—synthetic amorphous silica), CeO₂ (NM-212), and bentonite (NM-600) showing high intra-laboratory repeatability and robustness across repeated testing (I, II, and III) in triplicate (replicate 1, 2, and 3) in low-calcium Gamble’s solution. A two-way repeated-measures ANOVA was used to determine the intra-laboratory repeatability in low-calcium Gamble’s solution, where Al₂O₃ (p = 0.5277), ZnO (NM-110, p = 0.6578), ZnO (NM-111, p = 0.0627), and ZnO (NM-113, p = 0.4210) showed statistical identical repeatability across repeated testing (I, II, and III). The dissolution of the materials was also tested in phagolysosomal simulant fluid to demonstrate the applicability of the ATempH SBR system in other physiological fluids. We further show the uncertainty levels at which dissolution can be determined using the ATempH SBR system.

Trace elements are found in most drugs as a result of the drug formulation and drug production methods. An inductively coupled plasma-mass spectrometry method for the determination of 24 trace elements (Mg, Ti, V, Cr, Mn, Cu, Fe, Co, Ni, Zn, As, Se, Mo, Ru, Rh, Pd, Ag, Cd, Sb, Ba, Ir, Pt, Au, and Pb) in solid ibuprofen tablets was established in relation to the ICH Q3D(R1) guideline, to evaluate the possibility of linking trace elemental profiles to drug formulation strategies, and to differentiate between drug products based on the trace elemental profiles. Ten European ibuprofen drug products were evaluated (n=3). The sample preparation was performed by microwave-assisted acid digestion using only 10 mg of homogenized sample and 900 μL of a mix of 65% HNO₃, 37% HCl, and 30% H₂O₂. Solid residuals primarily composed of insoluble SiO₂ excipients were removed by centrifugation. Only concentrations of Mg, Fe, Ti, Mn, Cr, and Ni were detected above the limits of detection and did not exceed the ICH Q3D(R1) guideline permitted daily exposure limits. The trace elemental profiles were evaluated through principal component analysis. Three principal components describing 96% of the variance were useful in grouping the ibuprofen drug products, and the detected trace elemental remnants could be related to drug formulation and drug production strategies. An in-house quality control material was used in lack of certified reference materials and was in combination with spike recoveries used for method validation. Good spike recoveries (94-119%) were obtained for all measured trace elements except Mg. Mg showed acceptable spike recoveries (75-155%) for mid and high-spike concentrations, but poor recoveries (30-223%) were detected with low spike concentrations in spike matrices containing high amounts of Mg. Overall, the method is suggested applicable for solid drugs containing insoluble SiO₂ excipients and drugs comparable to ibuprofen.