Ejiabor Rita
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2026Explainable JSON risk reports; 99% confidence reliability

Requence: Genomic AMR Prediction (LaaS)

An antimicrobial resistance prediction and surveillance platform that turns pathogen DNA into explainable risk reports within hours instead of days.

  • Python
  • Scikit-learn
  • Gradient Boosting
  • SHAP
  • BioPython
  • FastAPI

Antimicrobial resistance is projected to claim up to 10 million lives annually by 2050, hitting low- and middle-income countries hardest. Requence attacks that timeline: where traditional susceptibility testing takes three to five days, it delivers explainable resistance predictions in four to six hours.

How the pipeline works

A pathogen FASTA file enters a Lab-as-a-Service architecture that identifies the organism and routes it to a dedicated prediction endpoint. From 900+ genome assemblies we engineered more than 10,000 features (amino-acid k-mers at k=10, SNPs, targeted resistance genes), feeding gradient boosted classifiers per outcome class.

  • Pearl: per-antibiotic resistance probability scores with SHAP-based attribution (e.g. +0.45 gyrA mutation impact)
  • Harmony: anonymized surveillance aggregation connecting local cases to global monitoring
  • Consensus checks across full and partial models guard against unreliable inference

Currently supporting Escherichia coli and Salmonella enterica.

Notable outcome

Explainable JSON risk reports; 99% confidence reliability