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Since 2016, results from physiologically based pharmacokinetic (PBPK) analyses have been routinely found in the clinical pharmacology section of regulatory applications submitted to the US Food and Drug Administration (FDA). In 2018, the Food and Drug Administration's Office of Clinical Pharmacology published a commentary summarizing the application of PBPK modeling in the submissions it received between 2008 and 2017 and its impact on prescribing information. In this commentary, we provide an update on the application of PBPK modeling in submissions received between 2018 and 2019 and highlight a few notable examples., (Published 2020. This article is a U.S. Government work and is in the public domain in the USA.)

Aims: To clarify the hypothesis tests associated with the full covariate modelling (FCM) approach in population pharmacokinetic analysis, investigate the potential impact of multiplicity in population pharmacokinetic analysis, and evaluate simultaneous confidence intervals (SCI) as an approach to control multiplicity., Methods: Clinical trial simulations were performed using a simple one-compartment pharmacokinetic model. Different numbers of covariates, sample sizes, effect sizes of covariates, and correlations among covariates were explored. The false positive rate (FPR) and power were evaluated., Results: The FPR for the FCM approach dramatically increases with number of covariates. The chance of incorrectly selecting ≥1 seemingly clinically relevant covariates can be increased from 5% to a 40-70% range for 10-20 covariates. The SCI approach may provide appropriate control of the family-wise FPR, allowing more appropriate decision making. As a result, the power detecting real effects without incorrectly identifying non-existing effects can be greatly improved by the SCI approach compared to the approach in current practice. The performance of the SCI approach is driven by the ratio of sample size to number of covariates. The FPR can be controlled at 5% and 10% using the SCI approach when the ratio was ≥20 and 10, respectively., Conclusion: The FCM approach still lies within the framework of statistical testing, and therefore multiplicity is an issue for this approach. It is imperative to consider multiplicity reporting and adjustments in FCM modelling practice to ensure more appropriate decision making., (© 2018 The British Pharmacological Society.)

Study Objective: Neonatal opioid withdrawal syndrome (NOWS) is a condition that often occurs in neonates born to mothers who received methadone treatment for opioid use disorder during pregnancy. Early identification and treatment of infants at risk of NOWS may improve clinical outcomes. The purpose of this study was to evaluate whether maternal and umbilical cord plasma concentrations of methadone and its metabolite, 2‐ethylidene‐1,5‐dimethyl‐3,3‐diphenylpyrrolidine (EDDP), could predict the need for NOWS treatment. Design: Single‐center prospective study. Setting: University of Michigan Neonatal Intensive Care Unit. Patients: The study included 11 opioid‐dependent mother–infant dyads, where the mothers were treated with methadone at 34 weeks' gestation or later. Intervention: Maternal and cord blood samples were collected from the study participants. Measurements and Main Results: Maternal and cord plasma concentrations of methadone and EDDP were determined. Six out of the 11 infants required treatment for NOWS. Maternal methadone plasma concentrations were comparable between infants requiring and not requiring NOWS treatment (329.1 ± 229.7 ng/mL vs. 413.2 ± 329.8 ng/mL). However, the average cord plasma methadone concentration in infants who did not require NOWS treatment was 2.9‐fold higher than in those who required the treatment (120.0 ± 88.6 ng/mL vs. 40.9 ± 24.4 ng/mL), although the difference was not statistically significant. The ratios of maternal‐to‐cord methadone plasma concentrations were significantly higher in patients who required treatment for NOWS compared with those who did not (7.7 ± 1.9 vs. 3.5 ± 1.6, p = 0.003). Maternal and cord plasma EDDP concentrations and the maternal‐to‐cord plasma EDDP concentration ratios did not differ between patients who required and did not require treatment for NOWS. Conclusions: The results suggest that methadone permeability across the blood–placental barrier may affect in utero exposure to methadone, and the maternal‐to‐cord methadone plasma concentration ratio could be a potential biomarker for predicting the need for NOWS treatment. [ABSTRACT FROM AUTHOR]

Obesity, which is defined as having a body mass index of 30 kg/m2 or greater, has been recognized as a serious health problem that increases the risk of many comorbidities (eg, heart disease, stroke, and diabetes) and mortality. The high prevalence of individuals who are classified as obese calls for additional considerations in clinical trial design. Nevertheless, gaining a comprehensive understanding of how obesity affects the pharmacokinetics (PK), pharmacodynamics (PD), and efficacy of drugs proves challenging, primarily as obese patients are seldom selected for enrollment at the early stages of drug development. Over the past decade, model‐informed drug development (MIDD) approaches have been increasingly used in drug development programs for obesity and its related diseases as they use and integrate all available sources and knowledge to inform and facilitate clinical drug development. This review summarizes the impact of obesity on PK, PD, and the efficacy of drugs and, more importantly, provides an overview of the use of MIDD approaches in drug development and regulatory decision making for patients with obesity: estimating PK, PD, and efficacy in specific dosing scenarios, optimizing dose regimen, and providing evidence for seeking new indication(s). Recent review cases using MIDD approaches to support dose selection and provide confirmatory evidence for effectiveness for patients with obesity, including pediatric patients, are discussed. These examples demonstrate the promise of MIDD as a valuable tool in supporting clinical trial design during drug development and facilitating regulatory decision‐making processes for the benefit of patients with obesity. [ABSTRACT FROM AUTHOR]

Aims: Enalapril is a prodrug and needs to be activated by carboxylesterase 1 (CES1). A previous in vitro study demonstrated the CES1 genetic variant, G143E (rs71647871), significantly impaired enalapril activation. Two previous clinical studies examined the impact of G143E on single‐dose enalapril PK (10 mg); however, the results were inconclusive. A prospective, multi‐dose, pharmacokinetics and pharmacodynamics (PK/PD) study was conducted to determine the impact of the CES1 G143E variant on enalapril steady‐state PK and PD in healthy volunteers. Methods: Study participants were stratified to G143E non‐carriers (n = 15) and G143E carriers (n = 6). All the carriers were G143E heterozygotes. Study subjects received enalapril 10 mg daily for seven consecutive days prior to a 72 hour PK/PD study. Plasma concentrations of enalapril and its active metabolite enalaprilat were quantified by an established liquid chromatography–tandem mass spectrometry (LC–MS/MS) method. Results: The CES1 G143E carriers had 30.9% lower enalaprilat Cmax (P = 0.03) compared to the non‐carriers (38.01 vs. 55.01 ng/mL). The carrier group had 27.5% lower AUC0–∞ (P = 0.02) of plasma enalaprilat compared to the non‐carriers (374.29 vs. 515.91 ng*h/mL). The carriers also had a 32.3% lower enalaprilat‐to‐enalapril AUC0–∞ ratio (P = 0.003) relative to the non‐carriers. The average maximum reduction of systolic blood pressure in the non‐carrier group was approximately 12.4% at the end of the study compared to the baseline (P = 0.001). No statistically significant blood pressure reduction was observed in the G143E carriers. Conclusions: The CES1 loss‐of‐function G143E variant significantly impaired enalapril activation and its systolic blood pressure‐lowering effect in healthy volunteers. [ABSTRACT FROM AUTHOR]

Iain Gardner (Certara-Simcyp) noted that the applications of PBPK are expanding in drug development, including predicting drug response in specific populations, integrating quantitative systems pharmacology (QSP) models, and informing formulation design. Model-informed drug development (MIDD) tools including physiologically based pharmacokinetic (PBPK) modeling can improve the mechanistic understanding of a drug's pharmacology and potentially translate into development efficiencies. The acceptance of PBPK modeling as a drug development tool has increased greatly in the past 2 decades and has the potential to continue to accelerate the pace of drug development. However, PBPK models have been shown to predict DDIs with acid-reducing agents, and commercial PBPK platforms have improved model quality, transparency, and reproducibility. [Extracted from the article]

Peak drug concentration (Cmax) and total exposure, such as area under the concentration‐time curve (AUC) from time zero to infinity may be insufficient for assessing relative bioavailability (BA) or bioequivalence (BE) among two products in cases where rapid onset of action or controlled duration of effect is needed to ensure similar drug efficacy. Regulatory agencies have recommended the use of partial AUC (pAUC) as an additional exposure measure for relative BA or BE assessments. The pAUC metric describes pharmacokinetic profiles with the focus on quantification of exposures over specific time intervals to support the determination of relative BA or BE for these drug products in relation to respective reference products. The principles and rationales for using pAUCs are included in the US Food and Drug Administration (FDA)'s general BA or BE guidances. Specific pAUC recommendations are also reflected in product‐specific guidances for generic drug development published by the FDA. Rationales for the use of pAUCs in relative BA or BE assessments are based on drug‐specific and product‐specific considerations. This white paper introduces the general framework, including rationales for pAUC recommendations, and provides an overview of the current status, challenges, and the FDA considerations on the use of pAUC for relative BA or BE assessments in the United States. [ABSTRACT FROM AUTHOR]

A critical step to evaluate the potential in vivo antiviral activity of a drug is to connect the in vivo exposure to its in vitro antiviral activity. The Anti–SARS‐CoV‐2 Repurposing Drug Database is a database that includes both in vitro anti–SARS‐CoV‐2 activity and in vivo pharmacokinetic data to facilitate the extrapolation from in vitro antiviral activity to potential in vivo antiviral activity for a large set of drugs/compounds. In addition to serving as a data source for in vitro anti–SARS‐CoV‐2 activity and in vivo pharmacokinetic information, the database is also a calculation tool that can be used to compare the in vitro antiviral activity with in vivo drug exposure to identify potential anti–SARS‐CoV‐2 drugs. Continuous development and expansion are feasible with the public availability of this database. [ABSTRACT FROM AUTHOR]

Trandolapril, an angiotensin‐converting enzyme inhibitor prodrug, needs to be activated by carboxylesterase 1 (CES1) in the liver to exert its intended therapeutic effect. A previous in vitro study demonstrated that the CES1 genetic variant G143E (rs71647871) abolished CES1‐mediated trandolapril activation in cells transfected with the variant. This study aimed to determine the effect of the G143E variant on trandolapril activation in human livers and the pharmacokinetics (PKs) and pharmacodynamics (PDs) in human subjects. We performed an in vitro incubation study to assess trandolapril activation in human livers (5 G143E heterozygotes and 97 noncarriers) and conducted a single‐dose (1 mg) PK and PD study of trandolapril in healthy volunteers (8 G143E heterozygotes and 11 noncarriers). The incubation study revealed that the mean trandolapril activation rate in G143E heterozygous livers was 42% of those not carrying the variant (p = 0.0015). The clinical study showed that, relative to noncarriers, G143E carriers exhibited 20% and 15% decreases, respectively, in the peak concentration (Cmax) and area under the curve from 0 to 72 h (AUC0–72 h) of the active metabolite trandolaprilat, although the differences were not statistically significant. Additionally, the average maximum reductions of systolic blood pressure and diastolic blood pressure in carriers were ~ 22% and 23% less than in noncarriers, respectively, but the differences did not reach a statistically significant level. In summary, the CES1 G143E variant markedly impaired trandolapril activation in the human liver under the in vitro incubation conditions; however, this variant had only a modest impact on the PK and PD of trandolapril in healthy human subjects. [ABSTRACT FROM AUTHOR]

Model‐informed drug development (MIDD) has been a powerful and efficient tool applied widely in pediatric drug development due to its ability to integrate and leverage existing knowledge from different sources to narrow knowledge gaps. The dose selection is the most common MIDD application in regulatory submission related to pediatric drug development. This article aims to give an overview of the 3 broad categories of use of MIDD in pediatric dose selection: leveraging from adults to pediatric patients, leveraging from animals to pediatric patients, and integrating mechanism in infants and neonates. Population pharmacokinetic analyses with allometric scaling can reasonably predict the clearance in pediatric patients aged >5 years. A mechanistic‐based approach, such as physiologically based pharmacokinetic accounting for ontogeny, or an allometric model with age‐dependent exponent, can be applied to select the dose in pediatric patients aged ≤2 years. The exposure‐response relationship from adults or from other drugs in the same class may be useful in aiding the pediatric dose selection and benefit‐risk assessment. Increasing application and understanding of use of MIDD have contributed greatly to several policy developments in the pediatric field. With the increasing efforts of MIDD under the Prescription Drug User Fee Act VI, bigger impacts of MIDD approaches in pediatric dose selection can be expected. Due to the complexity of model‐based analyses, early engagement between drug developers and regulatory agencies to discuss MIDD issues is highly encouraged, as it is expected to increase the efficiency and reduce the uncertainty. [ABSTRACT FROM AUTHOR]

The key parameters necessary to predict drug‐drug interactions (DDIs) are intrinsic clearance (CLint) and fractional contribution of the metabolizing enzyme toward total metabolism (fm). Herein, we summarize the accumulated knowledge from 53 approved new drug applications submitted to the Office of Clinical Pharmacology, US Food and Drug Administration, from 2016 to 2018 that contained physiologically based pharmacokinetic (PBPK) models to understand how in vitro data are used in PBPK models to assess drug metabolism and predict DDIs. For evaluation of CLint and fm, 29 and 20 new drug applications were included for evaluation, respectively. For CLint, 86.2% of the PBPK models used modified values based on in vivo data with modifications ranging from –82.5% to 2752.5%. For fm, 45.0% of the models used modified values with modifications ranging from –28% to 178.6%. When values for CLint were used from in vitro testing without modification, the model resulted in up to a 14.3‐fold overprediction of the area under the concentration‐time curve of the substrate. When values for fm from in vitro testing were used directly, the model resulted in up to a 2.9‐fold underprediction of its DDI magnitude with an inducer, and up to a 1.7‐fold overprediction of its DDI magnitude with an inhibitor. Our analyses suggested that the in vitro system usually provides a reasonable estimation of fm when the drug metabolism by a given CYP pathway is more than 70% of the total clearance. In vitro experiments provide important information about basic PK properties of new drugs and can serve as a starting point for building a PBPK model. However, key PBPK parameters such as CLint and fm still need to be optimized based on in vivo data. [ABSTRACT FROM AUTHOR]

The unique challenges in pediatric drug development require efficient and innovative tools. Model‐informed drug development (MIDD) offers many powerful tools that have been frequently applied in pediatric drug development. MIDD refers to the application of quantitative models to integrate and leverage existing knowledge to bridge knowledge gaps and facilitate development and decision‐making processes. This article discusses the current practices and visions of applying MIDD in pediatric drug development, regulatory evaluation, and labeling, with detailed examples. The application of MIDD in pediatric drug development can be broadly classified into 3 categories: leveraging knowledge for bridging the gap, dose selection and optimization, and informing clinical trial design. In particular, MIDD can provide evidence for the assumption of exposure‐response similarity in bridging existing knowledge from reference to target population, support the dose selection and optimization based on the "exposure‐matching" principle in the pediatric population, and increase the efficiency and success rate of pediatric trials. In addition, the role of physiologically based pharmacokinetics in drug‐drug interaction in children and adolescents and in utilizing ontogeny data to predict pharmacokinetics in neonates and infants has also been illustrated. Moving forward, MIDD should be incorporated into all pediatric drug development programs at every stage to inform clinical trial design and dose selection, with both its strengths and limitations clearly laid out. The accumulated experience and knowledge of MIDD has and will continue to drive regulatory policy development and refinement, which will ultimately improve the consistency and efficiency of pediatric drug development. [ABSTRACT FROM AUTHOR]

A rapid and sensitive method based on ultrafast liquid chromatography–tandem mass spectrometry was developed and validated for simultaneous determination of Sudan I, Sudan II, Sudan III, and Sudan IV levels in rat whole blood. Cleanert C18 mixed-mode polymeric sorbent was used for effective solid-phase extraction cleanup. Separation was carried out on a reversed-phase C 18 column (100 mm×2.1 mm, 1.8 μm) using 0.1% (v/v) formic acid in water/0.1% (v/v) formic acid in acetonitrile as the mobile phase in gradient elution. Quantification was performed by an electrospray ionization source in the positive multiple reaction monitoring mode using D 5 -Sudan I as the internal standard. Calibration curves showed good linearity between 0.2 and 20.0 μg/L, with correlation coefficients higher than 0.9990. The average recovery rates were between 93.05% and 114.98%. The intra- and inter-day relative standard deviations were within 6.2%. The lower limit of quantification was 0.2 μg/L. All the analytes were found to be stable in a series of stability studies. The proposed method was successfully applied to a pharmacokinetic study of four Sudan dyes after oral administration to rats. [ABSTRACT FROM AUTHOR]

Objective: The most widely utilized pharmacological treatment of attention-deficit/hyperactivity disorder (ADHD) is the psychostimulant methylphenidate (MPH). Most MPH formulations consist of the racemic mixture of d-threo-(R, R)-MPH and l- threo-( S, S)-MPH isomers. MPH is characterized by its low bioavailability and short half-life (2-3 hours). Additionally, significant inter-individual variability in MPH pharmacokinetics has been consistently documented. Accordingly, efforts have been directed at developing alternatives to MPH as therapeutic agents. A wide range of MPH analogues ( dl-α-[2-piperidyl]-phenylacetic acid esters) have been synthesized with the dopamine transporter (DAT) and norepinephrine transporter (NET) as principle neuropharmacological targets. The present study investigated the metabolic profiles and pharmacological activity of the isopropyl ester derivative of MPH, dl-isopropylphenidate (IPH), both in vitro and in vivo. Methods: The synthesis, monoaminergic transporter binding, cellular uptake profiles, and assessment of metabolic hydrolysis and transesterification in the presence of ethanol are described using MPH as a comparator. Additionally, an in vivo assessment of IPH stimulant effects (vs. saline) in rats was performed with locomotor activity as a pharmacodynamic outcome. Results: IPH displayed unique pharmacological characteristics including greater DAT than NET binding and cellular uptake activity, and greater resistance to hydrolysis and transesterification via carboxylesterase 1 relative to MPH. Further, sustained psychostimulant properties offer the prospect of an enhanced duration of action. Conclusions: Our findings are consistent with IPH exhibiting attributes distinguishing it from MPH and warranting further study and development of IPH as a novel psychotherapeutic agent. [ABSTRACT FROM AUTHOR]

Purpose: Membrane transporters mediate many biological effects of chemicals and play a major role in pharmacokinetics and drug resistance. The selection of viable drug candidates among biologically active compounds requires the assessment of their transporter interaction profiles. Methods: Using public sources, we have assembled and curated the largest, to our knowledge, human intestinal transporter database (>5,000 interaction entries for >3,700 molecules). This data was used to develop thoroughly validated classification Quantitative Structure-Activity Relationship (QSAR) models of transport and/or inhibition of several major transporters including MDR1, BCRP, MRP1-4, PEPT1, ASBT, OATP2B1, OCT1, and MCT1. Results: QSAR models have been developed with advanced machine learning techniques such as Support Vector Machines, Random Forest, and k Nearest Neighbors using Dragon and MOE chemical descriptors. These models afforded high external prediction accuracies of 71-100% estimated by 5-fold external validation, and showed hit retrieval rates with up to 20-fold enrichment in the virtual screening of DrugBank compounds. Conclusions: The compendium of predictive QSAR models developed in this study can be used for virtual profiling of drug candidates and/or environmental agents with the optimal transporter profiles. [ABSTRACT FROM AUTHOR]

Abstract: A number of analytical methods have been established to quantify methylphenidate (MPH). However, to date no HPLC methods are applicable to human pharmacokinetic studies without the use of mass spectrometry (MS) detection. We developed a sensitive and reliable HPLC-fluorescence method for the determination of MPH in human plasma using 4-(4,5-diphenyl-1H-imidazol-2-yl) benzoyl chloride (DIB-Cl) as the derivatizing agent. An established GC-MS method was adopted in this study as a comparator assay. MPH was derivatized using DIB-Cl, and separated isocratically on a C18 column using a HPLC system with fluorescence detection (λ ex =330nm, λ em =460nm). The lower limit of quantification was found to be 1ng/mL. A linear calibration curve was obtained over the concentrations ranging from 1ng/mL to 80ng/mL (r =0.998). The relative standard deviations of intra-day and inter-day variations were ≤9.10% and ≤7.58%, respectively. The accuracy ranged between 92.59% and 103.06%. The method was successfully applied to the pharmacokinetic study of a subject who received a single oral dose (0.3mg/kg) of immediate-release MPH and yielded consistent results with that of the GC-MS method. This method is the first HPLC assay with non-MS detection providing sufficient reliability and sensitivity for both pre-clinical and clinical studies of MPH. [Copyright &y& Elsevier]

Olanzapine (OLZ) is a second-generation antipsychotic agent available in 2 solid oral dosage forms, a standard oral tablet (SOT) and an orally disintegrating tablet (ODT). This study assessed the absorption of each by different routes of administration. Secondarily, the influence of P-glycoprotein (P-gp) genotype was assessed. It was hypothesized that more rapid absorption of the OLZ ODT would occur when administered sublingually versus standard oral administration. A randomized, 3-way crossover study assessed the 5-mg OLZ formulations in healthy volunteers (n = 10). Blood was collected (0-8 hours) to assess OLZ pharmacokinetics using liquid chromatography/mass spectrometry. Both routes of ODT administration resulted in more measurable early concentraions relative to SOT. However, there were no statistically significant differences observed between any of the OLZ exposures for observed pharmacokinetic parameters (Cmax, Tmax, AUC0-8h). The homozygous TT genotype for P-gp resulted in an increased AUC of OLZ for SOT administration but not for either condition where sublingual absorption could occur. [ABSTRACT FROM PUBLISHER]

Introduced by the Hatch‐Waxman Amendments of 1984, 505(b)(2) applications permit the US Food and Drug Administration to rely, for approval of a new drug application, on information from studies not conducted by or for the applicant and for which the applicant has not obtained a right of reference. This pathway is designed to circumvent the unnecessary duplication of studies already conducted on a previously approved drug. It can lead to a considerably more efficient and expedited route to approval compared to a traditional development path. Model‐informed drug development refers to the utilization of a diverse array of quantitative models in drug development to streamline the decision‐making process. In this approach, diverse quantitative models that integrate knowledge of physiology, disease processes, and drug pharmacology are employed to address drug development challenges and guide regulatory decisions. Integration of these model‐informed approaches into 505(b)(2) regulatory submissions and decision‐making can further expedite the approval of new drugs. This article discusses some applications of model‐informed approaches that were used to support 505(b)(2) drug development and regulatory actions. Specifically, various quantitative models such as population pharmacokinetic and exposure‐response models have been employed to provide evidence of effectiveness, guide dosing in subgroups such as subjects with hepatic or renal impairment, and inform policies. These case study examples collectively underscore the significance of model‐informed approaches in drug development and regulatory decisions associated with 505(b)(2) submissions. [ABSTRACT FROM AUTHOR]

The pharmacokinetics (PK) of methylphenidate (MPH) differ significantly among individuals. Carboxylesterase 1 (CES1) is the primary enzyme metabolizing MPH, and its function is affected by genetic variants, drug-drug interaction (DDI), and sex. The object of this study is to evaluate CES1 pharmacogenetics as related to MPH metabolism using human liver samples and develop a physiologically-based pharmacokinetic (PBPK) modeling approach to investigate the influence of CES1 genotypes and other factors on MPH PK. The effect of the CES1 variant G143E (rs71647871) on MPH metabolism was studied utilizing 102 individual human liver S9 (HLS9) fraction samples. PBPK models were developed using the population-based PBPK software PK-Sim® by incorporating the HLS9 incubation data. The established models were applied to simulate MPH PK profiles under various clinical scenarios, including different genotypes, drug-alcohol interactions, and the difference between males and females. The HLS9 incubation study showed that subjects heterozygous for the CES1 variant G143E metabolized MPH at a rate of approximately 50% of that in non-carriers. The developed PBPK models successfully predicted the exposure alteration of MPH from the G143E genetic variant, ethanol-MPH DDI, and sex. Importantly, the study suggests that male G143E carriers who are alcohol consumers are at a higher risk of MPH overexposure. PBPK modeling provides a means for better understanding the mechanisms underlying interindividual variability in MPH PK and PD and could be utilized to develop a safer and more effective MPH pharmacotherapy regimen. [ABSTRACT FROM AUTHOR]

[Display omitted] A pediatric formulation workshop entitled "Pediatric Formulations: Challenges of Today and Strategies for Tomorrow" was held to advance pediatric drug product development efforts in both pre-competitive and competitive environments. The workshop had four main sessions discussing key considerations of Formulation, Analytical, Clinical and Regulatory. This paper focuses on the clinical session of the workshop. It provides an overview of the discussion on the interconnection of pediatric formulation design and development, clinical development strategy and pediatric clinical pharmacology. The success of pediatric drug product development requires collaboration of multi-disciplinary teams across the pharmaceutical industry, consortiums, foundations, academia and global regulatory agencies. Early strategic planning is essential to ensure alignment among major stakeholders of different functional teams. Such an alignment is particularly critical in the collaboration between formulators and clinical pharmacology teams. [ABSTRACT FROM AUTHOR]

Gemcitabine is an intravenously administered anti-cancer nucleoside analogue. Systemic exposure following oral administration of gemcitabine is limited by extensive first-pass metabolism via cytidine deaminase (CDA) and potentially by saturation of nucleoside transporter-mediated intestinal uptake. An amino acid ester prodrug of gemcitabine, 5′-l-valyl-gemcitabine (V-Gem), was previously shown to be a substrate of the intestinally expressed peptide transporter 1 (PEPT1) and stable against CDA-mediated metabolism. However, preliminary studies did not evaluate the in vivo oral performance of V-Gem as compared to parent drug. In the present study, we evaluated the pharmacokinetics and in vivo oral absorption of gemcitabine and V-Gem following intravenous and oral administrations in mice. These studies revealed that V-Gem undergoes rapid systemic elimination (half-life < 1 min) and has a low oral bioavailability (<1%). Most importantly, the systemic exposure of gemcitabine was not different following oral administration of equimolar doses of gemcitabine (gemcitabine bioavailability of 18.3%) and V-Gem (gemcitabine bioavailability of 16.7%). Single-pass intestinal perfusions with portal blood sampling in mice revealed that V-Gem undergoes extensive activation in intestinal epithelial cells and that gemcitabine undergoes first-pass metabolism in intestinal epithelial cells. Thus, formulation of gemcitabine as the prodrug V-Gem does not increase systemic gemcitabine exposure following oral dosing, due, in part, to the instability of V-Gem in intestinal epithelial cells. [ABSTRACT FROM AUTHOR]

It is challenging to conduct a pharmacokinetic (PK) study on mice due to the limited amount of plasma one can obtain, which is also true for some clinical studies. Here, we developed and validated a simple, sensitive and robust LC-MS/MS method for measuring the prodrug valacyclovir (VACV) and its metabolite acyclovir (ACV) in mouse and human plasma. This assay utilized an acetonitrile protein precipitation method with isotope-labeled internal standards (IS) and enabled precise and accurate quantification of VACV and ACV in 10 μL plasma samples with a nine-min gradient. The analytes were separated on a Waters Atlantis T3 C18 column. The precursor-product ion transitions for VACV ( m / z 325.2 > 152.1), ACV ( m/z 226.2 > 152.1), VACV-D4 ( m/z 329.2 > 152.1, IS) and ACV-D4 ( m/z 230.2 > 152.1, IS) were detected in a multiple reaction monitoring (MRM) positive ion mode using an API4000 LC-MS/MS system. The lower limit of quantification (LLOQ) was 2 nM for both VACV and ACV. The linear range was validated over the concentration ranges of 2–200 nM and 200–5000 nM for both compounds. The matrix effect and stability of VACV and ACV were also evaluated. This assay was successfully applied to a PK study in mice. [ABSTRACT FROM AUTHOR]