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Journal of Clinical Pharmacology Jan 2024Small interfering RNAs (siRNAs) represent a new class of drugs with tremendous potential for battling previously "undruggable" diseases. After nearly 2 decades of... (Review)
Review
Small interfering RNAs (siRNAs) represent a new class of drugs with tremendous potential for battling previously "undruggable" diseases. After nearly 2 decades of efforts in addressing the problems of the poor drug profile of naked unmodified siRNAs, this new modality has finally come to fruition, with 5 agents (patisiran, givosiran, lumasiran, inclisiran, and vutrisiran) being approved since 2018, and with many others in the different phases of clinical development. Unlike small-molecule drugs and protein therapeutics, siRNAs have different sizes, distinct mechanisms of action, differing physicochemical and pharmacological properties, and, accordingly, a unique pharmacokinetic/pharmacodynamic (PK/PD) relationship. To support the continuous development of siRNAs, it is important to have a thorough and deep understanding of the PK/PD and clinical pharmacology related features of siRNAs. As most of the current siRNA products are conjugated by N-acetylgalactosamine (GalNAc), this review focuses on the PK/PD relationships and clinical pharmacology of GalNAc-conjugated siRNAs, including their absorption, distribution, metabolism, excretion (ADME) properties, PK/PD models, drug-drug interactions, clinical pharmacology in special populations, and safety evaluation. In addition, necessary background information related to the development of siRNAs as a therapeutic modality, including the mechanisms of action, the advantages of siRNAs, the problems of naked siRNAs, as well as the strategies used to enhance the clinical utility of siRNAs, have also been covered. The goal of this review is to serve as a "primer" on siRNA PK/PD, and I hope the readers, especially those who have a limited background on siRNA therapeutics, will have a fundamental understanding of siRNA PK/PD and clinical pharmacology after reading this review.
Topics: Humans; RNA, Small Interfering; Drug Interactions; Pharmacology, Clinical; Pharmacokinetics
PubMed: 37589246
DOI: 10.1002/jcph.2337 -
Journal of Pharmacokinetics and... Feb 2024The current demand for pharmacometricians outmatches the supply provided by academic institutions and considerable investments are made to develop the competencies of...
The current demand for pharmacometricians outmatches the supply provided by academic institutions and considerable investments are made to develop the competencies of these scientists on-the-job. Even with the observed increase in academic programs related to pharmacometrics, this need is unlikely to change in the foreseeable future, as the demand and scope of pharmacometrics applications keep expanding. Further, the field of pharmacometrics is changing. The field largely started when Lewis Sheiner and Stuart Beal published their seminal papers on population pharmacokinetics in the late 1970's and early 1980's and has continued to grow in impact and use since its inception. Physiological-based pharmacokinetics and systems pharmacology have grown rapidly in scope and impact in the last decade and machine learning is just on the horizon. While all these methodologies are categorized as pharmacometrics, no one person can be an expert in everything. So how do you train future pharmacometricians? Leading experts in academia, industry, contract research organizations, clinical medicine, and regulatory gave their opinions on how to best train future pharmacometricians. Their opinions were collected and synthesized to create some general recommendations.
Topics: Humans; Pharmacology; Pharmacokinetics; Career Choice
PubMed: 37573528
DOI: 10.1007/s10928-023-09878-4 -
Pharmaceutical Research Feb 2024To revise the IVIVC considering the physiologically sound Finite Absorption Time (F.A.T.) and Finite Dissolution Time (F.D.T.) concepts.
PURPOSE
To revise the IVIVC considering the physiologically sound Finite Absorption Time (F.A.T.) and Finite Dissolution Time (F.D.T.) concepts.
METHODS
The estimates τ and τ for F.A.T. and F.D.T., respectively are constrained by the inequality τ ≤ τ; their relative magnitude is dependent on drug's BCS classification. A modified Levy plot, which includes the time estimates for τ and τ was developed. IVIVC were also considered in the light of τ and τ estimates. The modified Levy plot of theophylline, a class I drug, coupled with the rapid (30 min) and very rapid (15 min) dissolution time limits showed that drug dissolution/absorption of Class I drugs takes place in less than an hour. We reanalyzed a carbamazepine (Tegretol) bioequivalence study using PBFTPK models to reveal its complex absorption kinetics with two or three stages.
RESULTS
The modified Levy plot unveiled the short time span (~ 2 h) of the in vitro dissolution data in comparison with the duration of in vivo dissolution/absorption processes (~ 17 h). Similar results were observed with the modified IVIVC plots. Analysis of another set of carbamazepine data, using PBFTPK models, confirmed a three stages absorption process. Analysis of steady-state (Tegretol) data from a paediatric study using PBFTPK models, revealed a single input stage of duration 3.3 h. The corresponding modified Levy and IVIVC plots were found to be nonlinear.
CONCLUSIONS
The consideration of Levy plots and IVIVC in the light of the F.A.T. and F.D.T. concepts allows a better physiological insight of the in vitro and in vivo drug dissolution/absorption processes.
Topics: Humans; Child; Solubility; Drug Liberation; Carbamazepine; Biological Availability; Therapeutic Equivalency
PubMed: 38191705
DOI: 10.1007/s11095-024-03653-x -
The Journal of Antimicrobial... Oct 2023Levofloxacin is used for treatment and prevention of rifampicin-resistant (RR)-TB in children. Recent data showed higher exposures with 100 mg dispersible compared with... (Clinical Trial)
Clinical Trial
BACKGROUND
Levofloxacin is used for treatment and prevention of rifampicin-resistant (RR)-TB in children. Recent data showed higher exposures with 100 mg dispersible compared with non-dispersible tablet formulations with potentially important dosing implications in children. We aimed to verify and better characterize this finding.
METHODS
We conducted a crossover pharmacokinetic trial in children aged ≤5 years receiving levofloxacin RR-TB preventive therapy. Pharmacokinetic sampling was done after 15-20 mg/kg doses of levofloxacin with 100 mg dispersible and crushed 250 mg non-dispersible levofloxacin formulations. A population pharmacokinetic model was developed.
RESULTS
Twenty-five children were included, median (IQR) weight and age 12.2 (10.7-15.0) kg and 2.56 (1.58-4.03) years, respectively. A two-compartment model with first-order elimination and transit compartment absorption best described levofloxacin pharmacokinetics. Allometric scaling adjusted for body size, and maturation of clearance with age was characterized. Typical clearance in a 12 kg child was estimated at 4.17 L/h. Non-dispersible tablets had 21.5% reduced bioavailability compared with the dispersible formulation, with no significant differences in other absorption parameters.Dosing simulations showed that current recommended dosing for both formulations result in median exposures below adult-equivalent exposures at a 750 mg daily dose, mainly in children >6 months. Higher levofloxacin doses of 16-30 mg/kg for dispersible and 20-38 mg/kg for crushed non-dispersible tablets may be required in children >6 months.
CONCLUSIONS
The dispersible paediatric levofloxacin formulation has improved bioavailability compared with the crushed non-dispersible adult formulation, but exposures remain below those in adults. We propose optimized age- and weight-based dosing for levofloxacin, which require further evaluation.
Topics: Adult; Child, Preschool; Humans; Biological Availability; Cross-Over Studies; Levofloxacin; Rifampin; Tablets; Infant
PubMed: 37596982
DOI: 10.1093/jac/dkad257 -
Expert Opinion on Drug Metabolism &... Dec 2023Advances in research and development (R&D) have enabled many approvals of antisense oligonucleotides (ASOs). Its administration expanded from systemic to local for... (Review)
Review
INTRODUCTION
Advances in research and development (R&D) have enabled many approvals of antisense oligonucleotides (ASOs). Its administration expanded from systemic to local for treating various diseases, where predicting target tissue exposures and pharmacokinetics (PK) and pharmacodynamics (PD) in human can be critical.
AREAS COVERED
A literature search for PBPK/PD models of ASOs was conducted using PubMed and Embase (to 1 April 2023). ASO PK and PD in animals and humans and modeling approaches including physiologically based (PB) are summarized; and relevance and impacts of PBPK/PD modeling are assessed.
EXPERT OPINION
Allometric scaling and compartmental PK/PD modeling have been successful to predict human ASO PK/PD, addressing most R&D needs. Understanding tissue distribution of ASOs can be crucial for their efficacy and safety especially for intrathecal (IT), pulmonary, or other local routes. PBPK/PD modeling is expected to improve such understanding, for which, efforts have been sporadic. However, developing a PBPK/PD model requires careful review of known biology/pharmacology and thoughtful experimental designs. Resulting models have the potential to predict target/specified tissue exposures and responses in human adults and pediatrics. Ultimately, a PBPK/PD modeling approach can lead to more efficient and rational clinical development, resulting in well-informed decision making and a shortened timeline.
Topics: Adult; Animals; Humans; Child; Oligonucleotides, Antisense; Models, Biological; Tissue Distribution; Lung; Pharmacokinetics
PubMed: 37970635
DOI: 10.1080/17425255.2023.2283524 -
Molecules (Basel, Switzerland) Aug 2023Tectorigenin is a well-known natural flavonoid aglycone and an active component that exists in numerous plants. Growing evidence suggests that tectorigenin has multiple... (Review)
Review
Tectorigenin is a well-known natural flavonoid aglycone and an active component that exists in numerous plants. Growing evidence suggests that tectorigenin has multiple pharmacological effects, such as anticancer, antidiabetic, hepatoprotective, anti-inflammatory, antioxidative, antimicrobial, cardioprotective, and neuroprotective. These pharmacological properties provide the basis for the treatment of many kinds of illnesses, including several types of cancer, diabetes, hepatic fibrosis, osteoarthritis, Alzheimer's disease, etc. The purpose of this paper is to provide a comprehensive summary and review of the sources, extraction and synthesis, pharmacological effects, toxicity, pharmacokinetics, and delivery strategy aspects of tectorigenin. Tectorigenin may exert certain cytotoxicity, which is related to the administration time and concentration. Pharmacokinetic studies have demonstrated that the main metabolic pathways in rats for tectorigenin are glucuronidation, sulfation, demethylation and methoxylation, but that it exhibits poor bioavailability. From our perspective, further research on tectorigenin should cover: exploring the pharmacological targets and mechanisms of action; finding an appropriate concentration to balance pharmacological effects and toxicity; attempting diversified delivery strategies to improve the bioavailability; and structural modification to obtain tectorigenin derivatives with higher pharmacological activity.
Topics: Rats; Animals; Isoflavones; Biological Availability; Flavonoids; Liver Cirrhosis
PubMed: 37570873
DOI: 10.3390/molecules28155904 -
The Journal of Pharmacology and... Dec 2023Agmatine, an endogenous polyamine, has been shown to reduce chronic pain behaviors in animal models and in patients. This reduction is due to inhibition of the GluN2B...
Agmatine, an endogenous polyamine, has been shown to reduce chronic pain behaviors in animal models and in patients. This reduction is due to inhibition of the GluN2B subunit of the N-methyl-D-aspartate receptor (NMDAR) in the central nervous system (CNS). The mechanism of action requires central activity, but the extent to which agmatine crosses biologic barriers such as the blood-brain barrier (BBB) and intestinal epithelium is incompletely understood. Determination of agmatine distribution is limited by analytical protocols with low sensitivity and/or inefficient preparation. This study validated a novel bioanalytical protocol using high-performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS) for quantification of agmatine in rat biologic matrices. These protocols were then used to determine the plasma pharmacokinetics of agmatine and the extent of distribution to the CNS. Precision and accuracy of the protocol met US Food and Drug Administration (FDA) standards in surrogate matrix as well as in corrected concentrations in appropriate matrices. The protocol also adequately withstood stability and dilution conditions. Upon application of this protocol to pharmacokinetic study, intravenous agmatine showed a half-life in plasma ranging between 18.9 and 14.9 minutes. Oral administration led to a prolonged plasma half-life (74.4-117 minutes), suggesting flip-flop kinetics, with bioavailability determined to be 29%-35%. Intravenous administration led to a rapid increase in agmatine concentration in brain but a delayed distribution and lower concentrations in spinal cord. However, half-life of agmatine in both tissues is substantially longer than in plasma. These data suggest that agmatine adequately crosses biologic barriers in rat and that brain and spinal cord pharmacokinetics can be functionally distinct. SIGNIFICANCE STATEMENT: Agmatine has been shown to be an effective nonopioid therapy for chronic pain, a significantly unmet medical necessity. Here, using a novel bioanalytical protocol for quantification of agmatine, we present the plasma pharmacokinetics and the first report of agmatine oral bioavailability as well as variable pharmacokinetics across different central nervous system tissues. These data provide a distributional rationale for the pharmacological effects of agmatine as well as new evidence for kinetic differences between brain and spinal cord.
Topics: Rats; Humans; Animals; Agmatine; Tissue Distribution; Chronic Pain; Tandem Mass Spectrometry; Spinal Cord; Brain; Biological Products
PubMed: 37770201
DOI: 10.1124/jpet.123.001828 -
Expert Opinion on Drug Metabolism &... 2023Perinatal asphyxia (PA) still causes significant morbidity and mortality. Therapeutic hypothermia (TH) is the only effective therapy for neonates with moderate to severe... (Review)
Review
INTRODUCTION
Perinatal asphyxia (PA) still causes significant morbidity and mortality. Therapeutic hypothermia (TH) is the only effective therapy for neonates with moderate to severe hypoxic-ischemic encephalopathy after PA. These neonates need additional pharmacotherapy, and both PA and TH may impact physiology and, consequently, pharmacokinetics (PK) and pharmacodynamics (PD).
AREAS COVERED
This review provides an overview of the available knowledge in PubMed (until November 2022) on the pathophysiology of neonates with PA/TH. In vivo pig models for this setting enable distinguishing the effect of PA versus TH on PK and translating this effect to human neonates. Available asphyxia pig models and methodological considerations are described. A summary of human neonatal PK of supportive pharmacotherapy to improve neurodevelopmental outcomes is provided.
EXPERT OPINION
To support drug development for this population, knowledge from clinical observations (PK data, real-world data on physiology), preclinical (in vitro and in vivo (minipig)) data, and molecular and cellular biology insights can be integrated into a predictive physiologically-based PK (PBPK) framework, as illustrated by the I-PREDICT project (Innovative physiology-based pharmacokinetic model to predict drug exposure in neonates undergoing cooling therapy). Current knowledge, challenges, and expert opinion on the future directions of this research topic are provided.
Topics: Humans; Animals; Infant, Newborn; Swine; Asphyxia; Models, Biological; Swine, Miniature; Hypothermia, Induced; Drug Development; Pharmacokinetics
PubMed: 37470686
DOI: 10.1080/17425255.2023.2237412 -
Clinical Pharmacokinetics Aug 2023High variability in vancomycin exposure in neonates requires advanced individualized dosing regimens. Achieving steady-state trough concentration (C) and steady-state...
BACKGROUND AND OBJECTIVE
High variability in vancomycin exposure in neonates requires advanced individualized dosing regimens. Achieving steady-state trough concentration (C) and steady-state area-under-curve (AUC) targets is important to optimize treatment. The objective was to evaluate whether machine learning (ML) can be used to predict these treatment targets to calculate optimal individual dosing regimens under intermittent administration conditions.
METHODS
C were retrieved from a large neonatal vancomycin dataset. Individual estimates of AUC were obtained from Bayesian post hoc estimation. Various ML algorithms were used for model building to C and AUC. An external dataset was used for predictive performance evaluation.
RESULTS
Before starting treatment, C can be predicted a priori using the Catboost-based C-ML model combined with dosing regimen and nine covariates. External validation results showed a 42.5% improvement in prediction accuracy by using the ML model compared with the population pharmacokinetic model. The virtual trial showed that using the ML optimized dose; 80.3% of the virtual neonates achieved the pharmacodynamic target (C in the range of 10-20 mg/L), much higher than the international standard dose (37.7-61.5%). Once therapeutic drug monitoring (TDM) measurements (C) in patients have been obtained, AUC can be further predicted using the Catboost-based AUC-ML model combined with C and nine covariates. External validation results showed that the AUC-ML model can achieve an prediction accuracy of 80.3%.
CONCLUSION
C-based and AUC-based ML models were developed accurately and precisely. These can be used for individual dose recommendations of vancomycin in neonates before treatment and dose revision after the first TDM result is obtained, respectively.
Topics: Infant, Newborn; Humans; Vancomycin; Bayes Theorem; Area Under Curve; Drug Monitoring; Anti-Bacterial Agents; Retrospective Studies
PubMed: 37300630
DOI: 10.1007/s40262-023-01265-z -
Drug Metabolism and Disposition: the... Oct 2023Antibody-drug conjugates (ADCs) are produced by the chemical linkage of cytotoxic agents and monoclonal antibodies. The complexity and heterogeneity of ADCs and the low... (Review)
Review
Antibody-drug conjugates (ADCs) are produced by the chemical linkage of cytotoxic agents and monoclonal antibodies. The complexity and heterogeneity of ADCs and the low concentration of cytotoxic agent released in vivo poses big challenges to their bioanalysis. Understanding the pharmacokinetic behavior, exposure-safety, and exposure-efficacy relationships of ADCs is needed for their successful development. Accurate analytical methods are required to evaluate intact ADCs, total antibody, released small molecule cytotoxins, and related metabolites. The selection of appropriate bioanalysis methods for comprehensive analysis of ADCs is mainly dependent on the properties of cytotoxic agents, the chemical linker, and the attachment sites. The quality of the information about the whole pharmacokinetic profile of ADCs has been improved due to the development and improvement of analytical strategies for detection of ADCs, such as ligand-binding assays and mass spectrometry-related techniques. In this article, we will focus on the bioanalytical assays that have been used in the pharmacokinetic study of ADCs and discuss their advantages, current limitations, and potential challenges. SIGNIFICANCE STATEMENT: This article describes bioanalysis methods which have been used in pharmacokinetic study of ADCs and discusses the advantages, disadvantages and potential challenges of these assays. This review is useful and helpful and will provide insights and reference for bioanalysis and development of ADCs.
Topics: Immunoconjugates; Tissue Distribution; Antibodies, Monoclonal; Antineoplastic Agents; Cytotoxins
PubMed: 37290939
DOI: 10.1124/dmd.123.001313