Evaluation of gender differences in the pharmacokinetics of oral zileuton nanocrystalline formulation using a rat model

Zileuton is a leukotriene inhibitor used to treat asthma. As a BCS class II drug it exhibits challenges with solubility which likely impact its absorption. As patient gender significantly impacts the pharmacokinetics of many drugs, this study aimed to investigate potential gender-based pharmacokinetic differences after oral zileuton administration in rats. Male and female Sprague Dawley rats received single oral gavage doses of pure zileuton as an active pharmaceutical ingredient (30 mg/kg body weight (bw)), physical mixture (PM; at 30 mg/kg bw of the formulation contains zileuton, kollidon VA64 fine, dowfax2A1 and trehalose), and nanocrystalline formulation of zileuton (NfZ; at 30 mg/kg bw of the formulation). Plasma, tissue, and urine concentrations were quantified using high performance liquid chromatography (HPLC). Noncompartmental pharmacokinetic analysis showed higher zileuton levels in the plasma of female versus male rats across all evaluated forms of zileuton (API, PM, and NfZ). Female rats demonstrated higher peak plasma concentrations (Cmax) and increased area under the plasma concentration-time curve (AUC) relative to males, regardless of formulation. These findings reveal substantial gender disparities in the pharmacokinetics of zileuton in the rat model. This study emphasizes the critical need to evaluate gender differences during preclinical drug development to enable gender-based precision dosing strategies for equivalent efficacy/safety outcomes in male and female patients. Additional studies are warranted to investigate underlying mechanisms of such pharmacokinetic gender divergences.

Pharmacological Activities of Plant-Derived Fraxin with Molecular Mechanisms: A Comprehensive Review

Fruits and vegetables serve not only as sources of nutrition but also as medicinal agents for the treatment of diverse diseases and maladies. These dietary components are significant resources of phytochemicals that demonstrate therapeutic properties against many illnesses. Fraxin is a naturally occurring coumarin glycoside mainly present in various species of Fraxinus genera, having a multitude of therapeutic uses against various diseases and disorders. This study focuses to investigate the pharmacological activities, botanical sources, and biopharmaceutical profile of the phytochemical fraxin based on different preclinical and non-clinical studies to show the scientific evidence and to evaluate the underlying molecular mechanisms of the therapeutic effects against various ailments. For this, data was searched and collected (as of February 15, 2024) in a variety of credible electronic databases, including PubMed/Medline, Scopus, Springer Link, ScienceDirect, Wiley Online, Web of Science, and Google Scholar. The findings demonstrated favorable outcomes in relation to a range of diseases or medical conditions, including inflammation, neurodegenerative disorders such as cerebral ischemia-reperfusion (I/R) and depression, viral infection, as well as diabetic nephropathy. The phytochemical also showed protective effects such as osteoprotective, renoprotective, pulmoprotective, hepatoprotective, and gastroprotective effects due to its antioxidant capacity. Fraxin has a great capability to diminish oxidative stress-related damage in different organs by stimulating the antioxidant enzymes, downregulating nuclear factor kappa B and NLRP3, and triggering the Nrf2/ARE signaling pathways. Fraxin exhibited poor oral bioavailability because of reduced absorption and a wide distribution into tissues of different organs. However, extensive research is required to decipher the biopharmaceutical profiles, and clinical studies are necessary to establish the efficacy of the natural compound as a reliable therapeutic agent.

Model-Informed Dose Selection for a Novel Human Immunoglobulin G4 Derived Monoclonal Antibody Targeting Proprotein Convertase Kwashiorkor Type 9: Insights from Population Pharmacokinetics-Pharmacodynamics and Systems Pharmacology

Monoclonal antibody drugs targeting proprotein convertase kwashiorkor type 9 (PCSK9) have recently demonstrated remarkable success in lipid-lowering therapies. Specifically, antibodies derived from immunoglobulin G1 (IgG1, alirocumab) and IgG2 (evolocumab) have been successfully utilized for this purpose. Recently, a novel recombinant fully human anti-PCSK9 monoclonal antibody, originally derived from IgG4 and designated as SAL003, was developed. This study aimed to explore the pharmacokinetics, efficacy, and safety of SAL003 in both single and multiple administrations. The investigation included both healthy individuals and individuals with hyperlipidemia. To comprehensively grasp the pharmacokinetic (PK) and pharmacodynamic (PD) attributes of SAL003, this study employed population PK-PD (popPK-PD) and mechanistic systems pharmacology (MSP) modeling. These models were employed for predicting low-density lipoprotein cholesterol (LDLc) concentrations and appropriate dosages across diverse potential clinical scenarios. The research results indicated that SAL003 demonstrated comparable pharmacokinetic properties to evolocumab, exhibited notable effectiveness in reducing lipid levels, and was confirmed to be safe and well-tolerated in both healthy individuals and individuals with hyperlipidemia. Notably, SAL003 displayed differing effectiveness between patients and healthy populations. This discrepancy was observed in the popPK-PD model, with a positive population influence on Emax, and the MSP model, indicating elevated PCSK9 clearance and LDLr-related LDLc clearance in the healthy group. Simulation results from the popPK-PD and MSP models indicated a dosage of 140 mg of Q4W and 420 mg of Q8W for phase II/III clinical trials. Reducing the drug dose or extending the dosing intervals may result in treatment failure. Additionally, the simultaneous use of statins led to elevated PCSK9 levels and intensified fluctuations in steady-state LDLc levels during SAL003 treatment.

Efficacy of Rotundic Acid and Its Derivatives as Promising Natural Anticancer Triterpenoids: A Literature-Based Study

Rotundic acid (RA) is a naturally occurring pentacyclic triterpene with a multitude of pharmacological activities. The primary emphasis of this study is on summarizing the anticancer properties with the underlying mechanisms of RA and its derivatives, as well as the pharmacokinetic features. Data was collected (up to date as of November 10, 2023) from various reliable and authentic literatures by searching in different academic search engines, including PubMed, Springer Link, Scopus, Wiley Online, Web of Science, ScienceDirect, and Google Scholar. The findings imply that RA and its synthetic derivatives possess promising anti-cancer properties against breast, colorectal, liver, and cervical cancers in various preclinical pharmacological test systems. The results also indicate that RA and its derivatives demonstrated anticancer effects via a number of cellular mechanisms, including apoptotic cell death, inhibition of oxidative stress, anti-inflammatory effect, cytotoxicity, cell cycle arrest, anti-proliferative effect, anti-angiogenic effect, and inhibition of cancer cell migration and invasion. It has been proposed that RA and its derived compounds have the capability to serve as a hopeful chemotherapeutic agent, so further extensive clinical research is necessary.

Pharmacokinetics-Pharmacodynamics Modeling and Evaluation of Tumor Response to Bortezomib Proteasome Inhibitor in Waldenstrom Macroglobulinemia

BACKGROUND

Waldenstrom's macroglobulinemia (WM), also known as lymphoplasmacytic lymphoma, is a type of non-Hodgkin's lymphoma in which the malignant cells produce many macroglobulin proteins. It originates from B cells and develops in the bone marrow, where Wm cells combine to produce distinct types of blood cells, resulting in reduced volumes of red blood cells, white blood cells, and platelets, making it harder for the body to fight diseases. Chemoimmunotherapy is being used for the clinical management of WM, but new targeted agents, the BTK inhibitor ibrutinib and the proteasome inhibitor bortezomib, have shown significant improvements in patients with relapsed/refractory WM. However, given its effectiveness, drug resistance and relapse are normal, and there is little research on the pathways responsible for drug effects on the tumor.

METHODS

In this study, Pharmacokinetics-pharmacodynamic simulations were done to assess the effect of the proteasome inhibitor bortezomib on the tumor. For this purpose, the Pharmacokinetics-pharmacodynamic model was developed. The model parameters were determined and calculated using the Ordinary Differential Equation solver toolbox and the least-squares function. Pharmacokinetic profiles and pharmacodynamic analysis were performed to determine the change in tumor weight associated with the use of proteasome inhibitors.

RESULTS

Bortezomib and ixazomib have been found to reduce tumor weight briefly, but once the dose is reduced, the tumor begins to grow again. Carfilzomib and oprozomib had better results, and rituximab reduced tumor weight more effectively.

CONCLUSION

Once validated, it is proposed that a combination of selected drugs can be evaluated in the laboratory to treat WM.

Review of Metabolomics-Based Biomarker Research for Parkinson's Disease

Parkinson's disease (PD), as the second most common neurodegenerative disease, is seriously affecting the life quality of the elderly. However, there is still a lack of efficient medical methods to diagnosis PD before apparent symptoms occur. In recent years, clinical biomarkers including genetic, imaging, and tissue markers have exhibited remarkable benefits in assisting PD diagnoses. Due to the advantages of high-throughput detection of metabolites and almost non-invasive sample collection, metabolomics research of PD is widely used for diagnostic biomarker discovery. However, there are also a few shortages for those identified biomarkers, such as the scarcity of verifications regarding the sensitivity and specificity. Thus, reviewing the research progress of PD biomarkers based on metabolomics techniques is of great significance for developing PD diagnosis. To comprehensively clarify the progress of current metabolic biomarker studies in PD, we reviewed 20 research articles regarding the discovery and validation of biomarkers for PD diagnosis from three mainstream academic databases (NIH PubMed, ISI Web of Science, and Elsevier ScienceDirect). By analyzing those materials, we summarized the metabolic biomarkers identified by those metabolomics studies and discussed the potential approaches used for biomarker verifications. In conclusion, this review provides a comprehensive and updated overview of PD metabolomics research in the past two decades and particularly discusses the validation of disease biomarkers. We hope those discussions might provide inspiration for PD biomarker discovery and verification in the future.

New approaches for developing multi-targeted drug combinations for disease modification of complex brain disorders. Does epilepsy prevention become a realistic goal?

Over decades, the prevailing standard in drug discovery was the concept of designing highly selective compounds that act on individual drug targets. However, more recently, multi-target and combinatorial drug therapies have become an important treatment modality in complex diseases, including neurodegenerative diseases such as Alzheimer's and Parkinson's disease. The development of such network-based approaches is facilitated by the significant advance in our understanding of the pathophysiological processes in these and other complex brain diseases and the adoption of modern computational approaches in drug discovery and repurposing. However, although drug combination therapy has become an effective means for the symptomatic treatment of many complex diseases, the holy grail of identifying clinically effective disease-modifying treatments for neurodegenerative and other brain diseases remains elusive. Thus, despite extensive research, there remains an urgent need for novel treatments that will modify the progression of the disease or prevent its development in patients at risk. Here we discuss recent approaches with a focus on multi-targeted drug combinations for prevention or modification of epilepsy. Over the last ~10 years, several novel promising multi-targeted therapeutic approaches have been identified in animal models. We envision that synergistic combinations of repurposed drugs as presented in this review will be demonstrated to prevent epilepsy in patients at risk within the next 5-10 years.

Pharmacodynamics-based approach for efficacious human dose projection of BMS-986260, a small molecule transforming growth factor beta receptor 1 inhibitor

Transforming growth factor beta (TGF-β) is a pleiotropic cytokine that has a wide array of biological effects. For decades, tumor biology implicated TGF-β as an attractive therapeutic target due to its immunosuppressive effects. Toward this end, multiple pharmaceutical companies developed a number of drug modalities that specifically target the TGF-β pathway. BMS-986260 is a small molecule, selective TGF-βR1 kinase inhibitor that was under preclinical development for oncology. In vivo studies across mouse, rat, dog, and monkey and cryopreserved hepatocytes predicted human pharmacokinetics (PK) and distribution of BMS-986260. Efficacy studies of BMS-986260 were undertaken in the MC38 murine colon cancer model, and target engagement, as measured by phosphorylation of SMAD2/3, was assessed in whole blood to predict the clinical efficacious dose. The human clearance is predicted to be low, 4.25 ml/min/kg. BMS-986260 provided a durable and robust antitumor response at 3.75 mg/kg daily and 1.88 mg/kg twice-daily dosing regimens. Phosphorylation of SMAD2/3 was 3.5-fold less potent in human monocytes than other preclinical species. Taken together, the projected clinical efficacious dose was 600 mg QD or 210 mg BID for 3 days followed by a 4-day drug holiday. Mechanism-based cardiovascular findings in the rat ultimately led to the termination of BMS-986260. This study describes the preclinical PK characterization and pharmacodynamics-based efficacious dose projection of a novel small molecule TGF-βR1 inhibitor.

In-Silico Modeling in Drug Metabolism and Interaction: Current Strategies of Lead Discovery

BACKGROUND

Drug metabolism is a complex mechanism of human body systems to detoxify foreign particles, chemicals, and drugs through bio alterations. It involves many biochemical reactions carried out by invivo enzyme systems present in the liver, kidney, intestine, lungs, and plasma. After drug administration, it crosses several biological membranes to reach into the target site for binding and produces the therapeutic response. After that, it may undergo detoxification and excretion to get rid of the biological systems. Most of the drugs and its metabolites are excreted through kidney via urination. Some drugs and their metabolites enter into intestinal mucosa and excrete through feces. Few of the drugs enter into hepatic circulation where they go into the intestinal tract. The drug leaves the liver via the bile duct and is excreted through feces. Therefore, the study of total methodology of drug biotransformation and interactions with various targets is costly.

METHODS

To minimize time and cost, in-silico algorithms have been utilized for lead-like drug discovery. Insilico modeling is the process where a computer model with a suitable algorithm is developed to perform a controlled experiment. It involves the combination of both in-vivo and in-vitro experimentation with virtual trials, eliminating the non-significant variables from a large number of variable parameters. Whereas, the major challenge for the experimenter is the selection and validation of the preferred model, as well as precise simulation in real physiological status.

RESULTS

The present review discussed the application of in-silico models to predict absorption, distribution, metabolism, and excretion (ADME) properties of drug molecules and also access the net rate of metabolism of a compound.

CONCLUSION

It helps with the identification of enzyme isoforms; which are likely to metabolize a compound, as well as the concentration dependence of metabolism and the identification of expected metabolites. In terms of drug-drug interactions (DDIs), models have been described for the inhibition of metabolism of one compound by another, and for the compound-dependent induction of drug-metabolizing enzymes.

Band-selective excitation NMR spectroscopy and quantitative time-domain analysis using Complete Reduction to Amplitude-Frequency Table (CRAFT) to determine distribution coefficients during drug development

A sensitive quantitative ¹ H NMR method for determining distribution or partition coefficients has been developed that is applicable to early drug discovery. After partitioning and equilibration, aliquots from each layer are analyzed using band-selective excitation ¹ H NMR spectroscopy in regions that are free of 1-octanol and water solvent signals. Signals are quantitated directly using CRAFT software, and their amplitudes are adjusted to correct for nonuniformity within the excitation band. Using this approach, the distribution coefficients for 20 drugs present at low concentrations were determined giving values that were in excellent agreement with literature values.

TGI-Simulator: a visual tool to support the preclinical phase of the drug discovery process by assessing in silico the effect of an anticancer drug

This paper presents TGI-Simulator, a software tool designed to show, through a 2-D graphical animation, the simulated time effect of an anticancer drug on a tumor mass by exploiting the well-known Tumor Growth Inhibition (TGI) model published by Simeoni et al. [1]. Simeoni TGI model is a mathematical model routinely used by pharma companies and researchers during the drug development process. The application is based on a Java graphical user interface (GUI) including a self installing differential equation solver implemented in Matlab together with an optimization algorithm that performs model identification via Weighted Least Squares (WLS). However, it can graphically show also the simulation results obtained within other scientific software tools, if they are preventively stored into a suitable ASCII file. The tool would be a valid support also for researchers with no specific skills in scientific calculations and in pharmacokinetic and pharmacodynamic modeling but daily involved in pharma companies drug development processes at different levels. The availability of a movie with a temporal varying 2-D iconographic representation is an original instrument to communicate results and learn Simeoni TGI model and its potential application in preclinical studies.

One-step method for plasma determination of ibuprofen by chemiluminescence-coupled ultrafiltration and application in a pharmacokinetic study

A simple one-step method is established for plasma determination of ibuprofen and its pharmacokinetic study. The method involves simple sample pre-treatment by dilution, rapid separation by ultrafiltration (UF) and online sensitive detection by chemiluminescence (CL) based on significant intensity enhancement of ibuprofen on the weak CL of potassium permanganate and sodium sulphite in an acidic system. The calibration curve for ibuprofen is linear in the range 0.1-50.0 µg/mL in rat plasma. Average recoveries of ibuprofen at 0.80, 12.0 and 40.0 µg/mL amounted to 98.0 ± 4.2%, 101.2 ± 3.6% and 99.3 ± 5.4%, respectively. Standard deviations of intra- and inter-day measurement precision and accuracy are within ±10.0%. The detection limit for ibuprofen is 10.0 µg/L in plasma samples. Pharmacokinetic study of ibuprofen by the validated method shows that the mean plasma drug concentration-time course confirms to a classical two-compartment open model with first-order absorption. The proposed method will be an alternative for pre-clinical pharmacokinetic study of ibuprofen and other non-steroidal anti-inflammatory drugs.