A pharmacokinetic–pharmacodynamic model predicting tumour growth inhibition after intermittent administration with the mTOR kinase inhibitor AZD8055

Yates, James; Holt, Sarah; Logié, Armelle; Payne, Kirsty; Woods, Karen; Wilkinson, Robert W.; Davies, Barry R.; Guichard, Sylvie

doi:10.1111/bph.13886

Cited by 7 publications

(4 citation statements)

References 32 publications

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“…Tumor growth dynamics of two cell lines of breast cancer (HER2+ and Triple Negative) were modelled in the absence (unperturbed) or presence (perturbed) of MBQ-167 using the model proposed by Simeoni et al [ 10 ]. There is vast scientific evidence regarding the ability of the model to quantitatively characterize the time-course of tumor dynamics in xenograft experiments and evaluate the efficacy of anticancer drugs early in discovery and development [ 15 , 34 , 35 , 36 , 37 , 38 , 39 , 40 ]. The mathematical framework allowed for an adequate prediction of the tumor dynamics under the different groups considered.…”

Section: Discussionmentioning

confidence: 99%

Physiologically-Based Pharmacokinetic/Pharmacodynamic Model of MBQ-167 to Predict Tumor Growth Inhibition in Mice

et al. 2020

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MBQ-167 is a dual inhibitor of the Rho GTPases Rac and Cdc42 that has shown promising results as an anti-cancer therapeutic at the preclinical stage. This drug has been tested in vitro and in vivo in metastatic breast cancer mouse models. The aim of this study is to develop a physiologically based pharmacokinetic/pharmacodynamic (PBPK-PD) model of MBQ-167 to predict tumor growth inhibition following intraperitoneal (IP) administration in mice bearing Triple Negative and HER2+ mammary tumors. PBPK and Simeoni tumor growth inhibition (TGI) models were developed using the Simcyp V19 Animal Simulator. Our developed PBPK framework adequately describes the time course of MBQ-167 in each of the mouse tissues (e.g., lungs, heart, liver, kidneys, spleen, plasma) and tumor, since the predicted results were consistent with the experimental data. The developed PBPK-PD model successfully predicts tumor shrinkage in HER2+ and triple-negative breast tumors after the intraperitoneal administration of 1 and 10 mg/kg body weight (BW) dose level of MBQ-167 three times a week. The findings from this study suggest that MBQ-167 has a higher net effect and potency inhibiting Triple Negative mammary tumor growth compared to HER2+ and that liver metabolism is the major route of elimination of this drug.

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Section: Discussionmentioning

confidence: 99%

Physiologically-Based Pharmacokinetic/Pharmacodynamic Model of MBQ-167 to Predict Tumor Growth Inhibition in Mice

et al. 2020

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“…The performance of gefitinib, a EGFR inhibitor, in treating intracerebral tumours was evaluated by a PBPK/PD model, which showed how intra-tumour non-uniformity could lead to variable drug exposure and pharmacological effects within the tumour, and how the model could be utilised to reshape the treatment regimen with an alternative dosage schedule [13]. Based on in vivo data, a PK/PD model for tumour growth inhibitor AZD8055 was built and further refined by using human tumour xenograft model with different drug sensitivities and cell growth rates towards optimising the drug dose and administration route [14].…”

Section: Pharmacokinetics/pharmacodynamics-based Compartmental Modelsmentioning

confidence: 99%

Computational modelling of drug delivery to solid tumour: Understanding the interplay between chemotherapeutics and biological system for optimised delivery systems

Zhan

Alamer

2018

Advanced Drug Delivery Reviews

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Drug delivery to solid tumour involves multiple physiological, biochemical and biophysical processes taking place across a wide range of length and time scales. The therapeutic efficacy of anticancer drugs is influenced by the complex interplays among the intrinsic properties of tumours, biophysical aspects of drug transport and cellular uptake. Mathematical and computational modelling allows for a well-controlled study on the individual and combined effects of a wide range of parameters on drug transport and therapeutic efficacy, which would not be possible or economically viable through experimental means. A wide spectrum of mathematical models has been developed for the simulation of drug transport and delivery in solid tumours, including PK/PD-based compartmental models, microscopic and macroscopic transport models, and molecular dynamics drug loading and release models. These models have been used as a tool to identify the limiting factors and for optimal design of efficient drug delivery systems. This article gives an overview of the currently available computational models for drug transport in solid tumours, together with their applications to novel drug delivery systems, such as nanoparticle-mediated drug delivery and convection-enhanced delivery.

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“…AZD8055 can inhibit mTORC1, mTORC2 and its downstream proteins through phosphorylation and markedly increase the survival of AML transplanted mice due to supress tumor growth [ 52 ]. Synergistic combinations of chemotherapy with low-dose AZD8055 could be more effective.…”

Section: Protein Serine/threonine Kinase Inhibitorsmentioning

confidence: 99%

Protein kinase inhibitors for acute leukemia

et al. 2018

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Conventional treatments for acute leukemia include chemotherapy, radiation therapy, and intensive combined treatments (including bone marrow transplant or stem cell transplants). Novel treatment approaches are in active development. Recently, protein kinase inhibitors are on clinical trials and offer hope as new drugs for acute leukemia treatment. This review will provide a brief summary of the protein kinase inhibitors in clinical applications for acute leukemia treatment.

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A pharmacokinetic–pharmacodynamic model predicting tumour growth inhibition after intermittent administration with the mTOR kinase inhibitor AZD8055

Cited by 7 publications

References 32 publications

Physiologically-Based Pharmacokinetic/Pharmacodynamic Model of MBQ-167 to Predict Tumor Growth Inhibition in Mice

Physiologically-Based Pharmacokinetic/Pharmacodynamic Model of MBQ-167 to Predict Tumor Growth Inhibition in Mice

Computational modelling of drug delivery to solid tumour: Understanding the interplay between chemotherapeutics and biological system for optimised delivery systems

Protein kinase inhibitors for acute leukemia

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