Frequency and component analysis of contaminants generated in preparation of anticancer agents using closed system drug transfer devices (CSTDs)

Occupational exposure of anticancer agents during their preparation has been recognized as a serious hazard. Closed system drug transfer devices (CSTDs) enable “safe” preparation of agents for medical personnel and ensure a safe hospital environment. However, artificial particles of infusion materials have been reported during CSTD use. Here, the incidence of insoluble fine particles during preparation of anticancer agents using CSTDs was examined. Visible insoluble fine particles were found in 465 (9.4%) of 4948 treatment cases at Ehime University Hospital with CSTD use. Contaminants occurred more frequently during preparation of monoclonal antibodies than cytotoxic anticancer agents (19.4% vs. 4.1%, respectively, P < 0.01). A similar survey was conducted at nine hospitals to investigate the incidence of insoluble fine particles with or without CSTDs. Insoluble fine particles were detected in 113 (15.4%) of 732 treatment cases during preparation of monoclonal antibodies with CSTD use. In contrast, the occurrence of insoluble fine particles without CSTDs was found in only 3 (0.073%) of 4113 treatment cases. Contamination with CSTDs might cause harmful effects on patients during cancer therapy. We strongly recommend the use of in-line filters combined with infusion routes after CSTD use to avoid contamination-associated adverse events.

A novel paclitaxel coated balloon with increased drug transfer for treatment of complex vascular lesions

Background Drug coated balloons (DCB) with paclitaxel (Ptx) dose of 2–3.5 μg/mm2 balloon surface inhibit restenosis with different effectiveness and duration of success. A clinical dose finding study is not known for any of the currently marketed products. The aim of the present preclinical trial was to investigate a novel DCB coated with 6 μg Ptx/mm2 in a porcine model. Methods and results The current study investigated a DCB with a novel, modified iopromide based matrix with 6 μg Ptx/mm2. Drug transfer to the vessel wall of peripheral arteries was compared with a dose of 3 μg Ptx/mm2 and two fully overlapping DCB with 3 μg Ptx/mm2, each. Ptx concentration in the vessel wall after drug transfer was about twice as high for balloons with 6 μg/mm2 (1957±1472 μg/g) and two overlapping DCB with 3 μg Ptx/mm2, each (1287±619 μg/g) compared to a single balloon with 3 μg Ptx/mm2, (787±738 μg/g), with statistical significant differences for 1x6 μg/mm2 vs. 1x3 μg/mm2 (p = 0.017) but not for 2x3 μg/mm2 vs. 1x3 μg/mm2 (p = 0.184) and 1x6 μg/mm2 vs. 2x3 μg/mm2 (p = 0.178). The proportion of residual Ptx on balloon after treatment was similar for all groups between 6±1% and 10±3% of dose on balloon. Conclusion The dose of 6 μg Ptx/mm2 was successfully as well as reproducibly coated on conventional balloon catheters. Increased Ptx on balloons resulted in increased drug concentration in the vessel wall. A single balloon with 6 μg Ptx/mm2 seems to provide double dose compared to 3 μg Ptx/mm2, facilitates the procedure, and may reduce medico-economic cost compared to the use of two standard DCB.

Mechanistic Modeling of Placental Drug Transfer in Humans: How Do Differences in Maternal/Fetal Fraction of Unbound Drug and Placental Influx/Efflux Transfer Rates Affect Fetal Pharmacokinetics?

Background: While physiologically based pharmacokinetic (PBPK) models generally predict pharmacokinetics in pregnant women successfully, the confidence in predicting fetal pharmacokinetics is limited because many parameters affecting placental drug transfer have not been mechanistically accounted for.Objectives: The objectives of this study were to implement different maternal and fetal unbound drug fractions in a PBPK framework; to predict fetal pharmacokinetics of eight drugs in the third trimester; and to quantitatively investigate how alterations in various model parameters affect predicted fetal pharmacokinetics.Methods: The ordinary differential equations of previously developed pregnancy PBPK models for eight drugs (acyclovir, cefuroxime, diazepam, dolutegravir, emtricitabine, metronidazole, ondansetron, and raltegravir) were amended to account for different unbound drug fractions in mother and fetus. Local sensitivity analyses were conducted for various parameters relevant to placental drug transfer, including influx/efflux transfer clearances across the apical and basolateral membrane of the trophoblasts.Results: For the highly-protein bound drugs diazepam, dolutegravir and ondansetron, the lower fraction unbound in the fetus vs. mother affected predicted pharmacokinetics in the umbilical vein by ≥10%. Metronidazole displayed blood flow-limited distribution across the placenta. For all drugs, umbilical vein concentrations were highly sensitive to changes in the apical influx/efflux transfer clearance ratio. Additionally, transfer clearance across the basolateral membrane was a critical parameter for cefuroxime and ondansetron.Conclusion: In healthy pregnancies, differential protein binding characteristics in mother and fetus give rise to minor differences in maternal-fetal drug exposure. Further studies are needed to differentiate passive and active transfer processes across the apical and basolateral trophoblast membrane.

Mechanistic Coupling of a Novel in silico Cotyledon Perfusion Model and a Physiologically Based Pharmacokinetic Model to Predict Fetal Acetaminophen Pharmacokinetics at Delivery

Little is known about placental drug transfer and fetal pharmacokinetics despite increasing drug use in pregnant women. While physiologically based pharmacokinetic (PBPK) models can help in some cases to shed light on this knowledge gap, adequate parameterization of placental drug transfer remains challenging. A novel in silico model with seven compartments representing the ex vivo cotyledon perfusion assay was developed and used to describe placental transfer and fetal pharmacokinetics of acetaminophen. Unknown parameters were optimized using observed data. Thereafter, values of relevant model parameters were copied to a maternal-fetal PBPK model and acetaminophen pharmacokinetics were predicted at delivery after oral administration of 1,000 mg. Predictions in the umbilical vein were evaluated with data from two clinical studies. Simulations from the in silico cotyledon perfusion model indicated that acetaminophen accumulates in the trophoblasts; simulated steady state concentrations in the trophoblasts were 4.31-fold higher than those in the perfusate. The whole-body PBPK model predicted umbilical vein concentrations with a mean prediction error of 24.7%. Of the 62 concentration values reported in the clinical studies, 50 values (81%) were predicted within a 2-fold error range. In conclusion, this study presents a novel in silico cotyledon perfusion model that is structurally congruent with the placenta implemented in our maternal-fetal PBPK model. This allows transferring parameters from the former model into our PBPK model for mechanistically exploring whole-body pharmacokinetics and concentration-effect relationships in the placental tissue. Further studies should investigate acetaminophen accumulation and metabolism in the placenta as the former might potentially affect placental prostaglandin synthesis and subsequent fetal exposure.

Effectiveness of Closed System Drug Transfer Devices in Reducing Leakage during Antineoplastic Drugs Compounding

This study, conducted in a centralized cytotoxic drug preparation unit, analyzes the effectiveness of two closed system drug transfer devices (CSTDs) in reducing leakage during antineoplastic drug compounding. Wipe/pad samplings inside and outside the preparation area were taken during surveillance programs from 2016 to 2021. All samples were analyzed for gemcitabine (GEM) contamination. In 2016, the presence of GEM in some samples and the contamination of the operators’ gloves in the absence of apparent drug spilling suggested unsealed preparation systems. In subsequent monitoring, GEM was also evaluated in the vial access device and in the access port system to the intravenous therapy bag of TexiumTM/SmartSiteTM and Equashield® II devices after the reconstitution and preparation steps of the drug. The next checks highlighted GEM dispersion after compounding using TexiumTM/SmartSiteTM, with positive samples ranging from 9 to 23%. In contrast, gemcitabine was not present at detectable levels in the Equashield® II system in all of the evaluated samples. The Equashield® II closed system seems effectively able to eliminate spills and leakage during gemcitabine compounding. Since drugs with different viscosities can have different effects on CSTDs, Equashield® II needs to be considered with other antineoplastic drugs during a structured surveillance program.

A Machine Learning Model to Predict Drug Transfer Across the Human Placenta Barrier

The development of computational models for assessing the transfer of chemicals across the placental membrane would be of the utmost importance in drug discovery campaigns, in order to develop safe therapeutic options. We have developed a low-dimensional machine learning model capable of classifying compounds according to whether they can cross or not the placental barrier. To this aim, we compiled a database of 248 compounds with experimental information about their placental transfer, characterizing each compound with a set of ∼5.4 thousand descriptors, including physicochemical properties and structural features. We evaluated different machine learning classifiers and implemented a genetic algorithm, in a five cross validation scheme, to perform feature selection. The optimization was guided towards models displaying a low number of false positives (molecules that actually cross the placental barrier, but are predicted as not crossing it). A Linear Discriminant Analysis model trained with only four structural features resulted to be robust for this task, exhibiting only one false positive case across all testing folds. This model is expected to be useful in predicting placental drug transfer during pregnancy, and thus could be used as a filter for chemical libraries in virtual screening campaigns.