An Artificial Intelligence-Assisted PARP-1-Targeted PET Imaging Agent [68Ga]Ga-DOTA-FZPF: From Bench to Clinic

Considering that clinical data of 68 Ga-labeled poly(ADP-ribose) polymerase (PARP)-targeted probes have not yet been reported, and integrated artificial intelligence (AI) workflows for radiotracer development are still lacking. To support radiotracer development and clinical translation, we constructed an AI-assisted multi-stage prioritization workflow and then synthesized two 68 Ga-labeled PARP-1-targeted probes, validating their performance through in vitro , in vivo , and clinical evaluations. An AI-guided multi-objective workflow (encoder-decoder recurrent neural network (RNN) generation, convolutional neural network (CNN) docking scoring, Synthetic Complexity Learned from a Reaction Corpus (SCScore)-based tractability triage, and deep neural network (DNN)) was used to prioritize a derivatization-ready Fuzuloparib analog (NH 2 -FZPF) and to guide chelator installation, yielding DOTA-FZPF and NOTA-FZPF precursors for subsequent 68 Ga radiolabeling. Both [ 68 Ga]Ga-DOTA-FZPF and [ 68 Ga]Ga-NOTA-FZPF exhibited high radiochemical purity, stability, and PARP-1-targeted specificity. In tumor models, [ 68 Ga]Ga-DOTA-FZPF displayed favorable tumor uptake and rapid background clearance, supporting further evaluation. Exploratory positron emission tomography (PET) assessments of Fuzuloparib target engagement show the specificity and functionality of [ 68 Ga]Ga-DOTA-FZPF, supporting in vivo evaluation of PARP inhibitor target engagement and pharmacodynamics. This study recruited 4 cancer patients and performed positron emission tomography/computed tomography (PET/CT) scans using [ 68 Ga]Ga-DOTA-FZPF. Biopsy specimens showed that PET/CT-positive lesions corresponded to regions of high PARP-1 expression. This study demonstrates how an AI rational design workflow can support decision-making in radiotracer design while maintaining synthetic feasibility and translational potential. These preliminary findings support the clinical feasibility of [ 68 Ga]Ga-DOTA-FZPF and suggest that it is promising for non-invasive assessment of PARP-1 expression and dynamic monitoring of in vivo target occupancy and pharmacodynamics.