Nonlinear Optimization via Explicit NRTL Model Solubility Prediction for Antisolvent Mixture Selection in Artemisinin Crystallization

Experimental and model-based approach to evaluate solvent effects on the solubility of the pharmaceutical artemisinin

The separation and purification of plant-based Active Pharmaceutical Ingredients (API) from extracts is a crucial part in pharmaceutical process development. For the purification of the antimalarial drug component artemisinin (ARTE) from an Artemisia anna L. toluene extract, antisolvent crystallization is considered. Solubilities of ARTE in binary solvent mixtures of toluene and two potential antisolvents, n-heptane and ethanol, were determined at temperatures from 278.15 K to 313.15 K. The experimental work was supported by the application of various models, utilizing varying amounts of experimental input data. The goal was the identification of models that are able to predict solubilities in binary solvent mixtures sufficiently accurate and, thus, can help to reduce the experimental effort for future solvent screenings. In this study, we applied the PC-SAFT model both with and without fitting the binary interaction parameter kij between ARTE and the respective solvent, as well as the empirical Jouyban-Acree model. From the experiments, n-heptane demonstrated to be a promising antisolvent, while ethanol acted more as a cosolvent. All models tested were capable of distinguishing between effective and ineffective antisolvents. The purely predictive PC-SAFT model applied with kij = 0 exhibited the largest deviation from the experimental data. This was followed by the PC-SAFT model including fitted kij values, based on at least four experimental data points. The Jouyban-Acree model fitted the data most accurately. Its parametrization required a minimum of ten experimental data points.

Insight of the various in silico screening techniques developed for assortment of cocrystal formers and their thermodynamic characterization

Most of the widely used drugs have problems associated with their oral bioavailability either due to their poor aqueous solubility or due to their poor permeability. Co-crystallization is an efficient and economically feasible approach that offers a great opportunity for improvement in physicochemical properties such as solubility, stability, and bioavailability of such type of therapeutic agent. Selection of the best co-former plays a major role in co-crystallization. Various approaches have been developed for the selection of suitable co-formers with API. In recent years in silico screening, a computational tool paying more attention for screening of co-formers has been developed. Numerous approaches can be used for in silico screening such as the Autodocking tool, COSMORS, COSMOTHERM, etc. Autodocking can predict several numbers of co-former effectively screened in silico method to identify a suitable co-former with an API. Prediction of solubility and dissolution is also important for the development of co-crystal. In this review, we discuss in silico screening of coformer and thermodynamic approaches to determine the dissolution and solubility of co-crystal specially with reference to the drugs belonging to BCS class II group.

Combining enyne metathesis with long-established organic transformations: a powerful strategy for the sustainable synthesis of bioactive molecules

This account surveys the current progress on the application of intra- and intermolecular enyne metathesis as main key steps in the synthesis of challenging structural motifs and stereochemistries found in bioactive compounds. Special emphasis is placed on ruthenium catalysts as promoters of enyne metathesis to build the desired 1,3-dienic units. The advantageous association of this approach with name reactions like Grignard, Wittig, Diels–Alder, Suzuki–Miyaura, Heck cross-coupling, etc. is illustrated. Examples unveil the generality of such tandem reactions in providing not only the intricate structures of known, in vivo effective substances but also for designing chemically modified analogs as valid alternatives for further therapeutic agents.