Research Deep‑Dive

Antimicrobial Resistance (AMR)

Predicting the next pandemic before it arrives.

We combine metagenomic surveillance, AI-driven evolution modelling, and phage discovery to understand and combat the rising threat of antimicrobial resistance in clinical and environmental settings.

Our Work ← Back to Research
🦠
1,000+
Metagenomes analysed for ARG profiles
85%
Prediction accuracy for AMR evolution
12
Novel phage candidates isolated
Our Approach

Genomic Surveillance + AI + Phage Therapy

We build end‑to‑end pipelines that process environmental and clinical metagenomes, track resistance gene flow, and design phage‑based interventions.

🧬 1. Metagenomic Profiling

Shotgun metagenomics (MEGAHIT, MetaSPAdes) with ARG annotation via CARD, MEGARes, and custom databases.

🤖 2. AI Evolution Modelling

Time‑series ML (LSTM, XGBoost) to predict resistance trajectory under selective pressure.

🦠 3. Phage Discovery & Therapy

Isolation and characterisation of lytic phages against MDR pathogens, with in vitro and in vivo efficacy testing.

Current Highlights

  • ✓ Identified a novel extended‑spectrum β‑lactamase (ESBL) variant in riverine metagenomes.
  • ✓ Developed a phage cocktail that lyses 90% of clinical K. pneumoniae isolates tested.
  • ✓ Collaboration with tertiary care hospitals for longitudinal AMR surveillance.
Associated Research Outputs
01
AI‑driven prediction of carbapenem resistance evolution — Manuscript under review, Nature Communications
02
Phage‑host interaction network in urban wastewater microbiomes — Data presented at ISME 2025
03
Metagenomic risk assessment framework for AMR in agroecosystems — In preparation