Effect of Ligand Amount and Fraction of Labeled Peptides on Internalized 177Lu-PSMA-I&T Concentrations in Tumors: Physiologically-based Pharmacokinetic Modeling

Introduction: Radiopharmaceutical therapy (RPT) with ligands or peptides is a molecular radiotherapy framework of significant potential for different diseases. In recent years, targeting the prostate specific membrane antigen (PSMA) has shown promising treatment outcomes. We aim to assess the effect of the fraction of labeled peptides and total ligand amount on the maximum internalized labeled peptide in the tumor for ¹⁷⁷Lu-PSMA-I&T.

Methods: Physiologically-based pharmacokinetic modeling (PBPK) is a powerful method to analyze, simulate and predict the biodistribution of radiolabeled substances. These models combine information on the drug with knowledge of the physiology and biology at the organism level to achieve a mechanistic representation of the drug in biological systems, allowing the simulation of drug concentration-time profiles. We implemented a PBPK model in Python to predict the distribution of ¹⁷⁷Lu-PSMA-I&T within various organs and tumors over time. To investigate the effect of fraction of labeled peptide on maximum internalized labeled peptide into the tumor cells, a fixed value of 105 [nmol] is considered for ligand amount, and a range of 1-10% of the ligand amount is assumed as labeled peptide. Furthermore, to study the effect of varying ligand amounts, the fraction of labeled peptide was set to 3%, and the ligand amount varied in the 100-1000 [nmol] range.

Results: The results showed that the amount of tumor-internalized labeled peptide reaches its peak after almost 5 hours. By altering the fraction of labeled peptides from 1 to 10%, with 1% intervals, the maximum concentration rises nearly 0.8% in each step. Increasing the ligand amount from 100 to 500 leads to increasing the maximum concentration. However, when the ligand amount exceeds 500 [nmol], the maximum concentration falls dramatically.

Conclusions: We implemented a PBPK model to determine the effect of ligand amount and the fraction of labeled peptide on maximum internalized labeled peptide in the tumor for ¹⁷⁷Lu-PSMA-I&T therapy of prostate cancer. Making use of these parameters can help enable optimization and personalization of RPTs, providing effective treatments for patients while minimizing absorbed doses and toxicities to organs-at-risk. Further model validations and variations are underway.

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