Work

Integrating Molecular Pathogenesis and Host Response into a Digital Twin Framework for Predicting Therapeutic Outcomes in Balamuthia mandrillaris Encephalitis

Year: 2026

Type: editorial

Abstract: Balamuthia mandrillaris is a free-living amoeba that causes granulomatous amoebic encephalitis, a rare but devastating central nervous system infection with mortality exceeding 95%. Treatment relies on empirical, multidrug regimens lasting several months, yet prognostic indicators and optimal dosing strategies remain undefined. Advances in computational biology now permit the creation of digital twins, data-driven and patient-specific virtual replicas that integrate clinical, imaging, molecular, and pharmacological data to simulate disease dynamics and therapeutic response. By incorporating molecular mechanisms of Balamuthia pathogenesis and host susceptibility into such a model, it becomes possible to forecast treatment trajectories, personalize drug dosing, and predict toxicity in real time. This paper outlines the molecular and immunological underpinnings of Balamuthia infection and proposes a digital twin framework that bridges mechanistic biology with predictive analytics to improve management and survival in this neglected infection.

Source: ACS Omega

DOI: 10.1021/acsomega.5c11417

Authors: Ruqaiyyah Siddiqui, Sutherland K. Maciver, Naveed Ahmed Khan

Institutions: Heriot-Watt University, Istinye University, University of Edinburgh, University of Derby

Language: English

Topic: Legionella and Acanthamoeba research

Subfield: Endocrinology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,935