Dr Nenad Macesic

EXPERTISE

  • AMR EVOLUTION IN PATIENTS, GENOMICS
  • CLINICAL & MACHINE LEARNING APPROACHES TO IMPROVING DIAGNOSIS
    AND TREATMENT OF AMR

Dr Nenad’s research focuses on using clinical medicine, bacterial genomic data and artificial intelligence approaches to improve the prevention, diagnosis and treatment of AMR infections. He recently conducted a genomic survey of clinical polymyxin-resistant (PR) Klebsiella pneumoniae to determine the molecular mechanisms of PR and the role of polymyxin exposure versus transmission in PR emergence. This work identified that exposure with de novo resistance emergence was a significant factor for resistance in the majority of patients, rather than transmission. To date, his work has focused mainly on extensively-drug resistant pathogens such as carbapenem- and polymyxin-resistant Klebsiella pneumoniae. As a physician, Dr Nenad cares for patients with infectious complications following solid organ and hematopoietic stem cell transplants.

Dr Nenad Macesic is an infectious diseases physician and research fellow based at the Department of Infectious Diseases at Alfred Hospital. Prior to beginning at Monash, Dr Nenad completed an Infectious Diseases fellowship and worked as an infectious disease physician and research fellow at Columbia University. He has a Masters in Bioinformatics and a passionate research interest in applying novel bioinformatics approaches to improving our diagnosis and treatment of antimicrobial resistance. He is currently an NHMRC Emerging Leader Fellow..

AMR FOCUS

  • Integrating genomic and artificial intelligence approaches to combat antimicrobial resistance.
  • Using clinical medicine, bacterial genomic data and artificial intelligence approaches to improve the prevention, diagnosis and treatment of AMR infections. Genomic approaches for understanding resistance to polymyxins in carbapenem-resistant Enterobacteriaceae.
  • Predicting resistance in Klebsiella pneumoniae through machine learning analysis of genomic data.

IMPACT

  • Translation of novel developments in whole-genome sequencing, machine learning and healthcare analytics into better outcomes for patients.

LEADERSHIP

Chair: Clinical Unmet Needs Working Group