(233w) Comparison of Raman and UV Spectroscopy for the in-Line Quantification of Active Ingredient in Pharmaceutical Semi-Solid and Liquid Formulations

N. Bostijn^1,*, C. Vervaet², T. De Beer¹

¹Laboratory of Pharmaceutical Process Analytical Technology, Ghent University, Ottergemsesteenweg 460, 9000 Ghent, Belgium

²Laboratory of Pharmaceutical Technology, Ghent University, Ottergemsesteenweg 460, 9000 Ghent, Belgium

Introduction

In-line spectroscopic techniques are increasingly proposed as alternative methods for the quantification of active ingredients in pharmaceuticals. This is due to their advantages over the traditional methods, such as fast and non-destructive measurements without the need of sample pretreatment. One of these spectroscopic techniques is Raman, that is until now, mostly applied for solid dosage forms. UV spectroscopy is a widely used quantification technique, although less frequently implemented inside a process environment for in-line monitoring.

This study compares the feasibility of in-line Raman and UV spectroscopy for the quantification of active ingredients in pharmaceutical formulations. A suspension and gel containing 0.09 % (w/w) and 2 % (w/w) active ingredient, respectively, were used as model formulations. The performance of both spectroscopic techniques was assessed via accuracy profiles [1-3].

MATERIALS AND METHODS

Materials

Two commercial available pharmaceutical formulations were selected from a pharmaceutical company. The suspension contained 0.09 % (w/w) active ingredient and the gel 2 % (w/w). Both formulations were prepared based on confidential information.

Methods

Calibration (80, 90, 95, 100, 105, 110 and 120 % of target) and validation (85, 95, 100, 105 and 115 % of target) samples were created by producing a batch for the lowest concentration. After batch completion, a specific amount of active ingredient was added, corresponding to the subsequent concentration level, followed by the collection of spectra. This procedure was repeated until the highest concentration level was reached and spectra were recorded from each concentration. In total, one calibration batch and three validation batches (three days) were produced for each formulation.

The suspension and gel were prepared using a customized IKA LR2000 modular mini plant reactor system (IKA, Staufen, Germany). The mixing vessel was equipped with a double wall for controlling the temperature of the process. A peristaltic pump (Watson-Marlow, Falmouth, Cornwall, UK) was used for pumping water from a water bath (Type 1032, GFL, Burgwedel, Germany) to the mixing vessel.

In-line Raman spectra were recorded using a Raman Rxn2 spectrometer (Kaiser Optical Systems, Ann Arbor, MI, USA), equipped with a fiber-optic PhAT probe. The laser wavelength was 785 nm. The spectral range of the system was from 150â??1890 cm^-1 with a resolution of 5 cm^-1. An exposure time of 15 s with no averaging was used.

An Avaspec-ULS2048L spectrometer (Avantes, Apeldoorn, The Netherlands) was connected by a fiber-optic cable to an immersion probe. The light source was an AvaLight Deuterium-Halogen Lamp. All spectra were acquired in the 200-1100 nm spectral range. The exposure time was 1000 ms and 950 ms for the gel and suspension, respectively, with each spectra the average of 5 scans.

The calibration models of the gel were developed using the mean-centered spectra, after standard normal variate (SNV) correction and first derivative transformation, over the regions of 390.1-404.8, 655.0-666.7, 1340.2-1354.9 and 1570.0-1600.0cm^-1for the Raman spectra, while for the UV spectra the region 280.1-296.9 nm was used.

The Raman spectra of the suspension were mean-centered and SNV corrected, followed by taking the first derivative and selecting the region between 1390.0-1430.2 cm^-1. For the UV spectra, the same preprocessing was applied, except for the SNV correction and the selection of another spectral region (310.1-325.6 nm).

Spectroscopic data were correlated with the actual concentration of active ingredient, through partial least square (PLS) regression. The PLS models were created using the SIMCA software (Version 14, Umetrics, Umeå, Sweden).

Accuracy profiles, introduced by the SFSTP [1-3], were used as validation approach for the quantitative analytical methods.

RESULTS AND DISCUSSION

Gel

The RMSEP values of the Raman prediction set (0.026, 0.024 and 0.039 %) were lower compared to the ones of the UV data (0.058, 0.071 and 0.059 %). Accuracy profiles confirm the better performance of Raman. The β-expectation tolerance intervals exceed the 5 % acceptance limits only at the 1.75 and 2.37 % (w/w) concentration levels, whereas for UV, the β-expectation tolerance intervals exceed the 5 % acceptance limits over the whole concentration range.

Suspension

It can be noticed from the accuracy profile of the Raman method that the low concentration levels (0.077 and 0.086 % w/w) were predicted higher, the middle concentration level (0.091 % w/w) was predicted correct and the high concentration levels (0.095 and 0.104 % w/w) predictions were lower, suggesting that all the different concentrations were predicted the same value. This observation, the spectral data and the high RMSEP values (0.0097, 0.01 and 0.098 %) confirm that it was not possible to discriminate between the different concentration levels with Raman spectroscopy. For the UV calibration model, the β-expectation tolerance intervals exceed the 5 % acceptance limits over the whole concentration range, but fall within the 10 % acceptance limits at the 0.0865, 0.091 and 0.0955 % (w/w) concentration levels. RMSEP values (0.0050, 0.0015 and 0.0017 %) were lower than the RMSEP values of the Raman based quantification method.

CONCLUSION

The study showed that Raman spectroscopy performed better than UV spectroscopy for the in-line quantification of 2 % (w/w) active ingredient in a gel, but both techniques were feasible. For the low dosed suspension (0.09 % w/w), Raman spectroscopy failed to discriminate between the different concentration levels and thus the quantification of the active ingredient. UV spectroscopy was adequate for the in-line quantification, however between the acceptance limits of 10 %, instead of 5 %.

 REFERENCES

1. P. Hubert et al. Harmonization of strategies for the validation of quantitative analytical procedures A SFSTP proposal-part I. Journal of Pharmaceutical and Biomedical Analysis. 2004; 36: 579â??586.
2. P. Hubert et al. Harmonization of strategies for the validation of quantitative analytical procedures A SFSTP proposal-part II. Journal of Pharmaceutical and Biomedical Analysis. 2007; 45: 70â??81.
3. P. Hubert et al. Harmonization of strategies for the validation of quantitative analytical procedures A SFSTP proposal-part III. Journal of Pharmaceutical and Biomedical Analysis. 2007; 45: 82â??96.