PKPD modeling of acquired resistance to anti-cancer drug treatment

Miro J. Eigenmann,Nicolas Frances,Thierry Lavé,Antje-Christine Walz

doi:10.1007/s10928-017-9553-x

Abstract

Non-small cell lung cancer (NSCLC) patients greatly benefit from the treatment with tyrosine kinase inhibitors (TKIs) targeting the epidermal growth factor receptor (EGFR). However, emergence of acquired resistance inevitable occurs after long-term treatment in most patients and limits clinical improvement. In the present study, resistance to drug treatment in patient-derived NSCLC xenograft mice was assessed and modeling and simulation was applied to understand the dynamics of drug resistance as a basis to explore more beneficial drug regimen. Two semi-mechanistic models were fitted to tumor growth inhibition profiles during and after treatment with erlotinib or gefitinib. The base model proposes that as a result of drug treatment, tumor cells stop proliferating and undergo several stages of damage before they eventually die. The acquired resistance model adds a resistance term to the base model which assumes that resistant cells are emerging from the pool of damaged tumor cells. As a result, tumor cells sensitive to drug treatment will either die or be converted to a drug resistant cell population which is proliferating at a slower growth rate as compared to the sensitive cells. The observed tumor growth profiles were better described by the resistance model and emergence of resistance was concluded. In simulation studies, the selection of resistant cells was explored as well as the time-variant fraction of resistant over sensitive cells. The proposed model provides insight into the dynamic processes of emerging resistance. It predicts tumor regrowth during treatment driven by the selection of resistant cells and explains why faster tumor regrowth may occur after discontinuation of TKI treatment. Finally, it is shown how the semi-mechanistic model can be used to explore different scenarios and to identify optimal treatment schedules in clinical trials.

Highlights

Targeted therapies such as tyrosine kinase inhibitors (TKIs) are widely used for cancer treatment
Resistance to drug treatment in patient-derived Non-small cell lung cancer (NSCLC) xenograft mice was assessed and modeling and simulation was applied to understand the dynamics of drug resistance as a basis to explore more beneficial drug regimen
PKPD model reveals acquired resistance in patient derived xenograft mice Data exploration (Fig. 2) shows dose dependent tumor growth inhibition in patient-derived NSCLC xenograft mice treated with erlotinib or gefitinib

Summary

Introduction

Targeted therapies such as tyrosine kinase inhibitors (TKIs) are widely used for cancer treatment. First generation of TKI includes erlotinib and gefitinib, two small molecule drugs with similar chemical structures which have been approved for the treatment of NSCLC [1,2,3] and subsequently of various solid epidermoid cancers [4, 5]. Both molecules target the ATP binding site of EGFR and inhibit EGFR-induced activation of downstream signaling [6]. Primary resistance, referring to patients who are not responsive to the drug treatment and secondary or acquired resistance, which is usually defined as progression of disease after an initial period of clinical benefit while the patient is still under treatment [9]

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