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The Future of Personalized Medicine: The Impact of Proteomics on Drug Discovery And Clinical Trial Design Product Image

The Future of Personalized Medicine: The Impact of Proteomics on Drug Discovery And Clinical Trial Design

  • ID: 235993
  • October 2004
  • Scripp Business Insights

‘Personalized Medicine: The impact of proteomics on drug discovery and clinical trial design’ is a management report that analyses how proteomics will streamline drug development and lead to the more cost-effective development of niche personalized products of the future. Proteomics promises lower R&D costs and the opportunities of new revenue streams through the identification of new drug targets in the treatment of diseases such as cancer and Alzheimer's. Use this report to identify the most important technologies, their applications in drug discovery and clinical trial design and the leading companies driving development of this exciting new area. The pharmaceutical industry has so far been slow to take up proteomic technology and strategic alliances and acquisitions will be central to the pharmaceutical industry's uptake of proteomics. This report identifies the key technologies that will enable pharmaceutical companies to develop new niche products, improve drug attrition rates, increase the speed of clinical development and target new drug markets.<BR><BR>The key findings of this report:<BR><BR>- Proteomics has the potential to reduce drug READ MORE >

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The Future of Personalized Medicine: The Impact of<BR>Proteomics on Drug Discovery and Clinical Trial Design<BR>Executive summary 10<BR>Introduction to proteomics 10<BR>Proteomic technologies 11<BR>Proteomic applications in drug discovery 13<BR>Proteomic applications in clinical trial design and personalized medicine 14<BR>Pharma and proteomic company alliances 15<BR><BR>Chapter 1 Introduction to proteomics 17<BR>Summary 17<BR>Introduction 18<BR>The human genome versus the proteome 20<BR>Identification of human genome 20<BR>Applications to proteomics 21<BR>The relationship between the proteome and the genome 23<BR>The genome 23<BR>Proteins 24<BR>From genes to proteins 27<BR>Proteomics 29<BR>Conclusions 30<BR><BR>Chapter 2 Proteomic technologies 33<BR>Summary 33<BR>Laboratory methods used in proteomics 34<BR>Separation techniques 34<BR>Identification techniques 34<BR>Interactions techniques 34<BR>Separation techniques 38<BR>2-dimensional polyacrylamide gel electrophoresis (2-D PAGE) 38<BR>Liquid chromatography (LC) 38<BR>Protein arrays 39<BR>Identification techniques 40<BR>Mass spectrometry 40<BR>Protein-protein interaction techniques 42<BR>Automation 43<BR>Pre-fractionation 43<BR>Separation 44<BR>Identification 45<BR>Complete proteomics solutions 46<BR>The future of automation in proteomics 46<BR>Conclusions 48<BR>Bioinformatics and databases 49<BR>Data analysis 50<BR>Databases 50<BR>Laboratory information management systems (LIMS) 52<BR>Conclusions 53<BR>Overall conclusions 53<BR><BR>Chapter 3 Proteomic applications in drug<BR>discovery 57<BR>Summary 57<BR>Introduction 58<BR>Optimizing the R&D process 60<BR>Early selection of efficacious and non-toxic drug targets 65<BR>Toxicoproteomics 67<BR>Pharmacoproteomics 68<BR>Conclusions 69<BR>Accelerating the discovery of new targets for therapeutic candidates 70<BR>Therapeutic proteins 70<BR>Protein targets 74<BR>Mining the proteome is an alternative approach for drug discovery 74<BR>Conclusions 75<BR><BR>Chapter 4 Proteomic applications in clinical<BR>trial design and personalized<BR>medicine 77<BR>Summary 77<BR>Development of new biomarkers 78<BR>Biomarkers as clinical endpoints 80<BR>Responders and non-responders 80<BR>Patients with adverse reactions 82<BR>Patients in different stages of a disease, or other subsets of patients 82<BR>Monitor clinical responses in new and comparator drugs - allowing potential<BR>strategic alliances 84<BR>Patients with disease resistance 85<BR>Niche markets 86<BR>Conclusions 86<BR>Application of biomarkers by therapy area 87<BR>Oncoproteomics 88<BR>Application in the diagnosis of ovarian cancer 88<BR>Application in the diagnosis of prostate cancer 89<BR>Application in the diagnosis of breast cancer 89<BR>Application in the diagnosis of esophageal cancer 90<BR>Neuroproteomics 90<BR>Application in the diagnosis of Alzheimer’s diseases 90<BR>Application in the diagnosis of amyotrophic lateral sclerosis (ALS) 91<BR>Cardioproteomics 91<BR>Cardiovascular markers 91<BR>Respiratory markers 92<BR>Application in organ transplantation 92<BR>Post-marketing applications of biomarkers 93<BR>Conclusions 94<BR>Conclusions 95<BR>Conclusions 95<BR><BR>Chapter 5 Pharmaceutical and proteomic<BR>company alliances 99<BR>Summary 99<BR>Introduction 100<BR>Recent collaborations and alliances of pharma and proteomic based<BR>companies 102<BR>Abbott 102<BR>Altana 102<BR>AstraZeneca 102<BR>Aventis 103<BR>Bayer 104<BR>Bristol-Myers Squibb 104<BR>Boehringer Ingelheim 105<BR>Daiichi 106<BR>Eli Lilly 106<BR>Fujisawa 107<BR>GlaxoSmithKline 107<BR>Johnson & Johnson 107<BR>Lundbeck 107<BR>Merck & Co. 108<BR>Merck KGaA 108<BR>Novartis 108<BR>Pfizer 109<BR>Proteome Sciences 110<BR>Procter & Gamble 110<BR>Roche 110<BR>Schering AG 111<BR>Sumitomo Chemical 111<BR>Takeda 113<BR>UCB 114<BR>Wyeth 114<BR>Conclusions 114<BR><BR>Chapter 6 Appendix 117<BR>2-dimensional polyacrylamide gel electrophoresis (2-D PAGE) 117<BR>Summary 119<BR>Liquid chromatography (LC) 120<BR>Gel filtration chromatography 121<BR>Ion exchange chromatography 121<BR>Affinity chromatography 121<BR>Partitioning chromatography 122<BR>LC summary 122<BR>High performance liquid chromatography 122<BR>Protein arrays 123<BR>Expression arrays 124<BR>Functional arrays 126<BR>Reverse arrays 126<BR>Protein array summary 127<BR>Mass spectrometry (MS) 128<BR>Electro-spray ionization 130<BR>Laser desorption/ionization 132<BR>MALDI 132<BR>SELDI 133<BR>Protein-protein interactions 135<BR>Fluorescence resonance energy transfer 137<BR>Bioinformatics databases 138<BR>Summary 138<BR>Sequence databases and alignment tools 139<BR>Domain and 3-dimensional structure databases 140<BR>Databases of biochemical pathways 142<BR>‘Techniques’ databases 143<BR>The human proteome organization 144<BR>Index 145<BR>References 147<BR>Website references 154<BR>List of Figures<BR><BR>Figure 1.1: Nearly 500 proteins identified through proteomics have known functions in disease21<BR>Figure 1.2: The basic structure of the (unwound) DNA helix 23<BR>Figure 1.3: The general structure of an amino acid and peptide bond 25<BR>Figure 1.4: The active site of the bacterial serine protease subtilisin 26<BR>Figure 1.5: The process of protein synthesis 27<BR>Figure 2.6: Techniques used in proteomics 36<BR>Figure 2.7: The role and scope of bioinformatics in proteomics research 49<BR>Figure 3.8: Only 30% of drugs produce revenues that exceed the average R&D cost 60<BR>Figure 3.9: Industry average attrition curves, 2004 61<BR>Figure 3.10: US pharmaceutical industry R&D expenditure and NCEs approvals, 1995-2003 62<BR>Figure 3.11: Strategies for analysis of toxicoproteomic data 67<BR>Figure 3.12: The impact of protein probes on drug discovery 73<BR>Figure 4.13: Three stages of diagnostic development 79<BR>Figure 4.14: The predicted individual response to any one drug 81<BR>Figure 6.15: Example of a 2-D PAGE gel 118<BR>Figure 6.16: Representation of liquid chromatography 120<BR>Figure 6.17: Typical high performance liquid chromatography set-up 123<BR>Figure 6.18: Representation of a ‘sandwich’ – type expression array 125<BR>Figure 6.19: A typical ESI instrument set up 131<BR>Figure 6.20: Simplified diagram of MALDI apparatus 133<BR>Figure 6.21: Representation of the yeast two hybrid system 136<BR>Figure 6.22: Schematic representation of FRET for investigating protein-protein interactions 137<BR>Figure 6.23: Representation of FRET for investigating protein-protein interactions 142<BR>Figure 6.24: Example of a pathway diagram from KEGG 143<BR>List of Tables<BR>Table 1.1: The single- and three-letter amino acid codes 24<BR>Table 1.2: The codons and the amino acids that they specify 28<BR>Table 2.3: Summary of key proteomics technologies 37<BR>Table 2.4: A selection of protein array manufacturers* 40<BR>Table 2.5: Automation of proteomic platforms 47<BR>Table 2.6: Summary of proteomics databases* 51<BR>Table 3.7: Constant dollar reduction in total cost per new drug, 2002 62<BR>Table 3.8: R&D spend on drug development, 2002 65<BR>Table 3.9: New biologics 70<BR>Table 3.10: Recombinant proteins 71<BR>Table 3.11: Protein drug targets 72<BR>Table 3.12: New proteomic targets 74<BR>Table 4.13: Proteomic biomarkers 79<BR>Table 4.14: Correlation of survival with HER-2 over-expression 83<BR>Table 5.15: Colloborations implementing proteomics technologies 101<BR>

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