The use of FT-NIR for API content assay in organic solvent media: a single calibration for multiple downstream processing streams.

The use of near infrared spectroscopy (NIRS) in downstream solvent based processing steps of an active pharmaceutical ingredient (API) is reported. A single quantitative method was developed for API content assessment in the organic phase of a liquid-liquid extraction process and in multiple process streams of subsequent concentration and depuration steps. A new methodology based in spectra combinations and variable selection by genetic algorithm was used with an effective improvement in calibration model prediction ability. Root mean standard error of prediction (RMSEP) of 0.05 in the range of 0.20-3.00% (w/w) was achieved. With this method, it is possible to balance the calibration data set with spectra of desired concentrations, whenever acquisition of new spectra is no longer possible or improvements in model's accuracy for a specific selected range are necessary. The inclusion of artificial spectra prior to genetic algorithms use improved RMSEP by 10%. This method gave a relative RMSEP improvement of 46% compared with a standard PLS of full spectral length.

The use of NIR as a multi-parametric in situ monitoring technique in filamentous fermentation systems.

The use of Fourier transform near infrared (FT-NIR) spectroscopy for simultaneous determination of multiple properties in an active pharmaceutical ingredient (API) fermentation process is described, together with procedures for developing accurate NIR calibrations with a performance independent of scale and the specific bioreactor used. Measurements were made in situ, by insertion of transflection probes into pilot and industrial bioreactors providing direct contact with the fermentation culture media. The ultimate goal was to establish methods for real time process monitoring aimed at enhanced process supervision, fault detection diagnosis and control of bioreactors. The in situ acquired spectra were related to lab results of samples taken from the reactors during the course of the manufacturing process. Suitable spectral wavenumber regions were selected and calibration models based on partial least squares (PLS) were developed. The root mean square errors of prediction for API content, viscosity, nitrogen source and carbon source concentration were all within acceptable ranges as compared to the off-line lab measurements, respectively, 0.03% (w/w), 150 cp, 0.01% (w/w), and 0.4% (w/w).

Applying near-infrared spectroscopy in downstream processing: one calibration for multiple clarification processes of fermentation media.

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.

Improving drug manufacturing with process analytical technology.

Within the process analytical technology (PAT) framework, as presented in the US Food and Drug Administration guidelines, the aim is to design, develop and operate processes consistently to ensure a pre-defined level of quality at the end of the manufacturing process. Three PAT implementation scenarios can be envisaged. Firstly, PAT could be used in its most modest version (in an almost non-PAT manner) to simply replace an existing quality control protocol (eg, using near-infrared spectroscopy for an in-process quality control, such as moisture content). Secondly, the use of in-process monitoring and process analysis could be integrated to enhance process understanding and operation for an existing industrial process. Thirdly, PAT could be used extensively and exclusively throughout development, scale-up and full-scale production of a new product and process. Although the first type of implementations are well known, reports of the second and third types remain scarce. Herein, results obtained from PAT implementations of the second and third types are described for two industrial processes for preparing bulk active pharmaceutical ingredients, demonstrating the benefits in terms of increased process understanding and process control.