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Record W4393005342 · doi:10.1136/ejhpharm-2024-eahp.70

3PC-013 Radiopharmaceutical single-vial cold kit formulation of FAPI-04, an experimental vector for gallium-68 PET imaging in oncology

2024· article· en· W4393005342 on OpenAlexfundno aff
François Garnier, Juliette Fouillet, Charlotte Donzé, Léa Rubira, Cyril Fersing

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicPeptidase Inhibition and Analysis
Canadian institutionsnot available
FundersInstitute of Cancer ResearchJohannes Gutenberg-Universität Mainz
KeywordsGalliumVialRadiochemistryChemistryNuclear chemistryNuclear medicineMaterials scienceChromatographyMedicine

Abstract

fetched live from OpenAlex

Background and Importance Targeting the tumour microenvironment recently gained interest in oncology, as evidenced by the use of fibroblasts activation protein inhibitors (FAPI) for cancer-associated fibroblasts imaging. Among these derivatives, FAPI-04 radiolabeled with gallium-68 emerged as a promising PET diagnostic agent. To date, [68Ga] Ga-FAPI-04 is considered an experimental radiopharmaceutical, with a tedious and intricate radiolabeling process. Thus, the development of a single-vial cold kit (SVCK) formulation of FAPI-04 to simplify the preparation of [68Ga] Ga-FAPI-04 would be of particular interest. Aim and Objectives Various parameters involved in the formulation of FAPI-04 as a SVCK were investigated. Then, optimal conditions for successful radiolabeling of [68Ga] Ga-FAPI-04 were identified. Material and Methods Kit vials were conditioned to contain several bulk agents (five tested), buffers (six tested), anti-radiolysis compound (three tested) and FAPI-04. Mixtures were solubilised in water for injection and then lyophilised. The influence of each component on the radiolabeling process was studied, as well as the amount of vector (30, 45 or 60 µg). [68Ga] GaCl3 was eluted from a GalliAD® generator directly into the kit vials, subsequently heated for 10 minutes at 97°C. Radiochemical purity (RCP) of each reaction was assessed by radio-TLC and radio- HPLC. The pH was checked by pH strips during the kit’s conditioning and after each reaction, aiming at an optimal value of 3.4 (ideal for 68Ga radiolabeling). Results Mannitol (50 mg) was the bulk agent with the best appearance after freeze-drying and was retained in subsequent assays. As expected, the pH of the reaction medium was critical to the success of radiolabeling. HEPES buffer 0.3 M pH 4 allowed RCP of 83.3% by TLC and 78.9% by HPLC, compared with extremely poor results obtained with the five other buffers. Anti-radiolysis agents showed a moderate improvement in RCP (~10% increase with ascorbic acid) which persisted over a period of 4 hours, confirming radiocomplex stability. Using 45 µg FAPI-04 instead of 30 µg in the reaction slightly increased RCP (>96% in TLC, >91% in HPLC). Conclusion and Relevance The importance of carefully selecting the ingredients of a radiopharmaceutical SVCK was demonstrated, resulting in excellent RCP values for [68Ga] Ga-FAPI-04. A terminal purification step would remove HEPES buffer to comply with European Pharmacopoeia requirements. References and/or Acknowledgements Conflict of Interest No conflict of interest.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.053
GPT teacher head0.398
Teacher spread0.345 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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