bioRxivMicrobiologyPreprint
BIOTIA-DX RESISTANCE Achieved the Best Antimicrobial Resistance Phenotype Prediction Accuracy at CAMDA 2026
Gábor Fidler, Heather WellsiD, Patrick Ford CombsiD, John C Papciak, Mara Couto-RodrigueziD, Sol Rey, Tiara Rivera, Lorenzo Uccellini, Christopher E. MasoniD, Niamh B. O’HaraiD, Dorottya Nagy‐SzakaliD, David DankoiD
Abstract
We present BIOTIA-DX RESISTANCE (BDXR), our submission to the CAMDA 2026 AMR Challenge. This work extends our CAMDA 2025 submission [1] to a new set of six species-drug pairs and adds k-mer-based feature engineering (both targeted and whole-genome) for pairs where the 2025 gene-presence base model underperforms. BDXR achieved a mean accuracy of 86.1% across the six pairs on the CAMDA 2026 test set, ranking first on four pairs, tied for first on Streptococcus pneumoniae (penicillin), and second on Campylobacter jejuni (nalidixic acid); per-pair test accuracy ranged from 69.9% (C. jejuni, nalidixic acid) to 98.8% (S. pneumoniae, penicillin). We refer the reader to our 2025 preprint [1] for the underlying workflow, dataset curation, and clinical motivation; this preprint focuses on the results and methodological changes that are new in 2026.
- organism: human
- assay: DNA methylation
- research focus: variant effect prediction
- research focus: drug response / drug discovery
- approach: machine learning (classical)
- Citations
- 0
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