Optimizing oncology therapeutics through quantitative translational and clinical pharmacology: challenges and opportunities.
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Computational neurorehabilitation: modeling plasticity and learning to predict recoveryTranslational Modeling of Drug-Induced Myelosuppression and Effect of Pretreatment Myelosuppression for AZD5153, a Selective BRD4 Inhibitor.Towards Quantitative Systems Pharmacology Models of Chemotherapy-Induced Neutropenia.Translational learning from clinical studies predicts drug pharmacokinetics across patient populations.Predictive biomarkers of immunotherapy for non-small cell lung cancer: results from an Experts Panel Meeting of the Italian Association of Thoracic Oncology.Modeling and simulation of maintenance treatment in first-line non-small cell lung cancer with external validationCombining an Aurora Kinase Inhibitor and a Death Receptor Ligand/Agonist Antibody Triggers Apoptosis in Melanoma Cells and Prevents Tumor Growth in Preclinical Mouse ModelsA Tumor Growth Inhibition Model Based on M-Protein Levels in Subjects With Relapsed/Refractory Multiple Myeloma Following Single-Agent Carfilzomib UseNivolumab dose selection: challenges, opportunities, and lessons learned for cancer immunotherapyPopulation Pharmacokinetic/Pharmacodynamic Modeling of Tumor Size Dynamics in Pembrolizumab-Treated Advanced Melanoma.A Pharmacometric Framework for Axitinib Exposure, Efficacy, and Safety in Metastatic Renal Cell Carcinoma Patients.Clinical Pharmacology & Therapeutics: the next five years.Developing Exposure/Response Models for Anticancer Drug Treatment: Special ConsiderationsDose and Schedule Selection of the Oral Proteasome Inhibitor Ixazomib in Relapsed/Refractory Multiple Myeloma: Clinical and Model-Based Analyses.Exposure-Response of Veliparib to Inform Phase II Trial Design in Refractory or Relapsed Patients with Hematological Malignancies.Optimizing drug development in oncology by clinical trial simulation: Why and how?Toward Optimum Benefit-Risk and Reduced Access Lag For Cancer Drugs in Asia: A Global Development Framework Guided by Clinical Pharmacology Principles.Model-based prediction of progression-free survival in patients with first-line renal cell carcinoma using week 8 tumor size change from baseline.Pharmacometric Modeling of Liver Metastases' Diameter, Volume, and Density and Their Relation to Clinical Outcome in Imatinib-Treated Patients With Gastrointestinal Stromal Tumors.Multi-scale Modeling in Clinical Oncology: Opportunities and Barriers to Success.Modeling and simulations relating overall survival to tumor growth inhibition in renal cell carcinoma patients.Enhancing value of clinical pharmacodynamics in oncology drug development: An alliance between quantitative pharmacology and translational science.Exposure-Response Analysis of Necitumumab Efficacy in Squamous Non-Small Cell Lung Cancer Patients.Simultaneous Modeling of Biomarker and Toxicity Response Predicted Optimal Regimen of Guadecitabine (SGI-110) in Myeloid Malignancies.Managing Innovation to Maximize Value Along the Discovery-Translation-Application Continuum.Moving Beyond Maximum Tolerated Dose for Targeted Oncology Drugs: Use of Clinical Utility Index to Optimize Venetoclax Dosage in Multiple Myeloma Patients.Systems Pharmacology Model of Gastrointestinal Damage Predicts Species Differences and Optimizes Clinical Dosing Schedules.Model-Informed Reverse and Forward Translation of Safety Risks in Drug Development.Model-Based Meta-Analysis for Multiple Myeloma: A Quantitative Drug-Independent Framework for Efficient Decisions in Oncology Drug Development.Effective chemotherapy of heterogeneous and drug-resistant early colon cancers by intermittent dose schedules: a computer simulation study.Challenges and Opportunities in Dose Finding in Oncology and Immuno-oncology.Reverse Translation of US Food and Drug Administration Reviews of Oncology New Molecular Entities Approved in 2011-2017: Lessons Learned for Anticancer Drug Development.Quantitative translational modeling to facilitate preclinical to clinical efficacy & toxicity translation in oncology.Pharmacometric Applications and Challenges in the Development of Therapeutic Antibodies in Immuno-Oncology
P2860
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P2860
Optimizing oncology therapeutics through quantitative translational and clinical pharmacology: challenges and opportunities.
description
2014 nî lūn-bûn
@nan
2014年の論文
@ja
2014年学术文章
@wuu
2014年学术文章
@zh-cn
2014年学术文章
@zh-hans
2014年学术文章
@zh-my
2014年学术文章
@zh-sg
2014年學術文章
@yue
2014年學術文章
@zh
2014年學術文章
@zh-hant
name
Optimizing oncology therapeuti ...... challenges and opportunities.
@en
type
label
Optimizing oncology therapeuti ...... challenges and opportunities.
@en
prefLabel
Optimizing oncology therapeuti ...... challenges and opportunities.
@en
P2093
P2860
P356
P1476
Optimizing oncology therapeuti ...... : challenges and opportunities
@en
P2093
J T Mettetal
K Venkatakrishnan
L E Friberg
N Mehrotra
P2860
P356
10.1002/CPT.7
P407
P577
2014-12-09T00:00:00Z