Risk Factors for Development of Cholestatic Drug-Induced Liver Injury: Inhibition of Hepatic Basolateral Bile Acid Transporters Multidrug Resistance-Associated Proteins 3 and 4

Impaired hepatic bile acid export may contribute to development of cholestatic drug-induced liver injury (DILI). The multidrug resistance-associated proteins (MRP) 3 and 4 are postulated to be compensatory hepatic basolateral bile acid efflux transporters when biliary excretion by the bile salt export pump (BSEP) is impaired. BSEP inhibition is a risk factor for cholestatic DILI. This study aimed to characterize the relationship between MRP3, MRP4, and BSEP inhibition and cholestatic potential of drugs. The inhibitory effect of 88 drugs (100 μM) on MRP3- and MRP4-mediated substrate transport was measured in membrane vesicles. Drugs selected for investigation included 50 BSEP non-inhibitors (24 non-cholestatic; 26 cholestatic) and 38 BSEP inhibitors (16 non-cholestatic; 22 cholestatic). MRP4 inhibition was associated with an increased risk of cholestatic potential among BSEP non-inhibitors. In this group, for each 1% increase in MRP4 inhibition, the odds of the drug being cholestatic increased by 3.1%. Using an inhibition cutoff of 21%, which predicted a 50% chance of cholestasis, 62% of cholestatic drugs inhibited MRP4 (P < 0.05); in contrast, only 17% of non-cholestatic drugs were MRP4 inhibitors. Among BSEP inhibitors, MRP4 inhibition did not provide additional predictive value of cholestatic potential; almost all BSEP inhibitors were also MRP4 inhibitors. Inclusion of pharmacokinetic predictor variables (e.g., maximal unbound concentration in plasma) in addition to percent MRP4 inhibition in logistic regression models did not improve cholestasis prediction. Association of cholestasis with percent MRP3 inhibition was not statistically significant, regardless of BSEP-inhibition status. Inhibition of MRP4, in addition to BSEP, may be a risk factor for the development of cholestatic DILI

Putting fossils on the map: Applying a geographical information system to heritage resources

A geographical information system (GIS) database was compiled of Permo-Triassic tetrapod fossils from the Karoo Supergoup in South African museum collections. This database is the first of its kind and has great time applicability for understanding tetrapod biodiversity change though time more than 200 million years ago. Because the museum catalogues all differed in recorded information and were not compliant with field capture requirements, this information had to be standardised to a format that could be utilised for archival and research application. Our paper focuses on the processes involved in building the GIS project, capturing metadata on fossil collections and formulating future best practices. The result is a multi-layered GIS database of the tetrapod fossil record of the Beaufort Group of South Africa for use as an accurate research tool in palaeo- and geoscience research with applications for ecology, ecosystems, stratigraphy and basin development.NCS201

Model-based prediction of myelosuppression and recovery based on frequent neutrophil monitoring

Purpose To investigate whether a more frequent monitoring of the absolute neutrophil counts (ANC) during myelo-suppressive chemotherapy, together with model-based predictions, can improve therapy management, compared to the limited clinical monitoring typically applied today. Methods Daily ANC in chemotherapy-treated cancer patients were simulated from a previously published population model describing docetaxel-induced myelosuppression. The simulated values were used to generate predictions of the individual ANC time-courses, given the myelosuppression model. The accuracy of the predicted ANC was evaluated under a range of conditions with reduced amount of ANC measurements. Results The predictions were most accurate when more data were available for generating the predictions and when making short forecasts. The inaccuracy of ANC predictions was highest around nadir, although a high sensitivity (&gt;= 90%) was demonstrated to forecast Grade 4 neutropenia before it occurred. The time for a patient to recover to baseline could be well forecasted 6 days (+/- 1 day) before the typical value occurred on day 17. Conclusions Daily monitoring of the ANC, together with model-based predictions, could improve anticancer drug treatment by identifying patients at risk for severe neutropenia and predicting when the next cycle could be initiated