Aerobic training reverses LV remodeling in clinically stable individuals with HF. This benefit was not confirmed with combined aerobic and strength training.

Continuous glucose monitoring (CGM) is a platform to measure blood glucose (BG) levels continuously in real time with high enough resolution to document their underlying fluctuations. Multiscale entropy (MSE) analysis has been proposed as a measure of time-series complexity, and when applied to clinical CGM data, MSE analysis revealed that diabetic patients have lower MSE complexity in their BG time series than healthy subjects. To determine if the clinical observations on complexity of glucose dynamics can be back-translated to relevant preclinical species used routinely in diabetes drug discovery, we performed CGM in both mouse (ob/ob) and rat (Zucker Diabetic Fatty, ZDF) models of diabetes. We demonstrate that similar to human data, the complexity of glucose dynamics is also decreased in diabetic mice and rats. We show that low complexity of glucose dynamics is not simply a reflection of high glucose values, but rather reflective of the underlying disease state (i.e. diabetes). Finally, we demonstrate for the first time that the complexity of glucose fluctuations in ZDF rats, as probed by MSE analysis, is decreased prior to the onset of overt diabetes, although complexity undergoes further decline during the transition to frank diabetes. Our study suggests that MSE could serve as a novel biomarker for the progression to diabetes and that complexity studies in preclinical models could offer a new paradigm for early differentiation, and thereby, selection of appropriate clinical candidate molecules to be tested in human clinical trials.

The pace and complexity of modern drug discovery places ever-increasing demands on scientists for data analysis and interpretation. Data flow programming and modern visualization tools address these demands directly. Three different requirements-one for allosteric modulator analysis, one for a specialized clotting analysis, and one for enzyme global progress curve analysis-are reviewed, and their execution in a combined data flow/visualization environment is outlined.

Quantitative reverse transcription PCR (qRT-PCR) is a valuable tool for characterizing the effects of inhibitors on viral replication. The amplification of target viral genes through the use of specifically designed fluorescent probes and primers provides a reliable method for quantifying RNA. Due to reagent costs, use of these assays for compound evaluation is limited. Until recently, the inability to accurately dispense low volumes of qRT-PCR assay reagents precluded the routine use of this PCR assay for compound evaluation in drug discovery. Acoustic dispensing has become an integral part of drug discovery during the past decade; however, acoustic transfer of microliter volumes of aqueous reagents was time consuming. The Labcyte Echo 525 liquid handler was designed to enable rapid aqueous transfers. We compared the accuracy and precision of a qPCR assay using the Labcyte Echo 525 to those of the BioMek FX, a traditional liquid handler, with the goal of reducing the volume and cost of the assay. The data show that the Echo 525 provides higher accuracy and precision compared to the current process using a traditional liquid handler. Comparable data for assay volumes from 500 nL to 12 µL allowed the miniaturization of the assay, resulting in significant cost savings of drug discovery and process streamlining.

Agonist shift assays feature cross-titrations of allosteric modulators and orthosteric ligands. Information generated in agonist shift assays can include a modulator's effect on the orthosteric agonist's potency (alpha) and efficacy (beta), as well as direct agonist activity of the allosteric ligand (tauB) and the intrinsic binding affinity of the modulator to the unoccupied receptor (KB). Because of the heavy resource demand and complex data handling, these allosteric parameters are determined infrequently during the course of a drug discovery program and on a relatively small subset of compounds. Automation of agonist shift assays enables this data-rich analysis to evaluate a larger number of compounds, offering the potential to differentiate compound classes earlier and prospectively prioritize based on desired molecular pharmacology. A high-throughput calcium-imaging agonist shift assay was pursued to determine the allosteric parameters of over 1000 positive allosteric modulator (PAM) molecules for the human muscarinic acetylcholine receptor 1 (M). Control compounds were run repeatedly to demonstrate internal consistency. Comparisons between potency measurements and the allosteric parameter results demonstrate that these different types of measurements do not necessarily correlate, highlighting the importance of fully characterizing and understanding the allosteric properties of leads.