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Frequency of Potentially Dangerous Prescribing of the Combinations of Medicinal Products in Senile Patients
Posters Many patients being treated with aripiprazole are either nonresponders or suffer adverse reactions. This high variability can be caused by genetic polymorphisms. We evaluated the influence of CYP2D6, CYP3A4, CYP3A5 and ABCB1 polymorphisms in the pharmacokinetic and safety of aripiprazole and its active metabolite (dehydro-aripiprazole). Methods: 148 volunteers from 6 bioequivalence studies. The plasma concentrations of aripiprazole (N= 145) and dehydroaripiprazole (N= 45) were measured by HPLC/MS/MS. The volunteers were genotyped for: CYP2D6 (*3,*4,*5,*6,*7,*9 and copy number variations), CYP3A4*20, CYP3A4*22, CYP3A5*3 and C3435T in ABCB1 gene. Reported adverse events were registered. Statistical analysis was performed with SPSS 15.0. Study was approved by local Research Ethics Committee and all subjects signed an informed consent. Results: Pharmacokinetic parameters were influenced by CYP2D6 phenotype, as the number of active alleles decreased, AUC, Cmax and t1/2 of aripiprazole were higher and clearance of aripiprazole, AUC of dehydro-aripiprazole and ratio dehydro-aripiprazole/aripiprazole were lower. CYP3A4 genotype influenced dehydro-aripiprazole AUC, since *1/*1 subjects had higher values. Subjects that were CYP3A5expressers had higher values of AUC and Cmax in the sum of aripiprazole and dehydro-aripiprazole. T carriers of C3435T polymorphism had higher values of AUC and Cmax in the sum of aripiprazole and dehydro-aripiprazole and a lower dehydro-aripiprazole/aripiprazole ratio (p= 0.031). CYP3A5 *1/*1 subjects reported neurologic adverse reactions more frequently (p= 0.017) than *3/*3. Nausea and vomits were related to CYP2D6 phenotype (p= 0.014), being more frequent in poor and intermediates metabolizers than in extensive and ultrarapids metabolizers. Conclusions: CYP2D6, CYP3A4, CYP3A5 and ABCB1 had an impact in the pharmacokinetic parameters of aripiprazole and dehydro-aripiprazole. CYP3A5 and CYP2D6 polymorphisms are also involved in occurrence of adverse reactions.
Pharmacokinetic and Pharmacodynamic Modeling and Simulation Analysis of Icure Donepezil Patch in Healthy Male Volunteers S. Kyu Yoon1; K.-S. Bae1; D. Hong2; S. Su Kim2; Y. Ho Shim2; Y. Kweon Choi2; and H.-S. Lim1 1 Department of Clinical Pharmacology and Therapeutics, College of Medicine, University of Ulsan, Asan Medical Center, Seoul, Republic of Korea; and 2iCure Pharmaceutical lncorporated, 3F Sehyun Bldg., 7, Saimdang-ro 1-gil, Seocho-gu, Seoul, Korea Background: Donepezil is a well-known reversible noncompetitive acetylcholinesterase inhibitor for the symptomatic treatment of Alzheimer’s disease. The purpose of this study was to characterize the pharmacokinetics of donepezil patch under development using mixed effect modeling analysis, and to expore optimal dosing regimens of the donepezil patch in comparison with donepezil oral formulation. Methods: PK data used in this analysis were from 60 Korean, healthy, male subjects in two Phase 1 studies, where all the subjects received single or multiple doses of donepezil patch of 43.75, 87.5, and 175 mg, and 12 of them received single oral dose of donepezil, 10 mg followed by single dose of donepezil patch. Concentrations of donepezil were measured using validated LC/MS-MS. Donepezil PK were analyzed by nonlinear mixed effect modeling implemented in NONMEM (version 7.3). Results: The PK modeling analysis were conducted seqentially for oral formulation and patch, which describes the data of oral formulation compared to simultaneous analysis of both oral and patch formulations. The final model predicted the real, observed concentration data reasonably well. The Monte-Carlo simulation for plasma
August 2017
donepezil concentration predicted that overall, exposure to plasma donepezil is similar between donepezil 10 mg oral dosing every 24 hours and donepezil patch 175 mg every 72 hours, and between donepezil 5 mg oral dosing every 24 hours and donepezil patch 87.5 mg every 72 hours Conclusions: We developed a population PK model describing the plasma PK of donepezil patch formulation and compared it with that of donepzeil oral formulation in healthy Korean adult males. PK simulation based on the final PK model suggested that donepezil 175 mg patch every 72 hours shows similar concentration profile with oral dosing of donepezil 10 mg every 24 hours, and 87.5 mg patch every 72 hours with oral dosing of 5 mg every 24 hours.
Frequency of Potentially Dangerous Prescribing of the Combinations of Medicinal Products in Senile Patients V. Nikulin1; E. Il’ina2; S. Bordovsky1; S. Gorbatenkova3; O. Bogova2; and D. Sychev2 1 I.M. Sechenov First Moscow State Medical University, Moscow, Russia; 2Russian Medical Academy of Postgraduate Education, Moscow, Russia; and 3Hospital For Wars Veterans No. 2, Moscow, Russia Background: Senile patients suffer from several kinds of nosology which cause polypharmacy. Taking a great number of drugs is connected with the risks of the adverse drug reaction (ADR) rise, which causes frequent sequels, repeated hospitalizations and the high cost treatment. AimTo analyze the prescription frequency of high-priority interactions (HPI) in senile patients with polypharmacy in the cardiology department. Methods: The analysis of 173 patient’s case history records(60 male and 113 female patients aged 85±5.31) was performed. All patients were under treatment in the cardiology department and took on average 8.810 ± 2.745 medications. Later the prescription analysis of the interactions was carried out with the help of the “Drug Interaction Checker” at www.drugs.com. Only drug interactions of “major” category were analyzed (HPI). Results: The following results were achieved: • The number of HPIs among the patients made 141 (7.79% of all) • The most frequently prescribed combinations (% of HPIs): o Anticoagulants and NSAIDs 45(32%) o ACE inhibitors and antimineralocorticoid 25(17,73%) o Concomitant prescription of 2 NSAIDs 14(9,93%) o ACE inhibitors and AT1-receptor antagonists 11(7,8%) o Antimineralocorticoids and AT1-receptor antagonists 10(7,09%) The obtained results suggest a frequent subscription of the combinations drugs with HPI. It is known that such interactions are characterized by the high risk due to the concomitant prescription which exceeds health benefits for the patient. Such combinations should be avoided. Table. Number of HPIs among the patients. Number of High-Priority Interactions 1 2 3 4 5 6
Number of Patients (% of All Patients) 46(26,59%) 16(9,25%) 10(5,78%) 2(1,156%) 2(1,156%) 2(1,156%)
Conclusions: The frequent prescribing of the combinations of drugs with HPI to the senile patients, causes ADRs and reduction of the
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Clinical Therapeutics quality of life. In order to improve the effectiveness and safety of the treatment the optimization of the pharmacotherapy by timely identifying of dangerous combinations is required.
Adverse Drug Events With Antipsychotics—A Sex Difference F.K.H. Sørup1,2; J. Hallas3; S. Brunak2; and S.E. Andersen1 1 Zealand University Hospital, Roskilde, Denmark; 2University of Copenhagen, Copenhagen, Denmark; and 3University of Southern Denmark, Odense, Denmark Background: Antipsychotics are a cornerstone in the treatment of schizophrenia. However, the treatment often results in adverse drug events (ADEs), which might be related to antipsychotic polypharmacy, high dose load or the type of antipsychotic prescribed. Little is known of which variables are most important. Methods: Data from 2240 90-day periods of stable antipsychotic treatment in 540 patients with schizophrenia from a psychiatric inpatient centre. Variables collected were age, gender, number of antipsychotics (1,2,3), total dose load (DDDs), type of antipsychotics (first generation antipsychotics (FGA), second generation antipsychotics (SGA) or combinations). The ADEs were text mined from the unstructured text of the electronic patient records by a previously developed method, finding mentioning of a drug and an adverse event within the same sentence, excluding negations, informing of the patient and mentioning of past events. The number of ADEs counted for each period. A multiple linear regression with number of ADEs as outcome was performed. Results: The only significant variable to predict ADEs with antipsychotic treatment was the sex of the patients (p= 0.00398). Subanalyses revealed that the dose was significant for women (p= 0.0387) and the number of antipsychotics for men (p= 0.026). Women got on average more ADEs (0.28 vs 0.19, P= 0.01816) on a lower dose (1.46 DDD vs 1.71 DDD, p= 0.00033) than men. Conclusions: The most prominent feature to predict ADEs with antipsychotic treatment was the sex of the patient. Women seemed more sensitive to total antipsychotic dose load and men to the number of different antipsychotics. Lower doses should be considered in women and fewer drugs in men experiencing ADEs with antipsychotic treatment.
Brown Adipose Tissue is a Putative Metformin Target P. Breining1; J.B. Jensen1; M. Busk1; S. Jakobsen1; P. Bross2; P.F. Guerra2; J. Hansen3; S.B. Pedersen1; B. Richelsen1; and N. Jessen1 1 Aarhus University Hospital, Aarhus, Denmark; 2Aarhus University, Aarhus, Denmark; and 3University of Copenhagen, Copenhagen, Denmark Background: Metformin is the most widely prescribed oral antidiabetic drug worldwide. In spite of well-documented beneficial effects on diabetes, target organs that mediate its effects remain to be established. In recent years, active brown adipose tissue (BAT) has been found in the deep neck of adult humans. Under the hypothesis that brown adipose tissue (BAT) is a metformin target tissue we investigated metformin uptake in vivo and studied the in vitro effects of metformin on cultured human brown adipocytes. Methods: Tissue-specific uptake of metformin was assessed by PET/ CT imaging after injection of [(11)C]-metformin in mice. Human brown adipose tissue was obtained from elective neck surgery and OCT expression levels in human and murine BAT were determined
e56
by qPCR. Oxygen consumption in immortalized brown adipocytes of human origin (TERT-hBA) during metformin exposure was assessed by Seahorse XF technology. Results: Injection of C11-metformin in mice revealed avid uptake in the interscapular BAT depot. Metformin exposure in BAT was comparable to hepatic exposure. Inhibition of OCT1, OCT2 and MATE1 function did not affect BAT exposure to metformin suggesting OCT3 mediated uptake. Determination of OCT3 mRNA expression in BAT supported this assumption. OCT3 levels were > 5000 fold higher than other metformin transporter genes in mouse BAT and 50-500 times higher in the adipose tissue from human deep neck. In vitro incubation of TERT-hBA cells with metformin inhibited cellular oxygen consumption. This effect was dose dependent with oxygen consumption seemingly settling at a lower rate. Conclusions: Metformin is transported into BAT in mice. This transport is likely mediated through OCT3. OCT3 is present in human brown adipocytes making an effect in human BAT likely. Metformin inhibits mitochondrial respiration in cultured brown adipocytes. Collectively, this suggests BAT as a putative metformin target in humans.
Hepatitis E Virus, A Diagnosis to Consider in Drug Induced Liver Injury Assessment J. Sanabria-Cabrera1; R. Sanjuan-Jiménez1; C. Stephens1; M. Robles-Díaz1; A. Ortega-Alonso1; M. Jiménez-Pérez2; I. Medina-Cáliz1; M. Slim1; R.J. Andrade1; and M.I. Lucena1 1 UGC Aparato Digestivo y Servicio de Farmacología Clínica, Instituto de Investigación Biomédica de Málaga (IBIMA), Hospital Universitario Virgen de la Victoria, Universidad de Málaga, CIBERehd, SCReN, Málaga, Spain; and 2UGC Aparato Digestivo, Instituto de Investigación Biomédica de Málaga (IBIMA), Hospital Universitario Regional de Málaga, Málaga, Spain Background: Drug-induced liver injury (DILI) remains one of the most challenging diseases due to the absence of diagnostic tests and biomarkers. DILI usually presents as an acute hepatitis-like picture requiring extensive differential diagnosis, hepatitis E virus (HEV), which is considered a rare condition in Spain, is not usually ruled out during acute hepatitis assessment. Methods: Analysis of a cohort of 180 patients from the Spanish DILI Registry diagnosed with DILI was undertaken. We analyzed HEV immunoglobulin (Ig) G and M from two groups of serum samples based on the time point of collection (27 samples during the episode of liver damage and 153 at different time points after resolution). In patients showing anti-HEV-IgM+, AgHEV and RNA-HEV were performed. Results: Out of 180 patients included, 60 (33, 3%) were tested positive for anti-HEV IgG and 6 for anti-HEV IgM (1 positive for HEVRNA and 2 for Ag-HEV). In the group of samples collected during the episode, 3/27 (11%) were positive for IgM-HEV. Table. Demographic and clinical data of patients with positive IgM anti-HEV.
Case nº Age (years) 1 2 3 4 5 6
49 74 26 56 35 75
Sex
Peak Latency ALT(1) or AST(2) HEV RNA Suspected Drug (days)
Female Paracetamol Male Cefditoren Female Dexketoprofen Female Isoniazid Male Erythromycin Male Amoxicillin
9 40 8 27 27 4
1840 (2) 4191 (1) 1561 (1) 954 (1) 2469 (1) 2967 (1)
Negative Positive Negative Negative Negative Negative
Ag HEV Positive Positive Negative Negative Negative Negative
Volume 39 Number 8S
Pharmacokinetic and Pharmacodynamic Modeling and Simulation Analysis of Icure Donepezil Patch in Healthy Male Volunteers S. Kyu Yoon1; K.-S. Bae1; D. Hong2; S. Su Kim2; Y. Ho Shim2; Y. Kweon Choi2; and H.-S. Lim1 1 Department of Clinical Pharmacology and Therapeutics, College of Medicine, University of Ulsan, Asan Medical Center, Seoul, Republic of Korea; and 2iCure Pharmaceutical lncorporated, 3F Sehyun Bldg., 7, Saimdang-ro 1-gil, Seocho-gu, Seoul, Korea Background: Donepezil is a well-known reversible noncompetitive acetylcholinesterase inhibitor for the symptomatic treatment of Alzheimer’s disease. The purpose of this study was to characterize the pharmacokinetics of donepezil patch under development using mixed effect modeling analysis, and to expore optimal dosing regimens of the donepezil patch in comparison with donepezil oral formulation. Methods: PK data used in this analysis were from 60 Korean, healthy, male subjects in two Phase 1 studies, where all the subjects received single or multiple doses of donepezil patch of 43.75, 87.5, and 175 mg, and 12 of them received single oral dose of donepezil, 10 mg followed by single dose of donepezil patch. Concentrations of donepezil were measured using validated LC/MS-MS. Donepezil PK were analyzed by nonlinear mixed effect modeling implemented in NONMEM (version 7.3). Results: The PK modeling analysis were conducted seqentially for oral formulation and patch, which describes the data of oral formulation compared to simultaneous analysis of both oral and patch formulations. The final model predicted the real, observed concentration data reasonably well. The Monte-Carlo simulation for plasma
August 2017
donepezil concentration predicted that overall, exposure to plasma donepezil is similar between donepezil 10 mg oral dosing every 24 hours and donepezil patch 175 mg every 72 hours, and between donepezil 5 mg oral dosing every 24 hours and donepezil patch 87.5 mg every 72 hours Conclusions: We developed a population PK model describing the plasma PK of donepezil patch formulation and compared it with that of donepzeil oral formulation in healthy Korean adult males. PK simulation based on the final PK model suggested that donepezil 175 mg patch every 72 hours shows similar concentration profile with oral dosing of donepezil 10 mg every 24 hours, and 87.5 mg patch every 72 hours with oral dosing of 5 mg every 24 hours.
Frequency of Potentially Dangerous Prescribing of the Combinations of Medicinal Products in Senile Patients V. Nikulin1; E. Il’ina2; S. Bordovsky1; S. Gorbatenkova3; O. Bogova2; and D. Sychev2 1 I.M. Sechenov First Moscow State Medical University, Moscow, Russia; 2Russian Medical Academy of Postgraduate Education, Moscow, Russia; and 3Hospital For Wars Veterans No. 2, Moscow, Russia Background: Senile patients suffer from several kinds of nosology which cause polypharmacy. Taking a great number of drugs is connected with the risks of the adverse drug reaction (ADR) rise, which causes frequent sequels, repeated hospitalizations and the high cost treatment. AimTo analyze the prescription frequency of high-priority interactions (HPI) in senile patients with polypharmacy in the cardiology department. Methods: The analysis of 173 patient’s case history records(60 male and 113 female patients aged 85±5.31) was performed. All patients were under treatment in the cardiology department and took on average 8.810 ± 2.745 medications. Later the prescription analysis of the interactions was carried out with the help of the “Drug Interaction Checker” at www.drugs.com. Only drug interactions of “major” category were analyzed (HPI). Results: The following results were achieved: • The number of HPIs among the patients made 141 (7.79% of all) • The most frequently prescribed combinations (% of HPIs): o Anticoagulants and NSAIDs 45(32%) o ACE inhibitors and antimineralocorticoid 25(17,73%) o Concomitant prescription of 2 NSAIDs 14(9,93%) o ACE inhibitors and AT1-receptor antagonists 11(7,8%) o Antimineralocorticoids and AT1-receptor antagonists 10(7,09%) The obtained results suggest a frequent subscription of the combinations drugs with HPI. It is known that such interactions are characterized by the high risk due to the concomitant prescription which exceeds health benefits for the patient. Such combinations should be avoided. Table. Number of HPIs among the patients. Number of High-Priority Interactions 1 2 3 4 5 6
Number of Patients (% of All Patients) 46(26,59%) 16(9,25%) 10(5,78%) 2(1,156%) 2(1,156%) 2(1,156%)
Conclusions: The frequent prescribing of the combinations of drugs with HPI to the senile patients, causes ADRs and reduction of the
e55
Clinical Therapeutics quality of life. In order to improve the effectiveness and safety of the treatment the optimization of the pharmacotherapy by timely identifying of dangerous combinations is required.
Adverse Drug Events With Antipsychotics—A Sex Difference F.K.H. Sørup1,2; J. Hallas3; S. Brunak2; and S.E. Andersen1 1 Zealand University Hospital, Roskilde, Denmark; 2University of Copenhagen, Copenhagen, Denmark; and 3University of Southern Denmark, Odense, Denmark Background: Antipsychotics are a cornerstone in the treatment of schizophrenia. However, the treatment often results in adverse drug events (ADEs), which might be related to antipsychotic polypharmacy, high dose load or the type of antipsychotic prescribed. Little is known of which variables are most important. Methods: Data from 2240 90-day periods of stable antipsychotic treatment in 540 patients with schizophrenia from a psychiatric inpatient centre. Variables collected were age, gender, number of antipsychotics (1,2,3), total dose load (DDDs), type of antipsychotics (first generation antipsychotics (FGA), second generation antipsychotics (SGA) or combinations). The ADEs were text mined from the unstructured text of the electronic patient records by a previously developed method, finding mentioning of a drug and an adverse event within the same sentence, excluding negations, informing of the patient and mentioning of past events. The number of ADEs counted for each period. A multiple linear regression with number of ADEs as outcome was performed. Results: The only significant variable to predict ADEs with antipsychotic treatment was the sex of the patients (p= 0.00398). Subanalyses revealed that the dose was significant for women (p= 0.0387) and the number of antipsychotics for men (p= 0.026). Women got on average more ADEs (0.28 vs 0.19, P= 0.01816) on a lower dose (1.46 DDD vs 1.71 DDD, p= 0.00033) than men. Conclusions: The most prominent feature to predict ADEs with antipsychotic treatment was the sex of the patient. Women seemed more sensitive to total antipsychotic dose load and men to the number of different antipsychotics. Lower doses should be considered in women and fewer drugs in men experiencing ADEs with antipsychotic treatment.
Brown Adipose Tissue is a Putative Metformin Target P. Breining1; J.B. Jensen1; M. Busk1; S. Jakobsen1; P. Bross2; P.F. Guerra2; J. Hansen3; S.B. Pedersen1; B. Richelsen1; and N. Jessen1 1 Aarhus University Hospital, Aarhus, Denmark; 2Aarhus University, Aarhus, Denmark; and 3University of Copenhagen, Copenhagen, Denmark Background: Metformin is the most widely prescribed oral antidiabetic drug worldwide. In spite of well-documented beneficial effects on diabetes, target organs that mediate its effects remain to be established. In recent years, active brown adipose tissue (BAT) has been found in the deep neck of adult humans. Under the hypothesis that brown adipose tissue (BAT) is a metformin target tissue we investigated metformin uptake in vivo and studied the in vitro effects of metformin on cultured human brown adipocytes. Methods: Tissue-specific uptake of metformin was assessed by PET/ CT imaging after injection of [(11)C]-metformin in mice. Human brown adipose tissue was obtained from elective neck surgery and OCT expression levels in human and murine BAT were determined
e56
by qPCR. Oxygen consumption in immortalized brown adipocytes of human origin (TERT-hBA) during metformin exposure was assessed by Seahorse XF technology. Results: Injection of C11-metformin in mice revealed avid uptake in the interscapular BAT depot. Metformin exposure in BAT was comparable to hepatic exposure. Inhibition of OCT1, OCT2 and MATE1 function did not affect BAT exposure to metformin suggesting OCT3 mediated uptake. Determination of OCT3 mRNA expression in BAT supported this assumption. OCT3 levels were > 5000 fold higher than other metformin transporter genes in mouse BAT and 50-500 times higher in the adipose tissue from human deep neck. In vitro incubation of TERT-hBA cells with metformin inhibited cellular oxygen consumption. This effect was dose dependent with oxygen consumption seemingly settling at a lower rate. Conclusions: Metformin is transported into BAT in mice. This transport is likely mediated through OCT3. OCT3 is present in human brown adipocytes making an effect in human BAT likely. Metformin inhibits mitochondrial respiration in cultured brown adipocytes. Collectively, this suggests BAT as a putative metformin target in humans.
Hepatitis E Virus, A Diagnosis to Consider in Drug Induced Liver Injury Assessment J. Sanabria-Cabrera1; R. Sanjuan-Jiménez1; C. Stephens1; M. Robles-Díaz1; A. Ortega-Alonso1; M. Jiménez-Pérez2; I. Medina-Cáliz1; M. Slim1; R.J. Andrade1; and M.I. Lucena1 1 UGC Aparato Digestivo y Servicio de Farmacología Clínica, Instituto de Investigación Biomédica de Málaga (IBIMA), Hospital Universitario Virgen de la Victoria, Universidad de Málaga, CIBERehd, SCReN, Málaga, Spain; and 2UGC Aparato Digestivo, Instituto de Investigación Biomédica de Málaga (IBIMA), Hospital Universitario Regional de Málaga, Málaga, Spain Background: Drug-induced liver injury (DILI) remains one of the most challenging diseases due to the absence of diagnostic tests and biomarkers. DILI usually presents as an acute hepatitis-like picture requiring extensive differential diagnosis, hepatitis E virus (HEV), which is considered a rare condition in Spain, is not usually ruled out during acute hepatitis assessment. Methods: Analysis of a cohort of 180 patients from the Spanish DILI Registry diagnosed with DILI was undertaken. We analyzed HEV immunoglobulin (Ig) G and M from two groups of serum samples based on the time point of collection (27 samples during the episode of liver damage and 153 at different time points after resolution). In patients showing anti-HEV-IgM+, AgHEV and RNA-HEV were performed. Results: Out of 180 patients included, 60 (33, 3%) were tested positive for anti-HEV IgG and 6 for anti-HEV IgM (1 positive for HEVRNA and 2 for Ag-HEV). In the group of samples collected during the episode, 3/27 (11%) were positive for IgM-HEV. Table. Demographic and clinical data of patients with positive IgM anti-HEV.
Case nº Age (years) 1 2 3 4 5 6
49 74 26 56 35 75
Sex
Peak Latency ALT(1) or AST(2) HEV RNA Suspected Drug (days)
Female Paracetamol Male Cefditoren Female Dexketoprofen Female Isoniazid Male Erythromycin Male Amoxicillin
9 40 8 27 27 4
1840 (2) 4191 (1) 1561 (1) 954 (1) 2469 (1) 2967 (1)
Negative Positive Negative Negative Negative Negative
Ag HEV Positive Positive Negative Negative Negative Negative
Volume 39 Number 8S