Sonja S. Sekulic

Automated system for the on-line monitoring of powder blending processes using near-infrared spectroscopy. Part II. Qualitative approaches to blend evaluation.

Near Infrared (NIR) spectroscopy is seen as a very powerful tool in a variety of applications involving powder characterisation. Here we deal with a typical pharmaceutical application of powder blend monitoring. A D-optimal experimental design is used to cover the 85-115% range of the target formulation which is comprised of the active component at 3.5% w/w, Microcrystalline Cellulose (Avicel PH102) at 62%, Dibasic Calcium Phosphate Anhydrous at 31.5%, Sodium Starch Glycolate (Explotab) at 2%, and 1% Magnesium Stearate. A miniature Flobin blender has been modified to enable the use of a fibre optic probe for on-line NIR spectral data collection. The experiments were successful in detecting spectral changes which eventually converged to constant variance. While the NIR spectrum of a powdered sample is rich in information which is representative of both the physical and chemical characteristics of the sample, it is at times difficult to select the appropriate mathematical treatments in order to extract the desired information. This article investigates several possible pre-treatments (including detrending (DT), standard normal variates (SNV), second derivatives, and the combination of SNV and DT) together with several ways in establishing blend homogeneity, which includes the running block standard deviation, dissimilarity calculations and principal components analysis (PCA). The focus of this work is to investigate qualitative tools of analysis for blend homogeneity determinations, while future work will focus on quantitative data interpretation.

Appearance of Discontinuities in Spectra Transformed by the Piecewise Direct Instrument Standardization Procedure

Several years ago, we noted that spectra transformed by the piecewise direct standardization (PDS) method may contain discontinuities. Having noticed that the problem was a recurring one, we studied it and recently diagnosed its source. Our investigations suggest that this problem also occurs in applications of window factor analysis, evolving factor analysis, and any other procedure that uses piecewise principal component models. In this work, we report the source of the problem and illustrate it with one example. A procedure is presented for eliminating the problem that is effective in PDS pattern recognition applications. Further work is needed to develop modified algorithms suitable for calibration applications.

On-Line Determination of Reaction Completion in a Closed-Loop Hydrogenator Using NIR Spectroscopy

An on-line near-infrared (NIR) spectroscopic method has been developed to determine in situ the endpoint of a bulk pharmaceutical hydrogenation reaction in a loop hydrogenator. This hydrogenation employs a 5% palladium-on-carbon catalyst with tetrahydrofuran (THF) as the reaction solvent. The traditional test for monitoring the endpoint of the hydrogenation is a gas chromatographic procedure that requires an estimated 60 min from the time a sample is taken to the point where the analysis results become available. The use of NIR spectroscopy in an on-line mode of operation allows spectra to be collected every 2 min and thereby significantly improves response time and result availability. The need for obtaining results in “real time” stems from the creation of undesired side products if the reaction is allowed to continue past the optimal endpoint. If the reaction is not stopped before these side products reach a level of approximately 0.8% (wt/wt), the batch requires additional purification at considerable time and cost. A partial least-squares model was constructed, validated, and successfully used to determine the endpoint of subsequent batches.

Effective mass sampled by NIR fiber-optic reflectance probes in blending processes

Abstract Recent efforts have demonstrated the in situ use of NIR spectroscopy to determine the homogeneity and potency of powder blends. This work has raised questions regarding the effective mass of a powder blend interrogated by a fiber-optic probe. The effective mass determined from experiments described herein is wavelength dependent and ranges from 0.154 to 0.858 g with a maximum standard deviation of about 0.16 g. Although the precision of this estimate is low, it is sufficiently accurate to demonstrate the usefulness of in situ NIR monitoring of blending operations in the pharmaceutical industry. The method was established by using the relationship between sample mass and spectral variance. Mixtures of lactose (50% w/w), microcrystalline cellulose (40% w/w), and sodium benzoate (10% w/w) were manually blended and sampled at selected intervals. The spectral variance at relevant wavelengths was determined as a function of blend homogeneity and sample mass using a standard micro-sample cup. The spectral variance obtained from micro-cup measurements was used to calibrate the effective mass sampled by a fiber-optic reflectance probe. The estimated mass was greatest at wavelengths where the minor constituent contributed most to the overall spectral variance. Typical pharmaceutical tablets have weights in the range of 0.1–1.0 g. According to FDA regulations, the maximum allowed sample mass for determining the homogeneity of these preparations is 0.3–3.0 g. For many formulations, the effective mass sampled by the fiber-optic probe easily falls below this range.

Absolute molecular weight determination of hypromellose acetate succinate by size exclusion chromatography: Use of a multi angle laser light scattering detector and a mixed solvent

Molecular weight distribution is an important quality attribute for hypromellose acetate succinate (HPMCAS), a pharmaceutical excipient used in spray-dried dispersions. Our previous study showed that neither relative nor universal calibration method of size exclusion chromatography (SEC) works for HPMCAS polymers. We here report our effort to develop a SEC method using a mass sensitive multi angle laser light scattering detector (MALLS) to determine molecular weight distributions of HPMCAS polymers. A solvent screen study reveals that a mixed solvent (60:40%, v/v 50mM NaH(2)PO(4) with 0.1M NaNO(3) buffer: acetonitrile, pH* 8.0) is the best for HPMCAS-LF and MF sub-classes. Use of a mixed solvent creates a challenging condition for the method that uses refractive index detector. Therefore, we thoroughly evaluated the method performance and robustness. The mean weight average molecular weight of a polyethylene oxide standard has a 95% confidence interval of (28,443-28,793) g/mol vs. 28,700g/mol from the Certificate of Analysis. The relative standard deviations of average molecular weights for all polymers are 3-6%. These results and the Design of Experiments study demonstrate that the method is accurate and robust.

De-risking Pharmaceutical Tablet Manufacture Through Process Understanding, Latent Variable Modeling, and Optimization Technologies

In pharmaceutical tablet manufacturing processes, a major source of disturbance affecting drug product quality is the (lot-to-lot) variability of the incoming raw materials. A novel modeling and process optimization strategy that compensates for raw material variability is presented. The approach involves building partial least squares models that combine raw material attributes and tablet process parameters and relate these to final tablet attributes. The resulting models are used in an optimization framework to then find optimal process parameters which can satisfy all the desired requirements for the final tablet attributes, subject to the incoming raw material lots. In order to de-risk the potential (lot-to-lot) variability of raw materials on the drug product quality, the effect of raw material lot variability on the final tablet attributes was investigated using a raw material database containing a large number of lots. In this way, the raw material variability, optimal process parameter space and tablet attributes are correlated with each other and offer the opportunity of simulating a variety of changes in silico without actually performing experiments. The connectivity obtained between the three sources of variability (materials, parameters, attributes) can be considered a design space consistent with Quality by Design principles, which is defined by the ICH-Q8 guidance (USDA 2006). The effectiveness of the methodologies is illustrated through a common industrial tablet manufacturing case study.

A Review of PAT Strategies in Secondary Solid Oral Dosage Manufacturing of Small Molecules

Pharmaceutical solid oral dosage product manufacturing is a well-established, yet revolutionizing area. To this end, process analytical technology (PAT) involves interdisciplinary and multivariate (chemical, physical, microbiological, and mathematical) methods for material (e.g., materials, intermediates, products) and process (e.g., temperature, pressure, throughput, etc.) analysis. This supports rational process modeling and enhanced control strategies for improved product quality and process efficiency. Therefore, it is often difficult to orient and find the relevant, integrated aspects of the current state-of-the-art. Especially, the link between fundamental research, in terms of sensor and control system development, to the application both in laboratory and manufacturing scale, is difficult to comprehend. This review compiles a nonexhaustive overview on current approaches from the recognized academia and industrial practices of PAT, including screening, selection, and final implementations in solid oral dosage manufacturing, through a wide diversity of use cases. Finally, the authors attempt to extract a common consensus toward developing PAT application guidance for different unit operations of drug product manufacturing.

APPLICATIONS OF A SENSITIVE LASER POLARIMETRIC HPLC DETECTOR: CONFIRMATION OF ENANTIOMERIC EXCESS FOR DANOFLOXACIN AND ANALYSIS OF A NOVEL MACROLIDE

A commercially available laser-based polarimetric detector (Chiral Detector) was used to confirm the enantiomeric excess of danofloxacin and to analyze a novel macrolide. The detector is based on the work of Yeung et al.[1] and uses a low noise laser diode which emits 675 nm radiation. Selectivity is obtained not through chromatographic resolution but through the sign and magnitude of detector response. An area ratio of the detector signals (Chiral/UV) was used to calculate Danofloxacins optical purity. By calculating the ratio of the two detector signals an accurate measure of optical purity or enantiomeric excess can be calculated relative to standard responses without concern for potency, optical rotation of impurities, exact sample concentration or injection precision. The molecule is ideal for this type of determination since it absorbs UV radiation strongly, has a large optical rotation and the HPLC method resolves potential process impurities, synthetic byproducts and degradation products. The signal ratio was found to be linear with respect to % optical purity from 100% to 0% and is expected to be accurate to within 2%. Samples of danofloxacin mesylate were optically pure to within the 2% limit of the methodology. A novel experimental macrolide was analyzed using a reversed phase HPLC system interfaced to both a UV detector and a laser-based polarimetric detector. Specific rotation of the novel macrolide was determined to be −23° in mobile phase using a bench top polarimeter. While polarimetric response for the experimental macrolide was shown to be reasonably linear from 0.1mg/mL to 1.5mg/mL, sensitivity was poor relative to UV detection at 210nm. The limit of quantitation was ∼5000 ng for the laser-based polarimetric detector which was 50 times less sensitive than the UV detector.

Feed-Forward Process Control Strategy for Pharmaceutical Tablet Manufacture Using Latent Variable Modeling and Optimization Technologies

Abstract In pharmaceutical tablet manufacturing processes, a major source of disturbance affecting drug product quality is the (lot to lot) variability of the incoming raw materials. A Feed-Forward process control strategy that compensates for raw material variability is presented. The approach involves building PLS (partial least squares) models that combine raw material attributes and tablet process parameters and relate these to final tablet attributes. The resulting models are used in an optimization framework to then find optimal process parameters which can satisfy all the desired requirements for the final tablet attributes, subject to the incoming raw material lots, prior to performing a batch. The connectivity obtained between the three sources of variability (materials, parameters, attributes) can be considered a design space consistent with Quality by Design (QbD) principles, which is defined by the ICH-Q8 guidance [1]. To implement the FF control, an in-house process simulator is presented. The effectiveness of the methodologies is illustrated through a common industrial tablet manufacturing case study.