臨床開發的生物標誌：對個別醫療與R＆D效率化的影響

本報告已在2011年07月19日停止出版。

簡介

目錄

Abstract

The cost to discover and develop a drug is increasing dramatically; however, the number approved new drug products on the decline. Drug manufacturers, desperate for ways to expedite the drug discovery process while decreasing the expense, are turning to biomarkers as one possible solution. Biomarkers in Clinical Development: Implications for Personalized Medicine and Streamlining R&D examines the current state of biomarker development and application, with a close look at the technologies and how they are being deployed from research to the clinic.

Biomarkers can be influential in every phase of drug development, from drug discovery and preclinical evaluations through each phase of clinical trials and into post-marketing studies. Biomarkers can predict a patients response to a compound, act as a surrogate endpoint, and aid in making efficacious and cost-saving decisions or terminating drug entities more quickly during the research process. Patient enrichment strategies are using biomarkers to identify certain patient populations that are m ore likely to respond to the drug therapy or to avoid specific adverse events. This shift toward "pe rsonalized medicine," in which the patient receives a treatment based on their genetic as well as medical profile, is helping the drug industry to achieve the goal of cost-effective and faster research.

Table of Contents

Chapter 1. Introduction

1.1. Scope of Report

1.2. Overview of Biomarkers

-Applications in Clinical Research

-Beneficial Impacts of Biomarkers

1.3. Biomarkers: Definitions and Taxonomy

1.4. The Rol e of Biomarkers in Drug Development

1.5. Risks Associated With Biomarker Usage

1.6. FDAs Perspective on Biomarkers in Clinical Development

-Accelerated Approval Provisions

-FDAs Guidelines on Pharmacogenomic Markers

-Industrys Response to FDAs Request for Pharmacogenomic Data

Chapter 2. From Discovery to Clinic

2.1. Technologies Used for Biomarker Discovery and Application

Pharmacogenomics

-Microarrays Predict Likelihood of Breast Cancer Metastases

-Specific Genes Predict Risk of Alzheimers Disease

Proteomics

-2-D PAGE

-Isotope-Coded Affinity Tags

-MALDI

-LC-MS/MS

-Imaging MS

-Free Flow Electrophoresis

-Protein Arrays

-Affinity-Based MS Techniques for the Identification of Biomarkers

--SELDI Protein Chip and Prostate Specific Membrane Antigen Marker

--SELDI and Intra-Amniotic Infection Biomarkers

-Tissue Arrays

Metabolomics

-Paradigm Genetics Focus on Metabolomic Biomarkers of Liver Damage

Systems Biology

Molecular Imaging

-Tomography Based Imaging Technologies

--Computed Tomography (CT)

--Magnetic Resonance Imaging (MRI)

-Emission-Based Tomography Methods

--Positron Emission Tomography (PET)

--Single-Photon Emission Computed Tomography (SPECT)

-Biophotonic Imaging

Chapter 3. Overall Approach Used by the Pharmaceutical Industry

3.1. Pfizer Global Research and Development

3.2. Roche

3.3. Bristol-Myers Squibb

3.4. Novartis

3.5. SurroMed

Chapter 4. Biomarkers: From Clinical Research to Diagnostic Tool

4.1. Imaging Technologies

4.2. Theranostics

Herceptin and DakoCytomations HercepTest

Gleevec and Ventana Medical Systems VentanaDx c-Kit Test

4.3. Iressa

4.4. Amevive and Enbrel

Chapter 5. Business Outlook and Conclusion

5.1. Biomarker Research within the Pharmaceutical Industry

5.2. Expert Interviews

Felix Frueh, FDA Center for Drug Evaluation and Research

Aaron Kantor, SurroMed

David Lester, Pfizer

Rick Ludwig, Indiana Center for Applied Protein Sciences

Robert McBurney, BG Medicine

Rudy Potenzone and Richard Chen, Ingenuity Systems

Michael T. Stocum, Personalized Medicine Partners

5.3. Company Profiles

Affymetrix

Beckman Coulter

BG Medicine

BioMarker Pharmaceuticals

Ciphergen Biosystems

Clinical MicroArrays

Gene Logic

High Throughput Genomics

MDS Pharma Services

ParAllele BioScience

SurroMed

Xenogen

Tables and Figures

• Figure 1.1: Phases of the Drug Development Process That Are Impacted by Biomarkers
• Figure 1.2: Effective Profitability of Approved and Released Pharmaceuticals
• Figure 1.3: Value Proposition of Biomarkers Throughout the Therapeutic Development and Application Phases
• Figure 1.4: Reasons Cited for Compound Failure
• Figure 1.5: The Biomarker Research and Development Process
• Figure 2.1: Linkage of a Basic Systems Biology Research Cycle with Drug Discovery and Treatment
• Figure 2.2: How Technologies Can Better Connect Discovery and Clinical Research
• Table 1.1: Biomarker/Surrogate Endpoints That Have Aided Drug Development
• Table 1.2: Classification of Biomarkers as Described by the FDA
• Table 2.1: Comparative Throughput of Biomarker Technologies
• Table 2.2: Gene Expression as a Prognostic Tool in Breast Cancer
• Table 2.3: Genes for Early-Onset Alzheimer?fs Disease
• Table 2.4: Genes for Late-Onset Alzheimer?fs Disease
• Table 2.5: Comparison of Proteomic Technologies Used for Biomarker Discovery
• Table 2.6: Comparison of Advantages and Disadvantages of Selected Molecular Imaging Technologies
• Table 4.1: Pharmacological MRI Studies Involving Psychiatric and Neurological Conditions
• Table 5.1: Selected Pharmaceutical Company Partnerships h

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