Comparison of In Vitro and In Vivo Results Using the GastroDuo and the Salivary Tracer Technique: Immediate Release Dosage Forms under Fasting Conditions.

The fasted state administration of immediate release (IR) dosage forms is often regarded as uncritical since physiological aspects seem to play a minor role for disintegration and drug release. However, recent in vivo studies in humans have highlighted that fasted state conditions are in fact highly dynamic. It was therefore the aim of this study to investigate the disintegration and drug release behavior of four different IR formulations of the probe drug caffeine under physiologically relevant conditions with the aid of the GastroDuo. One film-coated tablet and three different capsule formulations based on capsule shells either made from hard gelatin or hydroxypropylmethyl cellulose (HPMC) were tested in six different test programs. To evaluate the relevance of the data generated, the four IR formulations were also studied in a four-way cross-over study in 14 healthy volunteers by using the salivary tracer technique (STT). It could be shown that the IR formulations behaved differently in the in vitro test programs. Thereby, the simulated parameters affected the disintegration and dissolution behavior of the four IR formulations in different ways. Whereas drug release from the tablet started early and was barely affected by temperature, pH or motility, the different capsule formulations showed a longer lag time and were sensitive to specific parameters. However, once drug release was initiated, it typically progressed with a higher rate for the capsules compared to the tablet. Interestingly, the results obtained with the STT were not always in line with the in vitro data. This observation was due to the fact that the probability of the different test programs was not equal and that certain scenarios were rather unlikely to occur under the controlled and standardized conditions of clinical studies. Nonetheless, the in vitro data are still valuable as they allowed to discriminate between different formulations.

Psychosocial distress and desire for support among skin cancer patients - impact of treatment setting.

BACKGROUND: Diagnosis and treatment of malignancies are frequently associated with a variety of problems for affected individuals and their relatives. In order to ensure adequate psycho-oncological and social care, it is recommended to routinely assess patients' psychosocial distress. While psychosocial services for inpatients have been expanded in recent years, the outpatient care structure in terms of psycho-oncological support is far from satisfactory, especially in Mecklenburg-Western Pomerania. We therefore set out to investigate the following questions: Does the need for psychosocial care vary in relation to (a) the treatment setting (inpatients vs. outpatients) and (b) the diagnosis? (c) Do patients experiencing psychological distress desire support? PATIENTS AND METHODS: We asked both inpatients and outpatients to rate their psychosocial situation using the Hornheide Questionnaire. Patients were also asked about their desire for psychological support and the preferred contact person. RESULTS: (a) The treatment setting had no impact on the need for psychosocial care and the desire for support. (b) Depending on the type of skin cancer, there were significant differences in the need for such care among the 251 patients surveyed. (c) Despite a certain discrepancy, there was a significant correlation between psychosocial distress (39.0 %; n = 98/251) and desire for support (14.3 %; n = 35/245). (d) Patients experiencing distress primarily chose physicians (n = 21) and psychologists (n = 20) as potential contact persons. CONCLUSIONS: (1) In addition to the level of distress, the desire for support should be inquired. (2) Recommendations by physicians represent an important means of access to psycho-oncological services. (3) Services for outpatient support should be expanded.

Unraveling spurious properties of interaction networks with tailored random networks.

We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erdös-Rényi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures--known for their complex spatial and temporal dynamics--we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis.