Prostate cancer (PCa) is the most common malignancy in men of middle and older age. The standard treatment strategy for PCa ranges from active surveillance in low-grade, localized PCa to radical prostatectomy, external beam radiation therapy, hormonal treatment and chemotherapy. Recently, the use of prostate-specific membrane antigen (PSMA)-targeted radioligand therapy (RLT) for metastatic castration-resistant PCa has been approved. PSMA is predominantly, but not exclusively, expressed on PCa cells. Because of its high expression in PCa, PSMA is a promising target for diagnostics and therapy. To understand the currently used RLT, knowledge about pharmacokinetics (PK) and pharmacodynamics (PD) of the PSMA ligand and the PSMA protein itself is crucial. PK and PD properties of the ligand and its target determine the duration and extent of the effect. Knowledge on the concentration–time profile, the target affinity and target abundance may help to predict the effect of RLT. Increased specific binding of radioligands to PSMA on PCa cells may be associated with better treatment response, where nonspecific binding may increase the risk of toxicity in healthy organs. Optimization of the radioligand, as well as synergistic effects of concomitant agents and an improved dosing strategy, may lead to more individualized treatment and better overall survival.

Osimertinib, a tyrosine kinase inhibitor (TKI), treats non‐small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) mutations. However, its efficacy may vary due to heterogeneous drug distribution, assessable through microdosed radiolabeled drugs and positron emission tomography (PET). Precision dosing using microdosed TKI‐PET encounters challenges due to pharmacokinetic (PK) variations between micro‐ and therapeutic doses. This study aims to predict osimertinib's tissue concentration–time profiles for both microdose and therapeutic dose scenarios using a whole‐body physiologically based pharmacokinetic (PBPK) model, which incorporates nonlinear PK processes and target site occupancy. A target site PBPK model for osimertinib was developed to predict drug distribution across various tissues, including lung tumor, based on a previously published PBPK model. The model incorporated tissue‐specific parameters and accounted for both linear and nonlinear pharmacokinetic processes, including EGFR‐binding dynamics and tumor dynamics. Model predictions were verified with microdosed [ ¹¹ C]C‐osimertinib PET imaging data and clinical pharmacokinetic profiles to assess accuracy and reliability. The developed target site‐PBPK model accurately predicted osimertinib pharmacokinetics across multiple (tumor) tissues and dose levels within 2‐fold error compared to observed PET data. This study underscores the utility of PBPK modeling in predicting osimertinib's pharmacokinetics across diverse tissues, offering insights into drug distribution and predictions of target engagement in NSCLC patients using microdose PET imaging data. The developed model serves as a promising tool for optimizing dosing strategies and evaluating novel EGFR‐TKIs in NSCLC treatment.

Background: Platinum-based chemotherapy, a widely used backbone of systemic cytotoxic anticancer treatment, is associated with nephrotoxicity. Currently, renal function is generally assessed prior to each administration of cisplatin or carboplatin, but there is no guideline regarding the frequency of renal function determination. Objective: The primary objective was to determine the median time to a clinically relevant dosage adjustment (>10%) due to change in renal function in patients treated with cisplatin and carboplatin. Secondly, variables influencing changes in renal function were assessed. Methods: We conducted a retrospective analysis of serial renal function assessments in platinum-treated patients with cancer in two academic medical centers, using a query to extract data from the electronic health records between 2017 and 2019. Results: In total, 512 patients receiving cisplatin and 628 patients receiving carboplatin were included. In total, 15% of all cisplatin-treated patients were found to have a renal function less than 60 mL/min at least once during treatment, with a median time to renal function decline of 67 days (range 5-96 days), which did not differ between treatment regimens. For carboplatin 21% of patients were found to have had a dosage variation of more than 10% at least once during treatment, with a median time-to-event period of 64 days (range 5-100 days). Interpretation: Dose adjustments during platinum-based chemotherapy resulting from renal function decline occur after a median time of ≥64 days. Our data provide substantiated guidance to recommend renal function assessment during platinum-based chemotherapy in clinically stable patients to once every 3 weeks.

Introduction: Prostate cancer (PCa) represents a major global health concern due to biological heterogeneity and the complexity of its underlying molecular pathways, which contribute to substantial morbidity and mortality. Ongoing research continues to elucidate distinct molecular mechanisms that may inform diagnostic and therapeutic strategies. Among these, the prostate-specific membrane antigen (PSMA) has emerged as a pivotal biomarker and therapeutic target in PCa. PSMA is indirectly modulated by androgen signalling through the androgen receptor (AR) pathway and has been observed to undergo transient upregulation following treatment with AR targeting agents, such as darolutamide, particularly in patients with castration-resistant PCa. This transient increase in PSMA expression—termed the ‘PSMA flare phenomenon’—may enhance the sensitivity and accuracy of PSMA-based molecular imaging and disease staging. Methods and analysis: The DARO-flare trials are a prospective, single-centre, interventional, phase I–II proof-of-concept study evaluating whether short-term administration of darolutamide induces a PSMA-flare in patients with hormone-sensitive PCa. The cohort being investigated comprises patients with oligometastatic recurrence following prior therapy with curative intent. Within the cohort, participants are randomised (1:1) to receive darolutamide 600 mg two times a day for either 7 or 14 days. All participants undergo baseline PSMA positron emission tomography (PET)/CT imaging as standard-of-care and two follow-up scans on days 7 and 14. The primary endpoint was the change in the number of PSMA-expressing PCa lesions and/or PSMA expression per lesion maximum standardised uptake value on repeated PSMA PET/CT, indicative of a darolutamide flare response. Secondary endpoints included the impact on clinical management decisions, defined as a treatment change following short-course darolutamide, tolerability and toxicity as assessed by adverse event reporting, and patient-reported outcomes related to quality of life. Ethics and dissemination: The study protocol has been approved by the Medical Ethics Committee (METC) Amsterdam UMC and adheres to the Declaration of Helsinki. Written informed consent is obtained from all participants. Study findings will be disseminated through peer-reviewed publications and conference presentations. Trial registration number: 2025-520482-52-03 ( https://euclinicaltrials.eu/ctis-public/view/2025-520482-52-03?lang=en , protocol nr 6.0).

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.