Results of TOR001: An open-label single patient study using targeted bacteriophage therapy for the treatment of chronic urinary tract infection
Bibliographic record
Abstract
Chronic urinary tract infections are persistent bacterial infections with the potential to drive antibiotic resistance. Like other persistent bacterial infections, intracellular bacterial reservoirs and biofilm formation hinder the clearance of pathogens despite long courses of antibiotic therapy. New strategies for treatment of these persistent infections are needed. Here we describe the results of an open-label individual patient study using bacteriophage therapy to treat a chronic urinary tract infection in an immunocompetent 72-year-old woman without underlying urolithiasis or indwelling devices. We co-administered HP3.1, HP3, and ES19 bacteriophages with demonstrated in vitro activity via bladder instillation, orally, and as a topical formulation. The primary outcome was safety and tolerability of the treatment. Adverse events were monitored through daily symptom logs and laboratory analysis of blood samples obtained throughout the study. We found that the treatment was safe and well tolerated with no serious adverse events reported. No adverse events were deemed related to the study material. The secondary outcomes were clinical and microbiological efficacy as monitored through daily symptom logs and standard urine culture, respectively. Two weeks after initial clinical improvement, her condition relapsed and culture was consistent with previous isolates. Treatment with ertapenem following bacteriophage therapy led to sustained clinical and microbiologic cure. Exploratory analysis through whole genome sequencing of pre- and post-treatment isolates identified mutations in genes associated with adhesion and evasion that may influence virulence and promote clearance. These results inform expanded randomized clinical trials and support the growing literature that bacteriophage therapies are safe and effective.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".