From lab to industrial development of lipid nanocarriers using quality by design approach

Lipid nanocarriers have attracted a great deal of interest in the delivery of therapeutic molecules. Despite their many advantages, compliance with quality standards and reproducibility requirements still constrain their industrial production. The relatively high failure rate in lipid nanocarrier research and development can be attributed to immature bottom-up manufacturing practices, leading to suboptimal control of quality attributes. Recently, the pharmaceutical industry has moved toward quality-driven manufacturing, emphasizing the integration of product and process development through the principles of quality by design. Quality by design in the pharmaceutical industry involves a thorough understanding of the quality profile of the target product and involves an assessment of potential risks during the design and development phases of pharmaceutical dosage forms. By identifying essential quality characteristics, such as the active ingredients, excipients and manufacturing processes used during research and development, it becomes possible to effectively control these aspects throughout the life cycle of the drug. Successful commercialization of lipid nanocarriers can be achieved if large-scale challenges are addressed using the QbD approach. QbD has become an essential tool because of its advantages in improving processes and product quality. The application of the QbD approach to the development of lipid nanocarriers can provide comprehensive and remarkable knowledge enabling the manufacture of high-quality products with a high degree of regulatory flexibility. This article reviews the basic considerations of QbD and its application in the laboratory and large-scale development of lipid nanocarriers. Furthermore, it provides forward-looking guidance for the industrial production of lipid nanocarriers using the QbD approach.

Chemometrically-aided general approach to novel adsorbents studies: Case study on the adsorption of pharmaceuticals by the carbonized Ailanthus altissima leaves

A chemometrically based approach was applied to select the most efficient drug adsorbent among the biochars obtained from the novel feedstock, the leaves of the invasive plant (Ailanthus altissima). The representative target adsorbates (atenolol, paracetamol, ketorolac and tetracycline) were selected on the basis of their physicochemical properties to cover a wide chemical space, which is the usual analytical challenge. Their adsorption was investigated using design of experiments as a comprehensive approach to optimise the performance of the adsorption system, rationalise the procedure and overcome common drawbacks. Among the response surface designs, the central composite design was selected as it allows the identification of important experimental factors (solid-to-liquid ratio, pH, ionic strength) and their interactions, and allows the selection of optimal experimental conditions to maximise adsorption performance. The biochars were prepared by pyrolysis at 500 °C and 800 °C (BC-500 and BC-800) and the ZnCl2-activated biochars were prepared at 650 °C and 800 °C (AcBC-650 and AcBC-800). The FTIR spectra revealed that increasing the pyrolysis temperature without activator decreases the intensity of all bands, while activation preserves functional groups, as evidenced by the spectra of AcBC-650 and AcBC-800. High temperatures during activation promoted the development of an efficient surface area, with the maximum observed for AcBC-800 reaching 347 m2 g-1. AcBC-800 was found to be the most efficient adsorbent with removal efficiencies of 34.1, 51.3, 55.9 and 38.2 % for atenolol, paracetamol, ketorolac and tetracycline, respectively. The models describing the relationship between the removal efficiency of AcBC-800 and the experimental factors studied, showed satisfactory predictive ability (predicted R2 > 0.8) and no significant lack-of-fit was observed. The results obtained, including the mathematical models, the properties of the adsorbates and the adsorbents, clearly indicate that the adsorption mechanisms of activated biochars are mainly based on hydrophobic interactions, pore filling and hydrogen bonding.

Predicting liquid chromatography-electrospray ionization/mass spectrometry signal from the structure of model compounds and experimental factors; case study of aripiprazole and its impurities

A priori estimation of analyte response is crucial for the efficient development of liquid chromatography-electrospray ionization/mass spectrometry (LC-ESI/MS) methods, but remains a demanding task given the lack of knowledge about the factors affecting the experimental outcome. In this research, we address the challenge of discovering the interactive relationship between signal response and structural properties, method parameters and solvent-related descriptors throughout an approach featuring quantitative structure-property relationship (QSPR) and design of experiments (DoE). To systematically investigate the experimental domain within which QSPR prediction should be undertaken, we varied LC and instrumental factors according to the Box-Behnken DoE scheme. Seven compounds, including aripiprazole and its impurities, were subjected to 57 different experimental conditions, resulting in 399 LC-ESI/MS data endpoints. To obtain a more standard distribution of the measured response, the peak areas were log-transformed before modeling. QSPR predictions were made using features selected by Genetic Algorithm (GA) and providing Gradient Boosted Trees (GBT) with training data. Proposed model showed satisfactory performance on test data with a RMSEP of 1.57 % and a of 96.48 %. This is the first QSPR study in LC-ESI/MS that provided a holistic overview of the analyte's response behavior across the experimental and chemical space. Since intramolecular electronic effects and molecular size were given great importance, the GA-GBT model improved the understanding of signal response generation of model compounds. It also highlighted the need to fine-tune the parameters affecting desolvation and droplet charging efficiency.