Fingerprinting and validation of a LC-DAD method for the analysis of biflavanones in Garcinia kola-based antimalarial improved traditional medicines.

African populations use traditional medicines in their initial attempt to treat a range of diseases. Nevertheless, accurate knowledge of the composition of these drugs remains a challenge in terms of ensuring the health of population and in order to advance towards improved traditional medicines (ITMs). In this paper chromatographic methods were developed for qualitative and quantitative analyses of a per os antimalarial ITM containing Garcinia kola. The identified analytical markers were used to establish TLC and HPLC fingerprints. G. kola seeds were analysed by HPLC to confirm the identity of the extract used by the Congolese manufacturer in the ITM. The main compounds (GB1, GB2, GB-1a and Kolaflavanone) were isolated by preparative TLC and identified by UPLC-MS and NMR. For the quantification of the major compound GB1, a simple and rapid experimental design was applied to develop an LC method, and then its validation was demonstrated using the total error strategy with the accuracy profile as a decision tool. The accurate results were observed within 0.14-0.45mg/mL range of GB1 expressed as naringenin. The extracts used in several batches of the analysed oral solutions contained GB1 (expressed as naringenin) within 2.04-2.43%. Both the fingerprints and the validated LC-DAD were found suitable for the quality control of G. kola-based raw material and finished products, respectively.

Innovative high-performance liquid chromatography method development for the screening of 19 antimalarial drugs based on a generic approach, using design of experiments, independent component analysis and design space.

An innovative methodology based on design of experiments (DoE), independent component analysis (ICA) and design space (DS) was developed in previous works and was tested out with a mixture of 19 antimalarial drugs. This global LC method development methodology (i.e. DoE-ICA-DS) was used to optimize the separation of 19 antimalarial drugs to obtain a screening method. DoE-ICA-DS methodology is fully compliant with the current trend of quality by design. DoE was used to define the set of experiments to model the retention times at the beginning, the apex and the end of each peak. Furthermore, ICA was used to numerically separate coeluting peaks and estimate their unbiased retention times. Gradient time, temperature and pH were selected as the factors of a full factorial design. These retention times were modelled by stepwise multiple linear regressions. A recently introduced critical quality attribute, namely the separation criterion (S), was also used to assess the quality of separations rather than using the resolution. Furthermore, the resulting mathematical models were also studied from a chromatographic point of view to understand and investigate the chromatographic behaviour of each compound. Good adequacies were found between the mathematical models and the expected chromatographic behaviours predicted by chromatographic theory. Finally, focusing at quality risk management, the DS was computed as the multidimensional subspace where the probability for the separation criterion to lie in acceptance limits was higher than a defined quality level. The DS was computed propagating the prediction error from the modelled responses to the quality criterion using Monte Carlo simulations. DoE-ICA-DS allowed encountering optimal operating conditions to obtain a robust screening method for the 19 considered antimalarial drugs in the framework of the fight against counterfeit medicines. Moreover and only on the basis of the same data set, a dedicated method for the determination of three antimalarial compounds in a pharmaceutical formulation was optimized to demonstrate both the efficiency and flexibility of the methodology proposed in the present study.