Standardising neonatal and paediatric antibiotic clinical trial design and conduct: the PENTA-ID network view
Bibliographic record
Abstract
Antimicrobial development for children remains challenging due to multiple barriers to conducting randomised clinical trials (CTs). There is currently considerable heterogeneity in the design and conduct of paediatric antibiotic studies, hampering comparison and meta-analytic approaches. The board of the European networks for paediatric research at the European Medicines Agency (EMA), in collaboration with the Paediatric European Network for Treatments of AIDS-Infectious Diseases network (www.penta-id.org), recently developed a Working Group on paediatric antibiotic CT design, involving academic, regulatory and industry representatives. The evidence base for any specific criteria for the design and conduct of efficacy and safety antibiotic trials for children is very limited and will evolve over time as further studies are conducted. The suggestions being put forward here are based on the adult EMA guidance, adapted for neonates and children. In particular, this document provides suggested guidance on the general principles of harmonisation between regulatory and strategic trials, including (1) standardised key inclusion/exclusion criteria and widely applicable outcome measures for specific clinical infectious syndromes (CIS) to be used in CTs on efficacy of antibiotic in children; (2) key components of safety that should be reported in paediatric antibiotic CTs; (3) standardised sample sizes for safety studies. Summarising views from a range of key stakeholders, specific criteria for the design and conduct of efficacy and safety antibiotic trials in specific CIS for children have been suggested. The recommended criteria are intended to be applicable to both regulatory and clinical investigator-led strategic trials and could be the basis for harmonisation in the design and conduct of CTs on antibiotics in children. The next step is further discussion internationally with investigators, paediatric CTs networks and regulators.
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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 | 0.749 | 0.740 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.002 | 0.014 |
| Scholarly communication | 0.030 | 0.015 |
| Open science | 0.014 | 0.018 |
| Research integrity | 0.019 | 0.031 |
| Insufficient payload (model declined to judge) | 0.006 | 0.009 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".