IMI - oral biopharmaceutics tools project - evaluation of bottom-up PBPK prediction success part 1: Characterisation of the OrBiTo database of compounds.

Predicting oral bioavailability (Foral) is of importance for estimating systemic exposure of orally administered drugs. Physiologically-based pharmacokinetic (PBPK) modelling and simulation have been applied extensively in biopharmaceutics recently. The Oral Biopharmaceutical Tools (OrBiTo) project (Innovative Medicines Initiative) aims to develop and improve upon biopharmaceutical tools, including PBPK absorption models. A large-scale evaluation of PBPK models may be considered the first step. Here we characterise the OrBiTo active pharmaceutical ingredient (API) database for use in a large-scale simulation study. The OrBiTo database comprised 83 APIs and 1475 study arms. The database displayed a median logP of 3.60 (2.40-4.58), human blood-to-plasma ratio of 0.62 (0.57-0.71), and fraction unbound in plasma of 0.05 (0.01-0.17). The database mainly consisted of basic compounds (48.19%) and Biopharmaceutics Classification System class II compounds (55.81%). Median human intravenous clearance was 16.9L/h (interquartile range: 11.6-43.6L/h; n=23), volume of distribution was 80.8L (54.5-239L; n=23). The majority of oral formulations were immediate release (IR: 87.6%). Human Foral displayed a median of 0.415 (0.203-0.724; n=22) for IR formulations. The OrBiTo database was found to be largely representative of previously published datasets. 43 of the APIs were found to satisfy the minimum inclusion criteria for the simulation exercise, and many of these have significant gaps of other key parameters, which could potentially impact the interpretability of the simulation outcome. However, the OrBiTo simulation exercise represents a unique opportunity to perform a large-scale evaluation of the PBPK approach to predicting oral biopharmaceutics.

High-throughput quantitative and qualitative analysis of microsomal incubations by cocktail analysis with an ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometer system.

BACKGROUND: Metabolite identification studies are very resource intensive and also are rarely performed in early discovery. Here, we report the validation of an ultraperformance liquid chromatography-high-resolution mass spectrometry (UPLC-HRMS) platform for generating high-throughput stability data with structure elucidation in a single injection. MATERIALS & METHODS: Tandem mass spectrometry spectra were obtained for quantitative analysis using a generic information-dependent acquisition method from pooled microsomal samples incubated at low compound concentrations. RESULTS: A good correlation was observed between clearance determined using UPLC-HRMS and UPLC-triple-quadrupole analysis. Structural elucidation performed with MassMetaSite™ (Molecular Discovery, Perugia, Italy) software identified 85% of the major metabolites of eight marketed drugs and over 100 internal compounds under these conditions. CONCLUSION: For the first time, a high-throughput quantitative-qualitative workflow was established using a cocktail approach for sample analysis with UPLC-HRMS in order to enable metabolite identification in early discovery projects.

PDGF-CC induces tissue factor expression: role of PDGF receptor alpha/beta.

Tissue factor (TF) is the principal trigger of the coagulation cascade and involved in arterial thrombus formation. Platelet-derived growth factor CC (PDGF-CC) is a recently discovered member of the PDGF family released upon platelet activation. This study assesses the impact of PDGF-CC on TF expression in human cells. PDGF-CC concentration-dependently induced TF expression by 2.5-fold in THP-1 cells, by 2.0-fold in human peripheral blood monocytes, by 1.4-fold in vascular smooth muscle cells, and by 2.6-fold in microvascular endothelial cells, but did not affect TF expression in aortic endothelial cells. A similar pattern was observed with PDGF-BB. In contrast, PDGF-AA did not alter TF expression in THP-1 cells. TF whole cell activity was induced following stimulation with PDGF-BB and PDGF-CC in THP-1 cells. Real-time polymerase chain reaction revealed that PDGF-CC induced TF mRNA. PDGF-CC transiently activated p42/44 MAP kinase [extracellular signal-regulated kinase (ERK)], while phosphorylation of the MAP kinases c-Jun NH(2)-terminal kinase (JNK) and p38 remained unaffected. PD98059, a specific inhibitor of ERK phosphorylation, but not the p38 inhibitor SB203580 or the JNK inhibitor SP600125 prevented PDGF-CC induced TF expression in a concentration-dependent manner. The effect of PDGF-CC was antagonized by both PDGF receptor alpha and PDGF receptor beta neutralizing antibodies; in contrast, PDGF-BB was only inhibited by PDGF receptor beta blocking antibody. PDGF receptor alpha and PDGF receptor beta inhibition prevented PDGF-CC-induced ERK phosphorylation. PDGF-CC induces TF expression via activation of alpha/beta receptor heterodimers and an ERK-dependent signal transduction pathway.