Phenotypic and functional characterization of T-BAM (CD40 ligand)+ T- cell non-Hodgkin's lymphoma

The precise mechanisms regulating T-helper function have been intensively investigated. We and others have recently identified a new T-cell-B-cell-activating molecule called T-BAM that directs B-cell differentiation by interacting with the CD40 molecule on B cells. Using a specific monoclonal antibody against T-BAM (5C8), we have previously shown that T-BAM expressing T cells are predominantly CD4+CD8- and in normal lymphoid tissue have a unique distribution. However, no information has been obtained regarding the phenotype and functional properties of human neoplastic T cells. Therefore, we investigated T- BAM expression immunohistochemically in 87 well-characterized T-cell non-Hodgkin's lymphomas and lymphoid leukemias (LL). We found that 21/81 neoplasms expressed detectable T-BAM and these positive tumors belong almost exclusively to the CD4+CD8- subtype. In addition, to determine whether T-BAM expression could be induced on T-BAM-LL cells, we activated T-BAM-LLs in vitro and showed that T-BAM could be upregulated only in CD4+CD8- tumors. Our studies clearly show that T- BAM is constitutively expressed in a large number of T-cell neoplasms with a relative mature phenotype (CD4+CD8-) and that only CD4+ neoplastic T cells can be induced in vitro to express this molecule. Additional studies are necessary to identify the biologic significance of T-BAM expression and its potential and clinical implications.     

Platelet-derived growth factor in vivo: levels, activity, and rate of clearance

Platelet-derived growth factor (PDGF) is a potent mitogen for many cultured connective tissue cells. It is present in concentrated form within the platelet alpha-granules and is believed to be released during platelet degranulation at sites of vascular injury. We have used a sensitive radioreceptor assay to measure PDGF levels in whole blood serum from normal humans [17.5 +/- 3.1 (SD) ng/mL] and baboons (2.7 +/- 1.2 ng/mL). PDGF was not detected in plasma from either species. In addition, plasma was found to substantially reduce the ability of added purified PDGF to bind to the cell surface PDGF receptor on cultured cells, suggesting that plasma may contain a PDGF-binding protein that would serve to inactivate PDGF released into plasma. Calculations of PDGF concentrations in serum have been corrected for the effects of the binding protein. 125I-PDGF injected intravenously into normal baboons was cleared rapidly from the plasma (t1/2 = two minutes). The rapid clearance of 125I-PDGF did not result from iodination damage, as purified unlabeled PDGF was cleared with comparable kinetics. The rapid clearance of purified and iodinated PDGF did not result from changes in PDGF structure during purification or from removal of PDGF-associated proteins during purification, as PDGF present in freeze-thaw lysates of fresh platelets was cleared equally rapidly. We conclude that release of PDGF at sites of vascular injury would greatly increase the local concentration of PDGF and that PDGF not localized to the site of injury would be rapidly cleared from the circulation.     

Food Effect Projections via Physiologically Based Pharmacokinetic Modeling: Predictive Case Studies

Food can alter the absorption of orally administered drugs. Biopharmaceutics physiologically based pharmacokinetic (PBPK) modeling offers the possibility to simulate a compound's pharmacokinetics under fasted or fed states. To advance the utility of PBPK modeling, with a view to regulatory impact, we have pooled our experience across 4 pharmaceutical companies to propose a general multistep PBPK workflow leveraging pre-existing clinical data for immediate-release formulations of Biopharmaceutics Classification System I and II compounds. With this strategy, we wish to promote pragmatic PBPK approaches for compounds where absorption is well understood, that is, compounds with moderate-to-high permeability that are not substrates for uptake transporters. Five case studies demonstrate how food effect can be well predicted using appropriately established and validated models. The case studies integrate solubility and dissolution data for initial model development and apply a “middle-out” validation with clinical data in one prandial state. Then, whenever possible, a validation against both fasted and fed state data is recommended before application of the models prospectively for to-be-marketed formulations. Thus, when combined with limited clinical data, PBPK models could be used to simulate outcomes for new doses, formulations, or active pharmaceutical ingredient forms, in lieu of a clinical food-effect study.     

Prediction of ARA/PPI Drug-Drug Interactions at the Drug Discovery and Development Interface

Advances in understanding of human disease have prompted the U.S. Food and Drug Administration to classify certain molecules as “break-through therapies,” providing an accelerated review that may potentially enhance the quality of patient lives. With this designation come compressed timelines to develop drug products, which are not only suitable for clinic trials but can also be approved and brought to the market rapidly. Early risk identification for decreased oral absorption due to drug-drug interactions with proton pump inhibitors (PPIs) or acid-reducing agents (ARAs) is paramount to an effective drug product development strategy. An early ARA/PPI drug-drug interaction (DDI) risk identification strategy has been developed using physiologically based absorption modeling that readily integrates ADMET predictor generated in silico estimates or measured in vitro solubility, permeability, and ionization constants. Observed or predicted pH-solubility profile data along with pKas and drug dosing parameters were used to calculate a fraction of drug absorbed ratio in absence and presence of ARAs/PPIs. An integrated physiologically based pharmacokinetic absorption model using GastroPlus? with pKa values fitted to measured pH-solubility profile data along with measured permeability data correctly identified the observed ARA/PPI DDI for 78% (16/22) of the clinical studies. Formulation strategies for compounds with an anticipated pH-mediated DDI risk are presented.