Predicting the safety and efficacy of butter therapy to raise tumour pHe: an integrative modelling study

Background: Clinical positron emission tomography imaging has demonstrated the vast majority of human cancers exhibit significantly increased glucose metabolism when compared with adjacent normal tissue, resulting in an acidic tumour microenvironment. Recent studies demonstrated reducing this acidity through systemic buffers significantly inhibits development and growth of metastases in mouse xenografts.\ud \ud Methods: We apply and extend a previously developed mathematical model of blood and tumour buffering to examine the impact of oral administration of bicarbonate buffer in mice, and the potential impact in humans. We recapitulate the experimentally observed tumour pHe effect of buffer therapy, testing a model prediction in vivo in mice. We parameterise the model to humans to determine the translational safety and efficacy, and predict patient subgroups who could have enhanced treatment response, and the most promising combination or alternative buffer therapies.\ud \ud Results: The model predicts a previously unseen potentially dangerous elevation in blood pHe resulting from bicarbonate therapy in mice, which is confirmed by our in vivo experiments. Simulations predict limited efficacy of bicarbonate, especially in humans with more aggressive cancers. We predict buffer therapy would be most effectual: in elderly patients or individuals with renal impairments; in combination with proton production inhibitors (such as dichloroacetate), renal glomular filtration rate inhibitors (such as non-steroidal anti-inflammatory drugs and angiotensin-converting enzyme inhibitors), or with an alternative buffer reagent possessing an optimal pK of 7.1–7.2.\ud \ud Conclusion: Our mathematical model confirms bicarbonate acts as an effective agent to raise tumour pHe, but potentially induces metabolic alkalosis at the high doses necessary for tumour pHe normalisation. We predict use in elderly patients or in combination with proton production inhibitors or buffers with a pK of 7.1–7.2 is most promising

Ensemble-based methods for forecasting census in hospital units

BACKGROUND: The ability to accurately forecast census counts in hospital departments has considerable implications for hospital resource allocation. In recent years several different methods have been proposed forecasting census counts, however many of these approaches do not use available patient-specific information. METHODS: In this paper we present an ensemble-based methodology for forecasting the census under a framework that simultaneously incorporates both (i) arrival trends over time and (ii) patient-specific baseline and time-varying information. The proposed model for predicting census has three components, namely: current census count, number of daily arrivals and number of daily departures. To model the number of daily arrivals, we use a seasonality adjusted Poisson Autoregressive (PAR) model where the parameter estimates are obtained via conditional maximum likelihood. The number of daily departures is predicted by modeling the probability of departure from the census using logistic regression models that are adjusted for the amount of time spent in the census and incorporate both patient-specific baseline and time varying patient-specific covariate information. We illustrate our approach using neonatal intensive care unit (NICU) data collected at Women & Infants Hospital, Providence RI, which consists of 1001 consecutive NICU admissions between April 1st 2008 and March 31st 2009. RESULTS: Our results demonstrate statistically significant improved prediction accuracy for 3, 5, and 7 day census forecasts and increased precision of our forecasting model compared to a forecasting approach that ignores patient-specific information. CONCLUSIONS: Forecasting models that utilize patient-specific baseline and time-varying information make the most of data typically available and have the capacity to substantially improve census forecasts

The UBA-UIM Domains of the USP25 Regulate the Enzyme Ubiquitination State and Modulate Substrate Recognition

USP25m is the muscle isoform of the deubiquitinating (DUB) enzyme USP25. Similarly to most DUBs, data on USP25 regulation and substrate recognition is scarce. In silico analysis predicted three ubiquitin binding domains (UBDs) at the N-terminus: one ubiquitin-associated domain (UBA) and two ubiquitin-interacting motifs (UIMs), whereas no clear structural homology at the extended C-terminal region outside the catalytic domains were detected. In order to asses the contribution of the UBDs and the C-terminus to the regulation of USP25m catalytic activity, ubiquitination state and substrate interaction, serial and combinatorial deletions were generated. Our results showed that USP25m catalytic activity did not strictly depend on the UBDs, but required a coiled-coil stretch between amino acids 679 to 769. USP25 oligomerized but this interaction did not require either the UBDs or the C-terminus. Besides, USP25 was monoubiquitinated and able to autodeubiquitinate in a possible loop of autoregulation. UBDs favored the monoubiquitination of USP25m at the preferential site lysine 99 (K99). This residue had been previously shown to be a target for SUMO and this modification inhibited USP25 activity. We showed that mutation of K99 clearly diminished USP25-dependent rescue of the specific substrate MyBPC1 from proteasome degradation, thereby supporting a new mechanistic model, in which USP25m is regulated through alternative conjugation of ubiquitin (activating) or SUMO (inhibiting) to the same lysine residue (K99), which may promote the interaction with distinct intramolecular regulatory domains

Cerebrospinal fluid HIV-1 RNA, intrathecal immunoactivation, and drug concentrations after treatment with a combination of saquinavir, nelfinavir, and two nucleoside analogues: the M61022 study

BACKGROUND: The way various antiretroviral drugs and drug combinations affect HIV-1 infection in the central nervous system is still largely unknown. The aim of this study was to determine the cerebrospinal fluid (CSF) steady-state concentrations of saquinavir and nelfinavir in relation to plasma concentrations, and to study their effect in combination with two nucleoside reverse transcriptase inhibitors (NRTIs) on CSF viral loads, intrathecal immunoactivation, and blood-brain barrier integrity. METHODS: Paired CSF and plasma samples from 8 antiretroviral-naïve HIV-1 infected patients starting combination therapy with saquinavir, nelfinavir, and two nucleoside analogues were collected prior to treatment, and again after approximately 12 and 48 weeks of antiretroviral therapy. Additional plasma samples were taken at weeks 2, 4, 8, 24, and 36. The concentrations of protease inhibitors were analysed, as were levels of HIV-1 RNA, CD4+ T-cell count, β2-microglobulin, neopterin, albumin ratio, IgG index, and monocytic cell count. RESULTS: None of the patients in the study presented with HIV-1 RNA < 50 copies/mL in CSF or plasma prior to treatment, compared to 5/7 at the end of the study. Signs of cell-mediated intrathecal immunoactivation, measured by neopterin and β2-microglobulin, decreased significantly in both CSF and serum, although only 1/7 reached normal CSF neopterin levels after 48 weeks of treatment. There was no significant reduction of albumin ratio, IgG index or CSF monocytic cell count. Saquinavir median (range) concentrations were < 2.5 (< 2.5–96.0) nM unbound in plasma, and < 2.5 (< 2.5–9.0) nM total in CSF. Nelfinavir median (range) concentrations were 10.0 (< 2.0–31.0) nM unbound in plasma, and < 2.0 (< 2.0–23.0) nM total in CSF. Saquinavir and nelfinavir were detectable in 7/15 and 9/15 CSF samples, respectively. CONCLUSION: Saquinavir and nelfinavir, in combination with two NRTIs, decrease the CSF viral load and, to a lesser extent, intrathecal immunoactivation. We found reasonably high CSF concentrations of nelfinavir, but suboptimal concentrations of saquinavir

Mechanism-based pharmacokinetic-pharmacodynamic modeling of the dopamine D-2 receptor occupancy of olanzapine in rats

A mechanism-based PK-PD model was developed to predict the time course of dopamine D-2 receptor occupancy (D2RO) in rat striatum following administration of olanzapine, an atypical antipsychotic drug. A population approach was utilized to quantify both the pharmacokinetics and pharmacodynamics of olanzapine in rats using the exposure (plasma and brain concentration) and D2RO profile obtained experimentally at various doses (0.01-40 mg/kg) administered by different routes. A two-compartment pharmacokinetic model was used to describe the plasma pharmacokinetic profile. A hybrid physiology- and mechanism-based model was developed to characterize the D-2 receptor binding in the striatum and was fitted sequentially to the data. The parameters were estimated using nonlinear mixed-effects modeling . Plasma, brain concentration profiles and time course of D2RO were well described by the model; validity of the proposed model is supported by good agreement between estimated association and dissociation rate constants and in vitro values from literature. This model includes both receptor binding kinetics and pharmacokinetics as the basis for the prediction of the D2RO in rats. Moreover, this modeling framework can be applied to scale the in vitro and preclinical information to clinical receptor occupancy

Pharmacokinetic-Pharmacodynamic Modeling of the D2 and 5-HT2A Receptor Occupancy of Risperidone and Paliperidone in Rats

A pharmacokinetic-pharmacodynamic (PK-PD) model was developed to describe the time course of brain concentration and dopamine D-2 and serotonin 5-HT2A receptor occupancy (RO) of the atypical antipsychotic drugs risperidone and paliperidone in rats. A population approach was utilized to describe the PK-PD of risperidone and paliperidone using plasma and brain concentrations and D-2 and 5-HT2A RO data. A previously published physiology- and mechanism-based (PBPKPD) model describing brain concentrations and D-2 receptor binding in the striatum was expanded to include metabolite kinetics, active efflux from brain, and binding to 5-HT2A receptors in the frontal cortex. A two-compartment model best fit to the plasma PK profile of risperidone and paliperidone. The expanded PBPKPD model described brain concentrations and D-2 and 5-HT2A RO well. Inclusion of binding to 5-HT2A receptors was necessary to describe observed brain-to-plasma ratios accurately. Simulations showed that receptor affinity strongly influences brain-to-plasma ratio pattern. Binding to both D-2 and 5-HT2A receptors influences brain distribution of risperidone and paliperidone. This may stem from their high affinity for D-2 and 5-HT2A receptors. Receptor affinities and brain-to-plasma ratios may need to be considered before choosing the best PK-PD model for centrally active drugs

Translational Modeling in Schizophrenia:Predicting Human Dopamine D2 Receptor Occupancy

OBJECTIVES: To assess the ability of a previously developed hybrid physiology-based pharmacokinetic-pharmacodynamic (PBPKPD) model in rats to predict the dopamine D2 receptor occupancy (D2RO) in human striatum following administration of antipsychotic drugs.METHODS: A hybrid PBPKPD model, previously developed using information on plasma concentrations, brain exposure and D2RO in rats, was used as the basis for the prediction of D2RO in human. The rat pharmacokinetic and brain physiology parameters were substituted with human population pharmacokinetic parameters and human physiological information. To predict the passive transport across the human blood-brain barrier, apparent permeability values were scaled based on rat and human brain endothelial surface area. Active efflux clearance in brain was scaled from rat to human using both human brain endothelial surface area and MDR1 expression. Binding constants at the D2 receptor were scaled based on the differences between in vitro and in vivo systems of the same species. The predictive power of this physiology-based approach was determined by comparing the D2RO predictions with the observed human D2RO of six antipsychotics at clinically relevant doses.RESULTS: Predicted human D2RO was in good agreement with clinically observed D2RO for five antipsychotics. Models using in vitro information predicted human D2RO well for most of the compounds evaluated in this analysis. However, human D2RO was under-predicted for haloperidol.CONCLUSIONS: The rat hybrid PBPKPD model structure, integrated with in vitro information and human pharmacokinetic and physiological information, constitutes a scientific basis to predict the time course of D2RO in man.</p

Recent progress towards development of effective systemic chemotherapy for the treatment of malignant brain tumors

Systemic chemotherapy has been relatively ineffective in the treatment of malignant brain tumors even though systemic chemotherapy drugs are small molecules that can readily extravasate across the porous blood-brain tumor barrier of malignant brain tumor microvasculature. Small molecule systemic chemotherapy drugs maintain peak blood concentrations for only minutes, and therefore, do not accumulate to therapeutic concentrations within individual brain tumor cells. The physiologic upper limit of pore size in the blood-brain tumor barrier of malignant brain tumor microvasculature is approximately 12 nanometers. Spherical nanoparticles ranging between 7 nm and 10 nm in diameter maintain peak blood concentrations for several hours and are sufficiently smaller than the 12 nm physiologic upper limit of pore size in the blood-brain tumor barrier to accumulate to therapeutic concentrations within individual brain tumor cells. Therefore, nanoparticles bearing chemotherapy that are within the 7 to 10 nm size range can be used to deliver therapeutic concentrations of small molecule chemotherapy drugs across the blood-brain tumor barrier into individual brain tumor cells. The initial therapeutic efficacy of the Gd-G5-doxorubicin dendrimer, an imageable nanoparticle bearing chemotherapy within the 7 to 10 nm size range, has been demonstrated in the orthotopic RG-2 rodent malignant glioma model. Herein I discuss this novel strategy to improve the effectiveness of systemic chemotherapy for the treatment of malignant brain tumors and the therapeutic implications thereof