Spectroscopic approach for on-line monitoring of particle size during the processing of pharmaceutical nanoparticles

Feasibility of diffuser-incorporated near-infrared trans-reflectance measurement for quantitative detection of microplastics captured in perfluorocarbon

A diffuser-incorporated near-infrared (NIR) trans-reflectance measurement is demonstrated for quantitative detection of polyethylene (PE) particles captured in perfluorohexane (PFH, C₆F₁₄). PFH effectively captures PE particles through its hydrophobicity and absorbs little NIR radiation, recommending it for use in background-free NIR detection of captured PE particles. A reflective metal disk was used to push the captured PE particles in PFH toward the bottom of the vial that contained the sample, and the trans-reflectance measurement was performed by illuminating NIR radiation from the bottom of the vial at 45^o. Reproducibility is limited by the variation in the positions of small PE-particle aggregates at the water/PFH interface and the difficulty in ensuring full NIR sampling (coverage) of large aggregates. An effective way to secure improved reproducibility under these circumstances is illumination of broader and more uniform NIR radiation for measurement. For this purpose, a polytetrafluoroethylene (PTFE) disk was uniquely incorporated as a diffuser for the trans-reflectance measurement. Compared to the measurement with no diffuser, the diffuser-incorporated scheme produced more distinct PE peaks of low-quantity samples (0.1 and 0.2 mg) and enhanced the reproducibility in measurements of all the samples (0.1-4.0 mg of PE). As a result, the correlation between peak intensity and particle quantity was excellent (R²: 0.997), and a limit of detection of 0.07 mg was achieved.

A Novel Method for Rapid Particle Size Analysis of Ibuprofen Using Near-infrared Spectroscopy

Particle size distribution (PSD) is often considered as critical material attribute for active pharmaceutical ingredients (APIs), and the need for regular evaluation stands as an important quality control parameter in the pharmaceutical industry. Near-infrared (NIR) spectroscopy, used routinely for API identification, was introduced as analytical tool for simultaneous determination of particle size of ibuprofen. The demonstrated potential was highlighted by the development of rapid, robust, and noninvasive method coupled with multivariate data analysis (MVA), which can be easily transferred in QC laboratories for routine analysis. Principal component analysis (PCA) and partial least squares (PLS) regression analyses were performed on a calibration set of 61 ibuprofen samples, which differed in their median particle size Dv(50). The score scatterplots revealed evident clustering of ibuprofen samples according to their particle size, as well as occurrence of a distinctive outlying group of ibuprofen samples originating from one manufacturer. Further testing by means of mid-infrared spectroscopy, X-ray powder diffraction, and particle morphology analysis pinpointed particle morphology being responsible for the observed outlying group. Consequently, PLS class modeling based on particle morphology was introduced, which delivered two separate PLS regression models: one for blade-like ibuprofen crystals and another for irregular plate-like ibuprofen crystals. The former regression model exhibited high correlation coefficients and satisfactory predictive power (R²X = 0.999, R²Y = 0.917, Q² = 0.901), whereas the latter demonstrated lower statistical indicators (R²X = 0.99, R²Y = 0.72, Q² = 0.55). Additionally, the study underlines the importance of particle shape evaluation and sample classification according to particle morphology similarity prior to building NIRS-based regression models for PSD determination.

Formulation aspects of intravenous nanosuspensions

Intravenous (IV) route is preferred for rapid onset of action, avoiding first pass metabolism and achieving site specific delivery. Development of IV formulations for poorly water soluble drugs poses significant challenges. Formulation approaches like salt formation, co-solvents, surfactants and inclusion complexation using cyclodextrins are used for solubilisation. However, these approaches are not applicable universally and have limitations in extent of solubilisation, hypersensitivity, toxicity and application to only specific type of molecules. IV nanosuspension have been attracting attention as a viable strategy for development of IV formulations of poorly water-soluble drugs. Nanosuspension consists of nanocrystals of poorly water soluble drug suspended in aqueous media and stabilized using minimal concentration of stabilizers. Recent years have witnessed their potential in formulations for toxicological studies and clinical trials. However various challenges are associated with the translational development of IV nanosuspensions. Therefore, the objective of the current review is to provide a holistic view of formulation development and desired properties of IV nanosuspensions. It will also focus on advancements in characterization tools, manufacturing techniques and post-production processing. Challenges associated with translational development and regulatory aspects of IV nanosuspension will be addressed. Additionally, their role in preclinical evaluation and special applications like targeting will also be discussed with the help of case studies. The applications of IV nanosuspensions shall expand as their applications move from preclinical phase to commercialization.

Inorganic nanoparticle synthesis in flow reactors – applications and future directions

The use of flow technologies for obtaining nanoparticles can play an important role in the development of ecological and sustainable processes for obtaining inorganic nanomaterials, and the continuous methods are part of the Flow Chemistry trend.

Estimation of Particle Size Distribution from Bulk Scattering Spectra: Validation on Monomodal Suspensions

A particle size distribution (PSD) estimation method based on light-scattering properties was validated on experimental visible/near-infrared scattering spectra of polystyrene suspensions, with a nominal particle size ranging from 0.1 to 12 μm in diameter. On the basis of μ_s and g spectra extracted from double integrating sphere measurements, good PSD estimates were obtained for particles ≥1 μm. The particle volume fraction estimates in the case of μ_s were close to the target concentrations, although influenced by small baseline fluctuations on the spectra. For submicrometer particles, on the other hand, the non-oscillating μ_s spectra lack discriminating power, resulting in erroneous PSD estimates. The reduced scattering coefficient spectra (μ_s') were found less useful for particle size estimation as they lack a characteristic shape, causing an over- or underestimation of the distribution width. In summary, the estimation routine proved to deliver PSD estimates in line with the reference measurements for micrometer-sized or larger particles based on their μ_s and g scattering spectra. Additional validation on more polydisperse samples forms the next step before going to bimodal PSD estimates.

Predictive Evaluation of Pharmaceutical Properties of Ulinastatin-Containing Vaginal Suppositories as a Hospital Preparation by Near-Infrared Spectroscopy

A vaginal suppository containing ulinastatin (UTI) was developed as a hospital pharmacy product from UTI injection solution and Witepsol^® S-55. After mixing at 50°C for 0-8 h, UTI suppositories were prepared, which had good UTI content uniformity. Because 2% surfactant was contained in S-55, the UTI injection solution formed a water-in-oil type emulsion as a suppository base. The measured residual moisture content (loss on drying (LOD)) in the prepared vaginal suppositories decreased as the mixing time increased, but their hardness (hardness test (HT)) increased. Near (N) IR spectra of UTI suppositories were measured after mixing for 0-8 h. The best calibration models to predict the HT and LOD of the suppositories were determined based on the NIR spectra by the leave-one-out method in a partial least-squares regression analysis (PLS). The validation result indicated that PLS models for HT and LOD were obtained based on the spectra treated by a combination of smoothing and normalized, respectively, and the model consisted of three latent variables. The plots between the predicted and measured pharmaceutical properties (HT and LOD) based on the calibration data were superimposed with those of the external validation data. The developed NIR spectroscopy method was applied to the preparation process monitoring for UTI vaginal suppositories. In the prepared vaginal suppositories, the predicted LOD decreased as the mixing time increased, and the measured LOD values superimposed well with the predicted values. In contrast, the predicted HT increased as the mixing time increased, and the measured values superimposed with the predicted values.

Transmission near-infrared (NIR) and photon time-of-flight (PTOF) spectroscopy in a comparative analysis of pharmaceuticals

We present a comprehensive study of the application of photon time-of-flight spectroscopy (PTOFS) in the wavelength range 1050-1350 nm as a spectroscopic technique for the evaluation of the chemical composition and structural properties of pharmaceutical tablets. PTOFS is compared to transmission near-infrared spectroscopy (NIRS). In contrast to transmission NIRS, PTOFS is capable of directly and independently determining the absorption and reduced scattering coefficients of the medium. Chemometric models were built on the evaluated absorption spectra for predicting tablet drug concentration. Results are compared to corresponding predictions built on transmission NIRS measurements. The predictive ability of PTOFS and transmission NIRS is comparable when models are based on uniformly distributed tablet sets. For non-uniform distribution of tablets based on particle sizes, the prediction ability of PTOFS is better than that of transmission NIRS. Analysis of reduced scattering spectra shows that PTOFS is able to characterize tablet microstructure and manufacturing process parameters. In contrast to the chemometric pseudo-variables provided by transmission NIRS, PTOFS provides physically meaningful quantities such as scattering strength and slope of particle size. The ability of PTOFS to quantify the reduced scattering spectra, together with its robustness in predicting drug content, makes it suitable for such evaluations in the pharmaceutical industry.

Non-destructive prediction of the drug content of an acetaminophen suppository by near-infrared spectroscopy and X-ray computed tomography

The purpose of this study is to develop non-destructive methods to determine the drug content of suppositories using near-infrared (NIR) spectrometry and X-ray computed tomography (XCT). The suppository samples (acetaminophen content: 0, 100, 200, 300, 400 and 500 mg/suppository) consisted of acetaminophen powder and hard fat. NIR spectra of 18 standard suppository samples were recorded, and the data were divided into two wave number ranges, 4000-10 000 cm(-1) (LR), and 4280-6650 cm(-1) (SR). The best calibration model was determined to minimize the standard error of cross-validation (SECV) by the leave-one-out method in the partial least squares regression (PLS). Sliced XCT images of the suppositories were measured, and apparent density (AD) was evaluated using the image of the sample. The NIR models gave the best correlation coefficient constant (R) values, since the results for LR and SR gave straight lines with R of 0.9274 and 0.9707, respectively. The AD of the suppositories by XCT increased with increasing drug content, and the relationship between the AD and drug content had a straight line with R of 0.9958. Both NIR and X-ray CT performed accurate measurements of suppository samples through plastic packaging.

Nanosuspension: An approach to enhance solubility of drugs

One of the major problems associated with poorly soluble drugs is very low bioavailability. The problem is even more complex for drugs like itraconazole, simvastatin, and carbamazepine which are poorly soluble in both aqueous and nonaqueous media, belonging to BCS class II as classified by biopharmaceutical classification system. Formulation as nanosuspension is an attractive and promising alternative to solve these problems. Nanosuspension consists of the pure poorly water-soluble drug without any matrix material suspended in dispersion. Preparation of nanosuspension is simple and applicable to all drugs which are water insoluble. A nanosuspension not only solves the problems of poor solubility and bioavailability, but also alters the pharmacokinetics of drug and thus improves drug safety and efficacy. This review article describes the preparation methods, characterization, and applications of the nanosuspension.

Near-infrared reflection spectroscopy (NIRS) as a successful tool for simultaneous identification and particle size determination of amoxicillin trihydrate

A successful application of NIR spectroscopy (NIRS) in combination with multivariate data analysis (MVA) for the simultaneous identification and particle size determination of amoxicillin trihydrate particles was developed. Particle size analysis was ascertained by NIRS in diffuse reflection mode on different particle size fractions of amoxicillin trihydrate with D90 particle diameters ranging from 6.9 to 21.7 μm. The present problem of fractionating the powder into good enough size fractions to achieve a stable calibration model was solved. By probing dried suspensions measurement parameters were optimized and further combined with the best suitable chemometric operations. Thereby the quality of established regression models could be improved considerably. A linear coherence between particle size and absorbance signal was found at specific wavenumbers. Satisfactory clustering by particle size was achieved by principal component analysis (PCA) whereas partial least squares regression (PLSR) and principal component regression (PCR) was compared for quantitatively calibrating the NIRS data. PLSR turned out to predict unknown test samples slightly better than PCR.

Quality by design, part I: application of NIR spectroscopy to monitor tablet manufacturing process

To monitor tableting production using near infrared (NIR) spectroscopy, chemometric models were developed to analyze peak compression force, crushing strength and content uniformity. To measure tablet content uniformity, orbifloxacin tablets with drug content ranging from 60 to 90 mg were made and analyzed using ultraviolet (UV) and NIR spectroscopy. To assess the compression force and crushing strength, several batches of tablets were made on a Stokes B2 rotary tablet press and compression force was varied from 360 to 3500 lb. Principal component analysis (PCA) was used to identify tablets with regular and capped tablets breakage patterns. Comparison of statistical parameters showed that partial least squares (PLS) models gave better fit than the multiple linear regression (MLR) models. The best fit PLS models had a standard error of calibration (SEC) and a standard error of prediction (SEP) for content uniformity of 1.13 and 1.36 mg; for compression force of 69.86 and 59.48 lb and for crushing strength 0.55 kP and 0.57 kP, respectively. NIR spectroscopy in combination with multivariate modeling is a rapid and nondestructive technique that could reliably predict content uniformity, compression force and crushing strength for orbifloxacin tablets.

Characterization of carbon-containing aerosolized drugs using laser-induced breakdown spectroscopy

Aerosolized drug delivery methods have increasingly become popular for pharmaceutical applications. This is mainly due to their ease of application and the more recent advancements incorporating nano-sized generation of particles that find deeper penetration routes and more efficient administration of the drug to specific target organs. Their effectiveness heavily relies on the uniformity of the chemical composition of these aerosolized drugs. Thus, it calls for a real-time on-line analytical tool that can accurately characterize the chemical constituents of the drug powder particles generated to ensure a stringent quality control. We present laser-induced breakdown spectroscopy (LIBS) for the first time as an efficient analytical tool to carry out on-line quantitative chemical characterization of aerosolized drugs. We used three different carbon based aerosolized drugs, namely L-ascorbic acid 2-phosphate sesquimagnesium salt hydrate (C(6)H(9)Mg(1.5)O(9)P.xH(2)O), Iron(II) L-ascorbate (C(12)H(14)FeO(12)), and DL-pantothenic acid hemicalcium salt (C(9)H(16)NO(5)0.5Ca) for our quantitative LIBS studies here. Our results show that LIBS can effectively estimate the quantitative ratios of carbon to various trace elements for each of these drugs, thereby enabling on-line unique characterization of individual aerosolized drugs. The quantitative LIBS technique predicted the [C]/[Mg], [C]/[Fe], and [C]/[Ca] ratios as 4.02+/-0.76, 12.42+/-2.36, and 18.47+/-4.39 for each of the above aerosolized drugs, respectively. Within error limits, we find these ratios in good agreement with the respective stoichiometric values of 4, 12, and 18 corresponding to the drugs above. Thus, the work demonstrated the utility and validity of LIBS in accurate on-line identification of drug powders during real-time manufacturing processes.

Particle size determination in aluminum hydroxide suspensions using near-infrared transmittance spectroscopy

A new method for particle size determination in polystyrene and aluminum hydroxide suspensions using near-infrared transmittance spectroscopy is described. Mono-dispersed polystyrene particle size standards were used to establish the calibration model. The particle sizes used in the study are similar to the wavelength range of 700-1300 nm, where light scattering is wavelength dependent. The wavelength dependency of near-infrared (NIR) absorbance is found to be linear with the particle size when the analysis is based on the same spectrum starting point (the same absorbance at 700 nm). Partial least squares regression (PLSR) is applied to model this linear relationship. Compared to laser diffraction (LD) the NIR method has similar accuracy and precision in the measurement of particles with a uniform size. For a sample containing multiple sizes of particles, the mean size measured by the NIR method is shown to be weighted by the particle mass. The application of the model to aluminum hydroxide suspension shows that the NIR method is suitable for the detection of particle size changes during the production process and storage. The advantages of the NIR method are that no knowledge of the refractive index and the concentration of a sample are necessary and that the method is fast and easy to operate.

Chemoinformetrical Evaluation of Dissolution Property of Indomethacin Tablets by Near-Infrared Spectroscopy

PURPOSE

The purpose of this study was to use near-infrared spectrometry (NIR) with chemoinformetrics to predict the change of dissolution properties in indomethacin (IMC) tablets during the manufacturing process. A comparative evaluation of the dissolution properties of the tablets was performed by the diffused reflectance (DRNIR) and transmittance (TNIR) NIR spectroscopic methods.

METHODS

Various kinds of IMC tablets (200 mg) were obtained from a powder (20 mg of IMC, 18 mg of microcrystalline cellulose, 160 mg of lactose, and 2 mg of magnesium stearate) under various compression pressures (60-398 MPa). Dissolution tests were performed in phosphate buffer, and the time required for 75% dissolution (T75) and mean dissolution time (MDT) were calculated. DRNIR and TNIR spectra were recorded, and the both NIR spectra used to establish a calibration model for predicting the dissolution properties by principal component regression analysis (PCR).

RESULTS

The T75 and MDT increased as the compression pressure increased, since tablet porosity decreased with increasing pressure. Intensity of the DRNIR spectra of the compressed tablets decreased as the compression pressure increased. However, the intensity of TNIR spectra increased along with the pressure. The calibration models used to evaluate the dissolution properties of tablets were established by using PCR based on both DRNIR and TNIR spectra of the tablets. The multiple correlation coefficients of the relationship between the actual and predictive T75 by the DRNIR and TNIR methods were 0.831 and 0.962, respectively.

CONCLUSION

It is possible to predict the dissolution properties of pharmaceutical preparations using both DRNIR and TNIR chemoinformetric methods. The TNIR method was more accurate for predictions of the dissolution behavior of tablets than the DRNIR method.

Theoretical Analysis of Tablet Hardness Prediction Using Chemoinformetric Near-Infrared Spectroscopy

In order to clarify the theoretical basis of the variability in the measurement of tablet hardness by compression pressure, NIR spectroscopic methods were used to predict tablet hardness of the formulations. Tablets (200 mg, 8 mm in diameter) consisting of berberine chloride, lactose, and potato starch were formed at various compression pressures (59, 78, 98, 127, 195 MPa). The hardness and the distribution of micropores were measured. The reflectance NIR spectra of various compressed tablets were used as a calibration set to establish a calibration model to predict tablet hardness by principal component regression (PCR) analysis. The distribution of micropores was shifted to a smaller pore size with increasing compression pressure. The total pore volume of tablets decreased as the compression pressure increased. The hardness increased as the compression pressure increased. The hardness could be predicted using a calibration model consisting of 7 principal components (PCs) obtained by PCR. The relationship between the predicted and the actual hardness values exhibited a straight line, an R(2) of 0.925. In order to understand the theoretical analysis (scientific background) of calibration models used to evaluate tablet hardness, the standard error of cross validation (SEV) values, the loading vectors of each PC and the regression vector were investigated. The result obtained with the calibration models for hardness suggested that the regression vector might involve physical and chemical factors. In contrast, the porosity could be predicted using a calibration model composed of 2 PCs. The relationship between the predicted and the actual total pore volume showed a straight line with R(2) = 0.801. The regression vector of the total pore volume might be due to physical factors.

Prediction of Tablet Hardness Based on Near Infrared Spectra of Raw Mixed Powders by Chemometrics

The purpose of this research is to elucidate the effect of lubricant mixing on tablet hardness by near-infrared (NIR) chemometrics as a basic study of process analytical technology. Formulation cellulose (F-C) consisted of sulpyrine (SP), microcrystalline cellulose (MC), and magnesium stearate (MgSt). Formulation lactose/starch (F-L) consisted of SP bulk drug powder, spray-dried lactose (SL), corn starch (CS), and MgSt. First, F-L and F-C without MgSt were mixed in a twin-shell mixer for 60 min. MgSt was added to the mixed powder, and was mixed for various mixing times, after which the mixed powders were compressed by 8-mm diameter punch and die. NIR spectra of raw mixed powders of F-L and F-C were taken using a reflection type of Fourier transform NIR spectra spectrometer, and chemometric analysis was performed using principal component regression (PCR). The tablet hardnesses of F-L and F-C decreased with increasing mixing time. All NIR spectra of the mixed powders of F-L and F-C fluctuated depending on mixing time. In order to predict tablet hardness before tablet compression, NIR spectra of F-L and F-C mixed powders were analyzed and evaluated for hardness by PCR. The minimum standard error of cross-validation values could be realized by using five- and six-principal component models, respectively. In the cases of F-L and F-C, the relationships between the actual and predicted tablet hardnesses showed straight lines, respectively. In the regression vectors of F-L and FC, the peaks related to hydrogen groups of SP, CS, and MC appeared as positive peaks. In contrast, the peaks related to hydrocarbon due to MgSt appeared as negative peaks in the regression vectors. The calibration models to evaluate the tablet hardness were obtained based on NIR spectra of raw mixed powders by PCR. This approach to predicting tablet hardness prior to compression could be used as a routine test to indicate the quality of the final product without spending time and energy to produce samples of questionable quality.

Assessment of NIR spectroscopy for nondestructive analysis of physical and chemical attributes of sulfamethazine bolus dosage forms

The goal of this study was to assess the utility of near infrared (NIR) spectroscopy for the determination of content uniformity, tablet crushing strength (tablet hardness), and dissolution rate in sulfamethazine veterinary bolus dosage forms. A formulation containing sulfamethazine, corn starch, and magnesium stearate was employed. The formulations were wet granulated with a 10% (wt/vol) starch paste in a high shear granulator and dried at 60 degrees C in a convection tray dryer. The tablets were compressed on a Stokes B2 rotary tablet press running at 30 rpm. Each sample was scanned in reflectance mode in the wavelengths of the NIR region. Principal component analysis (PCA) of the NIR tablet spectra and the neat raw materials indicated that the scores of the first 2 principal components were highly correlated with the chemical and physical attributes. Based on the PCA model, the significant wavelengths for sulfamethazine are 1514, (1660-1694), 2000, 2050, 2150, 2175, 2225, and 2275 nm; for corn starch are 1974, 2100, and 2325 nm; and for magnesium stearate are 2325 and 2375 nm. In addition, the loadings show large negative peaks around the water band regions ( approximately 1420 and 1940 nm), indicating that the partial least squares (PLS) models could be affected by product water content. A simple linear regression model was able to predict content uniformity with a correlation coefficient of 0.986 at 1656 nm; the use of a PLS regression model, with 3 factors, had an r (2) of 0.9496 and a standard error of calibration of 0.0316. The PLS validation set had an r (2) of 0.9662 and a standard error of 0.0354. PLS calibration models, based on tablet absorbance data, could successfully predict tablet crushing strength and dissolution in spite of varying active pharmaceutical ingredient (API) levels. Prediction plots based on these PLS models yielded correlation coefficients of 0.84 and 0.92 on independent validation sets for crushing strength and Q(120) (percentage dissolved in 120 minutes), respectively.

In-Line Monitoring of Moisture Content in Fluid Bed Dryers Using Near-IR Spectroscopy with Consideration of Sampling Effects on Method Accuracy

In-line near-IR moisture monitoring of the dynamic, fluid bed drying environment has been reported in recent years by several research groups; however, analytical figures of merit with regard to prediction accuracy are discussed in only a subset of this work, and issues with sampling and sample presentation are scarcely addressed at all. In this study, experiments were performed at 65-, 300-, and 600-L drying scales using several different sampling configurations in an effort to better understand and improve in-line near-IR method accuracy. Findings from this work demonstrate that process heterogeneity plays a major role in determination of apparent prediction accuracy. This aspect is general to all in-line measurements and plays an especially important role in solids and slurry systems that are prone to heterogeneity. In addition to experimental results, simulations based on these findings and sampling theory demonstrate an interesting paradox: depending on the sampling configuration employed, the method with the smallest apparent error is not necessarily optimal for process monitoring and control. Furthermore, sampling configuration influences the number of samples necessary to define an adequate calibration set. Finally, process understanding that was gained as a result of temporally rich, in-line measurements will be presented.

Comparison of near-infrared and laser-induced breakdown spectroscopy for determination of magnesium stearate in pharmaceutical powders and solid dosage forms

Near-infrared (NIR) spectroscopy has become well established in both the pharmaceutical arena and other areas as a useful technique for rapid quantitative analysis of solid materials. Though laser-induced breakdown spectroscopy (LIBS) has not been widely applied in the pharmaceutical industry, the technique has been used for rapid quantitative analysis of solids in many other applications. One analysis amenable to each technique is the determination of magnesium stearate in solids during the lubrication blending unit operation of pharmaceutical processing. A comparative study of the utility of these two techniques for this application will be presented. Necessary sample preparations and the extent and type of matrix effects will be discussed. Additionally, it will be shown that NIR provides better accuracy and precision than LIBS with the experimental parameters used; however, LIBS showed superior selectivity as it was demonstrated to be more robust to sample matrix perturbations. Examples of blending applications will also be presented.

Cancer nanotechnology: opportunities and challenges

Nanotechnology is a multidisciplinary field, which covers a vast and diverse array of devices derived from engineering, biology, physics and chemistry. These devices include nanovectors for the targeted delivery of anticancer drugs and imaging contrast agents. Nanowires and nanocantilever arrays are among the leading approaches under development for the early detection of precancerous and malignant lesions from biological fluids. These and other nanodevices can provide essential breakthroughs in the fight against cancer.

Monitoring of a pharmaceutical nanomilling process using grating light reflection spectroscopy

An optical diagnostic method, grating light reflection spectroscopy (GLRS), has been demonstrated for the in situ monitoring of properties of heterogeneous matrices in industrial processes. The technique is based on measurements near the critical points of intensity and phase in waves reflected from a transmission diffraction grating in contact with a diagnostic sample. The features contained in the reflection spectrum near these thresholds allow for the simultaneous determination of the real and imaginary parts of the dielectric function of the sample. Using these data, the milling progress of highly concentrated fluid suspensions is observed as the material is milled from approximately 40 mm to 160 nm in diameter. A theoretical model that closely resembles experimentally determined spectra was constructed and applied in combination with principal components analysis (PCA) to demonstrate that GLRS can be used to closely monitor changes in the mean particle size of the nanomilled drug product.

Nanosuspensions in drug delivery

A surprisingly large proportion of new drug candidates emerging from drug discovery programmes are water insoluble, and therefore poorly bioavailable, leading to abandoned development efforts. These so-called 'brickdust' candidates can now be rescued by formulating them into crystalline nanosuspensions. In the process of overcoming issues involving solubility, additional pharmacokinetic benefits of the drugs so formulated have come to be appreciated. As such, insolubility issues of the past have provoked a paradigm change, which now offers novel solutions for innovative drugs of the future.