Biomedical subjects

Niklas Sandler

Publications and source records attributed to Niklas Sandler.

4 recordsLinked to original sources

PubMed2007

Influence of polymorphic form, morphology, and excipient interactions on the dissolution of carbamazepine compacts.

To gain a deeper understanding of the behavior of carbamazepine (CBZ) and CBZ dihydrate (DH) compacts during in vitro dissolution tests various factors were investigated: hydrate formation of CBZ, crystal morphology, surface area, and excipient influence. Dissolution tests were performed in three different dissolution media: distilled water, hydroxypropyl methylcellulose (HPMC), and polyethylene glycol (PEG) solutions. For the CBZ compacts, the dissolution rate of CBZ in water was fastest (0.338 mg L(-1) min(-1)). With increasing ability of the excipients to inhibit the hydration of CBZ (PEG < HPMC), surprisingly the dissolution rate of CBZ compacts decreased: PEG solution (0.314 mg L(-1) min(-1)) > HPMC solution (0.257 mg L(-1) min(-1)). This implies that DH formation resulted in an apparent increase in the dissolution rate rather than slowing it down. For the DH compacts, the dissolution rate in water (0.055 mg L(-1) min(-1)) was slower than that of PEG and HPMC solutions (0.174 and 0.178 mg L(-1) min(-1), respectively). The contact angle measurements showed a significantly higher value in water (61.0 degrees) than in PEG and HPMC solutions (44.8 degrees and 43.1 degrees, respectively). Although the dissolution of CBZ and DH compacts in various dissolution media are complex processes, the influence and relative importance of these factors were clearly detected providing better understanding of the dissolution behavior of the drug.

Carbamazepine↗

PubMed2007

Image analysis by pulse coupled neural networks (PCNN)--a novel approach in granule size characterization.

A biologically inspired spiking neural network model, the pulse coupled neural network (PCNN), has been applied for the first time in bulk particle characterization, and specifically in the characterization of pharmaceutical granule size distributions. The PCNN was trained on surface images of pharmaceutical granule beds, and the adjustable parameters (radius neuron interconnection, r0, linking weight coefficient, beta, local threshold potential, VTheta, and number of iterations) were successfully optimized using design of experiments. As demonstrated with size fractions of granules, it was found that the PCNN produced granule size-dependent signals. In general, a first highest and relatively narrow peak located in the region of two to twelve iterations corresponded to smaller particle size, while larger particles resulted in wider peaks and in highest (not first) peak at a range between 13 and 25 iterations. Better predictions, i.e. lower RMSEP (root mean squared error of prediction) values, were obtained using high beta value, low r0 and VTheta values, while the number of iterations had to exceed 110 and the optimized model (RMSEP lower than 5) corresponded to PCNN variables: r0=1, beta=0.4, VTheta=2, and number of iterations=150. The coefficient of determination (R2) of the model was 0.94 and the predicted variation (Q2) was 0.91, while the Pearson correlation coefficient between the predicted and the measured mean particle size by sieving for eight test batches was 0.98. These findings could be characterized as promising and encouraging for the further use of image analysis by PCNNs in pharmaceutical bulk particle size and shape characterization.

Image Processing, Computer-Assisted↗

PubMed2006

Screening for differences in the amorphous state of indomethacin using multivariate visualization.

The aim of this study was to examine molecular-level differences in the amorphous state of indomethacin prepared from both alpha- and gamma-polymorphs using various preparative techniques: milling, quench cooling of a melt, slow cooling of a melt and spray drying. X-ray powder diffraction (XRPD), polarizing light microscopy (PLM), differential scanning calorimetry, as well as mid-infrared (MIR), near infrared (NIR) and Raman spectroscopy were used to analyze the samples after preparation. Principal component analysis (PCA) was used to visualize the differences in the spectroscopic data. According to the XRPD and PLM measurements, all samples except the spray dried indomethacin were amorphous after preparation. Spray dried indomethacin had some remaining residual crystallinity. Differences in the amorphous samples could be found on molecular level: the milled samples clustered separately from the other amorphous samples in the PCA of MIR, NIR and Raman spectra. This could be due to either small degrees of undetected crystallinity remaining in the samples after milling or differences in the hydrogen bonding in the different amorphous samples of indomethacin. The spectroscopic techniques revealed different information about the samples. Raman spectroscopy was most sensitive to differences caused by the preparation techniques and degradation products. Multivariate methods, such as PCA, offer an efficient tool to screen for these differences in the amorphous state.

Chemistry, Pharmaceutical↗

PubMed2005

Pellet manufacturing by extrusion-spheronization using process analytical technology.

The aim of this study was to investigate the phase transitions occurring in nitrofurantoin and theophylline formulations during pelletization by extrusion-spheronization. An at-line process analytical technology (PAT) approach was used to increase the understanding of the solid-state behavior of the active pharmaceutical ingredients (APIs) during pelletization. Raman spectroscopy, near-infrared (NIR) spectroscopy, and X-ray powder diffraction (XRPD) were used in the characterization of polymorphic changes during the process. Samples were collected at the end of each processing stage (blending, granulation, extrusion, spheronization, and drying). Batches were dried at 3 temperature levels (60 degrees C, 100 degrees C, and 135 degrees C). Water induced a hydrate formation in both model formulations during processing. NIR spectroscopy gave valuable real-time data about the state of water in the system, but it was not able to detect the hydrate formation in the theophylline and nitrofurantoin formulations during the granulation, extrusion, and spheronization stages because of the saturation of the water signal. Raman and XRPD measurement results confirmed the expected pseudopolymorphic changes of the APIs in the wet process stages. The relatively low level of Raman signal with the theophylline formulation complicated the interpretation. The drying temperature had a significant effect on dehydration. For a channel hydrate (theophylline), dehydration occurred at lower drying temperatures. In the case of isolated site hydrate (nitrofurantoin), dehydration was observed at higher temperatures. To reach an understanding of the process and to find the critical process parameters, the use of complementary analytical techniques are absolutely necessary when signals from APIs and different excipients overlap each other.

Chemistry, Pharmaceutical↗