Changing face of healthcare: digital therapeutics in the management of diabetes.

Diagnosis, prevention, management and treatment of acute and chronic medical conditions have improved with technological advancements in terms of scalability, efficacy, access, and personalized approach. Digital therapeutic applications (DTx) (Blue Star, Diabeo System, Livongo Diabetes Program, Tidepool etc.,) use web-based applications/cloud platforms to provide evidence-based, personalized, rapid point of care management of chronic, behavior-modifiable conditions, including diabetes mellitus (DM). DTx has improved patient compliance, therapeutic success and economic outcomes in DM management by enabling active patient engagement, lifestyle change, comprehensive medical care, and periodic monitoring of glycemic status. Addressing concerns along DTx data vulnerability, comparative efficacy with conventional treatments, ability to accommodate diverse population needs, and resolving ambiguous regulatory policies and reimbursement guidelines are critical for increasing access to DTx, and overcoming availability, accessibility, and affordability issues in the existing resource limited healthcare environment. In this commentary the authors explore the potential, prospects, and challenges of DTx in the management of Diabetes Mellitus.

In silico evaluation of drugs used in treatment of oral lichen planus.

BACKGROUND: Oral lichen planus (OLP) is a chronic T cell-mediated, immunological, mucocutaneous disease with a number of genes and inflammatory mediators implicated in its pathogenesis. Heart shock protein 70 and the proinflammatory mediator TNFα have been predominantly involved in the etiopathogenesis of oral lichen planus. METHODS: In this study, the action of 27 commonly used drugs for treating OLP at HSP70 and TNFα were evaluated by molecular docking using Maestro Schrodinger version 10.1. X-ray crystallographic structures of the target proteins, that is, Heat Shock Protein 70 (PDB Code: 6FDT) and tumor necrosis factor alpha-1 (PDB Code: 1TNF) were obtained from Protein Data Bank (PDB). The structures of the ligands (27 drugs) were obtained from PubChem in.sdf format. Using Ligprep, pre-processing of the ligands was done. Extra-precision docking was performed with the prepared protein and the ligands. RESULTS: With respect to HSP70, the highest dock score (-4.768) and glide score (-4.818) were seen with hydroxychloroquine (HCQ), followed by epigallocatechin gallate (green tea), methotrexate, and curcumin. The highest dock (-9.525) and glide score (-9.584) in TNFα were seen in with epigallocatechin gallate, followed by HCQ, dapsone, and methotrexate. CONCLUSION: The results of the study tend to explain the clinical use of HCQ in recalcitrant and severe cases, as well as the anti-inflammatory property of epigallocatechin gallate. The results of the study open ventures for exploring the in silico behavior of drugs for effective pathological management.