Planning a Clinical Development Programme for Radiopharmaceuticals: An Analysis of International Guidelines and Expertise
Bibliographic record
Abstract
INTRODUCTION . Current scientific knowledge in the field of molecular biology and the associated manufacturing and technical capabilities enable the development of radiopharmaceuticals (RPs) with high specificity to the target organs, tissues, and receptors. The development of novel RPs requires mandatory clinical trials. However, at the moment, the Russian Federation and the Eurasian Economic Union (EAEU) lack documented guidance for drafting application dossiers for obtaining authorisation for clinical trials of RPs. There is a need for guidelines that will set forth recommendations for planning comprehensive clinical development programmes and regulate data submission requirements for clinical trials of various types of RPs. AIM . This study aimed to explore whether the methodological approaches outlined in international regulatory documents can be used to inform the development of a Russian guideline for the conduct of clinical trials of RPs. DISCUSSION . The authors conducted an extensive analysis of the Russian and EAEU laws and regulations and the guidelines by regulatory agencies in Europe (European Medicines Agency, Swissmedic), the US, and Canada that included provisions for planning and conducting clinical trials of RPs. This analysis identified the key considerations defining the clinical development programme for an RP (including its innovation level and administration route). This article describes the main phases of clinical trials and defines the phase-specific aspects of planning clinical trials of PRs. These aspects include the selection of the trial population, endpoints, design, and duration and considerations for special patient populations. The article summarises the requirements for the content of the application dossiers submitted to regulatory authorities to obtain authorisation to conduct clinical trials of RPs. The article outlines typical nonconformities and errors in application dossiers identified during the assessment of RP clinical trial protocols submitted to the Scientific Centre for Expert Evaluation of Medicinal Products of the Ministry of Health of the Russian Federation in 2020–2024. CONCLUSIONS . This comprehensive analysis of the documents regulating the leading regulators’ approaches supplemented with the critical assessment of the Russian experience can serve as a basis for the development of clinical programmes for both novel diagnostic/therapeutic RPs and well-characterised compounds. The considerations presented in the article may be used by experts reviewing clinical trial results and by RP developers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".