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Infection Banner.pngEnvisioned Future

Reducing/treating infections using augmented intelligence strategies:

  1. Develop augmented intelligence system to predict risk of multi-drug resistant (mdr) organism acquisition
  2. Develop augmented intelligence system to predict areas of intervention
  3. Develop further precision treatment based on individualised patient and organism factors

Key Strategies

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Multiple datasets that aim to achieve the following objectives are needed to achieve the envisioned future. 

  • To determine mechanisms of antimicrobial resistance using next generation sequencing
    • Evaluate how these mechanisms of resistance interplayed to guide empiric therapy
    • Assess the extent of each type of mechanism of resistance in transmission and the effect on infection control policies
    • Develop a rapid and high throughput platform to detect resistance genes to guide susceptibilities testing
  • To evaluate risk factors for acquisition of multi-drug resistant infections, and predictors for mortality
    • Identification of modifiable risk factors and predictors in different patient types will prevent unnecessary infections and negative clinical outcomes
  • To identify novel and optimize antimicrobial therapeutic strategies
    • Provide new compounds testing platform (from our well-characterized clinical isolates) via collaboration with external collaborators (including pharmaceutical industries)
    • Reposition current, and new/emerging antibiotics via strategies in dosing optimization (Pharmacokinetics/Pharmacodynamics bacterial strain specific  elucidation) and/ or as part of combination therapy to retard and prevent further emergence of resistance

  • Antimicrobial drug assays development
    • To guide individualized antimicrobial dosing to attain adequate antimicrobial drug levels using  therapeutic drug monitoring
  • To evaluate novel infection control methods for multi-drug-resistant organisms 
    • Serve as a test-bed for novel infection control methods  
  • To study the effects of Microbiome changes (in diversity and inoculum load) in AMR
  • Development of alternative therapies
    • Relevant Microbiome reconstitution to reinstate the necessary diversity and inoculum load for elimination of multi-drug resistant pathogens
    • Cell therapy (mait cells, target immunoglobulins) as an adjunct for AMR
    • Bacteriophages utility in AMR

Research Peak Leads

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Assoc Prof Andrea Kwa Lay Hoon
Specialty: Anitmicrobial Resistance
Assistant Director, Pharmacy (Research)

Assoc Prof Tan Thuan Tong
Specialty: Infectious Diseases

Head & Senior Consultant
Infectious Diseases
Singapore General Hospital