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Voriconazole is among the first-line antifungal drugs to treat invasive fungal infections in children and known for its pronounced inter- and intraindividual pharmacokinetic variability. Polymorphisms in genes involved in the metabolism and transport of voriconazole are thought to influence serum concentrations and eventually the therapeutic outcome. To investigate the impact of these genetic variants and other covariates on voriconazole trough concentrations, we performed a retrospective data analysis, where we used medication data from 36 children suffering from invasive fungal infections treated with voriconazole. Data were extracted from clinical information systems with the new infrastructure SwissPK(cdw), and linear mixed effects modelling was performed using R. Samples from 23 children were available for DNA extraction, from which 12 selected polymorphism were genotyped by real-time PCR. 192 (49.1%) of 391 trough serum concentrations measured were outside the recommended range. Voriconazole trough concentrations were influenced by polymorphisms within the metabolizing enzymes CYP2C19 and CYP3A4, and within the drug transporters ABCC2 and ABCG2, as well as by the co-medications ciprofloxacin, levetiracetam, and propranolol. In order to prescribe an optimal drug dosage, pre-emptive pharmacogenetic testing and careful consideration of co-medications in addition to therapeutic drug monitoring might improve voriconazole treatment outcome of children with invasive fungal infections., Pharmaceutics, 14 (6)

Clinical trials have been performed mainly in adults and accordingly the necessary information is lacking for pediatric patients, especially regarding dosage recommendation for approved drugs. This gap in information could be filled with results from pharmacokinetic (PK) modeling, based on data collected in daily clinical routine. In order to make this data accessible and usable for research, the Swiss Pharmacokinetics Clinical Data Warehouse (SwissPK(cdw)) project has been set up, including a clinical data warehouse (CDW) and the regulatory framework for data transfer and use within. Embedded into the secure BioMedIT network, the CDW can connect to various data providers and researchers in order to collaborate on the data securely. Due to its modularity, partially containerized deployment and open-source software, each of the components can be extended, modified, and re-used for similar projects that require integrated data management, data analysis, and web tools in a secure scientific data and information technology (IT) environment. Here, we describe a collaborative and interprofessional effort to implement the aforementioned infrastructure between several partners from medical health care and academia. Furthermore, we describe a real-world use case where blood samples from pediatric patients were analyzed for the presence of genetic polymorphisms and the results were aggregated and further analyzed together with the health-related patient data in the SwissPK(cdw)., CPT: Pharmacometrics and Systems Pharmacology, 10 (12), ISSN:2163-8306

Chiara Jeiziner,1 Samuel S Allemann,1 Kurt E Hersberger,1 Henriette E Meyer zu Schwabedissen2 1Pharmaceutical Care Research Group, Department Pharmaceutical Sciences, University of Basel, Basel, Switzerland; 2Biopharmacy, Department Pharmaceutical Sciences, University of Basel, Basel, SwitzerlandCorrespondence: Chiara Jeiziner, Pharmaceutical Care Research Group, Department Pharmaceutical Sciences, University of Basel, Klingelbergstrasse 50, Basel, 4056, Switzerland, Tel +41 61 207 61 80, Email chiara.jeiziner@unibas.chPurpose: Pharmacogenetic (PGx) panel testing could help to determine the heritable component of a rheumatoid arthritis (RA) patient’s susceptibility for therapy failure and/or adverse drug reactions (ADRs) from methotrexate (MTX). Considering the literature mentioning the potential applicability of PGx panel testing within MTX regimens, we discuss the case of a patient who was treated with MTX, suffered from ADRs, and obtained a reactive PGx panel testing.Genotyping: We used a commercial PGx panel test involving the ABC-transporters P-glycoprotein (P-gp; gene: ABCB1), and breast cancer resistance protein (BCRP; gene: ABCG2), the solute carriers reduced folate carrier 1 (RFC1; gene: SLC19A1), and organic anion transporting polypeptide 1B1 (OATP1B1; gene: SLCO1B1), and the enzymes inosine triphosphatase (ITPA), and glutathione transferase P1 (GSTP1). In addition, we genotyped the patient for the enzymes 5-aminoimidazole-4-carboxamide ribonucleotide formyltransferase (AICAR)/inosine monophosphate (IMP) cyclohydrolase (gene name: ATIC), gamma-glutamyl hydrolase (gene name: GGH) and methylenetetrahydrofolate reductase (gene name: MTHFR).Results: The PGx profile of the patient revealed genetic variants in SLC19A1, ABCB1, and MTHFR, which may explain the ADRs experienced during the treatment with MTX and a potentially lower efficacy of MTX. Based on our interpretation of the PGx profile, we recommended the patient to avoid MTX in the future.Conclusion: The MTX pathway is complex, which makes the interpretation of genetic variants affecting metabolism challenging. A reactive PGx panel test was applicable to explain ADRs experienced during MTX treatment for a patient with RA. However, the clinical utility of PGx-guided MTX treatment in a primary care setting is still limited. In order to base a recommendation for MTX on PGx data, we need genome-wide association studies, large prospective multicenter studies and PGx studies, which analyze different multi-gene haplotypes and gene-drug-drug interactions for MTX.Keywords: pharmacogenetics, PGx, ABCB1, SLC19A1, MTHFR, rheumatoid arthritis, methotrexate, MTX

ACT-1004-1239 is a potent, selective, first-in-class CXCR7 antagonist, which shows a favorable preclinical and clinical profile. Here we report the metabolites and the metabolic pathways of ACT-1004-1239 identified using results from in vitro and in vivo studies. Two complementary in vitro studies (incubation with human liver microsomes in the absence/presence of cytochrome P450- [CYP] specific chemical inhibitors and incubation with recombinant CYPs) were conducted to identify CYPs involved in ACT-1004-1239 metabolism. For the in vivo investigations, a microtracer approach was integrated in the first-in-human study to assess mass balance and absorption, distribution, metabolism, and excretion (ADME) characteristics of ACT-1004-1239. Six healthy male subjects received orally 100 mg non-radioactive ACT-1004-1239 together with 1 μCi 14C-ACT-1004-1239. Plasma, urine, and feces samples were collected up to 240 h post-dose and 14C-drug-related material was measured with accelerator mass spectrometry. This technique was also used to construct radiochromatograms of pooled human samples. Metabolite structure elucidation of human-relevant metabolites was performed using high performance liquid chromatography coupled with high resolution mass spectrometry and facilitated by the use of rat samples. CYP3A4 was identified as the major CYP catalyzing the formation of M1 in vitro. In humans, the cumulative recovery from urine and feces was 84.1% of the dose with the majority being eliminated via the feces (69.6%) and the rest via the urine (14.5%). In human plasma, two major circulating metabolites were identified, i.e., M1 and M23. Elimination via M1 was the only elimination pathway that contributed to ≥25% of ACT-1004-1239 elimination. M1 was identified as a secondary amine metabolite following oxidative N-dealkylation of the parent. M23 was identified as a difluorophenyl isoxazole carboxylic acid metabolite following central amide bond hydrolysis of the parent. Other metabolites observed in humans were A1, A2, and A3. Metabolite A1 was identified as an analog of M1 after oxidative defluorination, whereas both, A2 and A3, were identified as a reduced analog of M1 and parent, respectively, after addition of two hydrogen atoms at the isoxazole ring. In conclusion, CYP3A4 contributes to a relevant extent to ACT-1004-1239 disposition and two major circulating metabolites were observed in humans.Clinical Trial Registration: (https://clinicaltrials.gov/ct2/show/NCT03869320) ClinicalTrials.gov Identifier NCT03869320.