Differentiation is accompanied by a progressive loss in transcriptional memory.

BACKGROUND: Cell differentiation requires the integration of two opposite processes, a stabilizing cellular memory, especially at the transcriptional scale, and a burst of gene expression variability which follows the differentiation induction. Therefore, the actual capacity of a cell to undergo phenotypic change during a differentiation process relies upon a modification in this balance which favors change-inducing gene expression variability. However, there are no experimental data providing insight on how fast the transcriptomes of identical cells would diverge on the scale of the very first two cell divisions during the differentiation process. RESULTS: In order to quantitatively address this question, we developed different experimental methods to recover the transcriptomes of related cells, after one and two divisions, while preserving the information about their lineage at the scale of a single cell division. We analyzed the transcriptomes of related cells from two differentiation biological systems (human CD34+ cells and T2EC chicken primary erythrocytic progenitors) using two different single-cell transcriptomics technologies (scRT-qPCR and scRNA-seq). CONCLUSIONS: We identified that the gene transcription profiles of differentiating sister cells are more similar to each other than to those of non-related cells of the same type, sharing the same environment and undergoing similar biological processes. More importantly, we observed greater discrepancies between differentiating sister cells than between self-renewing sister cells. Furthermore, a progressive increase in this divergence from first generation to second generation was observed when comparing differentiating cousin cells to self renewing cousin cells. Our results are in favor of a gradual erasure of transcriptional memory during the differentiation process.

Clustering of strong replicators associated with active promoters is sufficient to establish an early-replicating domain.

Vertebrate genomes replicate according to a precise temporal program strongly correlated with their organization into A/B compartments. Until now, the molecular mechanisms underlying the establishment of early-replicating domains remain largely unknown. We defined two minimal cis-element modules containing a strong replication origin and chromatin modifier binding sites capable of shifting a targeted mid-late-replicating region for earlier replication. The two origins overlap with a constitutive or a silent tissue-specific promoter. When inserted side-by-side, these modules advance replication timing over a 250 kb region through the cooperation with one endogenous origin located 30 kb away. Moreover, when inserted at two chromosomal sites separated by 30 kb, these two modules come into close physical proximity and form an early-replicating domain establishing more contacts with active A compartments. The synergy depends on the presence of the active promoter/origin. Our results show that clustering of strong origins located at active promoters can establish early-replicating domains.

LC-MS/MS Bioanalysis of Radioligand Therapeutic Drug Candidate for Preclinical Toxicokinetic Assessment.

Radioligand therapy (RLT) has gained significant momentum in recent years in the diagnosis, treatment, and monitoring of cancers. In preclinical development, the safety profile of RLT drug candidate(s) is investigated at relatively low dose levels using the cold (non-radioactive, e.g., 175Lu) ligand as a surrogate of the hot (radioactive, e.g., 177Lu) one in the "ligand-linker-chelator" complex. The formulation of the test article used in preclinical safety studies contains a mixture of free ligand (i.e., ligand-linker-chelator without metal) and cold ligand (i.e., ligand-linker-chelator with non-radioactive metal) in a similar molar ratio as seen under the manufacturing conditions for the RLT drug for clinical use, where only a fraction of free ligand molecules chelate the radioactive metal to form a hot ligand. In this very first report of LC-MS/MS bioanalysis of RLT molecules in support of a regulated preclinical safety assessment study, a highly selective and sensitive LC-MS/MS bioanalytical method was developed for the simultaneous determination of free ligand (NVS001) and cold ligand (175Lu-NVS001) in rat and dog plasma. Several unexpected technical challenges in relation to LC-MS/MS of RLT molecules were successfully addressed. The challenges include poor assay sensitivity of the free ligand NVS001, formation of the free ligand (NVS001) with endogenous metal (e.g., potassium), Ga loss from the Ga-chelated internal standard during sample extraction and analysis, "instability" of the analytes at low concentrations, and inconsistent IS response in the extracted plasma samples. The methods were validated according to the current regulatory requirements in a dynamic range of 0.5-250 ng/mL for both the free and cold ligands using a 25 µL sample volume. The validated method was successfully implemented in sample analysis in support of regulated safety studies, with very good results from incurred sample reanalysis. The current LC-MS/MS workflow can be expanded to quantitative analysis of other RLTs in support of preclinical RLT drug development.

scAN1.0: A reproducible and standardized pipeline for processing 10X single cell RNAseq data.

Single cell transcriptomics has recently seen a surge in popularity, leading to the need for data analysis pipelines that are reproducible, modular, and interoperable across different systems and institutions.To meet this demand, we introduce scAN1.0, a processing pipeline for analyzing 10X single cell RNA sequencing data. scAN1.0 is built using the Nextflow DSL2 and can be run on most computational systems. The modular design of Nextflow pipelines enables easy integration and evaluation of different blocks for specific analysis steps.We demonstrate the usefulness of scAN1.0 by showing its ability to examine the impact of the mapping step during the analysis of two datasets: (i) a 10X scRNAseq of a human pituitary gonadotroph tumor dataset and (ii) a murine 10X scRNAseq acquired on CD8 T cells during an immune response.

Toxicokinetics in preclinical drug development of small-molecule new chemical entities.

Toxicokinetics (TK) is an integral part of nonclinical (preclinical) safety assessment of small-molecule new chemical entities in drug development. It is employed to describe the systemic exposure of a drug candidate and/or its important metabolite(s) achieved in study animals and elucidate the relationship (proportional, over-proportional, or under-proportional) between systemic exposure and dose administered and the associated differences/similarities between male and female animals along with the possible accumulation/induction. TK data and the derived parameters are employed to propose safe starting doses for clinical use of the new drug candidate through proper extrapolation of findings in study animals to humans. This review has attempted to highlight the health authority expectations on TK assessment in supporting preclinical safety profiling of new chemical entities. A robust TK assessment requires good understanding of absorption, distribution, metabolism, and elimination processes of drug candidate, adequate TK sampling (e.g., controls where relevant), implementation of fit-for-purpose bioanalytical methods (validated or scientifically qualified) along with necessary measures to prevent mis-dosing or ex vivo contamination, and establishment of stability of the drug candidate and/or its metabolite(s) in the intended species matrix to ensure the reliability of bioanalytical and TK data. The latter provides a vital link between animal experiments and human safety.

Evidence for close molecular proximity between reverting and undifferentiated cells.

BACKGROUND: According to Waddington's epigenetic landscape concept, the differentiation process can be illustrated by a cell akin to a ball rolling down from the top of a hill (proliferation state) and crossing furrows before stopping in basins or "attractor states" to reach its stable differentiated state. However, it is now clear that some committed cells can retain a certain degree of plasticity and reacquire phenotypical characteristics of a more pluripotent cell state. In line with this dynamic model, we have previously shown that differentiating cells (chicken erythrocytic progenitors (T2EC)) retain for 24 h the ability to self-renew when transferred back in self-renewal conditions. Despite those intriguing and promising results, the underlying molecular state of those "reverting" cells remains unexplored. The aim of the present study was therefore to molecularly characterize the T2EC reversion process by combining advanced statistical tools to make the most of single-cell transcriptomic data. For this purpose, T2EC, initially maintained in a self-renewal medium (0H), were induced to differentiate for 24H (24H differentiating cells); then, a part of these cells was transferred back to the self-renewal medium (48H reverting cells) and the other part was maintained in the differentiation medium for another 24H (48H differentiating cells). For each time point, cell transcriptomes were generated using scRT-qPCR and scRNAseq. RESULTS: Our results showed a strong overlap between 0H and 48H reverting cells when applying dimensional reduction. Moreover, the statistical comparison of cell distributions and differential expression analysis indicated no significant differences between these two cell groups. Interestingly, gene pattern distributions highlighted that, while 48H reverting cells have gene expression pattern more similar to 0H cells, they are not completely identical, which suggest that for some genes a longer delay may be required for the cells to fully recover. Finally, sparse PLS (sparse partial least square) analysis showed that only the expression of 3 genes discriminates 48H reverting and 0H cells. CONCLUSIONS: Altogether, we show that reverting cells return to an earlier molecular state almost identical to undifferentiated cells and demonstrate a previously undocumented physiological and molecular plasticity during the differentiation process, which most likely results from the dynamic behavior of the underlying molecular network.

A derived ZW chromosome system in Amborella trichopoda, representing the sister lineage to all other extant flowering plants.

The genetic basis and evolution of sex determination in dioecious plants is emerging as an active area of research with exciting advances in genome sequencing and analysis technologies. As the sole species within the sister lineage to all other extant flowering plants, Amborella trichopoda is an important model for understanding the evolution and development of flowers. Plants typically produce only male or female flowers, but sex determination mechanisms are unknown for the species. Sequence data derived from plants of natural origin and an F1 mapping population were used to identify sex-linked genes and the nonrecombining region. Amborella trichopoda has a ZW sex determination system. Analysis of genes in a 4 Mb nonrecombining sex-determination region reveals recent divergence of Z and W gametologs, and few Z- and W-specific genes. The sex chromosomes of A. trichopoda evolved less than 16.5 Myr ago, long after the divergence of the extant angiosperms.

Evolution of replication origins in vertebrate genomes: rapid turnover despite selective constraints.

The replication program of vertebrate genomes is driven by the chromosomal distribution and timing of activation of tens of thousands of replication origins. Genome-wide studies have shown the association of origins with promoters and CpG islands, and their enrichment in G-quadruplex motifs (G4). However, the genetic determinants driving their activity remain poorly understood. To gain insight on the constraints operating on origins, we conducted the first evolutionary comparison of origins across vertebrates. We generated a genome-wide map of chicken origins (the first of a bird genome), and performed a comparison with human and mouse maps. The analysis of intra-species polymorphism revealed a strong depletion of genetic diversity at the core of replication initiation loci. This depletion is not linked to the presence of G4 motifs, promoters or CpG islands. In contrast, we show that origins experienced a rapid turnover during vertebrate evolution, since pairwise comparisons of origin maps revealed that <24% of them are conserved among vertebrates. This study unravels the existence of a novel determinant of origins, the precise functional role of which remains to be determined. Despite the importance of replication initiation for the fitness of organisms, the distribution of origins along vertebrate chromosomes is highly flexible.

Probabilistic count matrix factorization for single cell expression data analysis.

MOTIVATION: The development of high-throughput single-cell sequencing technologies now allows the investigation of the population diversity of cellular transcriptomes. The expression dynamics (gene-to-gene variability) can be quantified more accurately, thanks to the measurement of lowly expressed genes. In addition, the cell-to-cell variability is high, with a low proportion of cells expressing the same genes at the same time/level. Those emerging patterns appear to be very challenging from the statistical point of view, especially to represent a summarized view of single-cell expression data. Principal component analysis (PCA) is a most powerful tool for high dimensional data representation, by searching for latent directions catching the most variability in the data. Unfortunately, classical PCA is based on Euclidean distance and projections that poorly work in presence of over-dispersed count data with dropout events like single-cell expression data. RESULTS: We propose a probabilistic Count Matrix Factorization (pCMF) approach for single-cell expression data analysis that relies on a sparse Gamma-Poisson factor model. This hierarchical model is inferred using a variational EM algorithm. It is able to jointly build a low dimensional representation of cells and genes. We show how this probabilistic framework induces a geometry that is suitable for single-cell data visualization, and produces a compression of the data that is very powerful for clustering purposes. Our method is competed against other standard representation methods like t-SNE, and we illustrate its performance for the representation of single-cell expression data. AVAILABILITY AND IMPLEMENTATION: Our work is implemented in the pCMF R-package (https://github.com/gdurif/pCMF). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Development and validation of an LC-MS/MS method for the quantitative analysis of the adenosine A2a receptor antagonist NIR178 and its monohydroxy metabolite in human plasma: Application to clinical pharmacokinetics.

We report a selective LC-MS/MS method for the simultaneous quantitative determinations of the adenosine A2a receptor antagonist NIR178 (NIR178) and its major metabolite NJI765 in human plasma. Sample preparation steps involved protein precipitation, sample evaporation and reconstitution using a plasma sample volume of 0.1 ml plasma. Separation was achieved in 10 min on an Acquity UPLC BEH C18 1.7 µm, 2.1 × 50 mm column heated at 60°C with a gradient elution at 0.6 ml/min mobile phase made of water and acetonitrile both acidified with 0.1% formic acid. The detection was performed in positive ion mode and quantification based on multiple reaction monitoring. The linear response range was 1.00-1,000 ng/ml using a 1/x2 weighting factor. The intra- and inter-day accuracies (bias %) and intra- and inter-day precisions (CV, %) obtained for NIR178 and NJI765 were within the acceptance criteria. The normalized NIR178 and NJI765 matrix factor calculated from six lots of normal, lipemic and hemolyzed plasmas ranged from 0.97 to 1.05. The normalized recoveries of both NIR178 and NJI765 compared with their internal standards were consistent and reproducible with a CV ≤8.0. This method was successfully applied to support pharmacokinetic studies in adult patients with cancer.

High dimensional classification with combined adaptive sparse PLS and logistic regression.

Motivation: The high dimensionality of genomic data calls for the development of specific classification methodologies, especially to prevent over-optimistic predictions. This challenge can be tackled by compression and variable selection, which combined constitute a powerful framework for classification, as well as data visualization and interpretation. However, current proposed combinations lead to unstable and non convergent methods due to inappropriate computational frameworks. We hereby propose a computationally stable and convergent approach for classification in high dimensional based on sparse Partial Least Squares (sparse PLS). Results: We start by proposing a new solution for the sparse PLS problem that is based on proximal operators for the case of univariate responses. Then we develop an adaptive version of the sparse PLS for classification, called logit-SPLS, which combines iterative optimization of logistic regression and sparse PLS to ensure computational convergence and stability. Our results are confirmed on synthetic and experimental data. In particular, we show how crucial convergence and stability can be when cross-validation is involved for calibration purposes. Using gene expression data, we explore the prediction of breast cancer relapse. We also propose a multicategorial version of our method, used to predict cell-types based on single-cell expression data. Availability and implementation: Our approach is implemented in the plsgenomics R-package. Contact: ghislain.durif@inria.fr. Supplementary information: Supplementary data are available at Bioinformatics online.

SNP calling from RNA-seq data without a reference genome: identification, quantification, differential analysis and impact on the protein sequence.

SNPs (Single Nucleotide Polymorphisms) are genetic markers whose precise identification is a prerequisite for association studies. Methods to identify them are currently well developed for model species, but rely on the availability of a (good) reference genome, and therefore cannot be applied to non-model species. They are also mostly tailored for whole genome (re-)sequencing experiments, whereas in many cases, transcriptome sequencing can be used as a cheaper alternative which already enables to identify SNPs located in transcribed regions. In this paper, we propose a method that identifies, quantifies and annotates SNPs without any reference genome, using RNA-seq data only. Individuals can be pooled prior to sequencing, if not enough material is available from one individual. Using pooled human RNA-seq data, we clarify the precision and recall of our method and discuss them with respect to other methods which use a reference genome or an assembled transcriptome. We then validate experimentally the predictions of our method using RNA-seq data from two non-model species. The method can be used for any species to annotate SNPs and predict their impact on the protein sequence. We further enable to test for the association of the identified SNPs with a phenotype of interest.

The spatiotemporal program of DNA replication is associated with specific combinations of chromatin marks in human cells.

The duplication of mammalian genomes is under the control of a spatiotemporal program that orchestrates the positioning and the timing of firing of replication origins. The molecular mechanisms coordinating the activation of about [Formula: see text] predicted origins remain poorly understood, partly due to the intrinsic rarity of replication bubbles, making it difficult to purify short nascent strands (SNS). The precise identification of origins based on the high-throughput sequencing of SNS constitutes a new methodological challenge. We propose a new statistical method with a controlled resolution, adapted to the detection of replication origins from SNS data. We detected an average of 80,000 replication origins in different cell lines. To evaluate the consistency between different protocols, we compared SNS detections with bubble trapping detections. This comparison demonstrated a good agreement between genome-wide methods, with 65% of SNS-detected origins validated by bubble trapping, and 44% of bubble trapping origins validated by SNS origins, when compared at the same resolution. We investigated the interplay between the spatial and the temporal programs of replication at fine scales. We show that most of the origins detected in regions replicated in early S phase are shared by all the cell lines investigated whereas cell-type-specific origins tend to be replicated in late S phase. We shed a new light on the key role of CpG islands, by showing that 80% of the origins associated with CGIs are constitutive. Our results further show that at least 76% of CGIs are origins of replication. The analysis of associations with chromatin marks at different timing of cell division revealed new potential epigenetic regulators driving the spatiotemporal activity of replication origins. We highlight the potential role of H4K20me1 and H3K27me3, the coupling of which is correlated with increased efficiency of replication origins, clearly identifying those marks as potential key regulators of replication origins.

Modeling overdispersion heterogeneity in differential expression analysis using mixtures.

Next-generation sequencing technologies now constitute a method of choice to measure gene expression. Data to analyze are read counts, commonly modeled using negative binomial distributions. A relevant issue associated with this probabilistic framework is the reliable estimation of the overdispersion parameter, reinforced by the limited number of replicates generally observable for each gene. Many strategies have been proposed to estimate this parameter, but when differential analysis is the purpose, they often result in procedures based on plug-in estimates, and we show here that this discrepancy between the estimation framework and the testing framework can lead to uncontrolled type-I errors. Instead, we propose a mixture model that allows each gene to share information with other genes that exhibit similar variability. Three consistent statistical tests are developed for differential expression analysis. We show through a wide simulation study that the proposed method improves the sensitivity of detecting differentially expressed genes with respect to the common procedures, since it reaches the nominal value for the type-I error, while keeping elevate discriminative power between differentially and not differentially expressed genes. The method is finally illustrated on prostate cancer RNA-Seq data.

Effect of esomeprazole, a proton pump inhibitor on the pharmacokinetics of sonidegib in healthy volunteers.

AIMS: This study aimed to evaluate the impact of esomeprazole on the pharmacokinetics of sonidegib. METHODS: This Phase I study evaluated the impact of the proton pump inhibitor (PPI) esomeprazole on the oral absorption and pharmacokinetics (PKs) of a single dose of sonidegib under fasted conditions. A total of 42 healthy subjects were enrolled to receive either sonidegib alone (200 mg single dose) or sonidegib in combination with esomeprazole (40 mg pre-treatment 5 days and combination were given on day 6). Primary PK parameters assessed in the study were area under the concentration-time curve (AUC) from 0-14 days and 0-7 days and maximum observed plasma concentration (Cmax ). RESULTS: The plasma exposure (AUC0-14d, AUC0-7d and Cmax ) of a single 200 mg oral dose of sonidegib was decreased by 32-38% when sonidegib was co-administered with esomeprazole compared with sonidegib alone, with no apparent change in elimination slope and tmax . Baseline gastric pH was similar between the two arms. CONCLUSIONS: These results suggest a modest reduction in the extent of sonidegib absorption by esomeprazole. There was no obvious metabolic drug-drug interaction between the two agents. Both sonidegib and esomeprazole were well tolerated in the study population.

Analysis of small molecule antibody-drug conjugate catabolites in rat liver and tumor tissue by liquid extraction surface analysis micro-capillary liquid chromatography/tandem mass spectrometry.

RATIONALE: Antibody-drug conjugates (ADCs) are some of the most promising antibody-related therapeutics. The fate of the cytotoxic moiety of ADCs in vivo after proteolytic degradation of the antibody needs to be well understood in order to mitigate toxicity risks and design proper first in patient studies. METHODS: The feasibility of liquid extraction surface analysis micro-capillary liquid chromatography/tandem mass spectrometry (LESA-µLC/MS/MS) was tested for direct surface sampling of two possible ADC catabolites composed of synthetically modified maytansinoid (DM1) and 4-[N-maleimidomethyl]cyclohexane-1-carbonyl (MCC) from rat liver and tumor tissue. Moreover, the iMatrixSpray was incorporated to prepare calibration standards (Cs) and quality control (QC) samples by spraying analyte solution at different concentrations directly on blank tissue. RESULTS: Lys-MCC-DM1 sprayed on blank liver tissue was homogeneously distributed (12.3% variability). The assay was selective (inference ≤20%) and linear from 50.0 to 1000 ng/mL without any carry-over. Inter-run accuracy and precision were ≤2.3% and ≤25.9% meeting acceptance. Lys-MCC-DM1 was the only catabolite detected in liver and tumor tissue and was most likely responsible for the total radioactivity signal in liver tissue 72 h post-dose measured by quantitative whole body autoradiography (QWBA). CONCLUSIONS: Both analytical assays (LESA-µLC/MS/MS and QWBA) are complementary to each other and provide useful quantitative and qualitative information in spatial tissue distribution of ADCs and their related catabolites. Copyright © 2016 John Wiley & Sons, Ltd.

The use of generic surrogate peptides for the quantitative analysis of human immunoglobulin G1 in pre-clinical species with high-resolution mass spectrometry.

In the present study, the application of a liquid chromatography high-resolution mass spectrometry (LC-HRMS) analytical assay for the quantitative analysis of a recombinant human immunoglobulin G1 (hIgG1) in rat serum is reported using three generic peptides GPSVFPLAPSSK (GPS), TTPPVLDSDGSFFLYSK (TTP), and VVSVLTVLHQDWLNGK (VVS). Moreover, the deamidation site of a fourth peptide FNWYVDGVEVHNAK (FNW) was identified and further excluded from the assay evaluation due to the inaccuracy of the quantitative results. The rat serum samples were spiked with a fully labeled hIgG1 as internal standard (ISTD). The digestion with trypsin was performed onto the pellet prior to peptide analysis by LC-HRMS using a quadrupole time of flight (QTOF) mass analyzer operating in selected reaction monitoring (SRM) mode with enhanced duty cycles (EDC). The assay linearity for the three investigated peptides was established for a hIgG1 (hIgG1A) from 1.00 to 1000 µg mL(-1) with a mean coefficient of determination (R (2)) higher than 0.9868. The inter-day accuracy and precision obtained in rat serum over 3 days were ≤11.4 and ≤10.5%, respectively. Short-term stability on the auto-sampler at 6 °C for 30 h, at RT for 48 h, and a 100-fold dilution factor were demonstrated. In addition, QC samples prepared in cynomolgus monkey serum and measured with the present method met the acceptance criteria of ±20.0 and ≤20.0% for all three peptides regarding accuracy and precision, respectively. The LC-HRMS method was applied to the analysis of samples from five individual cynomolgus monkeys dosed with a second hIgG1 (hIgG1B) and consistent data were obtained compared to the LC-MS/MS method (conventional triple quadrupole (QqQ) mass analyzer operating in SRM). The present data demonstrate that LC-HRMS can be used for the quantitative analysis of hIgG1 in both species and that quantification is not only limited to classical QqQ instruments.

New microfluidic-based sampling procedure for overcoming the hematocrit problem associated with dried blood spot analysis.

Hematocrit (Hct) is one of the most critical issues associated with the bioanalytical methods used for dried blood spot (DBS) sample analysis. Because Hct determines the viscosity of blood, it may affect the spreading of blood onto the filter paper. Hence, accurate quantitative data can only be obtained if the size of the paper filter extracted contains a fixed blood volume. We describe for the first time a microfluidic-based sampling procedure to enable accurate blood volume collection on commercially available DBS cards. The system allows the collection of a controlled volume of blood (e.g., 5 or 10 µL) within several seconds. Reproducibility of the sampling volume was examined in vivo on capillary blood by quantifying caffeine and paraxanthine on 5 different extracted DBS spots at two different time points and in vitro with a test compound, Mavoglurant, on 10 different spots at two Hct levels. Entire spots were extracted. In addition, the accuracy and precision (n = 3) data for the Mavoglurant quantitation in blood with Hct levels between 26% and 62% were evaluated. The interspot precision data were below 9.0%, which was equivalent to that of a manually spotted volume with a pipet. No Hct effect was observed in the quantitative results obtained for Hct levels from 26% to 62%. These data indicate that our microfluidic-based sampling procedure is accurate and precise and that the analysis of Mavoglurant is not affected by the Hct values. This provides a simple procedure for DBS sampling with a fixed volume of capillary blood, which could eliminate the recurrent Hct issue linked to DBS sample analysis.

Pharmacokinetics of fingolimod and metabolites in subjects with severe renal impairment: An open-label, single-dose, parallel-group study.

OBJECTIVE: This study assessed the pharmacokinetics and tolerability of fingolimod and its metabolites in severe renal impairment and healthy subjects. METHODS: In this single-dose, open-label study, 9 severe renal impairment subjects and 9 demographically matched healthy subjects were included. Each subject received a single oral dose of fingolimod 1.25 mg, and their blood and urine samples were assessed. The pharmacokinetics of fingolimod and its metabolites, fingolimod-phosphate (active metabolite, fingolimod-P), M2, and M3, were compared in both groups. Safety and tolerability were also assessed. RESULTS: In severe renal impairment subjects, mean±standard deviation values of Cmax (ng/mL) of fingolimod and fingolimod-P were 0.878±0.256 and 1.13±0.293 vs. 0.653±0.138 and 0.904±0.229 in healthy subjects, respectively. The overall drug exposures (AUCinf (ngxh/mL)) for fingolimod and fingolimod-P were 131±90.7 and 75.5±33.6 in severe renal impairment subjects vs. 82.3±36.9 and 65.9±30.6 in healthy subjects, respectively. t1/2 (hours) for fingolimod and fingolimod-P was comparable in severe renal impairment subjects (94±53 and 95±50) and healthy subjects (85±25 and 101±46). All adverse events were as expected for fingolimod 1.25 mg. CONCLUSIONS: The exposure to fingolimod and fingolimod-P was moderately increased (90% CI, 0.94-2.18) in severe renal impairment subjects, while half-lives and protein binding were similar to those in healthy subjects. Given that these changes are not clinically meaningful, fingolimod dose adjustment is considered unnecessary in patients with mild, moderate, or severe renal impairment.

Application of a deuterium replacement strategy to modulate the pharmacokinetics of 7-(3,5-dimethyl-1H-1,2,4-triazol-1-yl)-3-(4-methoxy-2-methylphenyl)-2,6-dimethylpyrazolo[5,1-b]oxazole, a novel CRF1 antagonist.

Deuterium isotope effects were evaluated as a strategy to optimize the pharmacokinetics of 7-(3,5-dimethyl-1H-1,2,4-triazol-1-yl)-3-(4-methoxy-2-methylphenyl)-2,6-dimethylpyrazolo[5,1-b]oxazole (NVS-CRF38), a novel corticotropin-releasing factor receptor 1 (CRF1) antagonist. In an attempt to suppress O-demethylation of NVS-CRF38 without losing activity against the CRF1 receptor, the protons at the site of metabolism were replaced with deuterium. For in vitro and in vivo studies, intrinsic primary isotope effects (KH/KD) were determined by the ratio of intrinsic clearance (CLint) obtained for NVS-CRF38 and deuterated NVS-CRF38. In vitro kinetic isotope effects (KH/KD) were more pronounced when CLint values were calculated based on the rate of formation of the O-desmethyl metabolite (KH/KD ∼7) compared with the substrate depletion method (KH/KD ∼2). In vivo isotope effects were measured in rats after intravenous (1 mg/kg) and oral (10 mg/kg) administration. For both administration routes, isotope effects calculated from in vivo CLint corresponding to all biotransformation pathways were lower (KH/KD ∼2) compared with CLint values calculated from the O-demethylation reaction alone (KH/KD ∼7). Comparative metabolite identification studies were undertaken using rat and human microsomes to explore the potential for metabolic switching. As expected, a marked reduction of the O-demethylated metabolite was observed for NVS-CRF38; however, levels of NVS-CRF38's other metabolites increased, compensating to some extent for the isotope effect.