Obinutuzumab Effectively Depletes Key B-cell Subsets in Blood and Tissue in End-stage Renal Disease Patients.

The THEORY study evaluated the effects of single and multiple doses of obinutuzumab, a type 2 anti-CD20 antibody that induces antibody-dependent cell-mediated cytotoxicity and direct cell death, in combination with standard of care in patients with end-stage renal disease. Methods: We measured B-cell subsets and protein biomarkers of B-cell activity in peripheral blood before and after obinutuzumab administration in THEORY patients, and B-cell subsets in lymph nodes in THEORY patients and an untreated comparator cohort. Results: Obinutuzumab treatment resulted in a rapid loss of B-cell subsets (including naive B, memory B, double-negative, immunoglobulin D+ transitional cells, and plasmablasts/plasma cells) in peripheral blood and tissue. This loss of B cells was associated with increased B cell-activating factor and decreased CXCL13 levels in circulation. Conclusions: Our data further characterize the mechanistic profile of obinutuzumab and suggest that it may elicit greater efficacy in indications such as lupus where B-cell targeting therapeutics are limited by the resistance of pathogenic tissue B cells to depletion.

Exposure driven dose escalation design with overdose control: Concept and first real life experience in an oncology phase I trial.

BACKGROUND: Escalation With Overdose Control (EWOC) designs are increasingly used to ensure dose-toxicity curve of investigational oncology drugs is efficiently characterized during dose escalation steps. We propose a novel EWOC-based method that integrates the longitudinal pharmacokinetic (PK) data of individual patients in a Bayesian forecasting exposure-safety framework. METHODS: The method, called exposure-driven EWOC (ED-EWOC), relies on a population PK model coupled with a Bayesian logistic regression model to make dose recommendation for the next cohort of patients. RESULTS: We applied ED-EWOC to a real oncology clinical trial in parallel to a traditional EWOC approach. We found that for comparable priors, ED-EWOC dose recommendations were equivalent to the one suggested by EWOC when PK is dose proportional with low inter-individual variability. CONCLUSION: This case example demonstrates that ED-EWOC is logistically feasible during a trial conduct when PK bioanalysis can be expedited in the dose escalation phase. Overall, we anticipate that exposure-guided Bayesian designs could benefit patients and drug developers to identify the optimal dose steps of novel compounds entering the clinic with suspected liability in PK or that exhibit large inter-individual variability.

First-in-human trial of the PI3Kß-selective inhibitor SAR260301 in patients with advanced solid tumors.

BACKGROUND: Phosphoinositide 3-kinase (PI3K) ß is the dominant isoform for PI3K activity in many phosphatase and tensin homolog (PTEN)-deficient tumor models. This was a first-in-human study to determine the maximum tolerated dose, safety, pharmacokinetics (PK), pharmacodynamics, and preliminary activity of SAR260301, a potent PI3Kß-selective inhibitor (clinicaltrials.gov identifier NCT01673737). METHODS: Successive cohorts of patients with advanced solid tumors received increasing doses of oral SAR260301 according to a Bayesian escalation with an overdose-control process based on the occurrence of dose-limiting toxicity in the first 28-day cycle. Adverse events, tumor response, PK, and the effect of food on PK were evaluated. Target engagement was assessed in platelets. Physiologically-based PK modeling was used for exposure predictions. RESULTS: Twenty-one patients received treatment at doses ranging from 100 mg once daily to 440 mg/m2 twice daily. Dose-limiting toxicities included 1 episode of grade 3 pneumonitis (400 mg twice daily) and 1 grade 3 γ-glutamyltransferase increase (600 mg twice daily). The maximum tolerated dose was not reached. The most frequently occurring treatment-related adverse events were nausea, vomiting, and diarrhea (14% each). Pharmacologically active concentrations were reached, but SAR260301 was rapidly cleared, and exposures associated with antitumor activity in preclinical models were not maintained at the highest dose tested. Food further decreased SAR260301 exposure. CONCLUSIONS: SAR260301 had an acceptable safety profile, but exposure sufficient to inhibit the PI3K pathway was unachievable because of rapid clearance, and clinical development was terminated. These results demonstrate the importance of PK and pharmacodynamic assessments in early drug development. Cancer 2018;124:315-24. © 2017 American Cancer Society.

Towards using a full spectrum of early clinical trial data: a retrospective analysis to compare potential longitudinal categorical models for molecular targeted therapies in oncology.

Following the pattern of phase I clinical trials for cytotoxic drugs, dose-finding clinical trials in oncology of molecularly targeted agents (MTA) aim at determining the maximum tolerated dose (MTD). In classical phase I clinical trials, MTD is generally defined by the number of patients with short-term major treatment toxicities (usually called dose-limiting toxicities, DLT), occurring during the first cycle of study treatment (e.g. within the first 3weeks of treatment). However, S. Postel-Vinay (2011) highlighted that half of grade 3 to 4 toxicities, usually considered as DLT, occur after the first cycle of MTA treatment. In addition, MTAs could induce other moderate (e.g. grade 2) toxicities which could be taken into account depending on their clinical importance, chronic nature and duration. Ignoring these late toxicities may lead to an underestimation of the drug toxicity and to wrong dose recommendations for phase II and III clinical trials. Some methods have been proposed, such as the time-to-event continuous reassessment method (Cheung 2000 and Mauguen 2011), to take into account the late toxicities. We suggest approaches based on longitudinal models (Doussau 2013). We compare several models for longitudinal data, such as transitional or marginal models, to take into account all relevant toxicities occurring during the entire length of the patient treatment (and not just the events within a predefined short-term time-window). These models allow the statistician to benefit from a larger amount of safety data which could potentially improve that accuracy in MTD assessment.

Joint modeling of survival and longitudinal non-survival data: current methods and issues. Report of the DIA Bayesian joint modeling working group.

Explicitly modeling underlying relationships between a survival endpoint and processes that generate longitudinal measured or reported outcomes potentially could improve the efficiency of clinical trials and provide greater insight into the various dimensions of the clinical effect of interventions included in the trials. Various strategies have been proposed for using longitudinal findings to elucidate intervention effects on clinical outcomes such as survival. The application of specifically Bayesian approaches for constructing models that address longitudinal and survival outcomes explicitly has been recently addressed in the literature. We review currently available methods for carrying out joint analyses, including issues of implementation and interpretation, identify software tools that can be used to carry out the necessary calculations, and review applications of the methodology.

MET genetic abnormalities unreliable for patient selection for therapeutic intervention in oropharyngeal squamous cell carcinoma.

BACKGROUND: Identification of MET genetic alteration, mutation, or amplification in oropharyngeal squamous cell carcinoma (OPSCC) could lead to development of MET selective kinase inhibitors. The aim of this study was to assess the frequency and prognostic value of MET gene mutation, amplification, and protein expression in primary OPSCC. METHODS: A retrospective chart review was conducted of patients treated for single primary OPSCC between January 2007 and December 2009. Pre-treatment OPSCC tissue samples were analyzed for MET mutations, gene amplification, and overexpression using Sanger sequencing, FISH analysis, and immunohistochemistry respectively. Univariate and multivariate analyses were used to analyze correlations between molecular abnormalities and patient survival. RESULTS: 143 patients were included in this study. Six cases (4%) were identified that had a genetic variation, but previously described mutations such as p.Tyr1235Asp (Y1235D) or p.Tyr1230Cys (Y1230C) were not detected. There were 15 high polysomy cases, and only 3 cases met the criteria for true MET amplification, with ≥10% amplified cells per case. Immunohistochemistry evaluation showed 43% of cases were c-MET negative and in 57% c-MET was observed at the tumor cell level. Multivariate analysis showed no significant association between MET mutation, amplification, or expression and survival. CONCLUSIONS: Our study shows a low frequency of MET mutations and amplification in this cohort of OPSCC. There was no significant correlation between MET mutations, amplification, or expression and patient survival. These results suggest that patient selection based on these MET genetic abnormalities may not be a reliable strategy for therapeutic intervention in OPSCC.

Use of historical control data for assessing treatment effects in clinical trials.

Clinical trials rarely, if ever, occur in a vacuum. Generally, large amounts of clinical data are available prior to the start of a study, particularly on the current study's control arm. There is obvious appeal in using (i.e., 'borrowing') this information. With historical data providing information on the control arm, more trial resources can be devoted to the novel treatment while retaining accurate estimates of the current control arm parameters. This can result in more accurate point estimates, increased power, and reduced type I error in clinical trials, provided the historical information is sufficiently similar to the current control data. If this assumption of similarity is not satisfied, however, one can acquire increased mean square error of point estimates due to bias and either reduced power or increased type I error depending on the direction of the bias. In this manuscript, we review several methods for historical borrowing, illustrating how key parameters in each method affect borrowing behavior, and then, we compare these methods on the basis of mean square error, power and type I error. We emphasize two main themes. First, we discuss the idea of 'dynamic' (versus 'static') borrowing. Second, we emphasize the decision process involved in determining whether or not to include historical borrowing in terms of the perceived likelihood that the current control arm is sufficiently similar to the historical data. Our goal is to provide a clear review of the key issues involved in historical borrowing and provide a comparison of several methods useful for practitioners.

A stochastic whole-body physiologically based pharmacokinetic model to assess the impact of inter-individual variability on tissue dosimetry over the human lifespan.

Physiologically based pharmacokinetic (PBPK) models have proven to be successful in integrating and evaluating the influence of age- or gender-dependent changes with respect to the pharmacokinetics of xenobiotics throughout entire lifetimes. Nevertheless, for an effective application of toxicokinetic modelling to chemical risk assessment, a PBPK model has to be detailed enough to include all the multiple tissues that could be targeted by the various xenobiotics present in the environment. For this reason, we developed a PBPK model based on a detailed compartmentalization of the human body and parameterized with new relationships describing the time evolution of physiological and anatomical parameters. To take into account the impact of human variability on the predicted toxicokinetics, we defined probability distributions for key parameters related to the xenobiotics absorption, distribution, metabolism and excretion. The model predictability was evaluated by a direct comparison between computational predictions and experimental data for the internal concentrations of two chemicals (1,3-butadiene and 2,3,7,8-tetrachlorodibenzo-p-dioxin). A good agreement between predictions and observed data was achieved for different scenarios of exposure (e.g., acute or chronic exposure and different populations). Our results support that the general stochastic PBPK model can be a valuable computational support in the area of chemical risk analysis.

Quantifying heterogeneity in exposure-risk relationships using exhaled breath biomarkers for 1,3-butadiene exposures.

The health effects of human exposure to 1,3-butadiene (BD) have been extensively studied using both epidemiological and animal toxicology approaches. However, various data and knowledge gaps remain, one of which is an understanding of the human heterogeneity in BD dosimetry. The objective of our study was to better understand the role of individual variability in delivered tissue dose. We designed a study of laboratory exposures of a relatively large group of healthy human subjects. Subjects were then exposed to 2.0 ppm BD through a face mask for 20 min, followed by 40 min of breathing clean air. Exhaled breath concentrations of BD were measured at ten time points during and after exposure, and a three-compartment physiologically based pharmacokinetic (PBPK) model was used to quantify the kinetic behavior of BD. We implemented a Markov chain Monte Carlo procedure to fit the model to the experimental data, and used global sensitivity analysis techniques to examine the sensitivity of exhaled breath concentrations to PBPK model parameters. Uptake during exposure was strongly influenced by rebreathing of exhaled BD during exposure; inclusion of rebreathing in the model simulations resulted in a 21% increase in the amount of BD retained in the body. We found that uptake ranged from 38% to 77% across individuals. We measured considerable intra-individual variability from 11 subjects who underwent the testing twice. Most of this variation stemmed from phase I metabolism of BD, which varied by as much as a factor of 2.6 within individuals. Overall, we have sought to quantify the sources of inter- and intra-individual variabilities in the pharmacokinetic behavior of BD. The results of our research may impact the current framework for biomarker and pharmacokinetic studies by improving our understanding of the sources of heterogeneity in response to chemical exposures.

Ventilatory response to a hyperoxic test is related to the frequency of short apneic episodes in late preterm neonates.

Chemoreception is frequently involved in the processes underlying apnea in premature infants. Apnea could result from a decrease in carotid body effectiveness. However, increased carotid body activity could also initiate apnea through hypocapnia following hyperventilation when the receptors are stimulated. The aim of this study was to analyze the relationship between carotid body effectiveness and short apneic episodes in older preterm neonates. Carotid body effectiveness was assessed at thermoneutrality in 36 premature neonates (2.07 +/- 0.26 kg) by performing a 30-s hyperoxic test during sleep, the oxygen inhalation involving a ventilation decrease. Blood O(2) saturation (Sp(o2)) and ventilatory parameters were monitored before and during the hyperoxic test. Short episodes of apnea (frequency and mean duration) were recorded during the morning's 3-h interfeeding interval. Pretest Sp(o2) was not related to any of the measured respiratory parameters. A higher frequency of short apneic episodes was linked to a greater ventilation decrease in response to the hyperoxic test (rho = -0.32; p = 0.01). Increased carotid body response is correlated with greater apneic episodes frequency, even in the absence of concomitant oxygen desaturation. Fetal or early postnatal hypoxemia could have increased peripheral chemoreceptor activity, which could initiate a "overshoot/undershoot" situation, which in turn could induce a critical P(o2)/P(co2) combination and apnea.

Sequential updating of a new dynamic pharmacokinetic model for caffeine in premature neonates.

BACKGROUND AND OBJECTIVE: Caffeine treatment is widely used in nursing care to reduce the risk of apnoea in premature neonates. To check the therapeutic efficacy of the treatment against apnoea, caffeine concentration in blood is an important indicator. The present study was aimed at building a pharmacokinetic model as a basis for a medical decision support tool. METHODS: In the proposed model, time dependence of physiological parameters is introduced to describe rapid growth of neonates. To take into account the large variability in the population, the pharmacokinetic model is embedded in a population structure. The whole model is inferred within a Bayesian framework. To update caffeine concentration predictions as data of an incoming patient are collected, we propose a fast method that can be used in a medical context. This involves the sequential updating of model parameters (at individual and population levels) via a stochastic particle algorithm. RESULTS: Our model provides better predictions than the ones obtained with models previously published. We show, through an example, that sequential updating improves predictions of caffeine concentration in blood (reduce bias and length of credibility intervals). The update of the pharmacokinetic model using body mass and caffeine concentration data is studied. It shows how informative caffeine concentration data are in contrast to body mass data. CONCLUSION: This study provides the methodological basis to predict caffeine concentration in blood, after a given treatment if data are collected on the treated neonate.

Toxicokinetics of inhaled trichloroethylene and tetrachloroethylene in humans at 1 ppm: empirical results and comparisons with previous studies.

Trichloroethylene (TRI) and tetrachloroethylene (TETRA) are solvents that have been widely used in a variety of industries, and both are widespread environmental contaminants. In order to provide a better basis for understanding their toxicokinetics at environmental exposures, seven human volunteers were exposed by inhalation to 1 ppm of TRI or TETRA for 6 h, with biological samples collected for analysis during exposure and up to 6-days postexposure. Concentrations of TRI, TETRA, free trichloroethanol (TCOH), total TCOH (free TCOH plus glucuronidated TCOH), and trichloroacetic acid (TCA) were determined in blood and urine; TRI and TETRA concentrations were measured in alveolar breath. Toxicokinetic time courses and empirical analyses of classical toxicokinetic parameters were compared with those reported in previous human volunteer studies, most of which involved exposures that were at least 10-fold higher. Qualitatively, TRI and TETRA toxicokinetics were consistent with previous human studies. Quantitatively, alveolar retention and clearance by exhalation were similar to those found previously but blood and urine data suggest a number of possible toxicokinetic differences. For TRI, data from the current study support lower apparent blood-air partition coefficients, greater apparent metabolic clearance, less TCA production, and greater glucuronidation of TCOH as compared to previous studies. For TETRA, the current data suggest TCA formation that is similar or slightly lower than that of previous studies. Variability and uncertainty in empirical estimates of total TETRA metabolism are substantial, with confidence intervals among different studies substantially overlapping. Relative contributions to observed differences from concentration-dependent toxicokinetics and interindividual and interoccasion variability remain to be determined.