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Abstract Background Low-dose weekly methotrexate (MTX) is the mainstay of treatment in juvenile idiopathic arthritis. Unfortunately, a substantial part of patients has insufficient efficacy of MTX. A potential cause of this inadequate response is suboptimal drug adherence. The aim of this study was to assess MTX adherence in juvenile idiopathic arthritis patients by quantification of MTX concentrations in plasma. Secondly, the association between MTX concentrations and either self-reported adherence issues, or concomitant use of biologics was examined. Methods This was a retrospective, observational study using plasma samples from juvenile idiopathic arthritis patients. An ultrasensitive liquid chromatography-tandem mass spectrometry method was developed for quantification of MTX and its metabolite 7-hydroxy-MTX in plasma. The determined MTX plasma concentrations in juvenile idiopathic arthritis patients were compared with corresponding adherence limits, categorising them as either adherent or possibly non-adherent to MTX therapy. Results Plasma samples of 43 patients with juvenile idiopathic arthritis were analysed. Adherence to MTX in this population was 88% shortly after initiation of MTX therapy and decreased to 77% after one year of treatment. Teenagers were more at risk for non-adherence (p = 0.002). We could not find an association between MTX adherence with either self-reported adherence issues, nor with the use of concomitant biological treatment (p = 1.00 and p = 0.27, respectively; Fisher’s Exact). Conclusions Quantification of MTX in plasma is a feasible and objective method to assess adherence in patients using low-dose weekly MTX. In clinical practice, the use of this method could be a helpful tool for physicians to refute or support suspicion of non-adherence to MTX therapy.

Abstract Background There is an unmet need for prediction of treatment outcome or patient selection for [177Lu]Lu-PSMA therapy in patients with metastatic castration-resistant prostate cancer (mCRPC). Quantification of the tumor exposure–response relationship is pivotal for further treatment optimization. Therefore, a population pharmacokinetic (PK) model was developed for [177Lu]Lu-PSMA-I&T using SPECT/CT data and, subsequently, related to prostate-specific antigen (PSA) dynamics after therapy in patients with mCRPC using a pharmacokinetic/pharmacodynamic (PKPD) modelling approach. Methods A population PK model was developed using quantitative SPECT/CT data (406 scans) of 76 patients who received multiple cycles [177Lu]Lu-PSMA-I&T (± 7.4 GBq with either two- or six-week interval). The PK model consisted of five compartments; central, salivary glands, kidneys, tumors and combined remaining tissues. Covariates (tumor volume, renal function and cycle number) were tested to explain inter-individual variability on uptake into organs and tumors. The final PK model was expanded with a PD compartment (sequential fitting approach) representing PSA dynamics during and after treatment. To explore the presence of a exposure–response relationship, individually estimated [177Lu]Lu-PSMA-I&T tumor concentrations were related to PSA changes over time. Results The population PK model adequately described observed data in all compartments (based on visual inspection of goodness-of-fit plots) with adequate precision of parameters estimates (

Abstract Background Steps have been taken by pharmaceutical companies to obtain marketing authorisation of PSMA ligands in the European Union. Since December 2022, Locametz® (PSMA-11, gozetotide) is licensed as kit for manual radiolabelling with gallium-68 and commercially available since mid-2023. The Summary of Product Characteristic (SmPC) describes manual radiolabelling with a maximum activity after radiolabelling of 1369 MBq. We aimed for radiolabelling with a higher activity to increase production efficiency, and thus, automated radiolabelling is strongly preferred over manual radiolabelling to reduce radiation exposure to personnel. The aim of this study was to develop and validate a method for automated radiolabelling of the Locametz® kit using ~ 2000 MBq of gallium-68 eluate for radiolabelling. Results Automated radiolabelling of [68Ga]Ga-PSMA-11 using the Locametz® kit provided a product which complies to the Ph. Eur., had a shelf-life of 6 h at room temperature, and theoretically reduced radiation exposure 5.7 times. Radiolabelling with one and two generator(s) resulted in a radiochemical yield of 91–102% and 96–101% after preparation, respectively. The radiochemical purity ranged from 98.0 to 99.6% for radiolabelling with one generator and ranged from 98.4 to 99.3% for radiolabelling with two generators with similar stability. The activity of the final product was much higher when using two generators, 1961–2035 MBq compared to 740–1260 MBq, which leads to ~ 1.5 times more patient syringes available per preparation. Conclusion Automated radiolabelling of [68Ga]Ga-PSMA-11 using the Locametz® kit with higher gallium-68 activity than specified in the SmPC results in a product that is in compliance with the Ph. Eur. monograph and has a shelf-life of 6 h at room temperature. Radiolabelling with two generators proved possible and resulted in a product with similar quality but with much higher efficiency.

Abstract Introduction Severe immune‐related adverse events (irAEs) due to immune checkpoint inhibitors (ICIs) can lead to admission to the intensive care unit (ICU). In this retrospective study, we determined the incidence, treatment patterns and survival outcomes of this patient population at a comprehensive cancer center. Methods All patients admitted to the ICU due to irAEs from ICI treatment between January 2015 and July 2022 were included. Descriptive statistics were reported on patient characteristics and treatment patterns during hospital admission. Overall survival (OS) from the time of ICU discharge to death was estimated using the Kaplan–Meier method. Results Over the study period, 5561 patients received at least one ICI administration, of which 32 patients (0.6%) were admitted to the ICU due to irAEs. Twenty patients were treated with anti‐PD‐1 plus anti‐CTLA‐4 treatment, whereas 12 patients were treated with ICI monotherapy. The type of irAEs were de novo diabetes‐related ketoacidosis (n = 8), immune‐related gastrointestinal toxicity (n = 8), myocarditis or myositis (n = 10), nephritis (n = 3), pneumonitis (n = 2), and myelitis (n = 1). The median duration of ICU admission was 3 days (interquartile range: 2–6 days). Three patients died during ICU admission. The median OS of the patients who were discharged from the ICU was 18 months (95% confidence interval, 5.0—NA). Conclusion The incidence of irAEs leading to ICU admission in patients treated with ICI was low in this study. ICU mortality due to irAEs was low and a subset of this patient population even had long‐term survival.

IKZF1-deletions occur in 10-15% of patients with B-cell precursor acute lymphoblastic leukemia (BCP-ALL) and predict a poor outcome. However, the impact of IKZF1-loss on sensitivity to drugs used in contemporary treatment protocols has remained underexplored. Here we show in experimental models and in patients that loss of IKZF1 promotes resistance to AraC, a key component of both upfront and relapsed treatment protocols. We attribute this resistance, in part, to diminished import and incorporation of cytarabine (AraC) due to reduced expression of the solute carrier hENT1. Moreover, we find elevated mRNA expression of Evi1, a known driver of therapy resistance in myeloid malignancies. Finally, a kinase directed CRISPR/Cas9-screen identified that inhibition of either mediator kinases CDK8/19 or casein kinase 2 can restore response to AraC. We conclude that this high-risk patient group could benefit from alternative antimetabolites, or targeted therapies that resensitize the cells to AraC.

Abstract Limited information is available concerning infant exposure and safety when breastfed by mothers receiving chemotherapy. Whereas defining distribution to breast milk is important to infer drug exposure, infant pharmacokinetics also determine to what extent the infant will be exposed to potential toxic effects. We aimed to assess the impact of chemotherapy containing breast milk on infants by predicting systemic and local (intestinal) exposure of paclitaxel and doxorubicin in infants through breast milk using a physiologically‐based pharmacokinetic (PBPK) approach. Whole‐body PBPK models of i.v. paclitaxel and doxorubicin were extended from the literature, with an oral absorption component to enable predictions in infants receiving paclitaxel or doxorubicin‐containing breast milk. For safety considerations, worst‐case scenarios were explored. Finally, paclitaxel and doxorubicin exposures in plasma and intestinal tissue of infants following feeding of breast milk from paclitaxel‐ or doxorubicin‐treated mothers were simulated and breast milk discarding strategies were evaluated. The upper 95th percentile of the predicted peak concentrations in peripheral venous blood were 3.48 and 0.74 nM (0.4%–1.7% and 0.1%–1.8% of on‐treatment) for paclitaxel and doxorubicin, respectively. Intestinal exposure reached peak concentrations of 1.0 and 140 μM for paclitaxel and doxorubicin, respectively. Discarding breast milk for the first 3 days after maternal chemotherapy administration reduced systemic and tissue exposures even further, to over 90% and 80% for paclitaxel and doxorubicin, respectively. PBPK simulations of chemotherapy exposure in infants after breastfeeding with chemotherapy containing breast milk suggest that particularly local gastrointestinal adverse events should be monitored, whereas systemic adverse events are not expected.

Abstract The traditional design of food‐effect studies has a high patient burden for toxic drugs with long half‐lives (e.g., anticancer agents). Microtracers could be used to assess food‐effect in patients without influencing their ongoing treatment. The feasibility of a microtracer food‐effect study during steady‐state of the therapeutic drug was investigated in an in silico simulation study with alectinib as an example for a relative toxic drug with a long half‐life. Microtracer pharmacokinetics were simulated based on a previously published population pharmacokinetic model and used for estimation of a model with and a model without food as a covariate on oral bioavailability of alectinib (assuming a 40% food‐effect). Power was defined as the fraction of clinical trials where a significant (p

Aquatic invertebrates are often used as indicator species for water quality. Aquatic invertebrates were collected and identified at a protected reserve for 30+ years and at a newly restored site, previously developed as a golf course. Dissolved oxygen and salinity measurements were also taken. Results show that salinity has a stronger influence on species communities than restored state.

BackgroundWith the current treatment options for visceral leishmaniasis (VL), recrudescence of the parasite is seen in a proportion of patients. Understanding parasite dynamics is crucial to improving treatment efficacy and predicting patient relapse in cases of VL. This study aimed to characterize the kinetics of circulating Leishmania parasites in the blood, during and after different antileishmanial therapies, and to find predictors for clinical relapse of disease.MethodsData from three clinical trials, in which Eastern African VL patients received various antileishmanial regimens, were combined in this study. Leishmania kinetoplast DNA was quantified in whole blood with real-time quantitative PCR (qPCR) before, during, and up to six months after treatment. An integrated population pharmacokinetic-pharmacodynamic model was developed using non-linear mixed effects modelling.ResultsParasite proliferation was best described by an exponential growth model, with an in vivo parasite doubling time of 7.8 days (RSE 12%). Parasite killing by fexinidazole, liposomal amphotericin B, sodium stibogluconate, and miltefosine was best described by linear models directly relating drug concentrations to the parasite elimination rate. After treatment, parasite growth was assumed to be suppressed by the host immune system, described by an Emax model driven by the time after treatment. No predictors for the high variability in onset and magnitude of the immune response could be identified. Model-based individual predictions of blood parasite load on Day 28 and Day 56 after start of treatment were predictive for clinical relapse of disease.ConclusionThis semi-mechanistic pharmacokinetic-pharmacodynamic model adequately captured the blood parasite dynamics during and after treatment, and revealed that high blood parasite loads on Day 28 and Day 56 after start of treatment are an early indication for VL relapse, which could be a useful biomarker to assess treatment efficacy of a treatment regimen in a clinical trial setting.