Development of a Modeling Framework to Simulate Efficacy Endpoints for Motesanib in Thyroid Cancer Patients

To develop a modeling framework that simulates clinical endpoints (objective response rate and progression-free survival) to support development of motesanib. The framework was evaluated using results from a phase 2 study of motesanib in thyroid cancer. Models of probability and duration of dose modifications and overall survival were developed using data from 93 patients with […]

Read More
Topics:

Prediction of Overall Survival or Progression Free Survival by Disease Control Rate at Week 8 Is Independent of Ethnicity: Western Versus Chinese Patients With First-Line Non-Small Cell Lung Cancer Treated With Chemotherapy With or Without Bevacizumab

Categorizations of best response observed at week 8 of first-line treatment in two studies of bevacizumab plus chemotherapy in Western and Chinese patients with non-small cell lung cancer were assessed together with baseline prognostic factors in multivariate parametric models to predict overall survival and progression free survival.

Read More
Topics:

Population Pharmacokinetic/Pharmacodynamic Modeling for the Time Course of Tumor Shrinkage by Motesanib in Thyroid Cancer Patients

To develop a population pharmacokinetic/pharmacodynamic model describing the relationship between motesanib exposure and tumor response in a phase 2 study of motesanib in patients with advanced differentiated thyroid cancer or medullary thyroid cancer. Data from patients (n = 184) who received motesanib 125 mg once daily were used for population pharmacokinetic/pharmacodynamic modeling. Motesanib concentrations were […]

Read More
Topics:

The ISoP Standards and Best Practices Committee

The mission of the International Society of Pharmacometrics (ISoP) Standards and Best Practices Committee is to provide best practices and recommendations for standard pharmacometric analyses—e.g., population pharmacokinetics/pharmacodynamics (PK/PD), exposure–response, disease models—with the goal of increasing consistency, productivity, quality, communication, and impact of pharmacometrics on decision making. We present the progress and plans of the committee […]

Read More
Topics:

Model-Based Prediction of Phase III Overall Survival in Colorectal Cancer on the Basis of Phase II Tumor Dynamics

We developed a drug-disease simulation model to predict antitumor response and overall survival in phase III studies from longitudinal tumor size data in phase II trials. We developed a longitudinal exposure-response tumor-growth inhibition (TGI) model of drug effect (and resistance) using phase II data of capecitabine (n = 34) and historical phase III data of […]

Read More
Topics:

On the Use of Change in Tumor Size to Predict Survival in Clinical Oncology Studies: Toward a New Paradigm to Design and Evaluate Phase II Studies

Drug-independent models that link biomarker response to clinical end points are critical to support early (end of phase II) clinical decisions. In oncology, change in tumor size (a biomarker of drug effect evaluated in phase II) is linked to survival (a phase III end point) in some solid tumors.

Read More
Topics:

Simulations to Assess Phase II Noninferiority Trials of Different Doses of Capecitabine in Combination With Docetaxel for Metastatic Breast Cancer

A phase II trial in metastatic breast cancer (MBC) (NO16853) failed to show noninferiority (progression-free survival, PFS) of capecitabine 825 mg/m2 plus docetaxel 75 mg/m2 to the registered capecitabine dose of 1,250 mg/m2 plus docetaxel 75 mg/m2 . We developed a modeling framework based on NO16853 and the pivotal phase III MBC study, SO14999, to […]

Read More
Topics:

Simulations Using a Drug-Disease Modeling Framework and Phase II Data Predict Phase III Survival Outcome in First-Line Non-Small-Cell Lung Cancer

Simulations were performed for carboplatin/paclitaxel (C/P) plus motesanib or bevacizumab vs. C/P as first-line treatment for advanced non small-cell lung cancer (NSCLC) using a published drug disease model. With 700 patients in each arm, simulated hazard ratios for motesanib (0.87; 95% confidence interval [CI], 0.71-1.1) and bevacizumab (0.89; 95% CI, 0.73-1.1) agreed with results from […]

Read More
Topics:

Model-Based Drug Development in Oncology: What’s Next?

Model-based estimates of tumor growth inhibition (TGI) metrics have the potential to enhance learning in early (phase II) clinical studies. They can be used as end points and biomarkers to predict treatment effect on clinical outcome measures—e.g., overall survival (OS)—and support phase II study design, end-of-phase II decisions, and phase III planning and execution. Efforts […]

Read More
Topics:

Evaluation of Tumor Size Response Metrics to Predict Survival in Oncology Clinical Trials

Model-based drug development in oncology is still lagging despite a good momentum in the clinical pharmacology and pharmacometry community in the past few years. The failure rate of late-stage oncology studies is one of the highest across therapeutic areas. The modeling of the relationship between longitudinal tumor size and overall survival has been proposed to […]

Read More
Topics:

Exploratory Modeling and Simulation to Support Development of Motesanib in Asian Patients With Non-Small Cell Lung Cancer Based on MONET1 Study Results

The motesanib phase III MONET1 study failed to show improvement in overall survival (OS) in non–small cell lung cancer, but a subpopulation of Asian patients had a favorable outcome. We performed exploratory modeling and simulations based on MONET1 data to support further development of motesanib in Asian patients. A model-based estimate of time to tumor […]

Read More
Topics:
Learn More
LinkedIn