To face SARS-CoV-2 pandemic various attempts are made to identify potential effective treatments by repurposing available drugs. Among them, indomethacin, an anti-inflammatory drug, was shown to have ...potent in-vitro antiviral properties on human SARS-CoV-1, canine CCoV, and more recently on human SARS-CoV-2 at low micromolar range. Our objective was to show that indomethacin could be considered as a promising candidate for the treatment of SARS-CoV-2 and to provide criteria for comparing benefits of alternative dosage regimens using a model-based approach. A multi-stage model-based approach was developed to characterize % of recovery and viral load in CCoV-infected dogs, to estimate the PK of indomethacin in dog and human using published data after administration of immediate (IR) and sustained-release (SR) formulations, and to estimate the expected antiviral activity as a function of different assumptions on the effective exposure in human. Different dosage regimens were evaluated for IR formulation (25 mg and 50 mg three-times-a-day, and 25 mg four-times-a-day), and SR formulation (75 mg once and twice-a-day). The best performing dosing regimens were: 50 mg three-times-a-day for the IR formulation, and 75 mg twice-a-day for the SR formulation. The treatment with the SR formulation at the dose of 75 mg twice-a-day is expected to achieve a complete response in three days for the treatment in patients infected by the SARS-CoV-2 coronavirus. These results suggest that indomethacin could be considered as a promising candidate for the treatment of SARS-CoV-2 whose potential therapeutic effect need to be further assessed in a prospective clinical trial.
Treatment effect in clinical trials for major depressive disorders (RCT) can be viewed as the resultant of treatment specific and non-specific effects. Baseline individual propensity to respond ...non-specifically to any treatment or intervention can be considered as a major non-specific confounding effect. The greater is the baseline propensity, the lower will be the chance to detect any treatment-specific effect. The statistical methodologies currently applied for analyzing RCTs doesn't account for potential unbalance in the allocation of subjects to treatment arms due to heterogenous distributions of propensity. Hence, the groups to be compared may be imbalanced, and thus incomparable. Propensity weighting methodology was used to reduce baseline imbalances between arms. A randomized, double-blind, placebo controlled, three arms, parallel group, 8-week, fixed-dose study to evaluate efficacy of paroxetine CR 12.5 and 25 mg/day is presented as a cases study. An artificial intelligence model was developed to predict placebo response at week 8 in subjects assigned to placebo arm using changes from screening to baseline of individual Hamilton Depression Rating Scale items. This model was used to predict the probability to respond to placebo in each subject. The inverse of the probability was used as weight in the mixed-effects model applied to assess treatment effect. The analysis with and without propensity weight indicated that the weighted analysis provided an estimate of treatment effect and effect-size about twice larger than the non-weighted analysis. Propensity weighting provides an unbiased strategy to account for heterogeneous and uncontrolled placebo effect making patients' data comparable across treatment arms.
The objective of this study was to evaluate the performances of the propensity score weighted (PSW) methodology in a post-hoc re-analysis of a failed and a negative RCTs in depressive disorders. The ...conventional study designs, randomizations, and statistical approaches do not account for the baseline distribution of major non-specific prognostic and confounding factors such as the individual propensity to show a placebo effect (PE). Therefore, the conventional analysis approaches implicitly assume that the baseline PE is the same for all subjects in the trial even if this assumption is not supported by our knowledge on the impact of PE on the estimated treatment effect (TE). The consequence of this assumption is an inflation of false negative results (type II error) in presence of a high proportion of subjects with high PE and an inflation of false positive (type I error) in presence of a high proportion of subjects with low PE value. Differently from conventional approaches, the inverse of the PE probability was used as weight in the mixed-effects analysis to assess TE in the PSW analysis. The results of this analysis indicated an enhanced signal of drug response in a failed trial and confirmed the absence of drug effect in a negative trial. This approach can be considered as a reference prospective or post-hoc analysis approach that minimize the risk of inflating either type I or type II error in contrast to what happens in the analyses of RCT studies conducted with the conventional statistical methodology.
Abstract
Our objective was to develop: 1) a longitudinal model to describe amyotrophic lateral sclerosis (ALS) disease progression using the revised Amyotrophic Lateral Sclerosis Functional Rating ...Scale (ALSFRS-R); and 2) a probabilistic model to estimate the presence of clusters of trajectories in ALS progression over 12 months of treatment. Three hundred and thirty-eight patients treated with placebo from the PRO-ACT database were included in the analyses. A non-linear Weibull model best described the ALS disease progression, and a stepwise logistic regression approach was used to select the variables predicting a slow or fast disease progression. Results identified two clusters of trajectories: 1) slow disease progressors (46% of patients with a change from baseline of 13%); 2) fast disease progressors (54% of patients with a change from baseline of 49%). ROC curve analysis estimated the optimal cut-off for classifying patients as slow or fast disease progressors given ALSFRS-R measurements at 2-4 weeks. Results showed that the degree of ALS disease progression quantified by the ALSFRS-R symptomatic change on placebo is highly heterogeneous. In conclusion, this finding indicates the potential interest of disease progression models for implementing a population enrichment strategy to control the level of heterogeneity in the patients included in new trials.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Delayed‐release and extended‐release methylphenidate hydrochloride (JORNAY PM®) is a novel capsule formulation of methylphenidate hydrochloride, used to treat attention deficit hyperactivity disorder ...in patients 6 years and older. In this paper, we develop a Level A in vitro‐in vivo correlation (IVIVC) model for extended‐release methylphenidate hydrochloride to support post‐approval manufacturing changes by evaluating a point‐to‐point correlation between the fraction of drug dissolved in vitro and the fraction of drug absorbed in vivo. Dissolution data from an in vitro study of three different release formulations: fast, medium, and slow, and pharmacokinetic data from two in vivo studies were used to develop an IVIVC model using a convolution‐based approach. The time‐course of the drug concentration resulting from an arbitrary dose was considered as a function of the in vivo drug absorption and the disposition and elimination processes defined by the unit impulse response function using the convolution integral. An IVIVC was incorporated in the model due to the temporal difference seen in the scatterplots of the estimated fraction of drug absorbed in vivo and the fraction of drug dissolved in vitro and Levy plots. Finally, the IVIVC model was subjected to evaluation of internal predictability. This IVIVC model can be used to predict in vivo profiles for different in vitro profiles of extended‐release methylphenidate hydrochloride.
Introduction
Attention‐deficit/hyperactivity disorder (ADHD) is associated with impairments related to peer relations (PR) and social activities (SA). The objective of this post hoc analysis was to ...assess the degree to which viloxazine extended‐release (viloxazine ER; viloxazine extended‐release capsules; Qelbree®) improves clinical assessments of PR and SA in children and adolescents with ADHD.
Methods
Data were used from four Phase III placebo‐controlled trials of 100 to 600 mg/day of viloxazine ER (N = 1354; 6–17 years of age). PR and SA were measured with the Peer Relations content scale of the Conners 3rd Edition Parent Short Form's Peer Relation content scale (C3PS‐PR) and the Social Activities domain of the Weiss Functional Impairment Rating Scale‐Parent Report's (WFIRS‐P‐SA) at baseline and end of study. ADHD symptoms were assessed weekly with the ADHD Rating Scale, 5th Edition. The analyses relied on the general linear mixed model with the subject as a random effect.
Results
Improvement in C3PS‐PR (p = .0035) and WFIRS‐P‐SA (p = .0029) scores were significantly greater in subjects treated with viloxazine ER compared with placebo. When using measures of clinically meaningful response, the C3PS‐PR responder rate was significantly higher for viloxazine ER (19.2%) compared with placebo (14.1%) and the difference was statistically significant (p = .0311); the Number Needed to Treat (NNT) was 19.6. The WFIRS‐P‐SA responder rate was significantly higher for viloxazine ER (43.2%) compared with placebo (28.5%) and the difference was statistically significant (p < .0001); the NNT was 6.8. The standardized mean difference effect size for both PR and SA was 0.09.
Conclusions
Viloxazine ER significantly reduces the impairment of PR and SA in children and adolescents with ADHD. Although its effects on PR and SA are modest, many ADHD patients can be expected to achieve clinically meaningful improvements in PR and SA with viloxazine ER treatment for longer than 6 weeks.
KEY POINTS
Children and adolescents with attention‐deficit/hyperactivity disorder (ADHD) commonly experience deficits associated with peer relations (PR) and social activities (SA).
Viloxazine extended‐release (viloxazine ER) is approved for the treatment of ADHD in children and adolescents.
In a post hoc analysis of pooled data from four pediatric, Phase III, placebo‐controlled trials, viloxazine ER significantly improved the outcome in assessments of both PR and SA in children and adolescents with ADHD.
•Uncontrolled levels of placebo response is a major reason of trial failure.•Individual propensity to respond to placebo is not controlled by randomization.•Artificial intelligence propensity ...weighting is used to estimate treatment effect.•The estimated a treatment effect is adjusted for high/low placebo response.
One of the major reasons for trial failures in major depressive disorders (MDD) is the presence of unpredictable levels of placebo response as the individual baseline propensity to respond to placebo is not adequately controlled by the current randomization and statistical methodologies.
The individual propensity to respond to any treatment or intervention assessed at baseline was considered as a major non-specific prognostic and confounding effect. The objective of this paper was to apply the propensity score methodology to control for potential imbalance at baseline in the propensity to respond to placebo in clinical trials in MDD.
Individual propensity was estimated using artificial intelligence (AI) applied to observations collected in two pre-randomization occasions.
Cases study are presented using data from two randomized, placebo-controlled trials to evaluate the efficacy of paroxetine in MDD. AI models were used to estimate the individual propensity probability to show a treatment non-specific placebo effect.
The inverse of the estimated probability was used as weight in the mixed-effects analysis to assess treatment effect. The comparison of the results obtained with and without propensity weight indicated that the weighted analysis provided an estimate of treatment effect and effect size significantly larger than the conventional analysis.
In the last decade, drug development has tackled substantial challenges to improve efficiency and facilitate access to innovative medicines. Integrated clinical protocols and the investigation of ...targeted oncology drugs in healthy volunteers (HVs) have emerged as modalities with an increase in scope and complexity of early clinical studies and first‐in‐human (FIH) studies in particular. However, limited work has been done to explore the impact of these two modalities, alone or in combination, on the scientific value and on the implementation of such articulated studies. We conducted an FIH study in HVs with an oncology targeted drug, an Mnk 1/2 small molecule inhibitor. In this article, we describe results, advantages, and limitations of an integrated clinical protocol with an oncology drug. We further discuss and indicate points to consider when designing and conducting similar scientifically and operationally demanding FIH studies.
The interest in the development and the therapeutic use of long‐acting injectable (LAI) products for chronic or long‐term treatments has grown exponentially. The complexity and the multiphase drug ...release process represent serious issues for an effective modeling of the PK properties of LAI products. The objective of this article is to show how convolution‐based models with piecewise‐linear approximation of the nonlinear drug release function can provide an enhanced modeling tool for (1) characterizing the complex PK profiles of LAI formulations with completely different drug release properties, and (2) addressing key questions supporting the optimal development of LAI products by simulating the PK time course resulting from different dosing strategies. Convolution‐based modeling and simulation were implemented in NONMEM, and 3 case studies were presented to assess the performances of this new modeling approach using PK data of LAI products developed using different technologies and administered using different routes: microsphere technology and aqueous nanosuspension intramuscularly administered and biodegradable polymer subcutaneously administered. The performance of the convolution‐based modeling approach was compared with the performance of conventional parametric models using a reference data set on theophylline. The results of the comparison indicated that the nonparametric input function provided a more accurate description of the data either in terms of global measure of goodness of fit (ie, Akaike information criterion and Bayesian information criterion) or in terms of performance of the fitted model (ie, the percent prediction error on Cmax and AUC0‐t).
Abstract The Hamilton depression rating scale (HAM-D17 ) has been the gold standard in depression trials since its introduction in 1960 by Max Hamilton. However, several authors have shown that the ...HAM-D17 is multi-dimensional and that subscales of the HAM-D17 outperform the total scale. In the current study, we assess the sensitivity of the individual HAM-D17 items in differentiating responders from non-responders over the typical treatment period used in clinical efficacy trials. Based on data from randomised, placebo-controlled trials with paroxetine, a graphical analysis and a statistical analysis were performed to identify the items that are most sensitive to the rate and extent of response irrespective of treatment. From these analyses, two subscales consisting of seven items each were derived and compared to the Bech and Maier and Philip subscales using a linear mixed-effects modelling approach for repeated measures. The evaluation of two clinical trials revealed endpoint sensitivity comparable to the existing subscales. Using a bootstrap technique, we show that the subscales consistently yield higher statistical power compared to the HAM-D17 , although no subscale consistently outperforms the others. In conclusion, this study provides further evidence that not all items of the HAM-D17 scale are equally sensitive to detect responding patients in a clinical trial. A HAM-D7 subscale with higher sensitivity to drug effect is proposed consisting of the HAM-D6 and the suicide item. This response-based subscale increases signal-to-noise ratio and could reduce failure rate in efficacy trials with antidepressant drugs.