Sustained synchronized neuronal network activity in a human astrocyte co-culture system

Impaired neuronal network function is a hallmark of neurodevelopmental and neurodegenerative disorders such as autism, schizophrenia, and Alzheimer's disease and is typically studied using genetically modified cellular and animal models. Weak predictive capacity and poor translational value of these models urge for better human derived in vitro models. The implementation of human induced pluripotent stem cells (hiPSCs) allows studying pathologies in differentiated disease-relevant and patient-derived neuronal cells. However, the differentiation process and growth conditions of hiPSC-derived neurons are non-trivial. In order to study neuronal network formation and (mal) function in a fully humanized system, we have established an in vitro co-culture model of hiPSC-derived cortical neurons and human primary astrocytes that recapitulates neuronal network synchronization and connectivity within three to four weeks after final plating. Live cell calcium imaging, electrophysiology and high content image analyses revealed an increased maturation of network functionality and synchronicity over time for co-cultures compared to neuronal monocultures. The cells express GABAergic and glutamatergic markers and respond to inhibitors of both neurotransmitter pathways in a functional assay. The combination of this co-culture model with quantitative imaging of network morphofunction is amenable to high throughput screening for lead discovery and drug optimization for neurological diseases

The Potential Mechanisms behind Loperamide-Induced Cardiac Arrhythmias Associated with Human Abuse and Extreme Overdose

Loperamide has been a safe and effective treatment for diarrhea for many years. However, many cases of cardiotoxicity with intentional abuse of loperamide ingestion have recently been reported. We evaluated loperamide in in vitro and in vivo cardiac safety models to understand the mechanisms for this cardiotoxicity. Loperamide slowed conduction (QRS-duration) starting at 0.3 µM [~1200-fold (×) its human Free Therapeutic Plasma Concentration; FTPC] and reduced the QT-interval and caused cardiac arrhythmias starting at 3 µM (~12,000× FTPC) in an isolated rabbit ventricular-wedge model. Loperamide also slowed conduction and elicited Type II/III A-V block in anesthetized guinea pigs at overdose exposures of 879× and 3802× FTPC. In ion-channel studies, loperamide inhibited hERG (IKr), INa, and ICa currents with IC50 values of 0.390 µM, 0.526 µM, and 4.091 µM, respectively (i.e., >1560× FTPC). Additionally, in silico trials in human ventricular action potential models based on these IC50s confirmed that loperamide has large safety margins at therapeutic exposures (≤600× FTPC) and confirmed repolarization abnormalities in the case of extreme doses of loperamide. The studies confirmed the large safety margin for the therapeutic use of loperamide but revealed that at the extreme exposure levels observed in human overdose, loperamide can cause a combination of conduction slowing and alterations in repolarization time, resulting in cardiac proarrhythmia. Loperamide’s inhibition of the INa channel and hERG-mediated IKr are the most likely basis for this cardiac electrophysiological toxicity at overdose exposures. The cardiac toxic effects of loperamide at the overdoses could be aggravated by co-medication with other drug(s) causing ion channel inhibition

Human In Silico Drug Trials Demonstrate Higher Accuracy than Animal Models in Predicting Clinical Pro-Arrhythmic Cardiotoxicity

Early prediction of cardiotoxicity is critical for drug development. Current animal models raise ethical and translational questions, and have limited accuracy in clinical risk prediction. Human-based computer models constitute a fast, cheap and potentially effective alternative to experimental assays, also facilitating translation to human. Key challenges include consideration of inter-cellular variability in drug responses and integration of computational and experimental methods in safety pharmacology. Our aim is to evaluate the ability of in silico drug trials in populations of human action potential (AP) models to predict clinical risk of drug-induced arrhythmias based on ion channel information, and to compare simulation results against experimental assays commonly used for drug testing. A control population of 1,213 human ventricular AP models in agreement with experimental recordings was constructed. In silico drug trials were performed for 62 reference compounds at multiple concentrations, using pore-block drug models (IC50/Hill coefficient). Drug-induced changes in AP biomarkers were quantified, together with occurrence of repolarization/depolarization abnormalities. Simulation results were used to predict clinical risk based on reports of Torsade de Pointes arrhythmias, and further evaluated in a subset of compounds through comparison with electrocardiograms from rabbit wedge preparations and Ca2+-transient recordings in human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs). Drug-induced changes in silico vary in magnitude depending on the specific ionic profile of each model in the population, thus allowing to identify cell sub-populations at higher risk of developing abnormal AP phenotypes. Models with low repolarization reserve (increased Ca2+/late Na+ currents and Na+/Ca2+-exchanger, reduced Na+/K+-pump) are highly vulnerable to drug-induced repolarization abnormalities, while those with reduced inward current density (fast/late Na+ and Ca2+ currents) exhibit high susceptibility to depolarization abnormalities. Repolarization abnormalities in silico predict clinical risk for all compounds with 89% accuracy. Drug-induced changes in biomarkers are in overall agreement across different assays: in silico AP duration changes reflect the ones observed in rabbit QT interval and hiPS-CMs Ca2+-transient, and simulated upstroke velocity captures variations in rabbit QRS complex. Our results demonstrate that human in silico drug trials constitute a powerful methodology for prediction of clinical pro-arrhythmic cardiotoxicity, ready for integration in the existing drug safety assessment pipelines