"MAP Bayesian modeling combining striatal dopamine receptor occupancy and plasma concentrations to optimize antipsychotic dose regimens in individual patients"

AIM

Develop a robust and user-friendly software tool for the prediction of dopamine D₂ receptor occupancy (RO) in patients with schizophrenia treated with either olanzapine or risperidone, in order to facilitate clinician exploration of the impact of treatment strategies on RO using sparse plasma concentration measurements.

METHODS

Previously developed population pharmacokinetic (PPK) models for olanzapine and risperidone were combined with a pharmacodynamic (PD) model for D2 RO and implemented in the R programming language. Maximum a posteriori (MAP) Bayesian estimation was used to provide predictions of plasma concentration and RO based on sparse concentration sampling. These predictions were then compared to observed plasma concentration and RO.

RESULTS

The average (standard deviation) response times of the tools, defined as the time required for the application to predict parameter values and display the output, were 2.8 (3.1) and 5.3 (4.3) seconds for olanzapine and risperidone, respectively. The mean error (95% confidence interval) and root mean squared error (RMSE, 95% CI) of predicted versus observed concentrations were 3.73 ng/mL (-2.42 - 9.87) and 10.816 ng/mL (6.71 - 14.93) for olanzapine, and 0.46 ng/mL (-4.56 - 5.47) and 6.68 ng/mL (3.57 - 9.78) for risperidone and its active metabolite (9-OH risperidone). Mean error and RMSE of RO were -1.47% (-4.65 - 1.69) and 5.80% (3.89 - 7.72) for olanzapine and -0.91% (-7.68 - 5.85) and 8.87% (4.56 - 13.17) for risperidone.

CONCLUSION

Our monitoring software predicts concentration-time profiles and the corresponding D₂ RO from sparsely-sampled concentration measurements in an accessible and accurate form.

Comprehensive assessment of exposure to clozapine in association with side effects among patients with treatment-resistant schizophrenia: a population pharmacokinetic study

BACKGROUND

There have been scarce data on the distribution of clozapine concentrations in comparison with the recommended range (350-600 ng/ml) or their relationship with side effects among patients with treatment-resistant schizophrenia. Furthermore, no studies have assessed the association between side effects and overall exposure to the drug by calculating the 24-h area-under-curve (AUC).

METHODS

In- and outpatients with schizophrenia or schizoaffective disorder (ICD-10) who were receiving a stable dose of clozapine for ⩾2 weeks were included. Side effects were assessed using the Glasgow antipsychotic side-effects scale for clozapine (GASS-C). Using two collected plasma samples, plasma clozapine and norclozapine concentrations at peak and trough and their 24-h AUC were estimated using population pharmacokinetic models.

RESULTS

A total of 108 patients completed the study (mean ± SD age, 43.0 ± 10.1 years; clozapine dose, 357.5 ± 136.9 mg/day); 33 patients (30.6%) showed estimated trough concentrations of clozapine within the recommended range (350-600 ng/ml) whereas the concentrations were higher and lower than this range among 37 (43.5%) and 28 (25.9%) patients (%), respectively. There were no significant correlations between estimated peak or trough concentrations or 24-h AUC of both clozapine or norclozapine, and GASS-C total or individual scores. No significant differences were found between GASS-C total or individual item scores between the patients with estimated trough concentrations of clozapine of >600 ng/ml and the other subjects.

CONCLUSION

The results suggest that clozapine or norclozapine concentrations are not linked directly to the extent of side effects experienced in clozapine-treated patients with treatment-resistant schizophrenia while the cross-sectional study design limits the interpretation of any causal relationships. These findings indicate that side effects associated with clozapine may occur at any dose or concentration.

Modeling HIV Pre-Exposure Prophylaxis

Pre-exposure prophylaxis (PrEP) has emerged as a promising strategy for preventing the transmission of HIV. Although only one formulation is currently approved for PrEP, research into both new compounds and new delivery systems for PrEP regimens offer intriguing challenges from the perspective of pharmacokinetic and pharmacodynamic modeling. This review aims to provide an overview the current modeling landscape for HIV PrEP, focused on PK/PD and QSP models relating to antiretroviral agents. Both current PrEP treatments and new compounds that show promise as PrEP agents are highlighted, as well as models of uncommon administration routes, predictions based on models of mechanism of action and viral dynamics, and issues related to adherence to therapy. The spread of human immunodeficiency virus (HIV) remains one of the foremost global health concerns. In the absence of a vaccine, other prophylactic strategies have been developed to prevent HIV transmission. One approach, known as pre-exposure prophylaxis (PrEP), allows HIV-negative individuals who are at high risk of exposure to the virus, be it through an HIV-positive sexual partner or through the shared use of drug injection equipment, to substantially reduce the risk of developing an HIV infection. PrEP is a relatively recent approach to combating the HIV epidemic, with the only currently approved treatment being Truvada, a daily oral antiretroviral (ARV) therapy initially indicated in the treatment of active HIV-1 infections, but approved for HIV PrEP in 2012. Although PrEP therapy has consistently demonstrated high efficacy in preventing HIV infection, this efficacy is dependent on patient adherence to the prescribed treatment regimen. This can present a significant problem in low- and middle-income countries, which may lack the infrastructure to provide sufficient access to PrEP medication to maintain daily dosing regimens. Furthermore, while the conventional approach has generally been to advocate for continuous administration akin to regimens used for viral suppression in infected patients, there has been some discussion of whether a better treatment paradigm might be to push for PrEP therapy primarily during those known periods of heightened exposure risk, while relying on post-exposure prophylaxis regimens to prevent infection after unanticipated exposures during low-risk periods. These considerations have led to a push for the development of long-duration and on-demand PrEP formulations, including subdermal and subcutaneous implants, slow-release intramuscular depot injections, vaginal and rectal antimicrobial gels, and intravaginal rings and dissolving films. PrEP therapy is a quickly evolving field, with a variety of antiretroviral compounds and formulations under investigation. This review aims to report on notable drugs and formulations from a pharmacokinetic/pharmacodynamic (PK/PD) modeling perspective. Given the nature of PrEP as a preventive therapy designed for long-term use, clinical trials for PrEP therapies can last for months or even years, particularly in the case of long-duration formulations. Furthermore, in contrast to antiretroviral trials in infected patients, pharmacodynamic endpoints in PrEP therapies are difficult to quantify, as the primary endpoint for efficacy is generally the rate of seroconversion. Computational modeling approaches offer flexible and powerful tools to provide insight into drug behavior in clinical settings, and can ultimately reduce the time, expense, and patient burden incurred in the development of PrEP therapies.

Favourable growth conditions for the preparation of bulk AlN single crystals by PVT

A high seed temperature (2251 °C) reveals the highest deep UV transparency (α_265nm = 27 cm⁻¹), a high structural perfection (EPD = 9 × 10³ cm⁻²) and a suitable growth rate (R = 200 μm h⁻¹).

Patterns of drug use among young adults

The present study assessed patterns of multiple drug use among a sample of university employees and students who had been identified as having moderately high drug use habits. Use of eleven categories of legal and illegal drugs was tested and subjects reported how much of each drug they currently and habitually used. Factor analysis yielded three factors of drug use. Four of the items in the first factor (hallucinogens, cocaine, marijuana, alcohol) exhibited moderately strong and positive intercorrelations, suggesting that this particular pattern of drug use was the most common and/or reliable among young adult drug users. Sedatives and opiates were the highest loading items on the second factor, suggesting a pattern of drug use motivated by the desire for relaxation and stress avoidance. The third factor identified a pattern of legal stimulant use involving two of the three food-like categories of items employed in the present study (i.e., caffeinated cola beverages and chocolate, but not coffee). The results provided only mixed support for the hypothesis that categories of drugs with similar pharmacological properties define patterns of multiple drug use.