Publications by authors named "Matthew Moye"

Introduction: Nonclinical evaluation of the cardiovascular effects of novel chemical or biological entities (NCE, NBEs) is crucial for supporting first-in-human clinical trials. One important aspect of these evaluations is the assessment of potential QT/QTc prolongation risk, as drug-induced QT prolongation can have catastrophic effects. The recent publication of E14/S7B Q&As allows for the situational incorporation of nonclinical QTc data as part of an integrated risk assessment for a Thorough QT (TQT) waiver application provided certain best practice criteria are met.

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Age-related central neurodegenerative diseases, such as Alzheimer's and Parkinson's disease, are a rising public health concern and have been plagued by repeated drug development failures. The complex nature and poor mechanistic understanding of the etiology of neurodegenerative diseases has hindered the discovery and development of effective disease-modifying therapeutics. Quantitative systems pharmacology models of neurodegeneration diseases may be useful tools to enhance the understanding of pharmacological intervention strategies and to reduce drug attrition rates.

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Circadian rhythms in mammals are orchestrated by a central clock within the suprachiasmatic nuclei (SCN). Our understanding of the electrophysiological basis of SCN activity comes overwhelmingly from a small number of nocturnal rodent species, and the extent to which these are retained in day-active animals remains unclear. Here, we recorded the spontaneous and evoked electrical activity of single SCN neurons in the diurnal rodent , and developed cutting-edge data assimilation and mathematical modeling approaches to uncover the underlying ionic mechanisms.

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Circadian transcriptional timekeepers in pacemaker neurons drive profound daily rhythms in sleep and wake. Here we reveal a molecular pathway that links core transcriptional oscillators to neuronal and behavioral rhythms. Using two independent genetic screens, we identified mutants of () with poor behavioral rhythmicity.

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This tutorial illustrates the use of data assimilation algorithms to estimate unobserved variables and unknown parameters of conductance-based neuronal models. Modern data assimilation (DA) techniques are widely used in climate science and weather prediction, but have only recently begun to be applied in neuroscience. The two main classes of DA techniques are sequential methods and variational methods.

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