A transdisciplinary framework for managing metabolic dysfunction associated steatotic liver disease

Read full text
Authors: Sania Kouser, Sanketh V Sharma, Arun Bhanu, Subrahmanya Kumar Kukkupuni, Chethala N. Vishnuprasad
Cited by: 1
References: 89

Abstract

Metabolic dysfunction-associated steatotic liver disease (MASLD) is rapidly emerging as a public health issue across the globe. Its complex etiopathology and association with diverse comorbidities poses significant challenges to conventional pharmacological drugs derived from the “ lock-and-key ” paradigm of pharmacology. To overcome the challenges of complexity and non-linear dynamics underlying the disease biology of MASLD, this article proposes a transdisciplinary framework combining holistic disease management principles of traditional medicines with molecular precision of modern biomedicine. Ayurveda - an exceptionally designed and widely practiced Indian Systems of Medicine (ISM) - is explored as a representative model for this framework. This article outlines a unified, biologically plausible transdisciplinary approach incorporating dual-diagnostic workflows, integrative decision interface, and stage-adaptive management algorithm for prevention, early intervention, and advanced disease care. The framework emphasizes integrative and personalized strategies integrating nutrition, lifestyle modification and drug interventions, harnessing the molecular precision of biomedicine alongside the systemic effects of phytochemical diversity. The transdisciplinary model seeks to shift the focus from ‘disease treatment’ to ‘health restoration’ and long-term wellness. The article highlights the scopes and challenges of this framework to offer more comprehensive, sustainable, and patient-centred solutions for MASLD.

Fields of Study & Subjects

Liver Disease Diagnosis and Treatment Traditional Chinese Medicine Studies Pharmacological Effects of Medicinal Plants

Publication details

Journal / source
Frontiers in Pharmacology
Publisher
Frontiers Media SA
Volume
17
Pages
1767844–1767844
Publication date
24 February 2026
Language
EN