Dried blood spot analysis:facing new challenges

Over the last decade, DBS analysis has gained popularity for TDM because it’s a patient friendly sampling proce- dure [1-4]. Additional advantages are prolonged sample stability, lower risk of infections and transportation at ambient temperature [1-3,5]. These advantages may fa- cilitate implementation of TDM in different clinical set- tings including resource limited areas. Patients will bene- fit from DBS analysis but the analytical development and validation of DBS methods is more complex compared to plasma or serum analysis. Additional validation parameters, like the effect of the hematocrit (HT) and blood spot volume need to be eval- uated. Drug substances may also interact with the blood matrix or with the DBS card, resulting in matrix related recovery effects. Unfortunately, official guidelines for val- idation of DBS are not available yet. However, in recent literature, several interesting issues related to analytical DBS research have been discussed [1,6-12]. Ongoing re- search and improved understanding of the factors that influence DBS analysis results will ultimately result in well-founded guidelines for DBS analytical method val- idation. This would be very helpful for daily practice but would also benefit patient safety because uniformity in method validation prevents potential pitfalls during val- idation or method development and increase credibility of assay results. Our aim is to discuss some relevant topics related to DBS development prior to development of future guidelines on DBS development and validation

User Acceptability and Technical Robustness Evaluation of a Novel Smart Pill Bottle Prototype Designed to Support Medication Adherence

Purpose: Smart medication adherence monitoring devices can provide objective and granular drug utilization data and help patients engaging with their treatment. In this proof-of-concept study, the acceptability and technical robustness of a novel smart pill bottle prototype (SPBP) were assessed in order to allow further optimization. Methods: The SPBP is an app-controlled automatic dispense system, capturing real-time data on a web-based platform, which sends text reminders and measures storage conditions. A heterogeneous group of ten volunteers was asked to dispense placebo capsules with the SPBP and to follow a predefined dosing schedule for a trial period of 2 weeks. Afterwards, a questionnaire was filled out during a short interview. Primary outcome was dispense adherence as measured by the bottle. Other study outcomes included system acceptability (System Usability Scale [SUS]), self-reported adherence (MARS) and technical robustness of the bottle’s mechanics (electronic pill dispenser) and sensors (bottle temperature). Results: The overall dispense adherence rate as measured by the SPBP was 88%. All participants completed the study and four participants had an adherence rate of 100% during the study. The dispense adherence rates corresponded well with participants’ self-reported adherence with an average MARS total score of 23.6 (out of 25). Participants judged the system easy to use, with a mean SUS score of 79.3 (range: 57.5– 97.5). The overall mean temperature difference between the bottle sensor and calibrated external sensor was − 0.82°C (range: − 1.37°C to − 0.21°C). Conclusion: The SPBP was well accepted and this study provides data for further optimization and follow-up studies. Smart adherence technologies such as these may change the way healthcare professionals, trialists and patients manage medication adherence

Treatment of High Dose Methotrexate Toxicity with Glucarpidase

High Dose Methotrexate (HD-MTX) toxicity can cause renal dysfunction in patients due to a presence of risk factors such as body mass index >25 kg/m2, comedication (salicylates, NSAID`s, sulfonamides, beta-lactam antibiotics, aminoglycosides), urine pH<7, iv fluid intake <3 l/m2/24 hours, hepatic dysfunction, renal insufficiency prior to HD-MTX, diarrhea and pleural effusions. To prevent renal dysfunction and further MTX toxicity Glucarpidase can be used which degrades MTX to its metabolites. Cases: A 17 year-old and a 14 year-old boy were treated with HD-MTX, developed renal insufficiency and were treated with Glucarpidase. In both patients unexpected renal dysfunction was seen still 3-4 weeks after treatment with Glucarpidase. A theoretic concern regarding the use of Glucarpidase is that the rapid formation of MTX metabolite called DAMPA, which is almost 10-fold less soluble than MTX, may lead to further renal toxicity by precipitation in the renal tubules. If we compare our patient data with data we found in the literature there is almost no difference in renal dysfunction duration between patients who got Glucarpidase (21 days) and those with only supportive therapy (19 and 12 days). After treatment with Glucarpidase the question on how and when to restart HDMTX therapy raised. The safe option for our two patients would be first a rechallange with 50-75% HD-MTX after a full recovery of the renal function. After the first rechallange kindey function and MTX levels should be closely monitored and if no problems are observed the second rechallange should be with 100% HD-MTX. If we closely look at our data and available data from the published articles there is a concern on how effective and safe Glucarpidase is. Glucarpidase should be given only in cases if supportive therapy is not effective enough in lowering MTX plasma levels. Even then, health care professionals should use Glucarpidase cautiously because of its uncertain benefits unpredictable side effect

Gentamicin Administration in Dialysis Patients:Before or After Hemodialysis?

BACKGROUND: Gentamicin is used to treat severe infections and has a small therapeutic window. This study aimed to optimize the dosing strategy of gentamicin in intermittently hemodialyzed patients by simulating concentration/time profiles during pre- and post-dialysis dosing, based on a published pharmacokinetic model.METHODS: Pharmacokinetic simulations were performed with virtual patients, including septic patients, who were treated with gentamicin and received weekly hemodialysis with an interval of 48h-48h-72h. The following dosing regimens were simulated: for non-septic patients, 5 mg/kg gentamicin was given 1h/2h before dialysis, or a starting dose of 2.5 mg/kg and a maintenance dose of 1.5 mg/kg immediately after dialysis; for septic patients, 6 mg/kg gentamicin was given 1h/2h before dialysis, or a starting dose of 3 mg/kg and a maintenance dose of 1.8 mg/kg immediately after dialysis. The mean Cmax, AUC24h, and target attainment (TA) of pharmacodynamic targets were calculated and compared. The following targets were adopted from literature: Cmax &gt;8 mg/L and &lt;20 mg/L and AUC24h &gt;70 mg·h/L and &lt;120 mg·h/L.RESULTS: In non-septic patients, postdialysis dosing resulted in a TA of 35% for Cmax &gt;8 mg/L, 100% for &lt;20 mg/L and AUC24h &gt;70 mg·h/L, and 45% for &lt;120 mg·h/L. Dosing 2h prior to dialysis resulted in a TA of 100% for Cmax&gt; 8 mg/L, 40% for &lt;20 mg/L, 65% for AUC24h &gt;70 mg·h/L, and 77% for &lt;120 mg·h/L. Simulations of septic patients resulted in comparable outcomes with higher TAs for Cmax &lt;20 mg/L (96%), AUC24h &gt;70 mg·h/L (90%), and &lt;120 mg·h/L (53%) for dosing 1h prior to dialysis.CONCLUSIONS: Postdialysis dosing resulted in a low TA of Cmax &gt;8 mg/L; however, predialysis dosing ensured a high TA of Cmax &gt;8 mg/L and acceptable TA of Cmax &lt;20 mg/L, AUC24h &gt;70 mg·h/L, and &lt;120 mg·h/L, which could increase the efficacy of gentamicin. Therefore, clinicians should consider predialysis dosing of gentamicin in patients undergoing intermittent hemodialysis.</p

Cobicistat as a Potential Booster of Ponatinib and Dasatinib Exposure in a CML Patient:A Case Study

The authors present a case of a 57-year-old patient with chronic myeloid leukemia who was treated with ponatinib and subsequently treated with dasatinib. The patient showed a major molecular response; however, the BCR-ABL1 signal increased with low ponatinib and dasatinib trough concentrations. Cobicistat was used as a pharmacokinetic booster to increase ponatinib and dasatinib exposure, as opposed to increasing the dose. However, ponatinib exposure was not sufficiently increased by cobicistat. The peak dasatinib concentration was successfully increased with cobicistat treatment. Dasatinib and cobicistat cotreatment induced a response in BCR-ABL1 PCR signal, was well tolerated, and led to a substantial reduction in drug costs.</p

Sertraline, citalopram and paroxetine in lactation: passage into breastmilk and infant exposure

ObjectivesThis study aimed to investigate the plasma and breastmilk concentrations for sertraline, citalopram and paroxetine for assessment of the Milk/Plasma (M/P) ratio and Absolute Infant Dose (AID), and to determine actual infant drug exposure through breastfeeding. Subsequently, informed recommendations will be formulated regarding the advisability of breastfeeding in women undergoing treatment with the three most widely used antidepressants.MethodsA pharmacokinetic study in lactating women and their infants using sertraline, citalopram or paroxetine was performed. Paired breastmilk and plasma samples and single point infant plasma samples were collected to determine antidepressant concentrations. An Area Under the Curve (AUC) based approach with the trapezoidal rule was used to calculate M/P ratios and AID for all three antidepressants by combining all measured concentrations for the same dose.ResultsThirty-seven lactating women and their infants participated in this study. 111 paired breastmilk and plasma samples and 37 single point infant plasma samples were collected. Detectable concentrations of sertraline, citalopram and paroxetine were present in all breastmilk samples. For sertraline and citalopram M/P ratio is above one, indicating higher breastmilk than plasma concentrations, however, drug exposure by breastmilk did not lead to detectable plasma drug levels in any of the 15 infants for sertraline, for nine (out of 13) infants for citalopram and for eight (out of nine) infants for paroxetine.ConclusionGiven the well-known benefits of breastfeeding, our findings support breastfeeding of infants by mothers who are taking sertraline, citalopram or paroxetine is safe. Sertraline and paroxetine are the preferred antidepressants during breastfeeding, reaching mostly undetectable infant drug levels

Managing intoxications with nicotine-containing e-liquids

INTRODUCTION: Nicotine is an addictive and poisonous agent. The recent development of e-cigarettes has caused a new demand for highly concentrated nicotine-containing solutions. These concentrated nicotine solutions have also increased the risk of nicotine overdoses. AREAS COVERED: Essential factors for nicotine exposure are the concentration of the nicotine-containing e-liquid solution and its pharmacokinetics. Liquid nicotine refills contain nicotine in varying concentrations, which vary widely between and within products. The pharmacokinetics of nicotine are dependent on the route of administration, renal/hepatic clearance and urinary pH. The dose is another essential determinant of nicotine exposure. There is a considerable discrepancy between the generally accepted lethal dose and symptoms reported in case studies. Ingested doses correlate poorly to clinical symptoms. Symptoms of liquid nicotine toxicity vary from mild to severe between patients and are the result of overstimulation of nicotinic acetylcholine receptors, which may lead to fatal respiratory failure and cardiovascular collapse. EXPERT OPINION: The literature on nicotine-containing e-liquid intoxications originating from vaping device refills are mainly case reports. Based on these case reports, we propose a treatment plan which is primarily symptomatic. Research should focus on providing insight on its toxicity, based on oral and transdermal pharmacokinetics and on toxicodynamics

Pharmacokinetic Modeling of Hydrocortisone by Including Protein Binding to Corticosteroid-Binding Globulin

BACKGROUND: Patients with adrenal insufficiency are treated with oral hydrocortisone (HC) to compensate for the loss of endogenous cortisol production. Intrinsic imperfections of cortisol replacement strategies in mimicking normal cortisol secretion are the underlying cause of the increased morbidity and mortality of patients suffering from secondary adrenal insufficiency (SAI). To improve oral hydrocortisone substitution therapy, a better understanding of its pharmacokinetics (PK) is necessary. The previous PK model did not include protein binding. It is known that protein binding can impact hydrocortisone pharmacokinetics. The aim of this study is to describe HC pharmacokinetics including the protein-binding state using Edsim++ (Mediware, Prague) pharmacokinetic modeling software, paving the way for an in-silico tool suitable for drug delivery design. METHODS: A total of 46 patients with SAI participated in a randomized double-blind crossover study Patients randomly received a low dose of HC (0.2-0.3 mg/kg body weight/day) for 10 weeks, followed by a high dose (0.4-0.6 mg/kg body weight/day) for another 10 weeks, or vice versa. Plasma samples were obtained and analyzed for free and total hydrocortisone. Single compartment population pharmacokinetic analysis was performed using an extended Werumeus-Buning model built in Edsim++. This model includes a mathematical approach for estimating free cortisol by Nguyen et al., taking the protein binding of HC to albumin and hydrocortisone-binding globulin (CBG, transcortin) into consideration, as well as different states of CBG which affect binding kinetics to HC. The goodness of fit for observed versus predicted values was calculated. RESULTS AND CONCLUSIONS: Nguyen's formula for free cortisol estimation was successfully implemented in a pharmacokinetic model. The model shows high Spearman's correlation for observed versus predicted hydrocortisone concentrations. Significantly higher correlations (Spearman's r, 0.901 vs. 0.836) between total and free hydrocortisone AUC24 (area-under the curve over 24 h) are found when comparing new and old models. This new model was used to simulate the plasma concentration-time behavior of a more suitable hydrocortisone formulation