Interactive medical and safety monitoring in clinical trials with clinDataReview: a validated and open-source reporting tool.

Continuous medical and safety monitoring of subject data during a clinical trial is a critical part of evaluating the safety of trial participants and as such is governed by protocol procedures and regulatory guidelines to meet the trial's intended objectives. We present an open-source validated graphical tool (clinDataReview R package) which provides access to the trial data with drill-down to individual patient profiles. The tool incorporates functionalities that facilitate detection of error and data inconsistencies requiring follow-up. It supports regular medical monitoring and oversight as well as safety monitoring committees with interactive tables and listings alongside graphical visualizations of the primary safety data in reports. An implementation example is given where the tool is used to deliver validated outputs following FDA/EMA guidelines. As such, this tool enables a more efficient, interactive, and reproducible review of safety data collected during an ongoing clinical trial.

Endovascular treatment of juxta-anastomotic venous stenoses of forearm radiocephalic fistulas: long-term results and prognostic factors.

PURPOSE: To evaluate long-term results of endovascular procedures in treatment of venous juxta-anastomotic stenoses (JASs) of native forearm radiocephalic arteriovenous fistulas (AVFs) and to identify prognostic factors influencing these results. MATERIALS AND METHODS: During a 124-month period, 147 endovascular interventions were performed in 75 forearm radiocephalic AVFs with JASs defined as stenoses located within the first 5 cm of the outflow vein. Prognostic factors included patient characteristics (age, sex, diabetes), AVF-related characteristics (location on forearm, age, maturity), stenosis-related characteristics (position relative to anastomosis, length, and degree), and degree of residual stenosis and delay of restenosis after the first endovascular procedure. RESULTS: At 1 and 3 years, access primary patency (PP) rates were 46.6% (95% confidence interval [CI], 36.3%-59.9%) and 25.5% (95% CI, 15.7%-41.6%) and assisted PP (APP) rates were 81.3% (95% CI, 72.6%-91.1%) and 63.2% (95% CI, 50.6%-79.0%), respectively. Stenosis degree of 50%-75% (P = .017), stenosis length of 10 mm or more (P = .017), and time before first restenosis of less than 6 months (P = .03) significantly increased the frequency of endovascular procedures during follow-up. However, only the degree of residual stenosis after the first endovascular treatment significantly affected long-term APP (P = .039). When residual stenosis was less than 50%, 1- and 2-year access APP rates were 84.6% (95% CI, 75.8%-94.4%) and 76.1% (95% CI, 64.6%-89.6%), respectively. When it was at least 50%, the respective APP rates were 62.3% (95% CI, 38.9%-99.9%) and 46.8% (95% CI, 22.4%-97.7%). CONCLUSIONS: Endovascular treatment of JASs in forearm radiocephalic AVFs provides good long-term results except when the residual stenosis after the first procedure is 50% or more. In that case, the optimal treatment remains to be determined.

Tales of 1,008 small molecules: phenomic profiling through live-cell imaging in a panel of reporter cell lines.

Phenomic profiles are high-dimensional sets of readouts that can comprehensively capture the biological impact of chemical and genetic perturbations in cellular assay systems. Phenomic profiling of compound libraries can be used for compound target identification or mechanism of action (MoA) prediction and other applications in drug discovery. To devise an economical set of phenomic profiling assays, we assembled a library of 1,008 approved drugs and well-characterized tool compounds manually annotated to 218 unique MoAs, and we profiled each compound at four concentrations in live-cell, high-content imaging screens against a panel of 15 reporter cell lines, which expressed a diverse set of fluorescent organelle and pathway markers in three distinct cell lineages. For 41 of 83 testable MoAs, phenomic profiles accurately ranked the reference compounds (AUC-ROC ≥ 0.9). MoAs could be better resolved by screening compounds at multiple concentrations than by including replicates at a single concentration. Screening additional cell lineages and fluorescent markers increased the number of distinguishable MoAs but this effect quickly plateaued. There remains a substantial number of MoAs that were hard to distinguish from others under the current study's conditions. We discuss ways to close this gap, which will inform the design of future phenomic profiling efforts.

High-Throughput Gene Expression Profiles to Define Drug Similarity and Predict Compound Activity.

By adding biological information, beyond the chemical properties and desired effect of a compound, uncharted compound areas and connections can be explored. In this study, we add transcriptional information for 31K compounds of Janssen's primary screening deck, using the HT L1000 platform and assess (a) the transcriptional connection score for generating compound similarities, (b) machine learning algorithms for generating target activity predictions, and (c) the scaffold hopping potential of the resulting hits. We demonstrate that the transcriptional connection score is best computed from the significant genes only and should be interpreted within its confidence interval for which we provide the stats. These guidelines help to reduce noise, increase reproducibility, and enable the separation of specific and promiscuous compounds. The added value of machine learning is demonstrated for the NR3C1 and HSP90 targets. Support Vector Machine models yielded balanced accuracy values ≥80% when the expression values from DDIT4 & SERPINE1 and TMEM97 & SPR were used to predict the NR3C1 and HSP90 activity, respectively. Combining both models resulted in 22 new and confirmed HSP90-independent NR3C1 inhibitors, providing two scaffolds (i.e., pyrimidine and pyrazolo-pyrimidine), which could potentially be of interest in the treatment of depression (i.e., inhibiting the glucocorticoid receptor (i.e., NR3C1), while leaving its chaperone, HSP90, unaffected). As such, the initial hit rate increased by a factor 300, as less, but more specific chemistry could be screened, based on the upfront computed activity predictions.

Functional and Transcriptional Characterization of Histone Deacetylase Inhibitor-Mediated Cardiac Adverse Effects in Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes.

UNLABELLED: Histone deacetylase (HDAC) inhibitors possess therapeutic potential to reverse aberrant epigenetic changes associated with cancers, neurological diseases, and immune disorders. Unfortunately, clinical studies with some HDAC inhibitors displayed delayed cardiac adverse effects, such as atrial fibrillation and ventricular tachycardia. However, the underlying molecular mechanism(s) of HDAC inhibitor-mediated cardiotoxicity remains poorly understood and is difficult to detect in the early stages of preclinical drug development because of a delayed onset of effects. In the present study, we show for the first time in human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs) that HDAC inhibitors (dacinostat, panobinostat, vorinostat, entinostat, and tubastatin-a) induce delayed dose-related cardiac dysfunction at therapeutic concentrations associated with cardiac adverse effects in humans. HDAC inhibitor-mediated delayed effects on the beating properties of hiPS-CMs developed after 12 hours by decreasing the beat rate, shortening the field potential duration, and inducing arrhythmic behavior under form of sustained contractions and fibrillation-like patterns. Transcriptional changes that are common between the cardiotoxic HDAC inhibitors but different from noncardiotoxic treatments identified cardiac-specific genes and pathways related to structural and functional changes in cardiomyocytes. Combining the functional data with epigenetic changes in hiPS-CMs allowed us to identify molecular targets that might explain HDAC inhibitor-mediated cardiac adverse effects in humans. Therefore, hiPS-CMs represent a valuable translational model to assess HDAC inhibitor-mediated cardiotoxicity and support identification of better HDAC inhibitors with an improved benefit-risk profile. SIGNIFICANCE: Histone deacetylase (HDAC) inhibitors are a promising class of drugs to treat certain cancers, autoimmune, and neurodegenerative diseases. However, treated patients can experience various cardiac adverse events such as hearth rhythm disorders. This study found that human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs) can predict cardiac adverse events in patients caused by HDAC inhibitors. Furthermore, transcriptional changes at the level of gene expression supported the effects on the beating properties of hiPS-CMs and highlight targets that might cause these cardiac adverse effects. hiPS-CMs represent a valuable translational model to assess HDAC inhibitor-mediated cardiotoxicity and to support development of safer HDAC inhibitors.