From bench to bedside: 64Cu/177Lu 1C1m-Fc anti TEM-1: mice-to-human dosimetry extrapolations for future theranostic applications - Nantes Université
Article Dans Une Revue EJNMMI Research Année : 2023

From bench to bedside: 64Cu/177Lu 1C1m-Fc anti TEM-1: mice-to-human dosimetry extrapolations for future theranostic applications

Résumé

The development of diagnostic and therapeutic radiopharmaceuticals is an hot topic in nuclear medicine. Several radiolabeled antibodies are under development necessitating both biokinetic and dosimetry extrapolations for effective human translation. The validation of different animal-to-human dosimetry extrapolation methods still is an open issue. This study reports the mice-to-human dosimetry extrapolation of 64 Cu/ 177 Lu 1C1m-Fc anti-TEM-1 for theranostic application in soft-tissue sarcomas. We adopt four methods; direct mice-to-human extrapolation (M1); dosimetry extrapolation considering a relative mass scaling factor (M2), application of a metabolic scaling factor (M3) and combination of M2 and M3 (M4). Predicted in-human dosimetry for the [ 64 Cu]Cu-1C1m-Fc resulted in an effective dose of 0.05 mSv/MBq. Absorbed dose (AD) extrapolation for the [ 177 Lu]Lu-1C1m-Fc indicated that the AD of 2 Gy and 4 Gy to the red-marrow and total-body can be reached with 5–10 GBq and 25–30 GBq of therapeutic activity administration respectively depending on applied dosimetry method. Dosimetry extrapolation methods provided significantly different absorbed doses in organs. Dosimetry properties for the [ 64 Cu]Cu-1C1m-Fc are suitable for a diagnostic in-human use. The therapeutic application of [ 177 Lu]Lu-1C1m-Fc presents challenges and would benefit from further assessments in animals’ models such as dogs before moving into the clinic.
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hal-04756493 , version 1 (28-10-2024)

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Silvano Gnesin, Nicolas Chouin, Michel Cherel, Steven Mark Dunn, Niklaus Schaefer, et al.. From bench to bedside: 64Cu/177Lu 1C1m-Fc anti TEM-1: mice-to-human dosimetry extrapolations for future theranostic applications. EJNMMI Research, 2023, 13 (1), pp.59. ⟨10.1186/s13550-023-01010-4⟩. ⟨hal-04756493⟩
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