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Clavulanic acid (CA) is an important secondary metabolite commercially produced by cultivation of Streptomyces clavuligerus (Sc). It is a potent inhibitor of bacterial β-lactamases. In this work, a specific and improved high performance liquid chromatography (HPLC) method, using a C-18 reversed phase column, diode array detector and gradient elution for CA quantification in fermentation broths of Sc, was developed and successfully validated. Samples were imidazole-derivatized for the purpose of creating a stable chromophore (clavulanate-imidazole). The calibration curve was linear over a typical range of CA concentration between 0.2 and 400mg/L. The detection and quantification limits were 0.01 and 0.02mg/L, respectively. The precision of the method was evaluated for CA spiked into production media and a recovery of 103.8%, on average, was obtained. The clavulanate-imidazole complex was not stable when the samples were not cooled during the analysis. The recovery rate was 39.3% on average. This assay was successfully tested for CA quantification in samples from Sc fermentation, using both, a chemically defined and a complex medium., (Copyright © 2015 Elsevier B.V. All rights reserved.)

The use of near-infrared spectroscopy (NIRS) is demonstrated in the first downstream processing (DSP) steps of an active pharmaceutical ingredient (API) manufacturing process. The first method developed was designed to assess the API content in the filtrate stream (aqueous) of a rotary drum vacuum filter. The PLS method, built after spectral preprocessing and variable selection, had an accuracy of 0.01% (w/w) for an API operational range between 0.20 and 0.45% (w/w). The robustness and extrapolation ability of the calibration was proved when samples from ultrafiltration and nanofiltration processes, ranging from 0 to 2% (w/w), were linearly predicted (R2=0.99). The development of a robust calibration model is generally a very time-consuming task, and once established it is imperative that it can be useful for a long period of time. This work demonstrates that NIR procedures, when carefully developed, can be used in different process conditions and even in different process steps of similar unit operations.