A model-based approach to investigating the relationship between glucose-insulin dynamics and dapagliflozin treatment effect in patients with type 2 diabetes

A mechanistic modeling platform of SGLT2 inhibition: Implications for type 1 diabetes

Type 1 diabetes mellitus (T1DM) is an autoimmune disease characterized by abnormally high blood glucose concentrations due to dysfunction of the insulin-producing beta-cells in the pancreas. Dapagliflozin, an inhibitor of renal glucose reabsorption, has the potential to improve often suboptimal glycemic control in patients with T1DM through insulin-independent mechanisms and to partially mitigate the adverse effects associated with long-term insulin administration. In this work, we have adapted a systems pharmacology model of type 2 diabetes mellitus to describe the T1DM condition and characterize the effect of dapagliflozin on short- and long-term glycemic markers under various treatment scenarios. The developed platform serves as a quantitative tool for the in silico evaluation of the insulin-glucose-dapagliflozin crosstalk, optimization of the treatment regimens, and it can be further expanded to include additional therapies or other aspects of the disease.

Recent applications of quantitative systems pharmacology and machine learning models across diseases

Quantitative systems pharmacology (QSP) is a quantitative and mechanistic platform describing the phenotypic interaction between drugs, biological networks, and disease conditions to predict optimal therapeutic response. In this meta-analysis study, we review the utility of the QSP platform in drug development and therapeutic strategies based on recent publications (2019-2021). We gathered recent original QSP models and described the diversity of their applications based on therapeutic areas, methodologies, software platforms, and functionalities. The collection and investigation of these publications can assist in providing a repository of recent QSP studies to facilitate the discovery and further reusability of QSP models. Our review shows that the largest number of QSP efforts in recent years is in Immuno-Oncology. We also addressed the benefits of integrative approaches in this field by presenting the applications of Machine Learning methods for drug discovery and QSP models. Based on this meta-analysis, we discuss the advantages and limitations of QSP models and propose fields where the QSP approach constitutes a valuable interface for more investigations to tackle complex diseases and improve drug development.

Dapagliflozin Mediates Plin5/PPARα Signaling Axis to Attenuate Cardiac Hypertrophy

Objective: The purpose of this study was to investigate the effect of dapagliflozin (DAPA), a sodium-glucose cotransporter 2 inhibitor, on relieving cardiac hypertrophy and its potential molecular mechanism.

Methods: Cardiac hypertrophy induced by abdominal aortic constriction (AAC) in mice, dapagliflozin were administered in the drinking water at a dose of 25 mg/kg/d for 12 weeks was observed. Echocardiography was used to detect the changes of cardiac function, including LVEF, LVFS, LVEDd, LVEDs, HR and LV mass. Histological morphological changes were evaluated by Masson trichrome staining and wheat germ agglutinin (WGA) staining. The enrichment of differential genes and signal pathways after treatment was analyzed by gene microarray cardiomyocyte hypertrophy was induced by AngII (2 μM) and the protective effect of dapagliflozin (1 μM) was observed in vitro. The morphological changes of myocardial cells were detected by cTnI immunofluorescence staining. ELISA and qRT-PCR assays were performed to detect the expressions levels of cardiac hypertrophy related molecules.

Results: After 12 weeks of treatment, DAPA significantly ameliorated cardiac function and inhibited cardiac hypertrophy in AAC-induced mice. In vitro, DAPA significantly inhibited abnormal hypertrophy in AngII-induced cardiacmyocytes. Both in vivo and in vitro experiments have confirmed that DAPA could mediate the Plin5/PPARα signaling axis to play a protective role in inhibiting cardiac hypertrophy.

Conclusion: Dapagliflozin activated the Plin5/PPARα signaling axis and exerts a protective effect against cardiac hypertrophy.