Leveraging [ ¹⁸ F ]F‐Piflufolastat PET for PBPK Prediction of Tissue Distribution and Therapy Optimization in Prostate Cancer

Prostate‐specific membrane antigen (PSMA) is overexpressed in over 90% of prostate cancer tumors, making it a strong target for imaging and therapy. The diagnostic tracer [ 18 F]F‐Piflufolastat provides high affinity and image quality, while the β‐emitter [ 177 Lu]Lu‐PSMA‐617 enables targeted treatment. Despite differences in radioactive half‐life, their shared PSMA‐binding and pharmacokinetic profiles suggest potential for translational pharmacokinetic modeling. We hypothesized that the published full‐body physiologically based pharmacokinetic (PBPK) model could be directly translated across the investigated PSMA ligands to predict tracer distribution within the same patient. A PBPK model was developed by rebuilding and modifying a published [ 68 Ga]Ga‐PSMA‐11/[ 177 Lu]Lu‐PSMA‐617 model to simulate [ 18 F]F‐Piflufolastat PK. Patient‐specific factors included tumor volume, PSMA receptor density, organ blood flow, and renal clearance. Verification used published data, dynamic positron emission tomography (PET) from eight patients, and static total‐body PET/computed tomography (CT) at 2 h from five patients. Extrapolation to [ 177 Lu]Lu‐PSMA‐617, using fitted receptor density, was evaluated against 24‐h and 7‐day Single‐Photon Emission Computed Tomography (SPECT) data from two patients using mean prediction error (PE). The model accurately predicted [ 18 F]F‐Piflufolastat tumor uptake (median PE −3.44% (IQR −3.79 to −3.17) and −3.53% (IQR −3.78 to −3.00) in internal and external cohorts) and showed consistency with 7‐day [ 177 Lu]Lu‐PSMA‐617 SPECT observations. However, predictions for other organs were variable (median PE ranging between −89.7 and 144), indicating limitations of a one‐to‐one molecular translational approach. These findings demonstrate that PBPK modeling can capture key determinants of PSMA tracer distribution, and link [ 18 F]F‐Piflufolastat imaging to [ 177 Lu]Lu‐PSMA‐617 predictions. However, improved representation of systemic and organ‐level kinetics is required. Future work should explore a limited PBPK approach, focusing on accurate blood kinetics and organ‐specific modeling.