Systems pharmacology for antimicrobial combinations
Designing model-informed antibiotic and phage-antibiotic combinations that maximise efficacy while reducing toxicity and resistance.
Monash Biomedicine Discovery Institute
Dr Jinxin Zhao
Computational biology, systems pharmacology and AI for antimicrobial therapy.
Hi, I am Jinxin.
I develop computational and experimental strategies for combating multidrug-resistant bacterial infections, with a focus on Acinetobacter baumannii and other priority pathogens.
My work integrates AI, microbial evolution, pharmacokinetics/pharmacodynamics, multi-omics, genome-scale metabolic modelling and systems pharmacology to design antibiotic and phage-antibiotic combination therapies.
65
authored and co-authored publications
2026
Humboldt Fellow / Group Leader
MDR
priority-pathogen antimicrobial research
Research
Computational and experimental antimicrobial science.
Microbial evolution and heteroresistance
Studying how bacterial populations adapt under antimicrobial pressure, including single-cell and evolutionary approaches to heteroresistance.
Bioinformatics, AI and genome-scale modelling
Integrating multi-omics, metabolic modelling and machine-learning approaches to explain bacterial physiology during infection and treatment.
Bacteriophage genomics
Building exploratory tools and computational workflows for interpreting bacteriophage genomes and phage-based therapeutic strategies.
Current Work
Roles and selected projects
- May 2026 - present Humboldt Fellow / Group Leader University of Hamburg, Germany
- May 2021 - present Research Fellow, Computational Biologist / Bioinformatician / Pharmacometrician Li's Laboratory of Antimicrobial Systems Pharmacology, Monash University
- Feb 2021 - present Conference Scientific Committee Member International Society of Antimicrobial Chemotherapy
- Feb 2021 - present Conference Organising Committee Member Victorian Infection and Immunity Network
PhageGE
An interactive web platform for exploratory analysis and visualization of bacteriophage genomes.
Dose optimisation against MDR Acinetobacter baumannii
Model-informed optimisation of polymyxin-rifampicin and related antimicrobial combinations.
Context-specific bacterial metabolic modelling
Genome-scale and context-aware modelling to understand bacterial metabolic adaptation during infection and treatment.
Single-cell heteroresistance
Single-cell sequencing approaches for understanding heteroresistance in Klebsiella pneumoniae.
Publications
Selected first, co-first and corresponding-author work.
See the full publication list on Google Scholar.
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Zhao J. et al. PhageGE: an interactive web platform for exploratory analysis and visualization of bacteriophage genomes.
GigaScience -
Zhao J. et al. Model-informed dose optimisation of polymyxin-rifampicin combination therapy against multidrug-resistant Acinetobacter baumannii.
International Journal of Antimicrobial Agents -
Zhao J. et al. Polymyxin dose tunes the evolutionary dynamics of resistance in multidrug-resistant Acinetobacter baumannii.
Clinical Microbiology and Infection -
Zhao J. et al. Comparative metabolomics reveals key pathways associated with the synergistic activity of polymyxin B and rifampicin combination against multidrug-resistant Acinetobacter baumannii.
Biochemical Pharmacology -
Zhao J. et al. Genome-scale metabolic modeling reveals metabolic alterations of multidrug-resistant Acinetobacter baumannii in a murine bloodstream infection model.
Microorganisms
Funding
Selected research grants.
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Context-specific metabolic modelling for understanding bacterial metabolic adaptation Monash Platform Access Grant, Monash University | PI | Sep 2025 - Sep 2026AUD $14,949
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Single-cell sequencing for understanding the heteroresistance in K. pneumoniae M20 Genomics | PI | Nov 2024 - Nov 2025AUD $88,400
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BioSAXS analysis of antimicrobial action of peptides/proteins Australian Synchrotron Beamtime | Co-PI | Oct 2024 - Sep 2025AUD $32,784
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Targeting bacterial membrane remodelling to combat antimicrobial resistance Azenta SPARK Grant | PI | Oct 2023 - Sep 2024AUD $10,000
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Evolution on lung-chip drives dose optimisation of antibiotic combination therapies International Society of Antimicrobial Chemotherapy Project Grant | PI | Jul 2022 - Jul 2024GBP 9,700
Recognition
Awards
- DAAD AInet Fellowship 2025
- 35th ECCMID Travel Award 2025
- Rod Rickards Fellowship 2025, Australian Academy of Science
- Finalist, Basic Science Researcher category, 2022 Premier's Awards for Health and Medical Research
- 33rd ECCMID Travel Award 2023
- Best Rapid-Fire Presentation, 1st International Conference on Antimicrobial Computational Pharmacology
- Azenta Life Sciences Publication Award 2022
- CSL Top Completing PhD Award 2022
Seminars
Invited talks
- Revolutionising Antimicrobial Therapy: Integration of Quantitative Systems Pharmacology and System Biology to Accelerate Bench-to-Bedside Translation National Taiwan University | September 2025
- Transforming antimicrobial pharmacokinetics/pharmacodynamics: An integrated microbial evolution and systems pharmacology approach Shandong University | September 2023
- Systems pharmacology informed dose optimisation of polymyxins and their synergistic combinations against Acinetobacter baumannii Huashan Hospital, Fudan University | September 2023
- Systems pharmacology of polymyxins and their synergistic combinations against Acinetobacter baumannii: A systems pharmacology approach Sir Run Run Shaw Hospital, Zhejiang University | August 2023
- Transforming antimicrobial pharmacokinetics/pharmacodynamics: A microbial evolution and computational approach Monash - State Key Lab of Microbial Technology, Shandong University | June 2023
Training
Education
- PhD of Antimicrobial Pharmacology Monash University | Feb 2017 - May 2021
- Master of Bioengineering Shandong University, in collaboration with Monash Institute of Pharmaceutical Sciences | Sep 2013 - Jun 2016
- Bachelor of Biological Science Shandong University | Sep 2008 - Jun 2012
Contact
Let us talk antimicrobial pharmacology, omics and modelling.
Melbourne, Australia / Hamburg, Germany
[email protected]