IT-Ausbildung an Berufsschulen: aus Sicht von BerufsschullehrerInnen

"Den modernen Technologien und den damit verbundenen Herausforderungen an die beruflichen Schulen und ihren Unterricht begegnen die Lehrkräfte überwiegend mit Engagement und Motivation. Dieses kann jedoch die zentralen Probleme – zeitliche und finanzielle Ressourcenknappheiten – nicht vollständig kompensieren. Die Kosten von Fortbildungen und Technologie werden als belastend empfunden, dennoch wird überwiegend ein gutes Qualifikations- und Ausstattungsniveau diagnostiziert; Fortbildungen finden überwiegend in der Freizeit statt. Die Personalsituation wird als uneinheitlich wahrgenommen, es deutet sich eine Spaltung an. Die Zusammenarbeit der betrieblichen und schulischen Lernorte gestaltet sich eher problematisch, wenngleich diese als sinnvoll angesehen wird. Zentrale Möglichkeiten zur Verbesserung der Ausbildungssituation bestehen in der Entlastung bzw. Erhöhung zeilicher und finanzieller Ressourcen für Fortbildungen und technischen Support. Zur Verbesserung der Zusammenarbeit von betrieblichen und schulischen Lernorten werden neben zeitlichen Ressourcen insbesondere neue, differenzierte Formen der Zusammenarbeit, die den unterschiedlichen Orientierungen von Betrieben und den verschiedenen schulischen Ausbildungszweigen gerecht werden, erwünscht." (Autorenreferat

Physiologically Based Pharmacokinetic Modeling to Describe the CYP2D6 Activity Score-Dependent Metabolism of Paroxetine, Atomoxetine and Risperidone

The cytochrome P450 2D6 (CYP2D6) genotype is the single most important determinant of CYP2D6 activity as well as interindividual and interpopulation variability in CYP2D6 activity. Here, the CYP2D6 activity score provides an established tool to categorize the large number of CYP2D6 alleles by activity and facilitates the process of genotype-to-phenotype translation. Compared to the broad traditional phenotype categories, the CYP2D6 activity score additionally serves as a superior scale of CYP2D6 activity due to its finer graduation. Physiologically based pharmacokinetic (PBPK) models have been successfully used to describe and predict the activity score-dependent metabolism of CYP2D6 substrates. This study aimed to describe CYP2D6 drug–gene interactions (DGIs) of important CYP2D6 substrates paroxetine, atomoxetine and risperidone by developing a substrate-independent approach to model their activity score-dependent metabolism. The models were developed in PK-Sim®, using a total of 57 plasma concentration–time profiles, and showed good performance, especially in DGI scenarios where 10/12, 5/5 and 7/7 of DGI AUClast ratios and 9/12, 5/5 and 7/7 of DGI Cmax ratios were within the prediction success limits. Finally, the models were used to predict their compound’s exposure for different CYP2D6 activity scores during steady state. Here, predicted DGI AUCss ratios were 3.4, 13.6 and 2.0 (poor metabolizers; activity score = 0) and 0.2, 0.5 and 0.95 (ultrarapid metabolizers; activity score = 3) for paroxetine, atomoxetine and risperidone active moiety (risperidone + 9-hydroxyrisperidone), respectively

Diclofenac does not interact with codeine metabolism in vivo: A study in healthy volunteers

BACKGROUND: Previously, we have demonstrated a marked inhibition of codeine glucuronidation by diclofenac in human liver tissue homogenate. We therefore aimed to investigate whether diclofenac inhibits glucuronidation of codeine also in vivo in healthy volunteers. METHODS: In a randomised, placebo-controlled, double-blind, cross-over study, 12 healthy volunteers received a singe of 100 mg codeine phosphate plus 50 mg diclofenac sodium or codeine phosphate plus placebo. Over a 36 hour period serum concentrations of codeine and its metabolites as well as urinary excretion were analysed using LC-mass spectrometry. Side effects were recorded and analgesic efficacy was determined using the cold pressor test (0–6 h). RESULTS: A single dose of diclofenac did not alter the formation of codeine-6-glucuronide in healthy volunteers. Metabolic clearance of codeine to morphine was not affected by diclofenac. In terms of side effects, both treatments were well tolerated. Diclofenac did not significantly influence the analgesic effects of codeine in the cold pressor test. CONCLUSIONS: In contrast to recent in vitro data, a single oral dose of diclofenac did not alter the glucuronidation of codeine in healthy volunteers

Dasatinib reverses Cancer-associated Fibroblasts (CAFs) from primary Lung Carcinomas to a Phenotype comparable to that of normal Fibroblasts

Cancer associated fibroblasts (CAFs) play a critical role for growth, invasion, and metastasis of cancer. Therefore, targeting CAFs with small molecule inhibitors may be an attractive anti-tumor strategy. The current study aims to identify small molecule kinase inhibitors affecting CAF's growth and to characterize the biological effects of active compounds on primary CAFs from lung cancer. We screened two individual CAF strains for their sensitivity to a panel of 160 kinase inhibitors. Five kinase inhibitors were identified inhibiting more than 50% of the growth of both cell lines. Three of them were inhibitors of PDGFR at nanomolar concentrations. Therefore, we further tested the FDA approved PDGFR inhibitors Dasatinib, Nilotinib, Sorafenib, and Imatinib. All 37 CAF strains investigated were highly sensitive to Dasatinib at clinically relevant concentrations. Imatinib was slightly less effective, whereas the inhibitory effects of Nilotinib and Sorafenib were significantly less pronounced

Obesity alters endoxifen plasma levels in young breast cancer patients: A pharmacometric simulation approach

Endoxifen is one of the most important metabolites of the prodrug tamoxifen. High interindividual variability in endoxifen steady‐state concentrations (CSS,min ENDX) is observed under tamoxifen standard dosing and patients with breast cancer who do not reach endoxifen concentrations above a proposed therapeutic threshold of 5.97 ng/mL may be at a 26% higher recurrence risk compared with patients with endoxifen concentrations exceeding this value. In this investigation, 10 clinical tamoxifen studies were pooled (1,388 patients) to investigate influential factors on CSS,min ENDX using nonlinear mixed‐effects modeling. Age and body weight were found to significantly impact CSS,min ENDX in addition to CYP2D6 phenotype. Compared with postmenopausal patients, premenopausal patients had a 30% higher risk for subtarget CSS,min ENDX at tamoxifen 20 mg per day. In treatment simulations for distinct patient subpopulations, young overweight patients had a 3.1–13.8‐fold higher risk for subtarget CSS,min ENDX compared with elderly low‐weight patients. Considering ever‐rising obesity rates and the clinical importance of tamoxifen for premenopausal patients, this subpopulation may benefit most from individualized tamoxifen dosing

Simulation-Based Assessment of the Impact of Non-Adherence on Endoxifen Target Attainment in Different Tamoxifen Dosing Strategies

Tamoxifen is widely used in breast cancer treatment and minimum steady-state concentrations of its active metabolite endoxifen (CSS,min ENDX) above 5.97 ng/mL have been associated with favourable disease outcome. Yet, about 20% of patients do not reach target CSS,min ENDX applying conventional tamoxifen dosing. Moreover, 4–75% of patients are non-adherent, resulting in worse disease outcomes. Assuming complete adherence, we previously showed model-informed precision dosing (MIPD) to be superior to conventional and CYP2D6-guided dosing in minimising the proportion of patients with subtarget CSS,min ENDX. Given the high non-adherence rate in long-term tamoxifen therapy, this study investigated the impact of non-adherence on CSS,min ENDX target attainment in different dosing strategies. We show that MIPD allows to account for the expected level of non-adherence (here: up to 2 missed doses/week): increasing the MIPD target threshold from 5.97 ng/mL to 9 ng/mL (the lowest reported CSS,min ENDX in CYP2D6 normal metabolisers) as a safeguard resulted in the lowest interindividual variability and proportion of patients with subtarget CSS,min ENDX even in non-adherent patients. This is a significant improvement to conventional and CYP2D6-guided dosing. Adding a fixed increment to the originally selected dose is not recommended, since it inflates interindividual variability

Prediction of Drug–Drug–Gene Interaction Scenarios of (E)-Clomiphene and Its Metabolites Using Physiologically Based Pharmacokinetic Modeling

Clomiphene, a selective estrogen receptor modulator (SERM), has been used for the treatment of anovulation for more than 50 years. However, since (E)-clomiphene ((E)-Clom) and its metabolites are eliminated primarily via Cytochrome P450 (CYP) 2D6 and CYP3A4, exposure can be affected by CYP2D6 polymorphisms and concomitant use with CYP inhibitors. Thus, clomiphene therapy may be susceptible to drug–gene interactions (DGIs), drug–drug interactions (DDIs) and drug–drug–gene interactions (DDGIs). Physiologically based pharmacokinetic (PBPK) modeling is a tool to quantify such DGI and DD(G)I scenarios. This study aimed to develop a whole-body PBPK model of (E)-Clom including three important metabolites to describe and predict DGI and DD(G)I effects. Model performance was evaluated both graphically and by calculating quantitative measures. Here, 90% of predicted Cmax and 80% of AUClast values were within two-fold of the corresponding observed value for DGIs and DD(G)Is with clarithromycin and paroxetine. The model also revealed quantitative contributions of different CYP enzymes to the involved metabolic pathways of (E)-Clom and its metabolites. The developed PBPK model can be employed to assess the exposure of (E)-Clom and its active metabolites in as-yet unexplored DD(G)I scenarios in future studies