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Article ; Online: Convolution-based approach for modeling the paliperidone extended release and Long-Acting Injectable (LAI) PK of once-, and three-monthly products administration and for optimizing the development of new LAI products.

Gomeni, Roberto / Bressolle-Gomeni, Françoise

Journal of pharmacokinetics and pharmacodynamics

2022 Volume 50, Issue 2, Page(s) 89–96

Abstract: The aim of this paper was to develop a convolution-based modeling approach for describing the paliperidone PK resulting from the administration of extended-release once-a-day oral dose, and once- and three monthly long-acting injectable products and to ... ...

Abstract	The aim of this paper was to develop a convolution-based modeling approach for describing the paliperidone PK resulting from the administration of extended-release once-a-day oral dose, and once- and three monthly long-acting injectable products and to compare the performances of this approach to the traditional modeling strategy. The results of the analyses indicated that the traditional and convolution-based models showed comparable performances in the characterization of the paliperidone PK. However, the convolution-based approach showed several appealing features that justify the choice of this modeling as a preferred tool for modeling Long Acting Injectable (LAI) products and for deploying an effective model-informed drug development process. In particular, the convolution-based modeling can (a) facilitate the development of in vitro/in vivo correlation, (b) be used to identify formulations with optimal in vivo release properties, and (c) be used for optimizing the clinical benefit of a treatment by supporting the implementation of integrated models connecting in vitro and in vivo drug release, in vivo drug release to PK, and PK to PD and biomarker endpoints. A case study was presented to illustrate the benefits and the flexibility of the convolution-based modeling outcomes. The model was used to evaluate the in vivo drug release properties associated with a hypothetical once-a-year administration of a LAI product with the assumption that the expected paliperidone exposure during a 3-year treatment overlays the exposure expected after repeated administrations of a 3-month LAI product.
MeSH term(s)	Humans ; Paliperidone Palmitate/therapeutic use ; Antipsychotic Agents/therapeutic use ; Schizophrenia/drug therapy ; Delayed-Action Preparations/therapeutic use ; Drug Liberation
Chemical Substances	Paliperidone Palmitate (R8P8USM8FR) ; Antipsychotic Agents ; Delayed-Action Preparations
Language	English
Publishing date	2022-12-09
Publishing country	United States
Document type	Journal Article
ZDB-ID	2041601-5
ISSN	1573-8744 ; 1567-567X
ISSN (online)	1573-8744
ISSN	1567-567X
DOI	10.1007/s10928-022-09835-7
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Article ; Online: Artificial intelligence approach for the analysis of placebo-controlled clinical trials in major depressive disorders accounting for individual propensity to respond to placebo.

Gomeni, Roberto / Bressolle-Gomeni, Françoise / Fava, Maurizio

Translational psychiatry

2023 Volume 13, Issue 1, Page(s) 141

Abstract: 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 ... ...

Abstract	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.
MeSH term(s)	Humans ; Depressive Disorder, Major/drug therapy ; Depressive Disorder, Major/diagnosis ; Artificial Intelligence ; Paroxetine/therapeutic use ; Double-Blind Method ; Treatment Outcome
Chemical Substances	Paroxetine (41VRH5220H)
Language	English
Publishing date	2023-04-29
Publishing country	United States
Document type	Randomized Controlled Trial ; Journal Article
ZDB-ID	2609311-X
ISSN	2158-3188 ; 2158-3188
ISSN (online)	2158-3188
ISSN	2158-3188
DOI	10.1038/s41398-023-02443-0
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Article ; Online: A new method for analyzing clinical trials in depression based on individual propensity to respond to placebo estimated using artificial intelligence.

Gomeni, Roberto / Bressolle-Gomeni, Françoise / Fava, Maurizio

Psychiatry research

2023 Volume 327, Page(s) 115367

Abstract: 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 ... ...

Abstract	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.
MeSH term(s)	Humans ; Artificial Intelligence ; Depression ; Depressive Disorder, Major/drug therapy ; Paroxetine/therapeutic use ; Randomized Controlled Trials as Topic
Chemical Substances	Paroxetine (41VRH5220H)
Language	English
Publishing date	2023-08-02
Publishing country	Ireland
Document type	Journal Article
ZDB-ID	445361-x
ISSN	1872-7123 ; 1872-7506 ; 0925-4927 ; 0165-1781
ISSN (online)	1872-7123 ; 1872-7506
ISSN	0925-4927 ; 0165-1781
DOI	10.1016/j.psychres.2023.115367
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Article ; Online: Modeling Complex Pharmacokinetics of Long-Acting Injectable Products Using Convolution-Based Models With Nonparametric Input Functions.

Gomeni, Roberto / Bressolle-Gomeni, Françoise

Journal of clinical pharmacology

2021 Volume 61, Issue 8, Page(s) 1081–1095

Abstract: 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 ...

Abstract	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 C
MeSH term(s)	Bayes Theorem ; Computer Simulation ; Drug Implants/pharmacokinetics ; Drug Liberation ; Humans ; Models, Biological
Chemical Substances	Drug Implants
Language	English
Publishing date	2021-03-15
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	188980-1
ISSN	1552-4604 ; 0091-2700 ; 0021-9754
ISSN (online)	1552-4604
ISSN	0091-2700 ; 0021-9754
DOI	10.1002/jcph.1842
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Article ; Online: Interpreting clinical trial outcomes complicated by placebo response with an assessment of false-negative and true-negative clinical trials in depression using propensity-weighting.

Gomeni, Roberto / Hopkins, Seth / Bressolle-Gomeni, Françoise / Fava, Maurizio

Translational psychiatry

2023 Volume 13, Issue 1, Page(s) 388

Abstract: 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 ... ...

Abstract	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.
MeSH term(s)	Humans ; Depression/drug therapy ; Prospective Studies ; Research Design ; Placebo Effect
Language	English
Publishing date	2023-12-14
Publishing country	United States
Document type	Journal Article
ZDB-ID	2609311-X
ISSN	2158-3188 ; 2158-3188
ISSN (online)	2158-3188
ISSN	2158-3188
DOI	10.1038/s41398-023-02685-y
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Article ; Online: Comparison of Alternative Population Modeling Approaches for Implementing a Level A IVIVC and for Assessing the Time-Scaling Factor Using Deconvolution and Convolution-Based Methods.

Gomeni, Roberto / Bressolle-Gomeni, Françoise

The AAPS journal

2020 Volume 22, Issue 3, Page(s) 67

Abstract: Different approaches based on deconvolution and convolution analyses have been proposed to establish IVIVC. A new implementation of the convolution-based model was used to evaluate the time-scaled IVIVC using the convolution (method 1) and the ... ...

Abstract	Different approaches based on deconvolution and convolution analyses have been proposed to establish IVIVC. A new implementation of the convolution-based model was used to evaluate the time-scaled IVIVC using the convolution (method 1) and the deconvolution-based (method 2) approaches. With the deconvolution-based approach, time-scaling was detected and estimated using Levy's plots while with the convolution-based approach, time-scaling was directly determined by a time-scaling sub-model of the convolution integral model by nonlinear regression. The objectives of this study were (i) to show how time-scaled deconvolution and convolution-based approaches can be implemented using population modeling approach using standard nonlinear mixed-effect modeling software such as NONMEM and R, and (ii) to compare the performances of the two methods for assessing IVIVC using complex in vivo drug release process. The impact of different PK scenarios (linear and nonlinear PK disposition models, and increasing levels of inter-individual variability (IIV) on in vivo drug release process) was considered. The performances of the methods were assessed by computing the prediction error (%PE) on C
MeSH term(s)	Drug Liberation ; Models, Theoretical
Language	English
Publishing date	2020-04-15
Publishing country	United States
Document type	Comparative Study ; Journal Article ; Validation Study
ISSN	1550-7416
ISSN (online)	1550-7416
DOI	10.1208/s12248-020-00445-0
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Article ; Online: Deconvolution Analysis by Non-linear Regression Using a Convolution-Based Model: Comparison of Nonparametric and Parametric Approaches.

Gomeni, Roberto / Bressolle-Gomeni, Françoise

The AAPS journal

2019 Volume 22, Issue 1, Page(s) 9

Abstract: The convolution-based modeling approach has been shown to be flexible and easy to implement for performing a deconvolution analysis and for assessing in vitro/in vivo correlation using non-linear regression and a pre-specified model describing the in ... ...

Abstract	The convolution-based modeling approach has been shown to be flexible and easy to implement for performing a deconvolution analysis and for assessing in vitro/in vivo correlation using non-linear regression and a pre-specified model describing the in vivo drug absorption. A generalization of this method has been developed using a nonparametric description of the in vivo drug absorption process in replacement of a model-based definition. A comparison of the parametric and nonparametric deconvolution and convolution analyses was conducted on the pharmacokinetic (PK) data observed in four published studies after the administration of an extended-release formulation of methylphenidate at the dose of 18 mg. All the analyses were conducted using a conventional non-linear regression software (NONMEM). The results of the deconvolution analysis indicated that the parametric and nonparametric approaches performed similarly. The parametric approach described the input function using a double Weibull equation (6 parameters) while the nonparametric approach described the input function using a piecewise approximation (12-13 parameters). The validation of the results of the deconvolution analysis was conducted by comparing observed and predicted PK concentrations by the convolution analysis. The performance of the parametric and nonparametric approaches for assessing deconvolution was evaluated using the Akaike and the Bayesian information criteria. These criteria indicated that, despite the similar results obtained with the two approaches, the nonparametric approach provided better results. In conclusion, these results indicated that the nonparametric approach should be considered as the preferred approach for conducting a deconvolution analysis.
MeSH term(s)	Drug Liberation ; Methylphenidate ; Models, Statistical
Chemical Substances	Methylphenidate (207ZZ9QZ49)
Language	English
Publishing date	2019-12-09
Publishing country	United States
Document type	Comparative Study ; Evaluation Study ; Journal Article
ISSN	1550-7416
ISSN (online)	1550-7416
DOI	10.1208/s12248-019-0389-8
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Article ; Online: A convolution-based in vitro-in vivo correlation model for methylphenidate hydrochloride delayed-release and extended-release capsule.

Gupta, Pawan Kumar / Incledon, Bev / Gobburu, Jogarao V S / Gomeni, Roberto

CPT: pharmacometrics & systems pharmacology

2023 Volume 13, Issue 1, Page(s) 132–142

Abstract: 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 ... ...

Abstract	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.
MeSH term(s)	Humans ; Methylphenidate ; Delayed-Action Preparations/pharmacokinetics ; Attention Deficit Disorder with Hyperactivity/drug therapy ; Area Under Curve
Chemical Substances	Methylphenidate (207ZZ9QZ49) ; Delayed-Action Preparations
Language	English
Publishing date	2023-10-31
Publishing country	United States
Document type	Journal Article
ZDB-ID	2697010-7
ISSN	2163-8306 ; 2163-8306
ISSN (online)	2163-8306
ISSN	2163-8306
DOI	10.1002/psp4.13067
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Article: Quantitative Characterization of the Smoothness of Extended-release Methylphenidate Pharmacokinetic Profiles.

Po, Michelle D / Gomeni, Roberto / Incledon, Bev

Innovations in clinical neuroscience

2022 Volume 19, Issue 7-9, Page(s) 32–37

Abstract: Objective: Extended-release methylphenidate (ER-MPH) formulations used to treat attention deficit hyperactivity disorder (ADHD) have complex pharmacokinetic (PK) profiles, resulting from differing ratios of immediate-release and extended-release ... ...

Abstract	Objective: Extended-release methylphenidate (ER-MPH) formulations used to treat attention deficit hyperactivity disorder (ADHD) have complex pharmacokinetic (PK) profiles, resulting from differing ratios of immediate-release and extended-release components and/or their site of absorption. This study aimed to evaluate the smoothness of PK curves of ER-MPHs. Design: The integral of the second derivative squared was evaluated for modeled PK curves, with smaller values indicating a smoother curve. The calculated smoothness of each PK curve was normalized by dividing by Cmax 2 to derive a normalized smoothness parameter appropriate across the dose range of each formulation. Calculations used modeled PK curves from 100mg delayed-release and ER-MPH (DR/ER-MPH), 54mg osmotic release oral system MPH (OROS MPH), 60mg MPH controlled-release delivery (MPH CD), 60mg ER-MPH oral suspension (MEROS), 20mg ER dexmethylphenidate (d-MPH ER), and 60mg multilayer-release MPH (MLR-MPH). Results: The Cmax2-normalized smoothness value was consistent across DR/ER-MPH doses, allowing for relevant comparisons across formulations. Normalized smoothness values differed widely; the lowest normalized smoothness was 0.05 with DR/ER-MPH and ranged up to 9.56 with d-MPH ER. Conclusion: DR/ER-MPH demonstrated a smoother PK profile compared to the highest dose of other ER-MPH formulations. While the benefits of a smooth PK profile remain to be tested clinically, having fewer peaks and troughs has been hypothesized to reduce waxing and waning of therapeutic effects throughout the day, and more gradual changes in MPH plasma levels have been hypothesized to lower the risk of likeability and potentially abate afternoon symptom rebound.
Language	English
Publishing date	2022-09-27
Publishing country	United States
Document type	Journal Article
ZDB-ID	2675366-2
ISSN	2158-8341 ; 2158-8333
ISSN (online)	2158-8341
ISSN	2158-8333
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Article ; Online: Model-based comparison of subcutaneous versus sublingual apomorphine administration in the treatment of motor fluctuations in Parkinson's disease.

Nasser, Azmi / Gomeni, Roberto / Ceresoli-Borroni, Gianpiera / Xie, Lanyi / Busse, Gregory D / Melyan, Zare / Rubin, Jonathan

Journal of pharmacokinetics and pharmacodynamics

2024

Abstract: The objective of this study was to compare the effectiveness of subcutaneous (SC) and sublingual (SL) formulations of apomorphine for the treatment of motor fluctuations in Parkinson's disease using a pharmacokinetics (PK)/pharmacodynamics (PD) modeling ... ...

Abstract	The objective of this study was to compare the effectiveness of subcutaneous (SC) and sublingual (SL) formulations of apomorphine for the treatment of motor fluctuations in Parkinson's disease using a pharmacokinetics (PK)/pharmacodynamics (PD) modeling approach. The PK of SC and SL apomorphine are best described by a one-compartment model with first-order absorption and a two-compartment model with delayed absorption, respectively. The PK/PD model relating apomorphine plasma concentrations to the Unified Parkinson's Disease Rating Scale (UPDRS) motor scores was described by a sigmoidal E
Language	English
Publishing date	2024-04-05
Publishing country	United States
Document type	Journal Article
ZDB-ID	2041601-5
ISSN	1573-8744 ; 1567-567X
ISSN (online)	1573-8744
ISSN	1567-567X
DOI	10.1007/s10928-024-09914-x
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