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Personalized Medicine - scientific & commercial aspects

Notes

This report describes the latest concepts of development of personalized medicine based on pharmacogenomics, pharmacogenetics, pharmacoproteomics, and metabolomics. The bibliography contains over 630 selected publications cited in the report.

The aim of personalized medicine or individualized treatment is to match the right drug to the right patient and, in some cases, even to design the appropriate treatment for a patient according to his/her genotype. This report describes the latest concepts of development of personalized medicine based on pharmacogenomics, pharmacogenetics,pharmacoproteomics, and metabolomics. Basic technologies of molecular diagnostics play an important role, particularly those for single nucleotide polymorphism (SNP) genotyping. Diagnosis is integrated with therapy for selection of the treatment as well for monitoring the results. Biochip/microarray technologies are also important and finally bioinformatics is needed to analyze the immense amount of data generated by various technologies.

Pharmacogenetics, the study of influence of genetic factors on drug action and metabolism, is used for predicting adverse reactions of drugs. Several enzymes are involved in drug metabolism of which the most important ones are those belonging to the family of cytochrome P450. The knowledge of the effects of polymorphisms of genes for the enzymes is applied in drug discovery and development as well as in clinical use of drugs. Cost-effective methods for genotyping are being developed and it would be desirable to include this information in the patient's record for the guidance of the physician to individualize the treatment. Pharmacogenomics, a term that overlaps with pharmacogenetics but is distinct, deals with the application of genomics to drug discovery and development. It involves the mechanism of action of drugs on cells as revealed by gene expression patterns. Pharmacoproteomics is an important contribution to personalized medicine as it is a more functional representation of patient-to-patient variation than that provided by genotyping.A 'pharmacometabonomic' approach to personalizing drug treatment is also described.

Biological therapies such as those which use patient's own cells are considered to be personalized medicines. Vaccines are prepared from individual patient's tumor cells. Individualized therapeutic strategies using monoclonal bodies can be directed at specific genetic and immunologic targets. Ex vivo gene therapy involves the genetic modification of the patient's cells in vitro, prior to reimplantation of these cells in the patient's body.

Various technologies are integrated to develop personalized therapies for specific therapeutic areas described in the report. Examples of this are genotyping for drug resistance in HIV infection, personalized therapy of cancer, antipsychotics for schizophrenia, antidepressant therapy, antihypertensive therapy and personalized approach to neurological disorders. Although genotyping is not yet a part of clinically accepted routine, it is expected to have this status by the year 2018.

Several players are involved in the development of personalized therapy. Pharmaceutical and biotechnology companies have taken a leading role in this venture in keeping with their future role as healthcare enterprises rather than mere developers of technologies and manufacturers of medicines.

Ethical issues are involved in the development of personalized medicine mainly in the area of genetic testing. These along with social issues and consideration of race in the development of personalized medicine are discussed. Regulatory issues are discussed mainly with reference to the FDA guidelines on pharmacogenomics.

Increase in efficacy and safety of treatment by individualizing it has benefits in financial terms. Information is presented to show that personalized medicine will be cost-effective in healthcare systems. For the pharmaceutical companies, segmentation of the market may not leave room for conventional blockbusters but smaller and exclusive markets for personalized medicines would be profitable. Marketing opportunities for such a system are described with market estimates from 2013-2023.

Profiles of 309 companies involved in developing technologies for personalized medicines, along with 546 collaborations are included in the part II of the report. Finally the bibliography contains over 750 selected publications cited in the report.The report is supplemented by 67 tables and 22 figures.

Table of Contents

Part I

0. Executive Summary 21

1. Basic Aspects 23

  • Definition of personalized medicine 23
  • History of medical concepts relevant to personalized medicine 24
  • Molecular biological basis of personalized medicine 26
  • The human genome 26
  • ENCODE 27
  • Chromosomes 27
  • Genes 28
  • The genetic code 28
  • Gene expression 28
  • DNA sequences and structure 29
  • Genetic variations in the human genome 29
  • Single nucleotide polymorphisms 30
  • Copy number variations in the human genome 30
  • Insertions and deletions in the human genome 32
  • Large scale variation in human genome 33
  • Structural variations in the human genome 33
  • Mapping and sequencing of structural variation from human genomes 34
  • 1000 Genomes Project 35
  • Role of DNA sequencing in the development of personalized medicine 36
  • Human Variome Project 36
  • Interconnected genetic and genomic patterns in human diseases 37
  • Basics technologies for developing personalized medicine 38
  • Definitions of technologies relevant to personalized medicine 38
  • Problems with the ICH definitions of pharmacogenomics and pharmacogenetics 38
  • 'Omics' and personalized medicine 39
  • Relationship of various technologies to personalized medicine 39
  • Conventional medicine versus personalized medicine 40
  • Personalized medicine and evidence-based medicine 40
  • Role of genetics in future approaches to healthcare 40
  • Genetic medicine 40
  • Human disease and genes 41
  • Genetic and environmental interactions in etiology of human diseases 41
  • Role of genetics in development of personalized medicines 42
  • Genetic databases 42
  • Clinical Genomic Database 42
  • Genetic epidemiology 43
  • Limitations of medical genetics and future prospects 43
  • Genetics vs. epigenetics 44
  • Role of systems biology in personalized medicine 44
  • Systems pharmacology 45
  • Systems medicine 46
  • Synthetic biology and development of personalized medicines 46
  • A personalized approach to environmental factors in disease 47
  • Reclassification of diseases 48
  • Translational science and personalized medicine 48

2. Molecular Diagnostics in Personalized Medicine 51

  • Introduction 51
  • Molecular diagnostic technologies 51
  • PCR-based methods 52
  • DirectLinear™ Analysis 52
  • Denaturing high-performance liquid chromatography 53
  • Multiplex Allele-Specific Diagnostic Assay 53
  • Representational oligonucleotide microarray analysis 53
  • Restriction fragment length polymorphism (RFLP) 53
  • Real-time PCR for detection of CNVs 54
  • Non-PCR methods 54
  • Arrayed primer extension (APEX) 54
  • Enzymatic Mutation Detection (EMD) 54
  • DNA sequencing 54
  • Sanger-sequencing technology 55
  • ABI PRISM® 310 Genetic Analyzer 56
  • High-throughput paired end transcriptome sequencing 56
  • Emerging sequencing technologies 56
  • 4300 DNA analyzer 57
  • Apollo 100 57
  • "Color blind" approach to DNA sequencing 58
  • Cyclic array sequencing 58
  • CEQ™ 8000 58
  • DeepCAGE sequencing 58
  • Electron microscope-based DNA sequencing 59
  • Genometrica™ sequencer 59
  • GS-FLEX system (Roche/454) 60
  • IBS sequencing technology 61
  • Illumina's sequencing technology 61
  • MegaBACE 500 62
  • Microdroplet-based PCR for large-scale targeted sequencing 62
  • Multiplex amplification of human DNA sequences 63
  • Nanoscale sequencing 63
  • Polonator sequencer 63
  • RainStorm™ microdroplet technology 64
  • Sequential DEXAS 64
  • SOLiD technology 65
  • Sequencing by hybridization 66
  • Whole genome sequencing 66
  • Bioinformatic tools for analysis of genomic sequencing data 67
  • Detection of single molecules in real time 67
  • Direct observation of nucleotide incorporation 67
  • Molecular Combing 67
  • Nanopore sequencing 67
  • DNA sequence by use of nanoparticles 68
  • Zero-mode waveguide nanostructure arrays 68
  • Future prospects of sequencing 68
  • Role of sequencing in development of personalized medicine 69
  • Biochips and microarrays 70
  • Role of biochip/microarray technology in personalized medicine 71
  • Applications of biochip/microarray technology in personalized medicine 71
  • Standardizing the microarrays 72
  • Biochip technologies 73
  • GeneChip 73
  • AmpliChip CYP450 73
  • Microfluidics 75
  • Lab-on-a-chip 75
  • Micronics' microfluidic technology 75
  • LabCD 76
  • Microfluidic automated DNA analysis using PCR 76
  • Integrated microfluidic bioassay chip 76
  • Electronic detection of nucleic acids on microarrays 77
  • Strand displacement amplification on a biochip 77
  • Rolling circle amplification on DNA microarrays 77
  • Universal DNA microarray combining PCR and ligase detection reaction 78
  • Protein biochips 78
  • ProteinChip 78
  • LabChip for protein analysis 79
  • TRINECTIN proteome chip 79
  • Protein expression microarrays 80
  • Microfluidic devices for proteomics-based diagnostics 80
  • New developments in protein biochips/microarrays 81
  • Protein biochips/microarrays for personalized medicine 81
  • SNP genotyping 82
  • Genotyping and haplotyping 83
  • Haplotype Specific Extraction 83
  • Computation of haplotypes 84
  • HapMap project 84
  • Haplotyping for whole genome sequencing 85
  • Predictingdrug response with HapMap 85
  • Companies developing haplotyping technology 86
  • Technologies for SNP analysis 86
  • Biochip and microarray-based detection of SNPs 87
  • SNP genotyping by MassARRAY 87
  • Biochip combining BeadArray and ZipCode technologies 88
  • SNP-IT primer-extension technology 88
  • Affymetrix Variation Detection Arrays 88
  • Use of NanoChip for detection of SNPs 88
  • Electrochemical DNA probes 89
  • Single base extension-tag array 89
  • Laboratory Multiple Analyte Profile 89
  • PCR-CTPP (confronting two-pair primers) 90
  • SNP genotyping on a genome-wide amplified DOP-PCR template 90
  • TaqMan real-time PCR 90
  • Non-Enzymatic Amplification Technology 91
  • SNP genotyping with gold nanoparticle probes 91
  • Locked nucleic acid 91
  • Molecular inversion probe based assays 92
  • Pyrosequencing 92
  • Reversed enzyme activity DNA interrogation test 93
  • Smart amplification process version 2 93
  • Zinc finger proteins 93
  • UCAN method (Takara Biomedical) 94
  • Mitochondrial SNPs 94
  • Limitations of SNP in genetic testing 94
  • Concluding remarks on SNP genotyping 95
  • Companies involved in developing technologies/products for SNP analysis 95
  • Impact of SNPs on personalized medicine 96
  • Detection of copy number variations 97
  • Study of rare variants in pinpointing disease-causing genes 97
  • Optical Mapping 98
  • Role of nanobiotechnology in molecular diagnostics 98
  • Cantilevers for personalized medical diagnostics 99
  • Nanopore-based technology for single molecule identification 99
  • Role of biomarkers in personalized medicine 100
  • Biomarkers for diagnostics 100
  • Biomarkers for drug development 101
  • Application of proteomics in molecular diagnosis 101
  • Proteomic strategies for biomarker identification 101
  • Proteomic technologies for detection of biomarkers in body fluids 102
  • Protein patterns 102
  • Layered Gene Scanning 102
  • Comparison of proteomic and genomic approaches in personalized medicine 103
  • Gene expression profiling 103
  • DNA microarrays 104
  • Analysis of single-cell gene expression 105
  • Gene expression profiling based on alternative RNA splicing 105
  • Whole genome expression array 106
  • Tangerine™ expression profiling 106
  • Gene expression analysis on biopsy samples 107
  • Profiling gene expression patterns of white blood cells 107
  • Serial analysis of gene expression (SAGE) 108
  • Multiplexed Molecular Profiling 108
  • Gene expression analysis using competitive PCR and MALDI TOF MS 109
  • Monitoring in vivo gene expression by magnetic resonance imaging 109
  • Companies involved in gene expression analysis 109
  • Monitoring in vivo gene expression by molecular imaging 110
  • Molecular imaging and personalized medicine 111
  • Glycomics-based diagnostics 111
  • Combination of diagnostics and therapeutics 112
  • Use of molecular diagnostics for stratification in clinical trials 112
  • Companion diagnostics 112
  • Companies involved in companion diagnostics 113
  • Point-of-care diagnosis 115
  • Companies developing point-of-care diagnostic technologies 116
  • Point-of-care diagnosis of infections 118
  • Advantages versus disadvantages of point-of-care diagnosis 118
  • Future prospects of point-of-care diagnosis 119
  • Genetic testing for disease predisposition 119
  • Preventive genetics by early diagnosis of mitochondrial diseases 120
  • Direct-to-consumer genetic services 120
  • Role of diagnostics in integrated healthcare 121
  • Concept of integrated healthcare 121
  • Components of integrated healthcare 122
  • Screening 122
  • Disease prediction 122
  • Early diagnosis 122
  • Prevention 122
  • Therapy based on molecular diagnosis 123
  • Monitoring of therapy 123
  • Advantages and limitations of integrated healthcare 123
  • Commercially available systems for integrated healthcare 123
  • Future of molecular diagnostics in personalized medicine 124

3. Pharmacogenetics 125

  • Basics of pharmacogenetics 125
  • Role of molecular diagnostics in pharmacogenetics 126
  • Role of pharmacogenetics in pharmaceutical industry 127
  • Study of the drug metabolism and pharmacological effects 127
  • Causes of variations in drug metabolism 127
  • Enzymes relevant to drug metabolism 128
  • Pharmacogenetics of phase I metabolism 128
  • CYP450 128
  • P450 CYP 2D6 inhibition by selective serotonin reuptake inhibitors 130
  • Cytochrome P450 polymorphisms and response to clopidogrel 131
  • Lansoprazole and cytochrome P450 131
  • Glucose-6-phosphate dehydrogenase 131
  • Pharmacogenetics of phase II metabolism 132
  • N-Acetyltransferase 132
  • Uridine diphosphate-glucuronosyltransferase 133
  • Measurement of CYP isoforms 133
  • Polymorphism of drug transporters 134
  • Genetic variation in drug targets 134
  • Polymorphisms of kinase genes 135
  • Effect of genetic polymorphisms on disease response to drugs 135
  • Ethnic differences in drug metabolism 136
  • Gender differences in pharmacogenetics 136
  • Role of pharmacogenetics in drug safety 137
  • Adverse drug reactions 137
  • Adverse drug reactions in children 138
  • Adverse drug reactions related to toxicity of chemotherapy 138
  • Genetically determined adverse drug reactions 138
  • Malignant hyperthermia 140
  • Pharmacogenetics of clozapine-induced agranulocytosis 140
  • Role of pharmacogenetics in warfarin therapy 140
  • Role of pharmacogenetics in antiplatelet therapy 141
  • Role of pharmacogenetics in carbamazepine therapy 143
  • Role of pharmacogenetics in statin therapy 143
  • FDA consortium linking genetic biomarkers to serious adverse events 144
  • Therapeutic drug monitoring, phenotyping, and genotyping 144
  • Therapeutic drug monitoring 145
  • Phenotyping 145
  • Genotyping 146
  • Genotyping vs phenotyping 146
  • Phenomics 147
  • Limitations of genotype-phenotype association studies 148
  • Molecular toxicology in relation to personalized medicines 148
  • Toxicogenomics 148
  • Biomarkers of drug toxicity 148
  • Drug-induced mitochondrial toxicity 149
  • Companies involved in molecular toxicology 149
  • Gene expression studies 150
  • Pharmacogenetics in clinical trials 150
  • Postmarketing pharmacogenetics 151
  • Clinical implications of pharmacogenetics 151
  • Application of CYP450 genotyping in clinical practice 151
  • Pharmacogenomic biomarker information in drug labels 151
  • Genotype-based drug dose adjustment 155
  • Use of pharmacogenetics in clinical pharmacology 155
  • Application of CYP2C19 pharmacogenetics for personalized medicine 155
  • Genotyping for identifying responders to sulfasalazine 156
  • HLA alleles associated with lumiracoxib-related liver injury 156
  • Pharmacogenetic basis of thiopurine toxicity 156
  • Tranilast-induced hyperbilirubinemia due to gene polymorphism 157
  • Linking pharmacogenetics with pharmacovigilance 157
  • Genetic susceptibility to ADRs 157
  • Linking genetic testing to postmarketing ADR surveillance 157
  • Recommendations for the clinical use of pharmacogenetics 158
  • Limitations of pharmacogenetics 158
  • Pharmacoepigenomics vs pharmacogenetics in drug safety 159
  • Future role of pharmacogenetics in personalized medicine 159

4. Pharmacogenomics 161

  • Introduction 161
  • Basics of pharmacogenomics 162
  • Pharmacogenomics and drug discovery 162
  • Preclinical prediction of drug efficacy 164
  • Pharmacogenomics and clinical trials 164
  • Impact of genetic profiling on clinical studies 165
  • Limitations of the pharmacogenomic-based clinical trials 166
  • Pharmacogenomic aspects of major therapeutic areas 167
  • Oncogenomics 167
  • Oncogenes 167
  • Tumor suppressor genes 168
  • Cardiogenomics 169
  • Neuropharmacogenomics 171
  • Pharmacogenomics of Alzheimer's disease 171
  • Pharmacogenomics of depression 172
  • Pharmacogenomics of schizophrenia 172
  • Companies involved in neurogenomics-based drug discovery 173
  • Current status and future prospects of pharmacogenomics 173

5. Role of Pharmacoproteomics 175

  • Basics of proteomics 175
  • Proteomic approaches to the study of pathophysiology of diseases 175
  • Single cell proteomics for personalized medicine 176
  • Diseases due to misfolding of proteins 176
  • Therapies for protein misfolding 177
  • Significance of mitochondrial proteome in human disease 177
  • Proteomic technologies for drug discovery and development 178
  • Role of reverse-phase protein microarray in drug discovery 178
  • Role of proteomics in clinical drug safety 178
  • Toxicoproteomics 178
  • Applications of pharmacoproteomics in personalized medicine 180

6. Role of Metabolomics in Personalized Medicine 181

  • Metabolomics and metabonomics 181
  • Metabolomics bridges the gap between genotype and phenotype 181
  • Metabolomics, biomarkers and personalized medicine 182
  • Metabolomic technologies 182
  • Urinary profiling by capillary electrophoresis 183
  • Lipid profiling 183
  • Role of metabolomics in biomarker identification and pattern recognition 184
  • Validation of biomarkers in large-scale human metabolomics studies 184
  • Pharmacometabonomics 184
  • Metabonomic technologies for toxicology studies 185
  • Metabonomics/metabolomics and personalized nutrition 185

7. Personalized Biological Therapies 187

  • Introduction 187
  • Recombinant human proteins 187
  • Therapeutic monoclonal antibodies 187
  • Cell therapy 188
  • Autologous tissue and cell transplants 188
  • Stem cells 188
  • iPSCs for personalized cell therapy 188
  • Role of stem cells derived from unfertilized embryos 188
  • Cloning and personalized cell therapy 189
  • Use of stem cells for drug testing 189
  • Gene therapy 189
  • Stem cell-based personalized gene therapy for cancer 190
  • Personalized vaccines 190
  • Personalized vaccines for viral diseases 190
  • Personalized cancer vaccines 190
  • Antisense therapy 191
  • RNA interference 191
  • MicroRNAs 192

8. Personalized Non-pharmacological Therapies 193

  • Introduction 193
  • Acupuncture 193
  • Personalized acupuncture therapy 193
  • Personalized hyperbaric oxygen therapy 194
  • Personalized nutrition 194
  • Nutrigenomics 195
  • Genomics of vitamin D and calcium supplementation 195
  • Nutrigenomics and functional foods 196
  • Nutrigenetics and personalized medicine 196
  • Nutrigenomics and personalized medicine 197
  • Nutrition and proteomics 197
  • Personalized diet prescription 197
  • Personalized physical exercise 198
  • Variations in response to aerobic exercise 198
  • Variations in exercise-induced muscle hypertrophy and strength 199
  • Personalized surgery 199

9. Personalized Medicine in Major Therapeutic Areas 201

  • Introduction 201
  • Management of infections 202
  • Management of HIV 202
  • CD4 counts as a guide to drug therapy for AIDS 202
  • Drug-resistance in HIV 202
  • Genetics of human susceptibility to HIV infection 203
  • Measurement of Replication Capacity 204
  • Personalized vaccine for HIV 204
  • Prevention of adverse reactions to antiviral drugs 204
  • Pharmacogenetics and HIV drug safety 205
  • Pharmacogenomics of antiretroviral agents 205
  • Role of diagnostic testing in management of HIV 206
  • Role of genetic variations in susceptibility to HIV-1 206
  • Role of personalized HIV therapy in controlling drug resistance 206
  • Sequencing for personalizing HIV therapy 207
  • Personalized treatment of hepatitis B 208
  • Personalized treatment of hepatitis C 208
  • Responders vs non-responders to treatment for hepatitis C 208
  • Drug resistance in hepatitis C 210
  • Personalized management of tuberculosis 210
  • Personalized management of fungal infections 210
  • Psychiatric disorders 211
  • Psychopharmacogenetics/psychopharmacodynamics 211
  • Serotonin genes 212
  • Calcium channel gene 212
  • Dopamine receptor genes 212
  • COMT genotype and response to amphetamine 212
  • Methylenetetrahydrofolate reductase 213
  • Genotype and response to methylphenidate in children with ADHD 213
  • GeneSight tests for individualized therapy of psychiatric disorders 213
  • Personalized antipsychotic therapy 214
  • Personalized antidepressant therapy 216
  • EEG to predict adverse effects and evaluate antidepressant efficacy 217
  • Individualization of SSRI treatment 217
  • Role of protein sFRP3 in predicting response to antidepressants 218
  • Treatment resistant depression 219
  • Vilazodone with a test for personalized treatment of depression 219
  • Neurological disorders 219
  • Personalized management of Alzheimer's disease 220
  • Personalized management of Parkinson's disease 221
  • Discovery of subgroup-selective drug targets in PD 222
  • Personalized cell therapy for PD 222
  • Personalized management of epilepsy 222
  • Choice of the right AED 223
  • Pharmacogenetics of epilepsy 223
  • Pharmacogenomics of epilepsy 223
  • Drug resistance in epilepsy 224
  • Future prospects for management of epilepsy 226
  • Personalized management of migraine 226
  • Individualization of use of triptans for migraine 227
  • Multitarget therapeutics for personalized treatment of headache 227
  • Personalized management of stroke 227
  • Application of proteomics for personalizing stroke management 228
  • Brain imaging in trials of restorative therapies for stroke 228
  • Decisions for evacuation of intracerebral hemorrhage 228
  • Revascularization procedures in chronic post-stroke stage 229
  • Personalized treatment of multiple sclerosis 229
  • Immunopathological patterns of demyelination for assessing therapy 230
  • Personalizing mitoxantrone therapy of multiple sclerosis 230
  • Fusokine method of personalized cell therapy of multiple sclerosis 230
  • MBP8298 231
  • Pharmacogenomics of IFN-β therapy in multiple sclerosis 231
  • T cell-based personalized vaccine for MS 233
  • Personalized management of pain 233
  • Pharmacogenetics/pharmacogenomics of pain 233
  • Mechanism-specific management of pain 234
  • Preoperative testing to tailor postoperative analgesic requirements 234
  • Personalized analgesics 235
  • Signature of pain on brain imaging 235
  • Personalized management of sleep disorders 236
  • Personalized therapy of insomnia 236
  • Cardiovascular disorders 236
  • Role of diagnostics in personalized management of cardiovascular disease 236
  • Cardiovascular disorders with a genetic component 236
  • Gene mutations associated with risk of coronary heart disease 238
  • Gene variant as a risk factor for sudden cardiac death 238
  • KIF6 gene test as a guide to management of heart disease 239
  • SNP Chip for study of cardiovascular diseases 239
  • SNP genotyping in cardiovascular disorders 240
  • Testing in coronary heart disease 240
  • Pharmacogenomics of cardiovascular disorders 241
  • Modifying the genetic risk for myocardial infarction 241
  • Management of chronic angina pectoris 241
  • Management of heart failure 242
  • β-blockers 242
  • Bucindolol 243
  • BiDil 243
  • Management of hypertension 244
  • Genes and hypertension 244
  • Choice of drugs for hypertension 244
  • Pharmacogenomics of diuretic drugs 244
  • Pharmacogenomics of ACE inhibitors 245
  • Management of hypertension by personalized approach 245
  • Prediction of antihypertensive activity of rostafuroxin 246
  • Pharmacogenetics of lipid-lowering therapies 247
  • Polymorphisms in genes involved in cholesterol metabolism 247
  • Role of eNOS gene polymorphisms 248
  • The STRENGTH study 248
  • Personalized management of women with hyperlipidemia 249
  • Thrombotic disorders 249
  • Factor V Leiden mutation 249
  • Anticoagulant therapy 250
  • Antiplatelet therapy 251
  • Nanotechnology-based personalized therapy of cardiovascular diseases 252
  • Project euHeart for personalized management of heart disease 252
  • Concluding remarks 253
  • Personalized management of pulmonary disorders 253
  • Role of genetic ancestory in lung function 253
  • Personalized therapy of asthma 253
  • Biomarkers for predicting response to corticosteroid therapy 254
  • Genetic polymorphism and response to β2-adrenergic agonists 254
  • Genotyping in asthma 254
  • IgE as guide to dosing of omalizumab for asthma 255
  • Lebrikizumab for personalised treatment of asthma 256
  • Personalized management of chronic obstructive pulmonary disease 256
  • Personalized management of skin disorders 257
  • Genetic testing for personalized skin care 257
  • Management of hair loss based on genetic testing 257
  • Personalized therapy of rheumatoid arthritis 258
  • Genetics and epigenetic aspects of rheumatoid arthritis 258
  • Variations in the effectiveness of various treatments of RA 258
  • Biomarkers for personalizing therapy of rheumatoid arthritis 259
  • DIATSTAT™ anti-cyclic citrullinated peptides in rheumatoid arthritis 259
  • Personalization of COX-2 inhibitor therapy 260
  • Personalization of infliximab therapy 260
  • Personalized approaches in immunology 260
  • Role of Mannose-binding lectin in personalized medicine 261
  • Pharmacogenetics and pharmacogenomics of immunosuppressive agents 261
  • Personalized management of patients with lupus erythematosus 261
  • Personalized management of diabetes 262
  • Management of genetic disorders 263
  • Personalized treatment of cystic fibrosis 263
  • Personalized management of gastrointestinal disorders 264
  • Personalized therapy of inflammatory bowel disease 264
  • Personalized management of lactose intolerance 265
  • Personalized approaches to improve organ transplantation 265
  • Personalization of kidney transplantation 265
  • Personalization of cardiac transplantation 266
  • Prediction of rejection for personalizig anti-rejection treatment 266
  • Personalized immunosuppressant therapy in organ transplants 267
  • Role of immunological biomarkers in monitoring grafted patients 267
  • Improved matching of blood transfusion 268
  • Personalized approach to addiction 268
  • Pharmacogenetics of drug addiction 268
  • Genetic polymorphism and management of alcoholism 269
  • Personalized therapy for smoking cessation 270
  • Antidepressant therapy for smoking cessation 270
  • Effectiveness of nicotine patches in relation to genotype 270
  • Personalized approaches to miscellaneous problems 271
  • Hormone replacement therapy in women 271
  • Personalized treatment of malaria 271
  • Personalized management of osteoporosis 272
  • Personalized management of renal disease 272
  • Gene associated with end-stage renal disease 273
  • Personalized care of trauma patients 273
  • Personalized anticoagulation 273
  • Personalized preventive medicine 274

10. Personalized Therapy of Cancer 275

  • Introduction 275
  • Challenges of cancer classification 275
  • Relationships of technologies for personalized management of cancer 276
  • Impact of molecular diagnostics on the management of cancer 276
  • Analysis of RNA splicing events in cancer 277
  • Analysis of chromosomal alterations in cancer cells 278
  • Cancer classification using microarrays 278
  • Catalog of cancer genes for personalized therapy 279
  • Circulating cancer cell analysis for personalizing therapy 279
  • Detection of loss of heterozygosity 279
  • BEAMing technology for analysis of circulating tumor DNA 280
  • Diagnosis of cancer of an unknown primary 280
  • Diagnostics for detection of minimal residual disease 280
  • DNA repair biomarkers 281
  • Fluorescent in situ hybridization 281
  • Gene expression profiling 281
  • OnkoMatch tumor genotyping 282
  • Gene expression profiles predict chromosomal instability in tumors 283
  • Isolation and characterization of circulating tumor cells 283
  • Modulation of CYP450 activity for cancer therapy 284
  • Pathway-based analysis of cancer 284
  • Conversion of gene-level information into pathway-level information 284
  • Personalized therapies based on oncogenic pathways signatures 284
  • Quantum dot-based test for DNA methylation 285
  • Role of molecular imaging in personalized therapy of cancer 285
  • Functional diffusion MRI 286
  • FDG-PET/CT for personalizing cancer treatment 286
  • Image-guided personalized drug delivery in cancer 287
  • Tumor imaging and elimination by targeted gallium corrole 287
  • Future prospects of molecular imaging in management of cancer 287
  • Unraveling the genetic code of cancer 287
  • Cancer prognosis 288
  • Detection of mutations for risk assessment and prevention 288
  • Impact of biomarkers on management of cancer 289
  • HER-2/neu oncogene as a biomarker for cancer 289
  • L-asparaginase treatment of cancer guided by a biomarker 290
  • Oncogene GOLPH3 as a cancer biomarker 290
  • Predictive biomarkers for cancer 290
  • Sequencing to discover biomarkers to personalize cancer treatment 290
  • VeraTag™ assay system for cancer biomarkers 291
  • Determination of response to therapy 292
  • Biomarker-based assays for predicting response to anticancer therapeutics 292
  • ChemoFx cell culture assay for predicting anticancer drug response 292
  • Ex vivo testing of tumor biopsy for chemotherapy sensitivity 292
  • Genomic approaches to predict response to anticancer agents 293
  • Gene expression patterns to predict response of cancer to therapy 293
  • Genomic analysis of tumor biopsies 293
  • Genotype-dependent efficacy of pathway inhibition in cancer 294
  • Mutation detection at molecular level 294
  • RNA Disruption Assay™ 294
  • Role of genetic variations in susceptibility to anticancer drugs 295
  • Non-genetic factors for variations in response of cancer cells to drugs 295
  • Proteomic analysis of tumor biopsies to predict response to treatment 295
  • Real-time apoptosis monitoring 296
  • Serum nucleosomes as indicators of sensitivity to chemotherapy 296
  • Targeted microbubbles to tumors for monitoring anticancer therapy 297
  • PET imaging for determining response to chemotherapy 297
  • PET imaging with tyrosine kinase inhibitors 297
  • Tissue systems biology approach to personalized management of cancer 298
  • Molecular diagnostics combined with cancer therapeutics 298
  • AmpliChip P53 as companion diagnostic for cancer 298
  • Aptamers for combined diagnosis and therapeutics of cancer 299
  • Combining diagnosis and therapy of metastatic cancer 299
  • Monoclonal antibodies for combining diagnosis with therapy of cancer 300
  • Molecular profiling of cancer 300
  • Targeted cancer therapies 301
  • Targeting glycoproteins on cell surface 301
  • Targeting pathways in cancer 301
  • Targeted personalized anticancer medicines in clinical use 301
  • Functional antibody-based therapies 302
  • Personalized cancer vaccines 303
  • Antigen-specific vaccines 303
  • Active immunotherapy based on antigen specific to the tumor 303
  • Tumor-derived vaccines 304
  • FANG vaccine 305
  • MyVax 305
  • OncoVAX 305
  • Tumor cells treated with dinitrophenyl 305
  • Prophage 306
  • Melacine 306
  • Patient-specific cell-based vaccines 306
  • Dendritic cell-based vaccines 306
  • Adoptive cell therapy 308
  • Combination of antiangiogenic agents with ACT 309
  • Genetically targeted T cells for treating B cell malignancies 310
  • Genetic engineering of tumor cells 310
  • Hybrid cell vaccination 310
  • Personalized peptide cancer vaccines 311
  • Current status and future prospects of personalized cancer vaccines 311
  • Personalized radiation therapy 312
  • Use of radiation sensitivity biomarkers to personalized radiotherapy 313
  • Use of imaging to monitor radioimmunotherapy of non-Hodgkin lymphoma 314
  • Role of nanobiotechnology in personalized management of cancer 314
  • Design of future personalized cancer therapies 315
  • Personalized therapy of cancer based on cancer stem cells 315
  • Role of epigenetics in development of personalized cancer therapies 316
  • Screening for personalized anticancer drugs 316
  • Selective destruction of cancer cells while sparing normal cells 316
  • Sphingolipids 317
  • Hyperbaric oxygen as adjunct to radiotherapy 317
  • Targeting response to transformation-induced oxidative stress 317
  • Targeting enzymes to prevent proliferation of cancer cells 318
  • Role of oncoproteomics in personalized therapy of cancer 318
  • Cancer tissue proteomics 318
  • Role of sequencing in personalized therapy of cancer 319
  • Pharmacogenomic-based chemotherapy 319
  • Whole genome technology to predict drug resistance 319
  • Anticancer drug selection based on molecular characteristics of tumor 320
  • Testing microsatellite-instability for response to chemotherapy 320
  • Pharmacogenetics of cancer chemotherapy 321
  • CYP 1A2 321
  • Thiopurine methyltransferase 321
  • Dihydropyrimidine dehydrogenase 322
  • UGT1A1 test as guide to irinotecan therapy 322
  • Role of computational models in personalized anticancer therapy 323
  • A computational model of kinetically tailored treatment 323
  • Mathematical modeling of tumor mivroenvironments 324
  • Modeling signaling pathways to reposition anticancer drugs 324
  • Therapy resistance in cancer 324
  • Mechanism of therapy resistance in cancer 325
  • Role of splice variants in resistance to cancer therapy 325
  • Expression of P-glycoprotein gene by tumor 325
  • Overexpression of multidrug resistance gene 325
  • P53 mutations 326
  • Detection of drug resistance 326
  • Anaplastic lymphoma kinase 326
  • Metabolic profiling of cancer 326
  • Management of drug resitance in cancer 327
  • Chemogenomic approach to drug resistance 327
  • Determination of chemotherapy response by topoisomerase levels 327
  • Management of drug resistance in leukemia 327
  • Resistance to vaccines in cancer recurrence after surgery 328
  • Systems biology approach to drug-resistant cancer 328
  • Personalized therapy of cancer metastases 329
  • Personalized management of cancers of various organs 329
  • Personalized management of brain tumors 329
  • Aptamers for selective targeting of tumor initiating cells in GBM 329
  • Bioinformatic approach to personalizing treatment of GBM 330
  • Biosimulation approach to personalizing treatment of brain cancer 330
  • Companion diagnostic for viral gene therapy of brain cancer 330
  • Drug resistance in GBM 331
  • Genetics and genomics of brain cancer 331
  • Glioma Actively Personalized Vaccine Consortium 332
  • Prognosis of glioblastoma multiforme based on its genetic landscape 333
  • Molecular diagnostics for personalized management of brain cancer 333
  • Personalized chemotherapy of brain tumors 335
  • Supratentorial hemispheric diffuse low-grade gliomas 336
  • Personalized therapy of oligodendroglial tumors (OTs) 337
  • Personalized therapy of neuroblastomas 337
  • Personalized therapy of medulloblastomas 338
  • Personalized management of germ cell brain tumors 338
  • Personalized management of meningiomas 339
  • Future prospects of personalized therapy of malignant gliomas 339
  • Personalized management of breast cancer 340
  • Developing personalized drugs for breast cancer 340
  • Gene expression plus conventional predictors of breast cancer 341
  • Her2 testing in breast cancer as a guide to treatment 342
  • HER2/neu-derived peptide vaccine for breast cancer 343
  • Molecular diagnostics in breast cancer 344
  • Monitoring of circulating tumor cells in metastatic breast cancer 346
  • Pharmacogenetics of breast cancer 346
  • Proteomics-based personalized management of breast cancer 347
  • Predicting response to chemotherapy in breast cancer 347
  • Prediction of resistance to chemotherapy in breast cancer 350
  • Prediction of adverse reaction to radiotherapy in breast cancer 351
  • Prediction of recurrence in breast cancer for personalizing therapy 351
  • Prognosistic tests for breast cancer 353
  • Racial factors in the management of breast cancer 355
  • RATHER consortium to study personalized approach to breast cancer 355
  • TAILORx (Trial Assigning Individualized Options for Treatment) 356
  • Tamoxin therapy for ER-positive breast cancer 356
  • Triple negative breast cancer 357
  • Trends and future prospects of breast cancer research 357
  • Understanding tumor diversity in mouse mammary cancer model 359
  • Personalized management of ovarian cancer 359
  • Early diagnosis of ovarian cancer 359
  • Determining response to chemotherapy in ovarian cancer 360
  • Prognosis of ovarian cancer based on CLOVAR 360
  • Recurrent and drug-resistant ovarian cancer 361
  • Pathway targeted therapies for ovarian cancer 362
  • Vynfinit ® for platinum-resistant ovarian cancer 363
  • Personalized management of head and neck cancer 364
  • Relevance of biomarkers of HPV-related head and neck cancer 364
  • Personalized management of hematological malignancies 365
  • Personalized management of acute lymphoblastic leukemia 365
  • Personalized management of acute myeloid leukemia 366
  • Personalized management of chronic lymphocytic leukemia 368
  • Personalized management of multiple myeloma 369
  • Personalized management of myelodysplastic syndrome 370
  • Personalized management of lymphomas 371
  • Personalized management B cell lymphomas 371
  • Personalized vaccine for follicular lymphoma 372
  • Companion diagnostic for treatment of lymphoma with Adcentris™ 372
  • Personalized management of hepatocellular carcinoma 372
  • Personalized management of gastrointestinal cancer 373
  • Personalized management of esophageal cancer 373
  • Personalized management of gastric cancer 373
  • Personalized management of colorectal cancer 374
  • Sequencing for personalized management of colorectal cancer 377
  • Systems biology approach to drug resistance in colorectal cancer 378
  • Resistance to targeted EGFR blockade in CRC 378
  • Personalized management of liver cancer 379
  • Personalized management of lung cancer 379
  • Crizotinib for personalized management of NSCLC 380
  • Ceritinib 380
  • EGFR tyrosine kinase inhibitor treatment 380
  • Development of resistance to EGFR inhibitors 382
  • Molecular subtyping of lung cancer 383
  • Personalized therapy of NSCLC based on KIF5B/RET fusion oncogene 383
  • Predicting response of NSCLC to platinum-based therapy 383
  • Proteomics for discovery of metabolic biomarkers of lung cancer 384
  • Role of a new classification system in the management of lung cancer 384
  • Selecting therapy of cancer arising from respiratory papillomatosis 384
  • Testing for response to chemotherapy in lung cancer 384
  • Testing for prognosis of lung cancer 385
  • Testing for recurrence of lung cancer 385
  • Personalized management of malignant melanoma 386
  • Inhibitors of BRAF mutation for metastatic melanoma 386
  • Management of drug-resistant metastatic melanoma 387
  • Vaccine for malignant melanoma based on heat shock protein 387
  • Personalized management of pancreatic cancer 387
  • Biomarkers of pancreatic cancer 388
  • Histone modifications predict treatment response in pancreatic cancer 388
  • Transport properties of pancreatic cancer and gemcitabine delivery 389
  • Personlized management of prostate cancer 389
  • Assessing susceptibility to prostate cancer by genotyping 389
  • Diagnostics for guiding therapy of prostate cancer 390
  • Detection of prostate cancer metastases 391
  • Early detection of cancer recurrence and guiding treatment 391
  • Effects of of lifestyle changes shown by gene expression studies 391
  • Prolaris assay for determining prognosis in prostate cancer 392
  • Personalized peptide vaccine for prostate cancer 392
  • Future of cancer therapy 392
  • Challenges for developing personalized cancer therapies 392
  • Cancer Genome Atlas 393
  • COLTHERES consortium 393
  • Computer and imaging technologies for personalizing cancer treatment 393
  • Genomic Cancer Care Alliance 394
  • Global Cancer Genomics Consortium 394
  • Integrated genome-wide analysis of cancer for personalized therapy 394
  • International Cancer Genome Consortium 395
  • National Cancer Institute of US 396
  • PREDICT Consortium 396
  • Quebec Clinical Research Organization in Cancer 396
  • Companies involved in developing personalized cancer therapy 397

11. Development of Personalized Medicine 401

  • Introduction 401
  • Non-genomic factors in the development of personalized medicine 401
  • Personalized medicine based on circadian rhythms 401
  • Cytomics as a basis for personalized medicine 402
  • Intestinal microflora 403
  • - 14 -
  • Gut microbiome compared to human genome 403
  • Metabolic interactions of the host and the intestinal microflora 403
  • Role of drug delivery in personalized medicine 404
  • Personalized approach to clinical trials 404
  • Use of Bayesian approach in clinical trials 404
  • Individualzing risks and benefits in clinical trials 405
  • Clinical trials of therapeutics and companion diagnostics 405
  • Players in the development of personalized medicine 406
  • Personalized Medicine Coalition 406
  • European Personalized Medicine Diagnostics Association 407
  • Role of pharmaceutical industry 407
  • Production and distribution of personalized medicines 408
  • Role of biotechnology companies 409
  • Role of life sciences industries 409
  • Role of molecular imaging in personalized medicine 410
  • Molecular imaging for personalized drug development in oncology 410
  • Molecular imaging and CNS drug development 412
  • Companies involved in molecular imaging 412
  • Role of the clinical laboratories 413
  • Role of the US government in personalized medicine 413
  • Department of Health and Human Services and personalized medicine 414
  • Agency for Healthcare Research and Quality 415
  • Comparative effectiveness research 416
  • Role of the US Government agencies in personalized medicine 417
  • NIH's Roadmap Initiative for Medical Research 417
  • NIH and personalized medicine 418
  • NIH collaboration with the FDA 418
  • NIH and Genetic Testing Registry 419
  • National Human Genome Research Institute 419
  • National Institute of General Medical Sciences 419
  • National Institute of Standards and Technology 421
  • Role of the Centers for Disease Control 422
  • Role of academic institutions in the US 422
  • Baylor College of Medicine 422
  • Clinical Proteomics Program of NCI & FDA 422
  • Coriell Personalized Medicine Collaborative™ 423
  • Delaware Valley Personalized Medicine Project 423
  • Duke University Medical Center and genomic medicine 424
  • Evaluation of genetic tests and genomic applications 424
  • Ignite Institute 425
  • Indiana University Institute for Personalized Medicine 425
  • Institute of Medicine's role in personalized medicine 426
  • Jackson Laboratory for Genomic Medicine 426
  • Johns Hopkins Center for Personalized Cancer Medicine Research 427
  • Mayo Clinic's Centers for Individualized Medicine 427
  • Mt. Sinai Medical Center's Personalized Medicine Research Program 428
  • P4 Medicine Institute 428
  • Personalized Medicine Partnership of Florida 428
  • Personalized oncology at Massachusetts General Hospital 429
  • Personalized oncology at Oregon Health & Science University 429
  • Pharmacogenetics Research Network and Knowledge Base 429
  • Southeast Nebraska Cancer Center's Personalized Medicine Network 430
  • Stanford Center for Genomics and Personalized Medicine 430
  • UAB-HudsonAlpha Center for Genomic Medicine 430
  • University of Colorado's Center for Personalized Medicine 431
  • UNC Institute for Pharmacogenomics and Individualized Therapy 431
  • Wisconsin Genomics Initiative 431
  • Role of academic collaborations with companies 432
  • New York Genome Center 432
  • Role of healthcare organizations 432
  • Role of the medical profession 432
  • The American Medical Association and personalized medicine 432
  • Education of the physicians 433
  • Off-label prescribing and personalized medicine 433
  • Medical education 434
  • Role of patients 434
  • Public attitude towards personalized medicine 434
  • Role of genetic banking systems and databases 435
  • Role of biobanks in development of personalized medicine 435
  • UK Biobank 436
  • Biobanking and development of personalized medicine in EU 436
  • - 15 -
  • CARTaGENE for biobanks in Canada 437
  • Personalized medicine based on PhysioGenomics™ technology 437
  • Role of bioinformatics in development of personalized medicine 437
  • Exploration of disease-gene relationship 439
  • Biosimulation techniques for developing personalized medicine 439
  • Health information management 440
  • Electronic health records 440
  • Cost of EHR and savings on healthcare expenses in the US 440
  • EHRs and genome-wide studies 441
  • Linking patient medical records and genetic information 441
  • Management of personal genomic data 442
  • Use of EHRs for improving safety of new medicines 442
  • Use of EHRs for genetic research 442
  • Use of EHRs for personalized drug discovery and development 443
  • Personalized prognosis of disease 443
  • Integration of technologies for development of personalized medicine 444
  • Global scope of personalized medicine 444
  • Personalized medicine in Canada 444
  • Personalized medicine at Ontario Institute for Cancer Research 444
  • Personalized Medicine Partnership for Cancer in Quebec 446
  • Quebec Center of Excellence in Personalized Medicine 446
  • Personalized medicine in the EU 447
  • UK National Health Service and medical genetics 447
  • Personalized medicine in Germany 448
  • Personalized medicine in Israel 448
  • Personalized medicine in the developing countries 449
  • Advantages and limitations of personalized medicine 450
  • Limitations of personalized medicine 451
  • Future of personalized medicine 452
  • Ongoing genomic projects 452
  • Understanding the genetic basis of diseases 452
  • Personal Genome Project 452
  • Genome-wide association studies 453
  • The 1000 Genomes Project 454
  • Genomics of aging in a genetically homogeneous population 454
  • Translational science and personalized medicine 455
  • Translation of genomic research into genetic testing for healthcare 455
  • Long-term behavioral effects of personal genetic testing 456
  • Personalized predictive medicine 456
  • Connected health and personalized medicine 457
  • Opportunities and challenges 457
  • Prospects and limitations of genetic testing 457
  • Genetic testing and concerns about equality of healthcare 458
  • Pharmacotyping 459
  • Comparative-effectiveness research and personalized medicine 459
  • Medicine in the year 2018 459
  • Concluding remarks about the future of personalized medicine 460

12. Ethical, Legal and Regulatory Aspects of Personalized Medicine 463

  • Introduction to ethical issues 463
  • Ethical issues of pharmacogenetics 463
  • Ethical aspects of genetic information 463
  • Ethical issues of whole genome analysis 463
  • Ethical aspects of direct-to-consumer genetic services 464
  • Privacy issues in personalized medicine 465
  • Genetic Information Nondiscrimination Act in the US 466
  • Genotype-specific clinical trials 466
  • Social issues in personalized medicine 466
  • Race and personalized medicine 467
  • Legal issues of personalized medicine 468
  • Gene patents and personalized medicine 469
  • Regulatory aspects 469
  • CLSI guideline for the use of RNA controls in gene expression assays 470
  • MicroArray Quality Control Project 470
  • Regulatory aspects of pharmacogenetics 471
  • Regulation of direct-to-consumer genetic testing 472
  • Need for regulatory oversight of DTC 472
  • FDA and pharmacogenomics 474
  • FDA guidance for pharmacogenomic data submissions 475
  • Joint guidelines of the FDA and EU regulators for pharmacogenomics 476
  • Pharmacogenomic/pharmacogenetic information in drug labels 476
  • FDA guidelines for pharmacogenomics-based dosing 477
  • FDA and validation of biomarkers 477
  • FDA and predictive medicine 478
  • FDA regulation of multivariate index assays 478
  • Evaluation of companion diagnostics/therapeutic 480

13. Commercial Aspects of Personalized Medicine 483

  • Introduction 483
  • Perceived financial concerns 483
  • Personalized medicine and orphan drug syndrome 483
  • Commercial aspects of pharmacogenomics 483
  • Cost of DNA testing 483
  • Cost of sequencing the human genome 484
  • Cost of genotyping 486
  • Cost of pharmacogenomics-based clinical trials 487
  • Business development of pharmacogenomic companies 487
  • Cost of personalized healthcare 488
  • The rising healthcare costs in the US 488
  • Genetic testing and cost of healthcare 488
  • Reducing healthcare costs by combining diagnostics with therapeutics 489
  • Cost-effectiveness of pharmacogenetic testing 489
  • Cost-effectiveness of CYP genotyping-based pharmacotherapy 490
  • Cost effectiveness of HIV genotyping in treatment of AIDS 490
  • Cost-effectiveness of warfarin pharmacogenomics 491
  • Cost-benefit analysis of KRAS and BRAF screening in CRC 491
  • Lowering the high costs of cancer chemotherapy 492
  • Overall impact of personalized medicine on healthcare 492
  • Drivers for the development of personalized medicine 492
  • Evolution of medicine as a driver for personalized therapy markets 493
  • Collaboration between the industry and the academia 494
  • Personalized medicine and drug markets 494
  • Segmentation of therapeutic drug markets 494
  • Reasons for increase of market values of personalized medicines 495
  • Growth of markets relevant to personalized medicine 495
  • Biochips 496
  • Pharmacogenetics 496
  • Pharmacogenomics 496
  • Pharmacoproteomics 496
  • Point-of-Care 496
  • SNP market 496
  • Markets for personalized medicines according to therapeutic areas 497
  • Market for personalized cancer therapy 497
  • Markets for personalized medicines according to geographical regions 497
  • Market opportunities for personalization of medicine 498
  • Impact of personalized medicine on other industries 498
  • Strategies for developing and marketing personalized medicine 499
  • Education of the public 499
  • Role of the Internet in development of personalized medicine 500
  • Marketing companion diagnostics for personalized medicine 500

14. References 503

Tables

  • Table 1-1: Selected terms relevant to the concept of personalized medicine 23
  • Table 1-2: Landmarks in the historical development of personalized medicine 24
  • Table 1-3: Genetic variations in the human genome 29
  • Table 2-1: Molecular diagnostic technologies used for personalized medicine 51
  • Table 2-2: Applications of biochip technology relevant to personalized medicine 71
  • Table 2-3: Companies developing haplotying technology 86
  • Table 2-4: Technologies for SNP analysis 86
  • Table 2-5: A sampling of companies involved in technologies for SNP genotyping 95
  • Table 2-6: Comparison of proteomic and genomic approaches in personalized medicine 103
  • Table 2-7: Selected methods for gene expression profiling 104
  • Table 2-8: A selection of companies with gene expression technologies 109
  • Table 2-9: Drugs requiring biomarker/companion diagnostic information in the label 112
  • Table 2-10: Companies involved in companion diagnostics 113
  • Table 2-11: Applications of point-of-care diagnosis 115
  • Table 2-12: Companies developing point-of-care diagnostic tests 116
  • Table 2-13: Companies offering genetic screening tests directly to consumers 120
  • Table 3-1: Pharmacogenetic vs. pharmacogenomic studies 126
  • Table 3-2: Enzymes relevant to drug metabolism 128
  • Table 3-3: Examples of mutation of the enzyme CYP450 129
  • Table 3-4: Frequency distribution of drugs metabolized by major isoforms of CYP450. 129
  • Table 3-5: Commonly prescribed medications, which are metabolized by CYP2D6 129
  • Table 3-6: Polymorphisms in drug target genes that can influence drug response 135
  • Table 3-7: Effect of genetic polymorphisms on disease response to drugs 136
  • Table 3-8: Examples of genetically determined adverse reactions to drugs 139
  • Table 3-9: Examples of genotyping and phenotyping in some diseases 147
  • Table 3-10: Companies with novel molecular toxicology technology 149
  • Table 3-11: Pharmacogenomic biomarkers in drug labeling 152
  • Table 4-1: Role of pharmacogenomics in variable therapy targets 161
  • Table 4-2: Role of pharmacogenomics in clinical trials 164
  • Table 4-3: Examples of pharmacogenomics-based clinical studies 165
  • Table 4-4: Tumor suppressor genes, their chromosomal location, function and associated tumors. 168
  • Table 4-5: Gene polymorphisms relevant to cardiovascular disease management 169
  • Table 4-6: Companies involved in cardiovascular genomics 171
  • Table 4-7: A sampling of companies involved in neuropharmacogenomics 173
  • Table 9-1: Important therapeutic areas for personalized medicine 201
  • Table 9-2: Enzymes that metabolize antipsychotics 215
  • Table 9-3: Enzymes that metabolize antidepressants 216
  • Table 9-4: Gene expression as biomarker of response to IFN-β in multiple sclerosis 232
  • Table 9-5: Genes that cause cardiovascular diseases 237
  • Table 9-6: Genetic influences on pharmacotherapy of alcoholism 269
  • Table 10-1: Factors that drive the development of personalized therapy in cancer 275
  • Table 10-2: Impact of molecular diagnostics on the management of cancer 277
  • Table 10-3: Marketed anticancer personalized medicines 301
  • Table 10-4: Clinical trials of personalized cancer vaccines 311
  • Table 10-5: Selected companies involved in developing personalized cancer therapies 397
  • Table 11-1: Players in the development of personalized medicine 406
  • Table 11-2: Members of the Personalized Medicine Coalition 406
  • Table 11-3: Biobanks relevant to personalized medicine 435
  • Table 11-4: Role of bioinformatics in the development of personalized medicine 438
  • Table 11-5: Advantages of personalized medicine for the biopharmaceutical industry 450
  • Table 11-6: Advantages of personalized medicine for the patients 450
  • Table 11-7: Advantage of personalized medicine for the physicians 450
  • Table 11-8: Advantage of personalized medicine for the healthcare providers 450
  • Table 11-9: Limitations of personalized medicine 451
  • Table 11-10: Methods of translational science that are relvant to personalized medicine 455
  • Table 11-11: Companies involved in predictive healthcare 456
  • Table 12-1: Drugs with genetic information in their labels 476
  • Table 13-1: Drivers for the development of personalized medicine 492
  • Table 13-2: Growth of markets relevant to personalized medicine 2013-2023 495
  • Table 13-3: Markets for personalized medicine according to therapeutic area 2013-2023 497
  • Table 13-4: Markets for personalized medicine in major regions 2013-2023 497
  • Table 13-5: Lack of efficacy in current therapy 498
  • Table 13-6: Impact of personalized medicine on other industries 498
  • Table 13-7: Strategies to develop personalized medicine 499
  • Table 13-8: Role of the Internet in development of personalized medicine 500

Figures

  • Figure 1-1: Relation of personalized medicine to other technologies 39
  • Figure 1-2: Relation of systems pharmacology to personalized medicine 45
  • Figure 2-1: Role of sequencing in personalized medicine 69
  • Figure 2-2: Role of biochip/microarray technology in personalized medicine 71
  • Figure 2-3: Application of biochips/microarrays in personalized therapy 72
  • Figure 2-4: Affymetrix GeneChip technology 73
  • Figure 2-5: Role of CYP450 genotyping in development of personalized medicine 74
  • Figure 2-6: Role of SNPs in personalized medicine 82
  • Figure 2-7: A scheme of integrated healthcare and personalized medicine 122
  • Figure 3-1: Pharmacogenetics as a link between genotype and phenotype 125
  • Figure 3-2: Role of pharmacogenetic technologies in personalized medicine 126
  • Figure 4-1: Impact of new technologies at various stages of the drug discovery process 163
  • Figure 4-2: Steps in the application of pharmacogenomics in clinical trials 165
  • Figure 7-1: Role RNAi in development of personalized medicine 191
  • Figure 9-1: Workflow of genotypic resistance analysis for personalized HIV therapy 207
  • Figure 9-2: Scheme of iPSCs for personalized cell therapy of Parkinson disease 222
  • Figure 9-3: A scheme of personalized management of pain 233
  • Figure 9-4: A scheme of personalized approach to management of hypertension 246
  • Figure 10-1: Relationships of technologies for personalized management of cancer 276
  • Figure 11-1: Integration of technologies for the development of personalized medicine 444
  • Figure 13-1: Cost of sequencing per genome 486
  • Figure 13-2: Evolution of personalized medicine as a market driver 493

Part II

14. Companies Involved in Developing Personalized Medicine 5

  • Introduction 5
  • Profiles 5
  • Collaborations 205

Tables

  • Table 14-1: Top five companies involved in personalized medicine 5
  • Table 14-2: Selected collaborations of companies in personalized medicine 205
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