Building Confidence in Physiologically Based Pharmacokinetic Modeling of CYP3A Induction Mediated by Rifampin: An Industry Perspective.

Physiologically-based pharmacokinetic (PBPK) modeling offers a viable approach to predict induction drug-drug interactions (DDIs) with the potential to streamline or reduce clinical trial burden if predictions can be made with sufficient confidence. In the current work, the ability to predict the effect of rifampin, a well-characterized strong CYP3A4 inducer, on 20 CYP3A probes with publicly available PBPK models (often developed using a workflow with optimization following a strong inhibitor DDI study to gain confidence in fraction metabolized by CYP3A4, f, and fraction available after intestinal metabolism, Fg), was assessed. Substrates with a range of f (0.

Physiologically Based Pharmacokinetic modelling of drugs in pregnancy: A mini-review on availability and limitations.

Physiologically based pharmacokinetic (PBPK) modelling in pregnancy is a relatively new approach that is increasingly being used to assess drug systemic exposure in pregnant women to potentially inform dosing adjustments. Physiological changes throughout pregnancy are incorporated into mathematical models to simulate drug disposition in the maternal and fetal compartments as well as the transfer of drugs across the placenta. This mini-review gathers currently available pregnancy PBPK models for drugs commonly used during pregnancy.

Safety, tolerability, and pharmacokinetics of half-life extended SARS-CoV-2-neutralizing monoclonal antibodies AZD7442 (tixagevimab/cilgavimab) in healthy Japanese adults.

Introduction: The aim of this study was to evaluate the safety, tolerability, pharmacokinetics, and pharmacodynamics of AZD7442 (tixagevimab/cilgavimab) in healthy Japanese adults.

Methods: In this randomized, double-blind, placebo-controlled, phase 1 study, AZD7442 was administered intramuscularly (300 or 600 mg) or intravenously (300 or 1000 mg) to healthy Japanese adults. Primary endpoints were safety, tolerability, and pharmacokinetics.

Interlaboratory Variability in the Madin-Darby Canine Kidney Cell Proteome.

Madin-Darby canine kidney (MDCK) cells are widely used to study epithelial cell functionality. Their low endogenous drug transporter protein levels make them an amenable system to investigate transepithelial permeation and drug transporter protein activity after their transfection. MDCK cells display diverse phenotypic traits, and as such, laboratory-to-laboratory variability in drug permeability assessments is observed.

Safety, Tolerability and Pharmacokinetics of Half-Life Extended Severe Acute Respiratory Syndrome Coronavirus 2 Neutralizing Monoclonal Antibodies AZD7442 (Tixagevimab-Cilgavimab) in Healthy Adults.

Background: AZD7442 is a combination of extended half-life, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific neutralizing monoclonal antibodies (tixagevimab and cilgavimab).

Methods: This phase 1, first-in-human, randomized, double-blind, placebo-controlled, dose-escalation study evaluated AZD7442 administered intramuscularly (300 mg) or intravenously (300, 1000, or 3000 mg) in healthy adults (aged 18-55 years). The primary end point was safety and tolerability.

Evaluating the performance of machine-learning regression models for pharmacokinetic drug-drug interactions.

Combination therapy or concomitant drug administration can be associated with pharmacokinetic drug-drug interactions, increasing the risk of adverse drug events and reduced drug efficacy. Thus far, machine-learning models have been developed that can classify drug-drug interactions. However, to enable quantification of the pharmacokinetic effects of a drug-drug interaction, regression-based machine learning should be explored.

Comparing the applications of machine learning, PBPK, and population pharmacokinetic models in pharmacokinetic drug-drug interaction prediction.

The gold-standard approach for modeling pharmacokinetic mediated drug-drug interactions is the use of physiologically-based pharmacokinetic modeling and population pharmacokinetics. However, these models require extensive amounts of drug-specific data generated from a wide variety of in vitro and in vivo models, which are later refined with clinical data and system-specific parameters. Machine learning has the potential to be utilized for the prediction of drug-drug interactions much earlier in the drug discovery cycle, using inputs derived from, among others, chemical structure.

Harnessing Clinical Trial and Real-World Data Towards an Understanding of Sex Effects on Drug Pharmacokinetics, Pharmacodynamics and Efficacy.

Increasing clinical data on sex-related differences in drug efficacy and toxicity has highlighted the importance of understanding the impact of sex on drug pharmacokinetics and pharmacodynamics. Intrinsic differences between males and females, such as different CYP enzyme activity, drug transporter expression or levels of sex hormones can all contribute to different responses to medications. However, most studies do not include sex-specific investigations, leading to lack of sex-disaggregated pharmacokinetic and pharmacodynamic data.

Development of and insights from systems pharmacology models of antibody-drug conjugates.

Antibody-drug conjugates (ADCs) have gained traction in the oncology space in the past few decades, with significant progress being made in recent years. Although the use of pharmacometric modeling is well-established in the drug development process, there is an increasing need for a better quantitative biological understanding of the pharmacokinetic and pharmacodynamic relationships of these complex molecules. Quantitative systems pharmacology (QSP) approaches can assist in this endeavor; recent computational QSP models incorporate ADC-specific mechanisms and use data-driven simulations to predict experimental outcomes.

Unraveling pleiotropic effects of rifampicin by using physiologically based pharmacokinetic modeling: Assessing the induction magnitude of P-glycoprotein-cytochrome P450 3A4 dual substrates.

Rifampicin induces both P-glycoprotein (P-gp) and cytochrome P450 3A4 (CYP3A4) through regulating common nuclear receptors (e.g., pregnane X receptor).

Tumour-on-chip microfluidic platform for assessment of drug pharmacokinetics and treatment response.

Microphysiological in vitro systems are platforms for preclinical evaluation of drug effects and significant advances have been made in recent years. However, existing microfluidic devices are not yet able to deliver compounds to cell models in a way that reproduces the real physiological drug exposure. Here, we introduce a novel tumour-on-chip microfluidic system that mimics the pharmacokinetic profile of compounds on 3D tumour spheroids to evaluate their response to the treatments.

ALT neuroblastoma chemoresistance due to telomere dysfunction-induced ATM activation is reversible with ATM inhibitor AZD0156.

Cancers overcome replicative immortality by activating either telomerase or an alternative lengthening of telomeres (ALT) mechanism. ALT occurs in ~25% of high-risk neuroblastomas, and progression in patients with ALT neuroblastoma during or after front-line therapy is frequent and often fatal. Temozolomide + irinotecan is commonly used as salvage therapy for neuroblastoma.

Mechanistic physiology-based pharmacokinetic modeling to elucidate vincristine-induced peripheral neuropathy following treatment with novel kinase inhibitors.

Purpose: Limited information is available regarding the drug-drug interaction (DDI) potential of molecular targeted agents and rituximab plus cyclophosphamide, doxorubicin (hydroxydaunorubicin), vincristine (Oncovin), and prednisone (R-CHOP) therapy. The addition of the Bruton tyrosine kinase (BTK) inhibitor ibrutinib to R-CHOP therapy results in increased toxicity versus R-CHOP alone, including higher incidence of peripheral neuropathy. Vincristine is a substrate of P-glycoprotein (P-gp, ABCB1); drugs that inhibit P-gp could potentially cause increased toxicity when co-administered with vincristine through DDI.

Blood retinal barrier and ocular pharmacokinetics: Considerations for the development of oncology drugs.

Tyrosine kinase inhibitors (TKIs) are an example of targeted drug therapy to treat cancer while minimizing damage to healthy tissue. In contrast to traditional oncology drugs, the toxicity profile of targeted therapies is less well understood and can include severe ocular adverse events, which are among the most common toxicity reported by these therapeutics. Inhibition of Mer receptor tyrosine kinase (MERTK) promotes innate tumor immunity by decreasing M2-macrophage polarization and efferocytosis.

Food constituent- and herb-drug interactions in oncology: Influence of quantitative modelling on Drug labelling.

Aims: Herbal products, spices and/or fruits are perceived as inherently healthy; for instance, St. John's wort (SJW) is marketed as a natural antidepressant and patients often self-administer it concomitantly with oncology medications. However, food constituents/herbs can interfere with drug pharmacokinetics, with risk of altering pharmacodynamics and efficacy.

Model-Informed Pediatric Dose Selection for Dapagliflozin by Incorporating Developmental Changes.

This analysis reports a quantitative modeling and simulation approach for oral dapagliflozin, a primarily uridine diphosphate-glucuronosyltransferase (UGT)-metabolized human sodium-glucose cotransporter 2 selective inhibitor. A mechanistic dapagliflozin physiologically based pharmacokinetic (PBPK) model was developed using in vitro metabolism and clinical pharmacokinetic (PK) data and verified for context of use (e.g.

Pharmacokinetics under the COVID-19 storm.

Aims: The storm-like nature of the health crises caused by COVID-19 has led to unconventional clinical trial practices such as the relaxation of exclusion criteria. The question remains: how can we conduct diverse trials without exposing subgroups of populations to potentially harmful drug exposure levels? The aim of this study was to build a knowledge base of the effect of intrinsic/extrinsic factors on the disposition of several repurposed COVID-19 drugs.

Methods: Physiologically based pharmacokinetic (PBPK) models were used to study the change in the pharmacokinetics (PK) of drugs repurposed for COVID-19 in geriatric patients, different race groups, organ impairment and drug-drug interactions (DDIs) risks.

Brain exposure of the ATM inhibitor AZD1390 in humans-a positron emission tomography study.

Background: The protein kinase ataxia telangiectasia mutated (ATM) mediates cellular response to DNA damage induced by radiation. ATM inhibition decreases DNA damage repair in tumor cells and affects tumor growth. AZD1390 is a novel, highly potent, selective ATM inhibitor designed to cross the blood-brain barrier (BBB) and currently evaluated with radiotherapy in a phase I study in patients with brain malignancies.

A Laboratory-Specific Scaling Factor to Predict the In Vivo Human Clearance of Aldehyde Oxidase Substrates.

Aldehyde oxidase (AO) efficiently metabolizes a range of compounds with N-containing heterocyclic aromatic rings and/or aldehydes. The limited knowledge of AO activity and abundance (in vitro and in vivo) has led to poor prediction of in vivo systemic clearance (CL) using in vitro-to-in vivo extrapolation approaches, which for drugs in development can lead to their discontinuation. We aimed to identify appropriate scaling factors to predict AO CL of future new chemical entities (NCEs).

Pediatric Pharmacokinetics and Dose Predictions: A Report of a Satellite Meeting to the 10th Juvenile Toxicity Symposium.

On April 24, 2019, a symposium on Pediatric Pharmacokinetics and Dose Predictions was held as a satellite meeting to the 10th Juvenile Toxicity Symposium. This symposium brought together scientists from academia, industry, and clinical research organizations with the aim to update each other on the current knowledge on pediatric drug development. Through more knowledge on specific ontogeny profiles of drug metabolism and transporter proteins, integrated into physiologically-based pharmacokinetic (PBPK) models, we have gained a more integrated understanding of age-related differences in pharmacokinetics (PKs), Relevant examples were presented during the meeting.

The Pharmacokinetic-Pharmacodynamic (PKPD) Relationships of AZD3229, a Novel and Selective Inhibitor of KIT, in a Range of Mouse Xenograft Models of GIST.

Purpose: The emergence of secondary mutations is a cause of resistance to current KIT inhibitors used in the treatment of patients with gastrointestinal stromal tumors (GIST). AZD3229 is a selective inhibitor of wild-type KIT and a wide spectrum of primary and secondary mutations seen in patients with GIST. The objective of this analysis is to establish the pharmacokinetic-pharmacodynamic (PKPD) relationship of AZD3229 in a range of mouse GIST tumor models harboring primary and secondary KIT mutations, and to benchmark AZD3229 against other KIT inhibitors.