Publications by authors named "Flora Musuamba"

The evolution of information and communication technologies has affected all fields of science, including health sciences. However, the rate of technological innovation adoption by the healthcare sector has been historically slow, compared to other industrial sectors. Innovation in computer modeling and simulation approaches has changed the landscape in biomedical applications and biomedicine, paving the way for their potential contribution in reducing, refining, and partially replacing animal and human clinical trials.

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The most intuitive question for market access for medicinal products is the benefit/risk (B/R) balance. The B/R assessment can conceptually be divided into subquestions related to establishing efficacy and safety. There are additional layers to the B/R ratio for medical products, including questions related to dose selection, clinical and nonclinical pharmacology, and drug quality.

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Empirical pharmacometric models are part of practically every regulatory submission for a new drug. The use of the models often exceeds descriptory roles and this change in their context of use increase the requirements on the evidence to support that they are credible. However, when it comes to assessing the trust in a model for a specific application, current tools are skewed to technical aspects and guidance documents often focused on model reporting or the iterative learning loops of model informed drug development (MIDD).

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Getting the right dose regimen for children and adolescents is important but poses great scientific, practical, and ethical challenges. At the same time, the availability of data in adults is a huge advantage and needs to be used optimally when designing studies in children and analyzing pediatric data. Furthermore, the processes of maturation and growth are always key when selecting doses for children.

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The value of in silico methods in drug development and evaluation has been demonstrated repeatedly and convincingly. While their benefits are now unanimously recognized, international standards for their evaluation, accepted by all stakeholders involved, are still to be established. In this white paper, we propose a risk-informed evaluation framework for mechanistic model credibility evaluation.

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Background: Despite the widespread use of amoxicillin in young children, efforts to establish the feasibility of simplified dosing regimens in resource-limited settings have relied upon empirical evidence of efficacy. Given the antibacterial profile of beta-lactams, understanding of the determinants of pharmacokinetic variability may provide a more robust guidance for the selection of a suitable regimen. Here we propose a simplified dosing regimen based on pharmacokinetic-pharmacodynamic principles, taking into account the impact of growth, renal maturation and disease processes on the systemic exposure to amoxicillin.

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Background And Objective: In the absence of characterization on pharmacokinetics and reference concentrations for hydroxychloroquine in COVID-19 patients, the dose and treatment duration for hydrochloroquine are currently empirical, mainly based on in vitro data, and may vary across national guidelines and clinical study protocols. The aim of this paper is to describe the pharmacokinetics of hydroxychloroquine in COVID-19 patients, considered to be a key step toward its dosing optimization.

Methods: We have developed a population pharmacokinetic model for hydroxychloroquine in COVID-19 patients using prospectively collected pharmacokinetic data from patients either enrolled in a clinical trial or treated with hydroxychloroquine as part of standard of care in two tertiary Belgian hospitals.

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Aims: In the absence of a commonly agreed dosing protocol based on pharmacokinetic (PK) considerations, the dose and treatment duration for hydroxychloroquine (HCQ) in COVID-19 disease currently vary across national guidelines and clinical study protocols. We have used a model-based approach to explore the relative impact of alternative dosing regimens proposed in different dosing protocols for hydroxychloroquine in COVID-19.

Methods: We compared different PK exposures using Monte Carlo simulations based on a previously published population pharmacokinetic model in patients with rheumatoid arthritis, externally validated using both independent data in lupus erythematous patients and recent data in French COVID-19 patients.

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Aims: The objective of this study is to develop a generic model for tacrolimus pharmacokinetics modelling using a meta-analysis approach, that could serve as a first step towards a prediction tool to inform pharmacokinetics-based optimal dosing of tacrolimus in different populations and indications.

Methods: A systematic literature review was performed and a meta-model developed with NONMEM software using a top-down approach. Historical (previously published) data were used for model development and qualification.

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Objective: The objective of this study was to develop a physiologically based pharmacokinetic model for meropenem using a retrograde approach, which could serve as a basis for prediction of the systemic and infection-site drug exposures in different populations and indications. We intended this model to be a useful tool to inform (local) pharmacokinetic-based optimal dosing of meropenem in different settings.

Methods: We developed a reduced physiologically based pharmacokinetic model with NONMEM software using a top-down approach.

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During the last 10 years the European Medicines Agency (EMA) organized a number of workshops on modeling and simulation, working towards greater integration of modeling and simulation (M&S) in the development and regulatory assessment of medicines. In the 2011 EMA - European Federation of Pharmaceutical Industries and Associations (EFPIA) Workshop on Modelling and Simulation, European regulators agreed to the necessity to build expertise to be able to review M&S data provided by companies in their dossier. This led to the establishment of the EMA Modelling and Simulation Working Group (MSWG).

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Objectives: The objective of this study was to propose an optimal treatment regimen of meropenem in critically ill patients with severe nosocomial pneumonia.

Patients And Methods: Among 55 patients in intensive care treated with 1 g of meropenem every 8 h for severe nosocomial pneumonia, 30 were assigned to intermittent infusion (II; over 0.5 h) and 25 to extended infusion (EI; over 3 h) groups.

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Aim: To characterize the effect of donor and recipient CYP3A4, CYP3A5 and ABCB1 genotypes as well as relevant patient characteristics on tacrolimus pharmacokinetics in pediatric liver transplantation.

Patients & Methods: Data from 114 pediatric liver transplant recipients were retrospectively collected during the first 3 months following transplantation. Population pharmacokinetic analysis was performed using nonlinear mixed effects modeling, including characterization of influential covariates.

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Objectives: Delayed graft function (DGF) is still a major issue in kidney transplantation. Plasma and urine neutrophil gelatinase-associated lipocalin (NGAL) were evaluated in a population of kidney donors and recipients to investigate their performance to predict early renal function.

Design And Methods: Plasma (pNGAL) and urine (uNGAL) samples were obtained from donors before organ procurement, and from recipients before transplantation, and then 6, 24 and 48h after the procedure.

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Aims: Paraquat poisoning is a medical problem in many parts of Asia and the Pacific. The mortality rate is extremely high as there is no effective treatment. We analyzed data collected during an ongoing cohort study on self-poisoning and from a randomized controlled trial assessing the efficacy of immunosuppressive therapy in hospitalized paraquat-intoxicated patients.

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Background: Tacrolimus (TAC) pharmacokinetics (PKs) show considerable unexplained variability, particularly in the early period after transplantation. Therefore, TAC is a good candidate for therapeutic drug monitoring. The main objective of the present work was to propose a robust PK model for TAC in the early period after transplantation, with the final goal to provide practitioners with a tool for dose individualization in pediatric patients.

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Purposes: Tacrolimus (TAC) is the most widely used immunosuppressant for the prevention of acute rejection after solid organ transplantation. Its pharmacokinetics (PK) show considerable variability, making TAC a good candidate for therapeutic drug monitoring (TDM). The principal aim of the study was to describe the PK of TAC in pediatric patients during the first year after transplantation.

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On August 1, 2010, a revised guidance regarding bioequivalence (BE) assessment for the approval of innovator (bridging studies, variations, line extensions) and generic medicinal products in the EU came into effect (EMA Guideline on the Investigation of Bioequivalence, CPMP/EWP/QWP/1401/98 Rev. 1/Corr**, London, 20 January 2010). This guideline specifies the requirements for BE assessment for immediate release oral dosage forms with systemic action.

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Aim: To predict simultaneously the area under the concentration-time curve during one dosing interval [AUC(0,12 h)] for mycophenolic acid (MPA) and tacrolimus (TAC), when concomitantly used during the first month after transplantation, based on common blood samples.

Methods: Data were from two different sources, real patient pharmacokinetic (PK) profiles from 65 renal transplant recipients and 9000 PK profiles simulated from previously published models on MPA or TAC in the first month after transplantation. Multiple linear regression (MLR) and Bayesian estimation using optimal samples were performed to predict MPA and TAC AUC(0,12 h) based on two concentrations.

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Purpose: We performed a dose-escalation study to investigate the safety of sorafenib in combination with docetaxel and prednisone in chemo-naïve patients with metastatic castration-resistant prostate cancer (mCRPC).

Methods: Six patients were included per dose level. Following docetaxel infusion on day 1 (75 mg/m(2)/q3 weeks), sorafenib was administered at 200 mg BID on days 2-19 (dose level 1), at 200 mg BID on days 1-21 (dose level 2), at 400 mg BID on days 2-19 (dose level 3), at 400 mg BID on days 1-21 (dose level 4).

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Objectives: The study aimed to characterize the pharmacokinetics (PK) of four β-lactams (piperacillin, ceftazidime, cefepime, and meropenem) in patients comedicated with amikacin (AMK), and to confirm the predictive performance of AMK data, obtained from therapeutic drug monitoring (TDM), on these PK, using a population modeling approach.

Design And Methods: Serum samples were collected in 88 critically ill septic patients. For each β-lactam, the covariate model was optimized using renal function.

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