1,130 research outputs found

    Differentiated effects of the multimodal antidepressant vortioxetine on sleep architecture: Part 1, a pharmacokinetic/pharmacodynamic comparison with paroxetine in healthy men

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    We compared the effect of vortioxetine, paroxetine and placebo after three days of dosing on sleep architecture. This was a randomised, double-blind, four-way crossover, placebo-controlled, multiple-dose study in 24 healthy young men. Subjects received 20mg vortioxetine, 40mg vortioxetine, 20mg paroxetine or placebo for three consecutive days in four different periods with at least three weeks between them. Polysomnography and blood sampling for pharmacokinetic analysis were performed on the pre-dose night and nights 1 and 3 of dosing in each period. Plasma concentrations of vortioxetine and paroxetine during the polysomnography measurement were used to estimate SERT occupancies using published relationships in healthy subjects. All three active treatments significantly increased REM onset latency and decreased time spent in REM sleep. In the pharmacokinetic/pharmacodynamics analysis significant relationships were found between REM onset latency and time spent in REM sleep and vortioxetine/paroxetine exposure. The relation between REM suppression parameters and SERT occupancy was significantly different between vortioxetine and paroxetine, despite the same SERT occupancy. This indicates that vortioxetine has a different clinical pharmacological profile from paroxetine, which may explain the differences in adverse effect profile of the two drugs, for instance the lower incidence of nausea, weight gain and sexual dysfunction with vortioxetine

    ์ •์ƒ์ธ์—์„œ ์•„๋ฆฌํ”ผํ”„๋ผ์กธ ๋‹จํšŒํˆฌ์•ฝ ์ž๋ฃŒ๋ฅผ ์ด์šฉํ•œ ์กฐํ˜„๋ณ‘ ํ™˜์ž์˜ ํ•ญ์ •์ƒํƒœ ๋‡Œ ์ˆ˜์šฉ์ฒด ์ ์œ ์œจ ๋ชจ๋ธ๋ง ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์˜๊ณผ๋Œ€ํ•™ ํ˜‘๋™๊ณผ์ • ์ž„์ƒ์•ฝ๋ฆฌํ•™์ „๊ณต, 2021.8. ๊ถŒ์ค€์ˆ˜.Background: While embarked from a serendipitous discovery, antipsychotic medications antagonising brain dopamine D2 receptor (D2R) have actively been developed. Recently, compounds possessing unique pharmacodynamic (PD) properties such as D2R partial agonist aripiprazole were developed as antipsychotics. Yet, despite unmet need for newer therapeutics in psychiatry, their development has been dampened by several difficulties in clinical trials. To facilitate drug development, strategies that employ healthy volunteers instead of patients has been suggested. Since few relevant studies have been conducted, we aimed to develop and validate a model predicting steady-state D2R occupancy by aripiprazole in patients with schizophrenia using data from a single-dosing study in healthy volunteers. Methods: Data were collected from a single-dosing study with 18 healthy volunteers which conducted serial pharmacokinetic (PK) samplings and [11C]raclopride positron emission tomography (PET) scans to obtain brain D2R occupancy after administering 2-30 mg aripiprazole. Steady-state D2R occupancy in patients with schizophrenia taking 2-30 mg aripiprazole was simulated using PK and PD parameters estimated from healthy volunteers. The simulated D2R occupancy was compared to the actual occupancy measured in 8 patients taking aripiprazole for 2 years on average, and measures to correct the difference was employed to better predict the actual occupancy. Results: Data from the single-dosing healthy volunteer study overestimated the steady-state D2R occupancy in the patients. The discrepancy in PD response was addressed with introduction of tolerance compartment in the PD modelling. Conclusion: The finding suggests that certain compounds such as aripiprazole behave distinctively at steady-state in patient with schizophrenia than single-dosing state in healthy individuals. The difference may be attributed to receptor internalisation and up-regulation following interaction of D2R with aripiprazole. The finding implies that although single-dosing studies could be used to inform steady-state in patients, considerations should be given to potential change of physiology due to characteristics of each drug and pathology of each illness to predict drug response more reliably.์—ฐ๊ตฌ๋ฐฐ๊ฒฝ: ์กฐํ˜„๋ณ‘ ๋“ฑ ์ •์‹ ์งˆํ™˜ ์น˜๋ฃŒ์— ์ฃผ๋กœ ์‚ฌ์šฉ๋˜๋Š” ํ•ญ์ •์‹ ๋ณ‘์•ฝ๋ฌผ์„ ๋Œ€๊ฐœ ๋„ํŒŒ๋ฏผ D2 ์ˆ˜์šฉ์ฒด ๊ธธํ•ญ์ œ์ด๋‚˜, ์ตœ๊ทผ ๋“ค์–ด D2 ์ˆ˜์šฉ์ฒด ๋ถ€๋ถ„์  ํšจํ˜„์ œ์ธ ์•„๋ฆฌํ”ผํ”„๋ผ์กธ ๋“ฑ ๋…ํŠนํ•œ ์•ฝ๋ ฅํ•™์  ํŠน์„ฑ์„ ๊ฐ€์ง€๋Š” ํ•ญ์ •์‹ ๋ณ‘์•ฝ๋ฌผ๋“ค์ด ๊ฐœ๋ฐœ๋˜๊ณ  ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ •์‹ ๊ณผํ•™ ๋ถ„์•ผ์˜ ์ž„์ƒ์  ํŠน์„ฑ์œผ๋กœ ์ธํ•ด ์ •์‹ ์งˆํ™˜ ์‹ ์•ฝ ๊ฐœ๋ฐœ์— ์–ด๋ ค์›€์ด ๊ฐ€์ค‘๋˜์–ด, ์ด๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ์ผ๋ถ€ ์ž„์ƒ์‹œํ—˜์„ ์ •์‹ ์งˆํ™˜ ํ™˜์ž ๋Œ€์‹  ๊ฑด๊ฐ•์ž์›์ž์—์„œ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ๋Š”์ง€์— ๋Œ€ํ•œ ๋…ผ์˜๊ฐ€ ์žˆ์–ด์™”๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ด๋ฅผ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•ด ์•„๋ฆฌํ”ผํ”„๋ผ์กธ์„ ๋‹จํšŒํˆฌ์•ฝํ•œ ๊ฑด๊ฐ•์ž์›์ž ์ž๋ฃŒ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์กฐํ˜„๋ณ‘ ํ™˜์ž์—์„œ ํ•ญ์ •์ƒํƒœ ์•„๋ฆฌํ”ผํ”„๋ผ์กธ D2 ์ˆ˜์šฉ์ฒด ์ ์œ ์œจ์„ ์˜ˆ์ธกํ•˜๋Š” ๋ชจ๋ธ์„ ๋งŒ๋“ค๊ณ  ๊ฒ€์ฆํ•˜๊ณ ์ž ํ•œ๋‹ค. ๋ฐฉ๋ฒ•: 2-30 mg ์•„๋ฆฌํ”ผํ”„๋ผ์กธ์„ ๋‹จํšŒ ํˆฌ์•ฝํ•œ ๊ฑด๊ฐ•์ž์›์ž 18๋ช…์„ ๋Œ€์ƒ์œผ๋กœ ์•ฝ๋™ํ•™์  ์ฑ„ํ˜ˆ๊ณผ [11C]raclopride ์–‘์ „์ž๋ฐฉ์ถœ๋‹จ์ธต์ดฌ์˜์„ ํ†ตํ•ด ๊ฐ๊ฐ ์•„๋ฆฌํ”ผํ”„๋ผ์กธ ํ˜ˆ์ค‘๋†๋„ ๋ฐ D2 ์ˆ˜์šฉ์ฒด ์ ์œ ์œจ์˜ ์˜ˆ์ธก๋ชจ๋ธ ์ˆ˜๋ฆฝ์„ ์œ„ํ•œ ์ž๋ฃŒ๋ฅผ ์ˆ˜์ง‘ํ–ˆ๊ณ , 2-30mg ์•„๋ฆฌํ”ผํ”„๋ผ์กธ์„ ํ‰๊ท  2๋…„์˜ ์žฅ๊ธฐ๊ฐ„ ํˆฌ์•ฝํ•œ ์กฐํ˜„๋ณ‘ ํ™˜์ž 8๋ช…์„ ๋Œ€์ƒ์œผ๋กœ ๊ฐ™์€ ๋ฐฉ๋ฒ•์„ ํ†ตํ•ด ๋ชจ๋ธ ๊ฒ€์ฆ์„ ์œ„ํ•œ ์ž๋ฃŒ๋ฅผ ์ˆ˜์ง‘ํ–ˆ๋‹ค. ์˜ˆ์ธก๋ชจ๋ธ์„ ์ด์šฉํ•ด ์‹œ๋ฎฌ๋ ˆ์ด์…˜ํ•œ D2 ์ˆ˜์šฉ์ฒด ์ ์œ ์œจ์„ ์‹ค์ œ ์กฐํ˜„๋ณ‘ ํ™˜์ž์—์„œ D2 ์ˆ˜์šฉ์ฒด ์ ์œ ์œจ ๊ฐ’๊ณผ ๋น„๊ตํ•˜๊ณ , ์ฐจ์ด๊ฐ€ ์žˆ๋Š” ๊ฒฝ์šฐ ์ฐจ์ด๋ฅผ ๋ณด์ •ํ•˜์—ฌ ์‹ค์ œ ์ˆ˜์šฉ์ฒด ์ ์œ ์œจ์„ ๋” ์ž˜ ์˜ˆ์ธกํ•˜๋Š” ๋ชจ๋ธ์„ ์ˆ˜๋ฆฝํ–ˆ๋‹ค. ๊ฒฐ๊ณผ: ๊ฑด๊ฐ•์ž์›์ž์—์„œ ๋‹จํšŒ ํˆฌ์•ฝํ•œ ์ž๋ฃŒ๋ฅผ ์ด์šฉํ•ด ์ˆ˜๋ฆฝํ•œ ์˜ˆ์ธก๋ชจ๋ธ์€ ์กฐํ˜„๋ณ‘ ํ™˜์ž์—์„œ ํ•ญ์ •์ƒํƒœ D2 ์ˆ˜์šฉ์ฒด ์ ์œ ์œจ์„ ์‹ค์ œ ๊ฐ’๋ณด๋‹ค ๋†’๊ฒŒ ์˜ˆ์ธกํ–ˆ๋‹ค. ์ด ์•ฝ๋ ฅํ•™์  ๋ฐ˜์‘์˜ ์ฐจ์ด๋ฅผ ์•ฝ๋ ฅํ•™ ๋ชจ๋ธ์— ๋‚ด์„ฑ ๊ตฌํš์„ ๋„์ž…ํ•˜์—ฌ ๋ณด์ •ํ–ˆ๋‹ค. ๊ฒฐ๋ก : ๋ณธ ์—ฐ๊ตฌ์˜ ๊ฒฐ๊ณผ์— ๋”ฐ๋ฅด๋ฉด ์•„๋ฆฌํ”ผํ”„๋ผ์กธ ๋“ฑ ํŠน์ • ์•ฝ๋ฌผ์€ ๊ฑด๊ฐ•์ž์›์ž์—์„œ ๋‹จํšŒํˆฌ์•ฝ ํ–ˆ์„ ๋•Œ์™€, ์กฐํ˜„๋ณ‘ ํ™˜์ž์—์„œ ํ•ญ์ •์ƒํƒœ์— ๋„๋‹ฌํ–ˆ์„ ๋•Œ ์„œ๋กœ ๋‹ค๋ฅธ ํšจ๊ณผ๋ฅผ ๋‚˜ํƒ€๋ƒ„์„ ์‹œ์‚ฌํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ํšจ๊ณผ์˜ ์ฐจ์ด๋Š” ์•ฝ๋ฌผ๋กœ ์ธํ•œ D2 ์ˆ˜์šฉ์ฒด ๋‚ด์žฌํ™” ๋˜๋Š” ์ƒํ–ฅ์กฐ์ ˆ์˜ ๊ฒฐ๊ณผ๋กœ ์ถ”์ธกํ•  ์ˆ˜ ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๊ฑด๊ฐ•์ž์›์ž์˜ ๋‹จํšŒํˆฌ์•ฝ ์ž๋ฃŒ๋กœ ํ™˜์ž์˜ ํ•ญ์ •์ƒํƒœ๋ฅผ ์˜ˆ์ธกํ•  ์ˆ˜ ์žˆ์ง€๋งŒ, ์ •ํ™•ํ•œ ์•ฝ๋ฌผ ๋ฐ˜์‘ ์˜ˆ์ธก์„ ์œ„ํ•ด ๊ฐ๊ฐ ์•ฝ๋ฌผ์˜ ์ž‘์šฉ๊ธฐ์ „ ๋ฐ ์งˆ๋ณ‘ ์—ฌ๋ถ€์— ๋”ฐ๋ฅธ ์ธ์ฒด์˜ ์ƒ๋ฆฌ์  ๋ณ€ํ™”๋ฅผ ๊ณ ๋ คํ•˜๋Š” ๊ฒƒ์ด ๊ถŒ์žฅ๋œ๋‹ค.Chapter 1. Introduction 1 Chapter 2. Methods 7 Chapter 3. Results 11 Chapter 4. Discussion 15 Chapter 5. Conclusion 23 References 24 Tables 30 Figures 33 Abstract in Korean 48๋ฐ•

    Population Pharmacokinetic-Pharmacodynamic Modeling of Haloperidol in Patients With Schizophrenia Using Positive and Negative Syndrome Rating Scale

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    The aim of this study was to develop a pharmacokinetic-pharmacodynamic (PKPD) model that quantifies the efficacy of haloperidol, accounting for the placebo effect, the variability in exposure-response, and the dropouts. Subsequently, the developed model was utilized to characterize an effective dosing strategy for using haloperidol as a comparator drug in future antipsychotic drug trials. The time course of plasma haloperidol concentrations from 122 subjects and the Positive and Negative Syndrome Scale (PANSS) scores from 473 subjects were used in this analysis. A nonlinear mixed-effects modeling approach was utilized to describe the time course of PK and PANSS scores. Bootstrapping and simulation-based methods were used for the model evaluation. A 2-compartment model adequately described the haloperidol PK profiles. The Weibull and E-max models were able to describe the time course of the placebo and the drug effects, respectively. An exponential model was used to account for dropouts. Joint modeling of the PKPD model with dropout model indicated that the probability of patients dropping out is associated with the observed high PANSS score. The model evaluation results confirmed that the precision and accuracy of parameter estimates are acceptable. Based on the PKPD analysis, the recommended oral dose of haloperidol to achieve a 30% reduction in PANSS score from baseline is 5.6 mg/d, and the corresponding steady-state effective plasma haloperidol exposure is 2.7 ng/mL. In conclusion, the developed model describes the time course of PANSS scores adequately, and a recommendation of haloperidol dose was derived for future antipsychotic drug trials

    Blood-Brain Barrier Penetration of Zolmitriptanโ€”Modelling of Positron Emission Tomography Data

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    Positron emissiontomography (PET) with the drug radiolabelled allows a direct measurement of brain or other organ kinetics, information which can be essential in drug development. Usually, however, a PET-tracer is administered intravenously (i.v.), whereas the therapeutic drug is mostly given orally or by a different route to the PET-tracer. In such cases, a recalculation is needed to make the PET data representative for the alternative administration route. To investigate the blood-brain barrier penetration of a drug (zolmitriptan) using dynamic PET and by PK modelling quantify the brain concentration of the drug after the nasal administration of a therapeutic dose. [11C]Zolmitriptan at tracer dose was administered as a short i.v. infusion and the brain tissue and venous blood kinetics of [11C]zolmitriptan was measured by PET in 7 healthy volunteers. One PET study was performed before and one 30min after the administration of 5mg zolmitriptan as nasal spray. At each of the instances, the brain radioactivity concentration after subtraction of the vascular component was determined up to 90min after administration and compared to venous plasma radioactivity concentration after correction for radiolabelled metabolites. Convolution methods were used to describe the relationship between arterial and venous tracer concentrations, respectively between brain and arterial tracer concentration. Finally, the impulse response functions derived from the PET studies were applied on plasma PK data to estimate the brain zolmitriptan concentration after a nasal administration of a therapeutic dose. The studies shows that the PET data on brain kinetics could well be described as the convolution of venous tracer kinetics with an impulse response including terms for arterial-to-venous plasma and arterial-to-brain impulse responses. Application of the PET derived impulse responses on the plasma PK from nasal administration demonstrated that brain PK of zolmitriptan increased with time, achieving about 0.5mg/ml at 30min and close to a maximum of 1.5mg/ml after 2hr. A significant brain concentration was observed already after 5min. The data support the notation of a rapid brain availability of zolmitriptan after nasal administratio

    A population approach to characterise amisulpride pharmacokinetics in older people and Alzheimer's disease

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    Introduction Current prescribing guidelines for the antipsychotic amisulpride are based largely on pharmacokinetic (PK) studies in young adults, and there is a relative absence of data on older patients, who are at greatest risk of developing adverse events. Methods This study aimed to develop a population PK model for amisulpride specifically in older people, by combining data from a richly sampled phase 1, single (50 mg) dose study in healthy older people (n = 20, 65โ€“79 years), with a clinical dataset obtained during off label, low-dose (25โ€“75 mg daily) amisulpride prescribing in older people with Alzheimerโ€™s disease (AD) (n = 25, 69โ€“92 years), as part of an observational study. Results After introducing a scaling factor based on body weight, age accounted for 20 % of the inter-individual variability in drug clearance (CL), resulting in a 54 % difference in CL between those aged 65 and those aged 85 years, and higher blood concentrations in older patients. Discussion These findings argue for the consideration of age and weight-based dose stratification to optimise amisulpride prescribing in older people, particularly in those aged 85 years and above
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