Simulating Healthy Participant Pharmacokinetics for Renal and Hepatic Impairment Studies: Retrospective Assessment of the Approach.

The recruitment of a parallel, healthy participants (HPs) arm in renal and hepatic impairment (RI and HI) studies is a common strategy to assess differences in pharmacokinetics. Limitations in this approach include the underpowered estimate of exposure differences and the use of the drug in a population for which there is no benefit. Recently, a method was published by Purohit et. al. (2023) that leveraged prior population pharmacokinetic (PopPK) modeling-based simulation to infer the distribution of exposure ratios between the RI/HI arms and HPs. The approach was successful, but it was a single example with a robust model having several iterations of development and fitting to extensive HP data. To test in more studies and models at different stages of development, our catalogue of RI/HI studies was searched, and those with suitable properties and from programs with available models were analyzed with the simulation approach. There were 9 studies included in the analysis. Most studies were associated with models that would have been available at the time (ATT) of the study, and all had a current, final model. For 3 studies, the HP PK was not predicted well by the ATT (2) or final (1) models. In comparison to conventional analysis of variance (ANOVA), the simulation approach provided similar point estimates and confidence intervals of exposure ratios. This PopPK based approach can be considered as a method of choice in situations where the simulation of HP data would not be an extrapolation, and when no other complicating factors are present.

First-in-Human Predictions of Hepatic Clearance for Drugs With the Well-Stirred Model: Comparative Assessment Between Models of Fraction Unbound Based Either on the Free Drug Hypothesis, Albumin-Facilitated Hepatic Uptake or Dynamic Binding Kinetics.

The well-stirred model (WSM) is commonly used to predict the hepatic clearance in vivo (CLH) of drugs. The necessary intrinsic clearance of the unbound drug (CLint-in vitro-unbound) is generated in the in vitro assays in the presence of microsomes or hepatocytes but in the absence of plasma proteins. The value of CLint-in vitro-unbound can be extrapolated with the fraction unbound determined in vitro in plasma (fup) only if the fraction unbound in vivo in liver is the same. However, this approach resulted to a systematic underprediction bias of CLH. With the goal of reducing this bias, two new models of fraction unbound were published in this journal. These models estimate the binding kinetics of the rates of association and dissociation of the drug-protein complex and propose that more dissociation in the liver compared to plasma will increase the fraction unbound available for the metabolism. Consequently, these two models generated higher values of fraction unbound, implying a lower underprediction bias of CLH with the WSM. The first model was developed by Poulin et al. and is referring to the value of fup that is adjusted (fu-adjusted) to quantify the effect of a full dissociation of the drug-protein complex at the hepatocyte membrane in accordance with the theory of the albumin-facilitated hepatic uptake. A second model was developed by Yan et al. who presented a dynamic fraction unbound (fu-dynamic) measuring the real dissociation kinetics of the drug-protein complex with a new in vitro assay in the presence and absence of a recombinant liver enzyme in plasma. Therefore, the objective of this study was to make the first comparative assessment between these two models. The results indicate that, in general, the WSM combined with the values of fu-adjusted was the most accurate approach for predicting CLH. The WSM combined with the values of fu-dynamic has underperformed particularly with the acidic and neutral drugs binding to the albumin and presenting a low metabolic turnover in vitro. Therefore, the new in vitro assay for fu-dynamic gave an underprediction bias of CLH for these drug properties. However, the values of fu-adjusted are significantly higher than those values of fu-dynamic, and, this resulted to no underprediction bias, which is reinforcing the theory of the ALB-facilitated hepatic uptake. For the other neutral and acidic drugs, the models of fu-dynamic and fu-adjusted are in closer agreement. Finally, for the basic drugs, the models of fu-adjusted and fu-dynamic as well as a third model only considering a pH gradient effect on fup are almost accurately equivalent.

In-depth analysis of patterns in selection of different physiologically-based pharmacokinetic modeling tools: Part II - Assessment of model reusability and comparison between open and non-open source-code software.

Whilst the reproducibility of models in the area of systems biology and quantitative systems pharmacology has been the focus of attention lately, the concept of 'reusability' is not addressed. With the advent of the 'Model Master File' dominating some regulatory discussions on pharmaceutical applications of physiologically-based pharmacokinetic (PBPK) models, reusability becomes a vital aspect of confidence in their use. Herein, we define 'reusability' specifically in the context of PBPK models and investigate the influence of open versus non-open source-code (NOSC) nature of the software on the extent of 'reusability'. Original articles (n = 145) that were associated with the development of novel PBPK models were identified as source models and citations to these reports, which involved further PBPK model development, were explored (n > 1800) for reuse cases of the source PBPK model whether in full or partial form. The nature of source-code was a major determinant of external reusability for PBPK models (>50% of the NOSC models as opposed <25% of open source-code [OSC]). Full reusability of the models was not common and mostly involved internal reuse of the OSC model (by the group who had previously developed the original model). The results were stratified by the software utilised (various), organisations involved (academia, industry, regulatory), and type of reusability (full vs. partial). The clear link between external reuse of models and NOSC PBPK software might stem from many elements related to quality and trust that require further investigation, and challenges the unfounded notion that OSC models are associated with higher uptake for reuse.

Determining the Delamanid Pharmacokinetics/Pharmacodynamics Susceptibility Breakpoint Using Monte Carlo Experiments.

Antimicrobial susceptibility testing, based on clinical breakpoints that incorporate pharmacokinetics/pharmacodynamics (PK/PD) and clinical outcomes, is becoming a new standard in guiding individual patient therapy as well as for drug resistance surveillance. However, for most antituberculosis drugs, breakpoints are instead defined by the epidemiological cutoff values of the MIC of phenotypically wild-type strains irrespective of PK/PD or dose. In this study, we determined the PK/PD breakpoint for delamanid by estimating the probability of target attainment for the approved dose administered at 100 mg twice daily using Monte Carlo experiments. We used the PK/PD targets (0- to 24-h area under the concentration-time curve to MIC) identified in a murine chronic tuberculosis model, hollow fiber system model of tuberculosis, early bactericidal activity studies of patients with drug-susceptible tuberculosis, and population pharmacokinetics in patients with tuberculosis. At the MIC of 0.016 mg/L, determined using Middlebrook 7H11 agar, the probability of target attainment was 100% in the 10,000 simulated subjects. The probability of target attainment fell to 25%, 40%, and 68% for PK/PD targets derived from the mouse model, the hollow fiber system model of tuberculosis, and patients, respectively, at the MIC of 0.031 mg/L. This indicates that an MIC of 0.016 mg/L is the delamanid PK/PD breakpoint for delamanid at 100 mg twice daily. Our study demonstrated that it is feasible to use PK/PD approaches to define a breakpoint for an antituberculosis drug.

Assessment of the nlmixr R package for population pharmacokinetic modeling: A metformin case study.

AIM: nlmixr offers first-order conditional estimation (FOCE), FOCE with interaction (FOCEi) and stochastic approximation estimation-maximisation (SAEM) to fit nonlinear mixed-effect models (NLMEM). We modelled metformin's pharmacokinetic data using nlmixr and investigated SAEM and FOCEi's performance with respect to bias and precision of parameter estimates, and robustness to initial estimates. METHOD: Compartmental models were fitted. The final model was determined based on the objective function value and inspection of goodness-of-fit plots. The bias and precision of parameter estimates were compared between SAEM and FOCEi using stochastic simulations and estimations. For robustness, parameters were re-estimated as the initial estimates were perturbed 100 times and resultant changes evaluated. RESULTS: The absorption kinetics of metformin depend significantly on food status. Under the fasted state, the first-order absorption into the central compartment was preceded by zero-order infusion into the depot compartment, whereas for the fed state, the absorption into the depot was instantaneous followed by first-order absorption from depot into the central compartment. The means of relative mean estimation error (rMEE) ( ME E SAEM ME E FOCEi ) and rRMSE ( RMS E SAEM RMS E FOCEi ) were 0.48 and 0.35, respectively. All parameter estimates given by SAEM appeared to be narrowly distributed and were close to the true value used for simulation. In contrast, the distribution of estimates from FOCEi were skewed and more biased. When initial estimates were perturbed, FOCEi estimates were more biased and imprecise. DISCUSSION: nlmixr is reliable for NLMEM. SAEM was superior to FOCEi in terms of bias and precision, and more robust against initial estimate perturbations.

Avaliação da bioequivalência entre duas formulações de rivaroxabana ­ 20 mg comprimido revestido ­ administradas em jejum e pós-prandial em voluntários sadios / Evaluation of bioequivalence between two rivaroxaban formulations ­ coated tablet 20 mg ­ administered under fasting and fed conditions in healthy volunteers

Objetivo: O objetivo deste trabalho foi avaliar a bioequivalência entre duas formulações de rivaroxabana 20 mg comprimido revestido, sendo a formulação teste produzida por Sanofi Medley, Brasil e a formulação referência (Xarelto®) comercializada por Bayer S/A. Métodos: Os estudos foram conduzidos em voluntários sadios de ambos os sexos e as formulações foram administradas em dose única, sob o estado de jejum e pós-prandial. Cada estudo foi conduzido de maneira independente, sendo ambos do tipo aberto, randomizado e com intervalo (washout) de sete dias entre os períodos. O estudo em jejum foi realizado em quatro períodos, com 48 voluntários, enquanto o pós-prandial foi realizado em dois períodos, com 36 voluntários. Resultados: Na administração em jejum, a razão entre a média geométrica da formulação teste e referência (T/R) de Cmáx foi de 100,77%, com intervalo de confiança de 90% (IC 90%) de 94,24% a 107,76%. Para ASC0-t, a razão T/R foi de 100,65%, com IC 90% de 96,13% a 105,39%. Na administração pós-prandial, a razão T/R de Cmáx foi de 110,63%, com IC 90% de 102,39% a 119,54%. Para ASC0-t, a razão T/R foi de 104,65%, com IC 90% de 98,44% a 109,12%. Conclusões: As formulações teste e referência foram consideradas estatisticamente bioequivalentes em ambas as condições de administração, de acordo com os critérios exigidos pela Agência Nacional de Vigilância Sanitária (Anvisa). A formulação teste foi registrada na Anvisa e disponibilizada para comercialização, contribuindo, assim, para a ampliação da disponibilidade do tratamento para doenças tromboembólicas e para a redução de custos ao paciente e ao Sistema Único de Saúde.

Objective: The objective of the present study was to evaluate the bioequivalence between two formulations of rivaroxaban 20 mg coated tablet, the test formulation being manufactured by Sanofi Medley, Brazil and the reference formulation (Xarelto® ) commercialized by Bayer S/A. Methods: The studies were conducted in healthy volunteers of both sexes and the formulations were administered in a single dose, under fasting and fed conditions. Each study was conducted independently, both being open-label, randomized and with a seven-day interval (washout) between periods. The fasting study was carried out in four periods, with 48 volunteers, while the fed study was carried out in two periods, with 36 volunteers. Results: In the fasting administration, the ratio between.

Characterizing the Pharmacokinetics and Biodistribution of Therapeutic Proteins: An Industry White Paper.

Characterization of the pharmacokinetics and biodistribution of therapeutic proteins (TPs) is a hot topic within the pharmaceutical industry, particularly with an ever-increasing catalog of novel modality TPs. Here, we review the current practices, and provide a summary of extensive cross-company discussions as well as a survey completed by International Consortium for Innovation and Quality members on this theme. A wide variety of in vitro, in vivo and in silico techniques are currently used to assess pharmacokinetics and biodistribution of TPs, and we discuss the relevance of these from an industry perspective, focusing on pharmacokinetic/pharmacodynamic understanding at the preclinical stage of development, and translation to human. We consider that the 'traditional in vivo biodistribution study' is becoming insufficient as a standalone tool, and thorough characterization of the interaction of the TP with its target(s), target biology, and off-target interactions at a microscopic scale are key to understand the overall biodistribution on a full-body scale. Our summary of the current challenges and our recommendations to address these issues could provide insight into the implementation of best practices in this area of drug development, and continued cross-company collaboration will be of tremendous value. SIGNIFICANCE STATEMENT: The Innovation and Quality Consortium Translational and ADME Sciences Leadership Group working group for the absorption, distribution, metabolism, and excretion of therapeutic proteins evaluates the current practices and challenges in characterizing the pharmacokinetics and biodistribution of therapeutic proteins during drug development, and proposes recommendations to address these issues. Incorporating the in vitro, in vivo and in silico approaches discussed herein may provide a pragmatic framework to increase early understanding of pharmacokinetic/pharmacodynamic relationships, and aid translational modeling for first-in-human dose predictions.

Pharmacokinetic Tools and Applications.

Drug toxicity, as well as therapeutic activity, is contingent upon the parent drug, or a derivative thereof, reaching the relevant site of action in the body, at sufficient concentration, over a given period of time. Thus, the potential to truly elicit an effect is governed by both the intrinsic activity/toxicity of the drug (or its transformation products) and its pharmacokinetic profile. As the pharmaceutical industry has become increasingly aware of the role of pharmacokinetics in determining drug activity and toxicity, the range of software, both freely available and commercial, to predict relevant properties has proliferated. Such tools can be considered on three different levels, applicable at different stages within the drug development process and providing increasing detail and relevance of information. Level (i) is the prediction of fundamental physicochemical properties that can be used to screen vast virtual libraries of potential candidates. Level (ii), predicting the individual absorption, distribution, metabolism, and excretion (ADME) characteristics of potential drugs, can also be applied to many compounds simultaneously. Level (iii), predicting the concentration-time profile of a drug in blood or specific tissues/organs for individuals or a population, is the most sophisticated level of prediction, applied to fewer candidates. In this chapter, in silico tools for predicting ADME-relevant properties, across these three levels, and the applications of this information, are described using exemplar, freely available resources. Further resources are signposted but not all are considered in detail as the purpose here is more to provide an introduction to the capabilities and practicalities of the tools, rather than to provide an exhaustive review of all the tools available.

Assessment of the Utility of Physiologically-based Pharmacokinetic Model for prediction of Pharmacokinetics in Chinese and Japanese Populations.

The objective for the present analyses was to evaluate the utility of physiologically-based pharmacokinetic (PBPK) modeling for prediction of the pharmacokinetics (PK) in Chinese and Japanese populations with a panel of Pfizer internal compounds. Twelve compounds from Pfizer internal development pipeline with available Westerner PK data and available PK data in at least one of the subpopulations of Japanese and Chinese populations were identified and included in the current analysis. These selected compounds represent various elimination pathways across different therapeutic areas. The Simcyp® PBPK simulator was used to develop and verify the PBPK models of individual compounds. The developed models for these compounds were verified by using the clinical PK data in Westerners. The verified PBPK models were further used to predict the PK of these compounds in Chinese and Japanese populations and the predicted PK parameters were compared with the observed PK parameters. Ten of the 12 compounds had PK data in Chinese, and all the 12 compounds had PK data in Japanese. In general, the PBPK models performed well in predicting PK in Chinese and Japanese, with 8 of 10 drugs in Chinese and 7 of 12 drugs in Japanese has AAFE values less than 1.25-fold. PBPK-guided predictions of the relative PK difference were successful for 75% and 50%, respectively, between Chinese and Western and between Japanese and Western of the tested drugs using 0.8-1.25 as criteria. In conclusion, well verified PBPK models developed using data from Westerners can be used to predict the PK in Chinese and Japanese populations.

Functional in vitro assessment of modified antibodies: Impact of label on protein properties.

Labelling of therapeutic antibodies with radionuclides or fluorophores is routinely used to study their pharmacokinetic properties. A critical assumption in utilizing labelled therapeutic antibodies is that the label has no unfavourable effects on antibody charge, hydrophobicity, or receptor affinity. Ideally, the labelled protein should not have any significant deviations from the physiological properties of the original molecule. This article describes an established quality in vitro assessment workflow for labelled antibodies that ensures better prediction of changes in antibody pharmacokinetic (PK) properties after modifications. This analysis package considers degradation and aggregation analysis by size-exclusion chromatography, changes in neonatal-Fc-receptor (FcRn) affinity, and heparin interaction. FcRn binding is important for antibody recycling and half-life extension, whereas heparin affinity provides estimates on the rate of endocytosis through unspecific cell surface binding. Additionally, mass spectrometric analysis to determine the degree of labelling (DoL) completes the package and the combined analysis data allow to predict the label contribution to the PK properties of the modified antibody. This analytical strategy for labelling 11 IgGs has been investigated using 2 different IgG1 constructs and applying 7 different types of labels. Each labelling resulted in a change in the physicochemical properties of the protein. Not only can the DoL of modified IgGs lead to a change in protein properties, but the type of label also can. Furthermore, it was demonstrated that the labelling process can also influence the behaviour of labelled mAbs. An identical label on different constructs of IgG1 can cause different affinities for FcRn and heparin. Considering the assessment data, only 6 of the 11 modified antibodies from this study can be recommended for subsequent experiments. In conclusion, a suitability assessment of labelled antibodies prior to any pharmacokinetic studies is essential to reduce cost, allocate resources and reduce the number of animal experiments during pre-clinical drug development.

Bioequivalence assessment of pharmaceutical aerosol products through IVIVC.

Many pharmaceutical developers of generic orally inhaled products (OIPs) are facing significant issues in passing the regulatory requirement to show pharmacokinetic (PK) bioequivalence (BE) to the originator product. The core of the issue is that no reliable in vitro-in vivo correlation (IVIVC) is available to guide their development. In this paper, several issues are identified and means to improve the data used for developing an IVIVC are discussed. The article also presents an "IVIVC-free" approach for developing a formulation matching the originator's PK performance.

Association Between Use of Pharmacokinetic-Interacting Drugs and Effectiveness and Safety of Direct Acting Oral Anticoagulants: Nested Case-Control Study.

Concomitant use of direct oral anticoagulants (DOACs) and medications with inhibition/induction effect on P-gp/CYP3A might increase risk of bleeding/treatment failure, respectively. We designed a nested case-control study within a Clalit cohort of patients with atrial fibrillation (AF) and a cohort of patients with venous thromboembolism, new users of a DOAC (January 1, 2010 to August 24, 2020). Propensity scores were constructed from demographic/clinical characteristics, and medications at cohort entry. Each case of: (i) serious bleeding event; (ii) stroke/systemic emboli (SE) in patients with AF; (iii) recurrent thromboembolism in patients with thromboembolism, was matched by age, sex, length of follow-up, year of cohort entry, DOAC type, and DOAC indication, to up to 20 controls. Within 89,284 patients with AF and venous thromboembolism and 126,302 patient-years of follow-up, there were 1,587 serious bleeding events. Risk of serious bleeding increased in association with concurrent prescription of P-gp/CYP3A4 inhibitors. Specifically, higher bleeding risk was associated with dabigatran-verapamil, rivaroxaban-verapamil, and rivaroxaban-amiodarone concurrent prescriptions: adjusted odds ratios (ORs) 2.29 (1.13-4.60), 2.18 (1.07-4.40), and 1.68 (1.14-2.49), respectively. There were 1,116 events of stroke/SE, in 79,302 DOAC-treated patients with AF and 118,124 patient-years of follow-up. Concomitant use of phenytoin, carbamazepine, valproic acid, or levetiracetam was associated with risk for stroke/SE: adjusted OR 2.18 (1.55-3.10). Risk of recurrent venous thromboembolism could not be assessed due to the low number of cases. Concurrent prescriptions of dabigatran or rivaroxaban with verapamil, and of rivaroxaban with amiodarone, are associated with increased risk for serious bleeding. Higher risk for stroke/SE in patients with AF is associated with concurrent prescriptions of DOACs with phenytoin, carbamazepine, valproic acid, or levetiracetam.

Understanding the Role of Pharmacometrics-Based Clinical Decision Support Systems in Pediatric Patient Management: A Case Study Using Lyv Software.

Pharmacometrics could play a key role in shifting pediatric pharmacotherapy from dosing for an average patient to individualizing dosing. Clinicians can have these quantitative tools at their disposal without requiring significant training through the development of clinical decision support systems with easy-to-use interfaces that have a back-end analysis engine or pharmacometric model that uses extensive electronic health record data to predict an individualized dose for each patient. There has been increased development of these clinical decision support systems recently, and for these tools to make the proper breakthrough into clinical practice, it is of utmost importance to perform rigorous testing to ensure adequate predictive performance. In this article, we walk through the components of a decision support tool and the testing required to determine its robustness using an example of a decision support tool we developed for vancomycin dosing in pediatrics.

Do Inhibitory Metabolites Impact DDI Risk Assessment? Analysis of in vitro and in vivo Data from NDA Reviews Between 2013 and 2018.

Evaluating the potential of new drugs and their metabolites to cause drug-drug interactions (DDIs) is critical for understanding drug safety and efficacy. Although multiple analyses of proprietary metabolite testing data have been published, no systematic analyses of metabolite data collected according to current testing criteria have been conducted. To address this knowledge gap, 120 new molecular entities approved between 2013 and 2018 were reviewed. Comprehensive data on metabolite-to-parent area under the curve ratios (AUCM /AUCP ), inhibitory potency of parent and metabolites, and clinical DDIs were collected. Sixty-four percent of the metabolites quantified in vivo had AUCM /AUCP  ≥ 0.25 and 75% of these metabolites were tested for cytochrome P450 (CYP) inhibition in vitro, resulting in 15 metabolites with potential DDI risk identification. Although 50% of the metabolites with AUCM /AUCP  < 0.25 were also tested in vitro, none of them showed meaningful CYP inhibition potential. The metabolite percentage of plasma total radioactivity cutoff of ≥ 10% did not appear to add value to metabolite testing strategies. No relationship between metabolite versus parent drug polarity and inhibition potency was observed. Comparison of metabolite and parent maximum concentration (Cmax ) divided by inhibition constant (Ki ) values suggested that metabolites can contribute to in vivo DDIs and, hence, quantitative prediction of clinical DDI magnitude may require both parent and metabolite data. This systematic analysis of metabolite data for newly approved drugs supports an AUCM /AUCP cutoff of ≥ 0.25 to warrant metabolite in vitro CYP screening to adequately characterize metabolite inhibitory DDI potential and support quantitative DDI predictions.

Modelagem farmacocinética/farmacodinâmica do florfenicol para o tratamento da adenite equina por meio da simulação de Monte Carlo / Pharmacokinetic/pharmacodynamic modeling of florfenicol for the treatment of equine adenitis using Monte Carlo simulation

O objetivo deste trabalho foi avaliar a eficácia do florfenicol na dose usualmente empregada em equinos de 22 mg/kg pelas vias intravenosa, intramuscular e oral para o tratamento de adenite equina por Streptococcus equi. subsp. equi, usando a modelagem farmacocinética/farmacodinâmica (PK/PD – Pharmacokinetic/Pharmacodynamic) e a simulação de Monte Carlo. Foi realizada uma simulação de Monte Carlo a partir dos parâmetros PK, logo depois, efetuou-se a modelagem PK/PD para determinar as taxas de eficácia do antimicrobiano para o tratamento dessa infecção bacteriana, de acordo com o valor da concentração inibitória mínima (CIM), em um intervalo de CIM de 0,125 – 4 μg/mL. Pela via intravenosa, a probabilidade de erradicação bacteriana foi de 100% para CIM até 0,5 μg/mL e efeito bacteriostático com probabilidades de 99% e 80% para CIMs de 2 e 4 μg/mL, respectivamente. Já pelas vias intramuscular e oral a probabilidade de se atingir o índice de erradicação bacteriológica foi de 100% para CIM de até 0,5 μg/mL, contudo, atinge valores de 80% e 81%, respectivamente, para CIM de 1 μg/mL considerando o efeito bactericida (p<0,01). Portanto, através desse estudo é evidenciado a eficácia do florfenicol até a CIM de 0,5 μg/mL para as três vias de administração citadas, entretanto, para CIMs superiores a esse valor, é imprescindível o ajuste da dose farmacológica, evitando falhas na terapêutica e possível resistência microbiana.

The objective of this study was to evaluate the efficacy of florfenicol at the dose usually used in horses of 22 mg/kg by intravenous, intramuscular and oral routes for the treatment of equine adenitis caused by Streptococcus equi. subsp. equi, using Pharmacokinetic/Pharmacodynamic (PK/PD) modeling and Monte Carlo simulation. A Monte Carlo simulation was performed from the PK parameters, then PK/PD modeling was performed to determine the antimicrobial efficacy rates for the treatment of this bacterial infection, according to the minimum inhibitory concentration (MIC) value, in a MIC range of 0.125 - 4 μg/mL. Intravenously, the probability of bacterial eradication was 100% for MICs up to 0.5 μg/mL, and the bacteriostatic effect was 99% and 80% for MICs of 2 and 4 μg/mL, respectively. However, for the intramuscular and oral routes, the probability of reaching the bacteriologic eradication index was 100% for MICs of up to 0.5 μg/mL, however, it reaches values of 80% and 81%, respectively, for MICs of 1 μg/mL considering the bactericidal effect (p<0.01). Therefore, through this study the efficacy of florfenicol is evidenced up to the MIC of 0.5 μg/mL for the three routes of administration cited, however, for MICs higher than this value, it is essential to adjust the pharmacological dose, avoiding failures in therapy and possible microbial resistance.

Modelagem farmacocinética/farmacodinâmica do florfenicol para o tratamento da adenite equina por meio da simulação de Monte Carlo / Pharmacokinetic/pharmacodynamic modeling of florfenicol for the treatment of equine adenitis using Monte Carlo simulation

O objetivo deste trabalho foi avaliar a eficácia do florfenicol na dose usualmente empregada em equinos de 22 mg/kg pelas vias intravenosa, intramuscular e oral para o tratamento de adenite equina por Streptococcus equi. subsp. equi, usando a modelagem farmacocinética/farmacodinâmica (PK/PD ­ Pharmacokinetic/Pharmacodynamic) e a simulação de Monte Carlo. Foi realizada uma simulação de Monte Carlo a partir dos parâmetros PK, logo depois, efetuou-se a modelagem PK/PD para determinar as taxas de eficácia do antimicrobiano para o tratamento dessa infecção bacteriana, de acordo com o valor da concentração inibitória mínima (CIM), em um intervalo de CIM de 0,125 ­ 4 µg/mL. Pela via intravenosa, a probabilidade de erradicação bacteriana foi de 100% para CIM até 0,5 µg/mL e efeito bacteriostático com probabilidades de 99% e 80% para CIMs de 2 e 4 µg/mL, respectivamente. Já pelas vias intramuscular e oral a probabilidade de se atingir o índice de erradicação bacteriológica foi de 100% para CIM de até 0,5 µg/mL, contudo, atinge valores de 80% e 81%, respectivamente, para CIM de 1 µg/mL considerando o efeito bactericida (p<0,01). Portanto, através desse estudo é evidenciado a eficácia do florfenicol até a CIM de 0,5 µg/mL para as três vias de administração citadas, entretanto, para CIMs superiores a esse valor, é imprescindível o ajuste da dose farmacológica, evitando falhas na terapêutica e possível resistência microbiana.

The objective of this study was to evaluate the efficacy of florfenicol at the dose usually used in horses of 22 mg/kg by intravenous, intramuscular and oral routes for the treatment of equine adenitis caused by Streptococcus equi. subsp. equi, using Pharmacokinetic/Pharmacodynamic (PK/PD) modeling and Monte Carlo simulation. A Monte Carlo simulation was performed from the PK parameters, then PK/PD modeling was performed to determine the antimicrobial efficacy rates for the treatment of this bacterial infection, according to the minimum inhibitory concentration (MIC) value, in a MIC range of 0.125 - 4 µg/mL. Intravenously, the probability of bacterial eradication was 100% for MICs up to 0.5 µg/mL, and the bacteriostatic effect was 99% and 80% for MICs of 2 and 4 µg/mL, respectively. However, for the intramuscular and oral routes, the probability of reaching the bacteriologic eradication index was 100% for MICs of up to 0.5 µg/mL, however, it reaches values of 80% and 81%, respectively, for MICs of 1 µg/mL considering the bactericidal effect (p<0.01). Therefore, through this study the efficacy of florfenicol is evidenced up to the MIC of 0.5 µg/mL for the three routes of administration cited, however, for MICs higher than this value, it is essential to adjust the pharmacological dose, avoiding failures in therapy and possible microbial resistance.

Assessment of brain-to-blood drug distribution using liquid chromatography.

Delivery of already existing and new drugs under development to the brain necessitates passage across the blood-brain barrier (BBB) with its tight intercellular junctions, molecular components and transporter systems. Consequently, it is critical to identify the extent of brain permeation and the partitioning across the BBB. The interpretation of brain-to-blood ratios is considered to be a significant and fundamental approach for estimating drug penetration through BBB, the brain-targeting ability and central nervous system (CNS) pharmacokinetics. Among the different bioanalytical techniques, liquid chromatography with various detectors has been widely used for determination of these ratios. This review defines the different approaches for sample preparation, extraction techniques and liquid chromatography procedures concerned with the determination of drugs in blood and brain tissues and the assessment of brain-to-blood levels. These approaches are expanded to cover the analysis of several drug classes such as CNS-acting drugs, chemotherapeutics, antidiabetics, herbal medicinal products, radiopharmaceuticals, antibiotics and antivirals. Accordingly, stability in biological matrices and matrix effects are investigated. The different administration/formulation effects and the possible deviations in these ratios are also disscussed.

Model-based Target Pharmacology Assessment (mTPA): An Approach Using PBPK/PD Modeling and Machine Learning to Design Medicinal Chemistry and DMPK Strategies in Early Drug Discovery.

The optimal pharmacokinetic (PK) required for a drug candidate to elicit efficacy is highly dependent on the targeted pharmacology, a relationship that is often not well characterized during early phases of drug discovery. Generic assumptions around PK and potency risk misguiding screening and compound design toward nonoptimal absorption, distribution, metabolism, and excretion (ADME) or molecular properties and ultimately may increase attrition as well as hit-to-lead and lead optimization timelines. The present work introduces model-based target pharmacology assessment (mTPA), a computational approach combining physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling, sensitivity analysis, and machine learning (ML) to elucidate the optimal combination of PK, potency, and ADME specific for the targeted pharmacology. Examples using frequently encountered PK/PD relationships are presented to illustrate its application, and the utility and benefits of deploying such an approach to guide early discovery efforts are discussed.

Opportunities and challenges for applying model-informed drug development approaches to gene therapies.

As part of the US Food and Drug Administration (FDA)'s Prescription Drug User Fee Act (PDUFA) VI commitments, the Center for Biologics Evaluation and Research (CBER) and Center for Drug Evaluation and Research (CDER) are conducting a model-informed drug development (MIDD) pilot program. Sponsor(s) who apply and are selected will be granted meetings that aim to facilitate the application of MIDD approaches throughout the product development lifecycle and the regulatory process. Due to their complex mechanisms of action and limited clinical experience, cell and gene therapies have the potential to benefit from the application of MIDD methods, which may facilitate their safety and efficacy evaluations. Leveraging data that are generated from all stages of drug development into appropriate modeling and simulation techniques that inform decisions remains challenging. Additional discussions regarding the application of quantitative modeling approaches to drug development decisions, such as through the MIDD pilot program, may be crucial for both the sponsor(s) and regulatory review teams. Here, we share some perspectives on the opportunities and challenges for utilizing MIDD approaches for product review, which we hope will encourage investigators to publish their experiences and application of MIDD in gene therapy product development.