Sublingual Dexmedetomidine for Agitation Associated with Schizophrenia or Bipolar Disorder: A Post Hoc Analysis of Number Needed to Treat, Number Needed to Harm, and Likelihood to be Helped or Harmed.

INTRODUCTION: The objective was to use the evidence-based medicine metrics of number needed to treat, number needed to harm, and likelihood to be helped or harmed to appraise the clinical efficacy and tolerability of sublingual dexmedetomidine in adults with agitation associated with schizophrenia or bipolar disorder. METHODS: Sublingual dexmedetomidine data for this post hoc analysis were obtained from two similarly designed, double-blind, randomized, placebo-controlled studies of adults with schizophrenia or bipolar disorder. Response to treatment was defined as a ≥ 40% reduction from baseline in the Positive and Negative Syndrome Scale-Excited Component (PEC). Tolerability was assessed by evaluating rates of adverse events. RESULTS: The number needed to treat (95% confidence interval) estimate versus placebo for PEC response at 2 h post-dose was 3 (2, 3) for the sublingual dexmedetomidine 180-µg group (n = 125) and 3 (3, 4) for the 120-µg group (n = 129) in the study of patients with schizophrenia and 3 (2, 3) for the sublingual dexmedetomidine 180-µg group (n = 126) and 4 (3, 6) for the 120-µg group (n = 126) in the study of patients with bipolar disorder. Number needed to harm values versus placebo were greater than 10 for all adverse events except somnolence, where the number needed to harm (95% confidence interval) was 7 (5, 10) for all doses pooled from both studies. In all instances, likelihood to be helped or harmed values were greater than 1 for efficacy versus applicable tolerability outcomes. CONCLUSIONS: The number needed to treat, number needed to harm, and likelihood to be helped or harmed of sublingual dexmedetomidine support a favorable benefit-risk profile in adults with acute agitation associated with schizophrenia or bipolar disorder. TRIAL REGISTRATION: ClinicalTrials.gov, https://clinicaltrials.gov/ct2/show/NCT04268303 , NCT04268303. CLINICALTRIALS: gov, https://clinicaltrials.gov/ct2/show/NCT04276883 , NCT04276883.

Risk assessment of latent tuberculosis infection through a multiplexed cytokine biosensor assay and machine learning feature selection.

Accurate detection and risk stratification of latent tuberculosis infection (LTBI) remains a major clinical and public health problem. We hypothesize that multiparameter strategies that probe immune responses to Mycobacterium tuberculosis can provide new diagnostic insights into not only the status of LTBI infection, but also the risk of reactivation. After the initial proof-of-concept study, we developed a 13-plex immunoassay panel to profile cytokine release from peripheral blood mononuclear cells stimulated separately with Mtb-relevant and non-specific antigens to identify putative biomarker signatures. We sequentially enrolled 65 subjects with various risk of TB exposure, including 32 subjects with diagnosis of LTBI. Random Forest feature selection and statistical data reduction methods were applied to determine cytokine levels across different normalized stimulation conditions. Receiver Operator Characteristic (ROC) analysis for full and reduced feature sets revealed differences in biomarkers signatures for LTBI status and reactivation risk designations. The reduced set for increased risk included IP-10, IL-2, IFN-γ, TNF-α, IL-15, IL-17, CCL3, and CCL8 under varying normalized stimulation conditions. ROC curves determined predictive accuracies of > 80% for both LTBI diagnosis and increased risk designations. Our study findings suggest that a multiparameter diagnostic approach to detect normalized cytokine biomarker signatures might improve risk stratification in LTBI.

Identification of lipid biomarkers of metastatic potential and gene expression (HER2/p53) in human breast cancer cell cultures using ambient mass spectrometry.

In breast cancer, overexpression of human epidermal growth factor receptor 2 (HER2) correlates with overactivation of lipogenesis, mutation of tumor suppressor p53, and increased metastatic potential. The mechanisms through which lipids mediate p53, HER2, and metastatic potential are largely unknown. We have developed a desorption electrospray ionization mass spectrometry (DESI-MS) method to identify lipid biomarkers of HER2/p53 expression, metastatic potential, and disease state (viz. cancer vs. non-cancerous) in monolayer and suspension breast cancer cell cultures (metastatic potential: MCF-7, T-47D, MDA-MB-231; HER2/p53: HCC2218 (HER2+++/p53+), HCC1599 (HER2-/p53-), HCC202 (HER2++/p53-), HCC1419 (HER2+++/p53-) HCC70 (HER2-/p53+++); non-cancerous: MCF-10A). Unsupervised principal component analysis (PCA) of DESI-MS spectra enabled identification of twelve lipid biomarkers of metastatic potential and disease state, as well as ten lipids that distinguish cell lines based on HER2/p53 expression levels (> 200 lipids were identified per cell line). In addition, we developed a DESI-MS imaging (DESI-MSI) method for mapping the spatial distribution of lipids in metastatic spheroids (MDA-MB-231). Of the twelve lipids that correlate with changes in the metastatic potential of monolayer cell cultures, three were localized to the necrotic core of spheroids, indicating a potential role in promoting cancer cell survival in nutrient-deficient environments. One lipid species, which was not detected in monolayer MDA-MB-231 cultures, was spatially localized to the periphery of the spheroid, suggesting a potential role in invasion and/or proliferation. These results demonstrate that combining DESI-MS/PCA of monolayer and suspension cell cultures with DESI-MSI of spheroids is a promising approach for identifying lipid biomarkers of specific genotypes and phenotypes, as well as elucidating the potential function of these biomarkers in breast cancer. Graphical Absract.

Precision immunoprofiling to reveal diagnostic signatures for latent tuberculosis infection and reactivation risk stratification.

Latent tuberculosis infection (LTBI) is estimated in nearly one quarter of the world's population, and of those immunocompetent and infected ~10% will proceed to active tuberculosis (TB). Current diagnostics cannot definitively identify LTBI and provide no insight into reactivation risk, thereby defining an unmet diagnostic challenge of incredible global significance. We introduce a new machine-learning-driven approach to LTBI diagnostics that leverages a high throughput, multiplexed cytokine detection technology and powerful bioinformatics to reveal multi-marker signatures for LTBI diagnosis and risk stratification. This approach is enabled through an individualized normalization procedure that allows disease-relevant biomarker signatures to be revealed despite heterogeneity in basal immune response. Specifically, cytokines secreted from antigen-challenged peripheral blood mononuclear cells were detected using silicon photonic sensor arrays and multidimensional data correlation of individually-normalized immune responses revealed signatures important for LTBI status. These results demonstrate a powerful combination of multiplexed biomarker detection technologies, precision immune normalization, and feature selection algorithms that revealed positively correlated multi-biomarker signatures for LTBI status and reactivation risk stratification from a relatively simple blood-based assay.

Recent advances in environmental and clinical analysis using microring resonator-based sensors.

Progress in the development of biosensors has dramatically improved analytical techniques. Biosensors have advantages over more conventional analytical techniques arising from attributes such as straightforward analyses, higher throughput, miniaturization, smaller sample input, and lower cost. Microring optical resonators have emerged in the area of optical sensors as an exceptional choice due to their sensitivity, ease of fabrication, multiplexity capability and label-free detection. In this paper, the sensing principle of these sensors is described. In addition, we summarize and highlight their most recent and relevant applications in environmental and clinical detection analysis.

A Guide to Quantitative Biomarker Assay Development using Whispering Gallery Mode Biosensors.

Whispering gallery mode (WGM) sensors are a class of powerful analytical techniques defined by the measurement of changes in the local refractive index at or near the sensor surface. When functionalized with target-specific capture agents, analyte binding can be measured with very low limits of detection. There are many geometric manifestations of WGM sensors, with chip-integrated silicon photonic devices first commercialized because of the robust, wafer-scale device fabrication, facile optical interrogation, and amenability to the creation of multiplexed sensor arrays. Using these arrays, a number of biomolecular targets have been detected in both label-free and label-enhanced assay formats. For example, sub-picomolar detection limits for multiple cytokines were achieved using an enzymatically enhanced sandwich immunoassay that showed high analyte specificity suitable for detection in complex, clinical matrices. This protocol describes a generalizable approach for the development of quantitative, multiplexed immunoassays using silicon photonic microrings as an example WGM platform. © 2017 by John Wiley & Sons, Inc.

Rapid and sharp decline in HCV upon monotherapy with NS3 protease inhibitor, ACH-1625.

BACKGROUND: ACH-1625 is a linear peptidomimetic inhibitor that non-covalently binds to HCV NS3 protease with high potency and specificity. Short-term monotherapy of HCV genotype-1 infection with ACH-1625 was found to be safe and resulted in ≥3.3 log(10) IU/ml mean viral load reduction. These viral load decay data were analysed to compare HCV dynamics with prior reports and estimate the antiviral efficiency of ACH-1625. METHODS: Drug efficiency was estimated by analysing the viral decay following initiation of up to 5 days of monotherapy with ACH-1625 in 36 chronically infected HCV genotype-1 patients. During this monotherapy study, ACH-1625 was administered either twice-a-day for 4.5 days or once daily for 5 days at 5 different dose levels in 36 patients. RESULTS: A sharp viral decay during the first 48 h following the initiation of ACH-1625 treatment afforded high drug efficiency estimates (≥0.9934). In addition, an increase in the estimated drug efficiency was observed with increasing ACH-1625 dose. The observed anti-HCV response was fairly uniform in this proof-of-concept study across the population of 36 patients. CONCLUSIONS: Estimates of the treatment-independent viral kinetics parameters were consistent with prior reports and the estimated drug efficiency of ACH-1625 monotherapy was very high (≥0.9934) in fasted and fed states.

Multiple-dose pharmacokinetic behavior of elvucitabine, a nucleoside reverse transcriptase inhibitor, administered over 21 days with lopinavir-ritonavir in human immunodeficiency virus type 1-infected subjects.

The purpose of this study was to describe the plasma pharmacokinetics (PK) of elvucitabine at different doses when administered daily or every other day for 21 days with lopinavir-ritonavir (Kaletra) in human immunodeficiency virus (HIV)-infected subjects. Three different dosing regimens of elvucitabine were administered with lopinavir-ritonavir to 24 subjects with moderate levels of HIV. Plasma samples were collected over 35 days. Elvucitabine concentrations were analyzed using a validated liquid chromatography-tandem mass spectrometry assay. The PK of elvucitabine was determined using both noncompartmental and compartmental analyses. Models were developed and tested using ADAPT II, while a population analysis was performed using IT2S. The PK behavior of elvucitabine was best described by a two-compartment linear model using two absorption rates and an increase in the bioavailability after day 1. The augmentation in the bioavailability after day 1 was variable, with some subjects demonstrating a major increase while others had little or no increase. Elvucitabine has a long half-life of approximately 100 h. The increase in elvucitabine bioavailability may be due to ritonavir inhibiting an efflux gut transporter with activity present in various levels between subjects. The proposed PK model may be utilized and improved further by linking the PK behavior of elvucitabine to various markers of efficacy.

Effect of a single dose of ritonavir on the pharmacokinetic behavior of elvucitabine, a nucleoside reverse transcriptase inhibitor, administered in healthy volunteers.

The purpose of this study was to determine the effect of a single dose of 300 mg of ritonavir on the plasma pharmacokinetics (PK) of a single dose of 20 mg of elvucitabine when the two drugs were coadministered in healthy subjects. In a three-way crossover design, 30 subjects received 20 mg of elvucitabine, 300 mg of ritonavir, or 20 mg of elvucitabine coadministered with 300 mg of ritonavir. Elvucitabine concentrations were analyzed using a validated liquid chromatography-tandem mass spectrometry assay. The PK of elvucitabine was determined using both noncompartmental and compartmental analyses. Models were developed and tested using ADAPT-II, while a population analysis was performed using IT2S. Comparisons of PK parameters between groups were done with SAS. The pharmacokinetic behavior of elvucitabine was best described by a two-compartment linear model using two absorption rates and a first-order elimination rate. Ritonavir significantly impacted the PK of elvucitabine by reducing elvucitabine's bioavailability, with the most plausible explanation being an inhibition on influx transporters by ritonavir. The decrease in elvucitabine bioavailability when elvucitabine was coadministered with ritonavir may be due to ritonavir's inhibiting influx gut transporters. Continued development of elvucitabine is warranted to better characterize its PK and to determine its in vivo efficacy against human immunodeficiency virus.