The use of truncated area under the curves in the bioequivalence evaluation of long half-life drugs. Studies with donepezil and memantine

Evaluation of the antimalarial activity of SAM13-2HCl with morpholine amide (SKM13 derivative) against antimalarial drug-resistant Plasmodium falciparum and Plasmodium berghei infected ICR mice

Antimalarial drugs are an urgently need and crucial tool in the campaign against malaria, which can threaten public health. In this study, we examined the cytotoxicity of the 9 antimalarial compounds chemically synthesized using SKM13-2HCl. Except for SKM13-2HCl, the 5 newly synthesized compounds had a 50% cytotoxic concentration (CC50) > 100 µM, indicating that they would be less cytotoxic than SKM13-2HCl. Among the 5 compounds, only SAM13-2HCl outperformed SKM13-2HCl for antimalarial activity, showing a 3- and 1.3-fold greater selective index (SI) (CC50/IC50) than SKM13-2HCl in vitro against both chloroquine-sensitive (3D7) and chloroquine -resistant (K1) Plasmodium falciparum strains, respectively. Thus, the presence of morpholine amide may help to effectively suppress human-infectious P. falciparum parasites. However, the antimalarial activity of SAM13-2HCl was inferior to that of the SKM13-2HCl template compound in the P. berghei NK65-infected mouse model, possibly because SAM13-2HCl had a lower polarity and less efficient pharmacokinetics than SKM13-2HCl. SAM13-2HCl was more toxic in the rodent model. Consequently, SAM13-2HCl containing morpholine was selected from screening a combination of pharmacologically significant structures as being the most effective in vitro against human-infectious P. falciparum but was less efficient in vivo in a P. berghei-infected animal model when compared with SKM13-2HCl. Therefore, SAM13-2HCl containing morpholine could be considered a promising compound to treat chloroquine-resistant P. falciparum infections, although further optimization is crucial to maintain antimalarial activity while reducing toxicity in animals.

Simulations of symptomatic treatments for Alzheimer's disease: computational analysis of pathology and mechanisms of drug action

Introduction

A substantial number of therapeutic drugs for Alzheimer's disease (AD) have failed in late-stage trials, highlighting the translational disconnect with pathology-based animal models.

Methods

To bridge the gap between preclinical animal models and clinical outcomes, we implemented a conductance-based computational model of cortical circuitry to simulate working memory as a measure for cognitive function. The model was initially calibrated using preclinical data on receptor pharmacology of catecholamine and cholinergic neurotransmitters. The pathology of AD was subsequently implemented as synaptic and neuronal loss and a decrease in cholinergic tone. The model was further calibrated with clinical Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-Cog) results on acetylcholinesterase inhibitors and 5-HT6 antagonists to improve the model's prediction of clinical outcomes.

Results

As an independent validation, we reproduced clinical data for apolipoprotein E (APOE) genotypes showing that the ApoE4 genotype reduces the network performance much more in mild cognitive impairment conditions than at later stages of AD pathology. We then demonstrated the differential effect of memantine, an N-Methyl-D-aspartic acid (NMDA) subunit selective weak inhibitor, in early and late AD pathology, and show that inhibition of the NMDA receptor NR2C/NR2D subunits located on inhibitory interneurons compensates for the greater excitatory decline observed with pathology.

Conclusions

This quantitative systems pharmacology approach is shown to be complementary to traditional animal models, with the potential to assess potential off-target effects, the consequences of pharmacologically active human metabolites, the effect of comedications, and the impact of a small number of well described genotypes.