Mathematical modeling of tumor growth and tumor growth inhibition in oncology drug development

Bernard, Apexa; Kimko, Holly; Mital, Dinesh P.; Poggesi, Italo

doi:10.1517/17425255.2012.693480

Cited by 45 publications

(21 citation statements)

References 62 publications

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“…Modeling the complex time course and temporal delay of anticancer agents was successful by introducing a series of transit compartments that were related to a cascade of kinetic events that yield drug effects (Lobo and Balthasar, 2002). Tumor growth kinetics were included in similar models to characterize tumor growth inhibition of anticancer drugs (Simeoni et al, 2004; Bernard et al, 2012), while a semi-mechanistic transit compartment tumor kill PK/PD model was used to describe anti-tumor activity of Trastuzumab-DMI (Jumbe et al, 2010). Finally, target binding kinetics may be an important consideration for compounds that bind tightly to the receptor target.…”

Section: Data Analysis and Interpretation Of Pk/pd Studiesmentioning

confidence: 99%

Implementation of pharmacokinetic and pharmacodynamic strategies in early research phases of drug discovery and development at Novartis Institute of Biomedical Research

et al. 2014

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Characterizing the relationship between the pharmacokinetics (PK, concentration vs. time) and pharmacodynamics (PD, effect vs. time) is an important tool in the discovery and development of new drugs in the pharmaceutical industry. The purpose of this publication is to serve as a guide for drug discovery scientists toward optimal design and conduct of PK/PD studies in the research phase. This review is a result of the collaborative efforts of DMPK scientists from various Metabolism and Pharmacokinetic (MAP) departments of the global organization Novartis Institute of Biomedical Research (NIBR). We recommend that PK/PD strategies be implemented in early research phases of drug discovery projects to enable successful transition to drug development. Effective PK/PD study design, analysis, and interpretation can help scientists elucidate the relationship between PK and PD, understand the mechanism of drug action, and identify PK properties for further improvement and optimal compound design. Additionally, PK/PD modeling can help increase the translation of in vitro compound potency to the in vivo setting, reduce the number of in vivo animal studies, and improve translation of findings from preclinical species into the clinical setting. This review focuses on three important elements of successful PK/PD studies, namely partnership among key scientists involved in the study execution; parameters that influence study designs; and data analysis and interpretation. Specific examples and case studies are highlighted to help demonstrate key points for consideration. The intent is to provide a broad PK/PD foundation for colleagues in the pharmaceutical industry and serve as a tool to promote appropriate discussions on early research project teams with key scientists involved in PK/PD studies.

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Section: Data Analysis and Interpretation Of Pk/pd Studiesmentioning

confidence: 99%

Implementation of pharmacokinetic and pharmacodynamic strategies in early research phases of drug discovery and development at Novartis Institute of Biomedical Research

et al. 2014

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“…In our approach, a tumor growth model was first established to characterize tumor growth curves in the vehicle control group. Typical tumor growth curves in nonclinical tumor models are known to follow an exponential growth in the early phases followed by a linear growth, and then eventually reach a plateau phase (Bissery et al, 1996;Bernard et al, 2012). Accordingly, the individual tumor growth curves in the vehicle control group were first modeled by using a first-order growth rate with and without a logistic function that constrains the maximum tumor volume.…”

Section: Pkpd Modelingmentioning

confidence: 99%

Translational Pharmacokinetic-Pharmacodynamic Modeling for an Orally Available Novel Inhibitor of Anaplastic Lymphoma Kinase and c-Ros Oncogene 1

Yamazaki

Lam

Zou

et al. 2014

J Pharmacol Exp Ther

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An orally available macrocyclic small molecule, PF06463922 [(10R)-7-amino-12-fluoro-2,10,16-trimethyl-15-oxo-10,15,16,17-tetrahydro-2H-8,4-(metheno)pyrazolo [4,3-h][2,5,11]benzoxadiazacyclotetradecine-3-carbonitrile], is a selective inhibitor of anaplastic lymphoma kinase (ALK) and c-Ros oncogene 1 (ROS1). The objectives of the present study were to characterize the pharmacokinetic-pharmacodynamic relationships of PF06463922 between its systemic exposures, pharmacodynamic biomarker (target modulation), and pharmacologic response (antitumor efficacy) in athymic mice implanted with H3122 non-small cell lung carcinomas expressing echinoderm microtubule-associated protein-like 4 (EML4)-ALK mutation (EML4-ALK L1196M ) and with NIH3T3 cells expressing CD74-ROS1. In these nonclinical tumor models, PF06463922 was orally administered to animals with EML4-ALK L1196M and CD74-ROS1 at twice daily doses of 0.3-20 and 0.01-3 mg/kg per dose, respectively. Plasma concentration-time profiles of PF06463922 were adequately described by a one-compartment pharmacokinetic model. Using the model-simulated plasma concentrations, a pharmacodynamic indirect response model with a modulator sufficiently fit the time courses of target modulation (i.e., ALK phosphorylation) in tumors of EML4-ALK L1196M -driven models with EC 50,in vivo of 36 nM free. A drug-disease model based on an indirect response model reasonably fit individual tumor growth curves in both EML4-ALK L1196M-and CD74-ROS1-driven models with the estimated tumor stasis concentrations of 51 and 6.2 nM free, respectively. Thus, the EC 60,in vivo (52 nM free) for ALK inhibition roughly corresponded to the tumor stasis concentration in an EML4-ALK L1196M -driven model, suggesting that 60% ALK inhibition would be required for tumor stasis. Accordingly, we proposed that the EC 60,in vivo for ALK inhibition corresponding to the tumor stasis could be considered a minimum target efficacious concentration of PF06463922 for cancer patients in a phase I trial.

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“…[19][20][21][22][23] Some of the metrics and parameters estimated by these models were shown to be useful in predicting survival outcomes of patients with mCRC. Furthermore, the models proved useful for the design of phase III trials based on modelling survival outcomes from phase II (or other clinical trial) data.…”

Section: How Might This Impact On Clinical Practice?mentioning

confidence: 99%

Exploration of time points and cut-off values for early tumour shrinkage to predict survival outcomes of patients with metastatic colorectal cancer treated with first-line chemotherapy using a biexponential model for change in tumour size

Sakamaki

Kito²,

Yamazaki³

et al. 2017

ESMO Open

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BackgroundSeveral studies reported that early tumour shrinkage (ETS) was associated with overall survival in patients with metastatic colorectal cancer (mCRC) treated with first-line chemotherapy. However, appropriate time point and cut-off value for ETS remain unclear because these varied in previous studies.Patients and methodsWe investigated patients with mCRC who received FOLFOX or FOLFIRI with/without molecular-targeted agents as first-line treatment between 2005 and 2014. Using a biexponential model for change in tumour size, a relative change in the sum of the longest diameters of target lesions from baseline was estimated at a certain time point in each individual patient. Associations of survival outcomes with ETS at various time points based on various cut-off values were evaluated by Cox regression analysis with a landmark approach.ResultsAmong the 67 patients reviewed, the objective response rate was 73.1% (95% CI 62.5% to 83.7%), the median progression-free survival was 10.9 months (95% CI 8.7 to 13.0 months) and the median overall survival was 25.6 months (95% CI 20.1 to 27.3 months). The model for change in tumour size agreed with the actual measured sizes well. Multivariate Cox regression analysis, including performance status, number of metastatic sites and use of targeted agents, showed that ETS at 8 weeks based on a cut-off value of 20% was most significantly associated with overall survival (HR: 0.404, 95% CI 0.231 to 0.707, P=0.0015).ConclusionIt is suggested that a time point of 8 weeks and a cut-off value of 20% may be optimal criteria for defining ETS.

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Mathematical modeling of tumor growth and tumor growth inhibition in oncology drug development

Cited by 45 publications

References 62 publications

Implementation of pharmacokinetic and pharmacodynamic strategies in early research phases of drug discovery and development at Novartis Institute of Biomedical Research

Implementation of pharmacokinetic and pharmacodynamic strategies in early research phases of drug discovery and development at Novartis Institute of Biomedical Research

Translational Pharmacokinetic-Pharmacodynamic Modeling for an Orally Available Novel Inhibitor of Anaplastic Lymphoma Kinase and c-Ros Oncogene 1

Exploration of time points and cut-off values for early tumour shrinkage to predict survival outcomes of patients with metastatic colorectal cancer treated with first-line chemotherapy using a biexponential model for change in tumour size

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