佐藤 洋美

As Parkinson's disease (PD) progresses, there are multiple biomarker changes, and sex and genetic variants may influence the rate of progression. Data-driven, long-term disease progression model analysis may provide precise knowledge of the relationships between these risk factors and progression and would allow for the selection of appropriate diagnosis and treatment according to disease progression. To construct a long-term disease progression model of PD based on multiple biomarkers and evaluate the effects of sex and leucine-rich repeat kinase 2 (LRRK2) mutations, a technique derived from the nonlinear mixed-effects model (Statistical Restoration of Fragmented Time course [SReFT]) was applied to datasets of patients provided by the Parkinson's Progression Markers Initiative. Four biomarkers, including the Unified PD Rating Scale, were used, and a covariate analysis was performed to investigate the effects of sex and LRRK2-related mutations. A model of disease progression over ~30 years was successfully developed using patient data with a median of 6 years. Covariate analysis suggested that female sex and LRRK2 G2019S mutations were associated with 21.6% and 25.4% significantly slower progression, respectively. LRRK2 rs76904798 mutation also tended to delay disease progression by 10.4% but the difference was not significant. In conclusion, a long-term PD progression model was successfully constructed using SReFT from relatively short-term individual patient observations and depicted nonlinear changes in relevant biomarkers and their covariates, including sex and genetic variants.

In vitro methods are widely used in modern toxicological testing; however, the data cannot be directly employed for risk assessment. In vivo toxicity of chemicals can be predicted from in vitro data using physiologically based toxicokinetic (PBTK) modelling-facilitated reverse dosimetry (PBTK-RD). In this study, a minimal-PBTK model was constructed to predict the in-vivo kinetic profile of fenarimol (FNL) in rats and humans. The model was verified by comparing the observed and predicted pharmacokinetics of FNL for rats (calibrator) and further applied to humans. Using the PBTK-RD approach, the reported in vitro developmental toxicity data for FNL was translated to in vivo dose-response data to predict the assay equivalent oral dose in rats and humans. The predicted assay equivalent rat oral dose (36.46 mg/kg) was comparable to the literature reported in vivo BMD10 value (22.8 mg/kg). The model was also employed to derive the chemical-specific adjustment factor (CSAF) for interspecies toxicokinetics variability of FNL. Further, Monte Carlo simulations were performed to predict the population variability in the plasma concentration of FNL and to derive CSAF for intersubject human kinetic differences. The comparison of CSAF values for interspecies and intersubject toxicokinetic variability with their respective default values revealed that the applied uncertainty factors were adequately protective.

BACKGROUND: The aim of this study was to identify significant factors affecting the effectiveness of exercise training using information of the HF-ACTION (Heart Failure: A Controlled Trial Investigating Outcomes of Exercise Training) study. METHODS: Background factors influencing the effect of exercise training were comprehensively surveyed for 2,130 patients by multivariable Cox regression analysis with the stepwise variable selection, and only significant factors were selected that were statistically distinguished from dummy noise factors using the Boruta method. RESULTS: The analysis suggested that the use of beta-blockers, pulse pressure, hemoglobin level, electrocardiography findings, body mass index, and history of stroke at baseline potentially influenced the exercise effect on all-cause death (AD). Therefore, a hypothetical score to estimate the effect of exercise training was constructed based on the analysis. The analysis suggested that the score is useful in identifying patients for whom exercise training may be significantly effective in reducing all-caused death and hospitalization (ADH) as well as AD. Such a subpopulation accounted for approximately 40% of the overall study population. On the other hand, in approximately 45% of patients, the effect of exercise was unclear on either AD or ADH. In the remaining 15% of patients, it was estimated that the effect of exercise might be unclear for ADH and potentially rather increase AD. CONCLUSIONS: This study is the first analysis to comprehensively evaluate the effects of various factors on the outcome of exercise training in chronic heart failure, underscoring the need to carefully consider the patient's background before recommending exercise training. However, it should be noted that exercise training can improve many outcomes in a wide variety of diseases. Therefore, given the limitations involved in post-hoc analyses of a single clinical trial, the characteristics of patients to whom the results of this analysis can be applied need attention, and also further research is necessary on the relationship between the degree of exercise and the outcomes. A new clinical trial would be needed to confirm the factors detected and the appropriateness of the score.

In this study, the ethnic ratios (ERs) of oral clearance between Japanese and Western populations were subjected to model-based meta-analysis (MBMA) for 81 drugs evaluated in 673 clinical studies. The drugs were classified into eight groups according to the clearance mechanism, and the ER for each group was inferred together with interindividual variability (IIV), interstudy variability (ISV), and inter-drug variability within a group (IDV) using the Markov chain Monte Carlo (MCMC) method. The ER, IIV, ISV, and IDV were dependent on the clearance mechanism, and, except for particular groups such as drugs metabolized by polymorphic enzymes or their clearance mechanism is not confirmative, the ethnic difference was found to be generally small. The IIV was well-matched across ethnicities, and the ISV was approximately half of the IIV as the coefficient of variation. To adequately assess ethnic differences in oral clearance without false detections, phase I studies should be designed with full consideration of the mechanism of clearance. This study suggests that the methodology of classifying drugs based on the mechanism that causes ethnic differences and performing MBMA with statistical techniques such as MCMC analysis is helpful for a rational understanding of ethnic differences and for strategic drug development.