客置化醫療：科學・商業情勢

Abstract

Summary

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 2012.

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 2008-2018.

Profiles of 210 companies involved in developing technologies for personalized medicines, along with 402 collaborations are included in the part II of the report. Finally the bibliography contains over 500 selected publications cited in the report.The report is supplemented by 57 tables and 17 figures.

Table of Contents

0. Executive Summary 17

1. Basic Aspects 19

• Definition of personalized medicine 19
• History of medical concepts relevant to personalized medicine 20
• Molecular biological basis of personalized medicine 22
• The human genome 22
• Chromosomes 23
• Genes 23
• The genetic code 23
• Gene expression 23
• DNA sequences and structure 24
• Single nucleotide polymorphisms 24
• Genotype and haplotypes 25
• Genetic variations in the human genome 25
• Insertions and deletions in the human genome 25
• Large scale variation in human genome 26
• Variation in copy number in the human genome 26
• Structural variations in the human genome 27
• Mapping and sequencing of structural variation from human genomes 27
• 1000 Genomes Project 28
• Human Variome Project 29
• Basics technologies for developing personalized medicine 29
• Definitions of technologies relevant to personalized medicine 29
• Problems with the ICH definitions of pharmacogenomcis and pharmacogenetics 30
• Relationship of various technologies to personalized medicine 30
• Conventional medicine versus personalized medicine 31
• Role of genetics in future approaches to healthcare 32
• Genetic medicine 32
• Human disease and genes 32
• Genetic and environmental interactions in etiology of human diseases 32
• Mass analysis of DNA from whole populations 33
• Role of genetics in development of personalized medicines 33
• Genetic databases 33
• Genetic epidemiology 34
• Limitations of medical genetics and future prospects 34
• Genetics vs. epigenetics 35
• Role of systems biology in personalized medicine 35
• Systems pharmacology 36
• Systems medicine 37
• A personalized approach to environmental factors in disease 37
• Reclassification of diseases 37

2. Molecular Diagnostics in Personalized Medicine 39

• Introduction 39
• Molecular diagnostic technologies 39
• PCR-based methods 40
• DirectLinear"! Analysis 40
• Denaturing high-performance liquid chromatography 41
• Multiplex Allele-Specific Diagnostic Assay 41
• Representational oligonucleotide microarray analysis 41
• Restriction fragment length polymorphism (RFLP) 41
• Real-time PCR for detection of CNVs 41
• Non-PCR methods 42
• Arrayed primer extension (APEX) 42
• Enzymatic Mutation Detection (EMD) 42
• DNA sequencing 42
• Sanger-sequencing technology 43
• Cyclic array sequencing 44
• 454 Pyrosequencing technology 44
• Electron microscope-based DNA sequencing 44
• Illumina Genome Analyzer System 45
• Multiplex amplification of human DNA sequences 45
• Sequencing by hybridization 46
• SOLiD technology 46
• Whole genome sequencing 46
• Bioinformatic tools for analysis of genomic sequencing data 47
• Detection of single molecules in real time 47
• Direct observation of nucleotide incorporation 47
• Molecular Combing 47
• Nanopore sequencing 48
• DNA sequence by use of nanoparticles 48
• Zero-mode waveguide nanostructure arrays 48
• Future prospects of sequencing 48
• Biochips and microarrays 49
• Application of biochip technology in developing personalized medicine 49
• Standardizing the microarrays 50
• Biochip technologies 51
• GeneChip 51
• AmpliChip CYP450 51
• Microfluidics 54
• Lab-on-a-chip 54
• Micronics' microfluidic technology 55
• LabCD 55
• Microfluidic automated DNA analysis using PCR 55
• Integrated microfluidic bioassay chip 55
• Electronic detection of nucleic acids on microarrays 56
• Strand displacement amplification on a biochip 56
• Rolling circle amplification on DNA microarrays 57
• Universal DNA microarray combining PCR and ligase detection reaction 57
• Protein biochips 57
• ProteinChip 58
• LabChip for protein analysis 58
• TRINECTIN proteome chip 59
• Protein expression microarrays 59
• Microfluidic devices for proteomics-based diagnostics 60
• New developments in protein chips 60
• Protein chips for personalized medicine 61
• SNP genotyping 61
• Haplotyping 62
• Haplotype Specific Extraction 62
• Computation of haplotypes 63
• HapMap project 63
• Predictingdrug response with HapMap 64
• Companies developing haplotyping technology 64
• Technologies for SNP analysis 64
• Biochip and microarray-based detection of SNPs 65
• SNP genotyping by MassARRAY 65
• Biochip combining BeadArray and ZipCode technologies 66
• SNP-IT primer-extension technology 66
• OmniScan SNP genotyping 67
• Affymetrix Variation Detection Arrays 67
• Use of NanoChip for detection of SNPs 67
• DNA sequencing 67
• Electrochemical DNA probes 68
• Single base extension-tag array 68
• Laboratory Multiple Analyte Profile 68
• PCR-CTPP (confronting two-pair primers) 69
• SNP genotyping on a genome-wide amplified DOP-PCR template 69
• TaqMan real-time PCR 69
• Non-Enzymatic Amplification Technology 70
• SNP genotyping with gold nanoparticle probes 70
• Locked nucleic acid 70
• Molecular inversion probe based assays 71
• Pyrosequencing 71
• Reversed enzyme activity DNA interrogation test 72
• Smart amplification process version 2 72
• Zinc finger proteins 73
• UCAN method (Takara Biomedical) 73
• Mitochondrial SNPs 73
• Limitations of SNP in genetic testing 73
• Concluding remarks on SNP genotyping 74
• Companies involved in developing technologies/products for SNP analysis 74
• Impact of SNPs on personalized medicine 76
• Optical Mapping 76
• Role of nanobiotechnology in molecular diagnostics 76
• Cantilevers for personalized medical diagnostics 77
• Nanopore-based technology for single molecule identification 78
• Role of biomarkers in personalized medicine 78
• Biomarkers for diagnostics 78
• Biomarkers for drug development 79
• Application of proteomics in molecular diagnosis 79
• Proteomic strategies for biomarker identification 80
• Proteomic technologies for detection of biomarkers in body fluids 80
• Protein patterns 80
• Layered Gene Scanning 81
• Comparison of proteomic and genomic approaches in personalized medicine 81
• Gene expression profiling 82
• DNA microarrays 83
• Analysis of single-cell gene expression 83
• Gene expression profiling based on alternative RNA splicing 83
• Whole genome expression array 84
• Tangerine"! expression profiling 85
• Gene expression analysis on biopsy samples 85
• Profiling gene expression patterns of white blood cells 85
• Serial analysis of gene expression (SAGE) 86
• Multiplexed Molecular Profiling 87
• Gene expression analysis using competitive PCR and MALDI TOF MS 87
• Monitoring in vivo gene expression by magnetic resonance imaging 87
• Companies involved in gene expression analysis 88
• Monitoring in vivo gene expression by molecular imaging 89
• Molecular imaging and personalized medicine 89
• Glycomics-based diagnostics 89
• Combination of diagnostics and therapeutics 90
• Companies combining diagnostics and therapeutics 90
• Point-of-care diagnosis 92
• Companies developing point-of-care diagnostic technologies 93
• Point-of-care diagnosis of infections 95
• Advantages versus disadvantages of point-of-care diagnosis 95
• Future prospects of point-of-care diagnosis 96
• Genetic testing for disease predisposition 96
• Personal genetic service 96
• Role of diagnostics in integrated healthcare 98
• Concept of integrated healthcare 98
• Components of integrated healthcare 98
• Screening 98
• Disease prediction 99
• Early diagnosis 99
• Prevention 99
• Therapy based on molecular diagnosis 99
• Monitoring of therapy 99
• Advantages and limitations of integrated healthcare 99
• Commercially available systems for integrated healthcare 100
• Future of molecular diagnostics in personalized medicine 100

3. Pharmacogenetics 103

• Basics of pharmacogenetics 103
• Role of molecular diagnostics in pharmacogenetics 104
• Role of pharmacogenetics in pharmaceutical industry 105
• Study of the drug metabolism and pharmacological effects 105
• Causes of variations in drug metabolism 105
• Enzymes relevant to drug metabolism 106
• Pharmacogenetics of phase I metabolism 106
• CYP450 106
• P450 CYP 2D6 inhibition by selective serotonin reuptake inhibitors 108
• Cytochrome P450 polymorphisms and response to clopidogrel 109
• Lansoprazole and cytochrome P450 109
• Glucose-6-phosphate dehydrogenase 109
• Pharmacogenetics of phase II metabolism 110
• N-Acetyltransferase 110
• Uridine diphosphate-glucuronosyltransferase 111
• Measurement of CYP isoforms 111
• Polymorphism of drug transporters 112
• Genetic variation in drug targets 112
• Polymorphisms of kinase genes 113
• Effect of genetic polymorphisms on disease response to drugs 113
• Ethnic differences in drug metabolism 113
• Gender differences in pharmacogenetics 114
• Role of pharmacogenetics in drug safety 114
• Adverse drug reactions 114
• Adverse drug reactions in children 115
• Adverse drug reactions related to toxicity of chemotherapy 115
• Genetically determined adverse drug reactions 116
• Malignant hyperthermia 117
• Pharmacogenetics of clozapine-induced agranulocytosis 117
• Role of pharmacogenetics in warfarin therapy 117
• Role of pharmacogenetics in carbamazepine therapy 118
• Role of pharmacogenetics in statin therapy 119
• FDA consortium linking genetic biomarkers to serious adverse events 119
• Therapeutic drug monitoring, phenotyping, and genotyping 120
• Therapeutic drug monitoring 120
• Phenotyping 120
• Genotyping 122
• Genotyping vs phenotyping 122
• Phenomics 122
• Limitations of genotype-phenotype association studies 123
• Molecular toxicology in relation to personalized medicines 123
• Toxicogenomics 123
• Companies involved in molecular toxicology 124
• Gene expression studies 125
• Genomics and the prediction of xenobiotic toxicity 125
• Pharmacogenetics in clinical trials 126
• Postmarketing pharmacogenetics 126
• Clinical implications of pharmacogenetics 127
• Application of CYP450 genotyping in clinical practice 127
• Genotype-based drug dose adjustment 127
• Examples of use of pharmacogenetics in clinical pharmacology 127
• Linking pharmacogenetics with pharmacovigilance 128
• Genetic susceptibility to ADRs 128
• Linking genetic testing to postmarketing ADR surveillance 129
• Recommendations for the clinical use of pharmacogenetics 129
• Limitations of pharmacogenetics 129
• Academic research in pharmacogenetics 130
• Future role of pharmacogenetics in personalized medicine 131

4. Pharmacogenomics 133

• Introduction 133
• Basics of pharmacogenomics 134
• Pharmacogenomics and drug discovery 134
• Preclinical prediction of drug efficacy 136
• Pharmacogenomics and clinical trials 136
• Impact of genetic profiling on clinical studies 138
• Limitations of the pharmacogenomic-based clinical trials 139
• Pharmacogenomic aspects of major therapeutic areas 139
• Oncogenomics 139
• Oncogenes 140
• Tumor suppressor genes 140
• Cardiogenomics 141
• Neuropharmacogenomics 143
• Pharmacogenomics of Alzheimer' s disease 144
• Pharmacogenomics of depression 144
• Pharmacogenomics of schizophrenia 144
• Companies involved in neurogenomics-based drug discovery 145

5. Role of Pharmacoproteomics 147

• Basics of proteomics 147
• Proteomic approaches to the study of pathophysiology of diseases 147
• Single cell proteomics for personalized medicine 148
• Diseases due to misfolding of proteins 148
• Therapies for protein misfolding 149
• Significance of mitochondrial proteome in human disease 150
• Proteomic technologies for drug discovery and development 150
• Role of reverse-phase protein microarray in drug discovery 150
• Role of proteomics in clinical drug safety 150
• Toxicoproteomics 151
• Application of pharmacoproteomics in personalized medicine 152

6. Role of Metabolomics in Personalized Medicine 153

• Metabolomics and metabonomics 153
• Metabolomics bridges the gap between genotype and phenotype 153
• Metabolomics, biomarkers and personalized medicine 154
• Metabolomic technologies 154
• Urinary profiling by capillary electrophoresis 155
• Lipid profiling 155
• Role of metabolomics in biomarker identification and pattern recognition 156
• Validation of biomarkers in large-scale human metabolomics studies 156
• Pharmacometabonomics 157
• Metabonomic technologies for toxicology studies 157
• Metabonomics/metabolomics and personalized nutrition 158

7. Personalized Biological Therapies 159

• Introduction 159
• Recombinant human proteins 159
• Therapeutic monoclonal antibodies 159
• Cell therapy 160
• Autologous tissue and cell transplants 160
• Stem cells 160
• Role of stem cells derived from unfertilized embryos 160
• Cloning and personalized cell therapy 161
• Use of stem cells for drug testing 161
• Gene therapy 161
• Personalized vaccines 162
• Personalized vaccines for viral diseases 162
• Personalized cancer vaccines 162
• Patient-specific cancer vaccines 162
• Antigen-specific vaccines 163
• Autologous cell vaccines 163
• Personalized melanoma vaccines 164
• Antisense therapy 165
• RNA interference 165
• MicroRNAs 166

8. Personalized Medicine in Major Therapeutic Areas 167

• Introduction 167
• Management of infections 168
• Management of HIV 168
• Genetics of human susceptibility to HIV infection 168
• Pharmacogenomics of antiretroviral agents 168
• Role of diagnostic testing in HIV 169
• CD4 counts as a guide to drug therapy for AIDS 169
• Drug-resistance in HIV 169
• Measurement of Replication Capacity 171
• Prevention of adverse reactions to antiviral drugs 171
• Role of genetic variations in susceptibility to HIV-1 171
• Pharmacogenetics and HIV drug safety 172
• Treatment of hepatitis B 172
• Treatment of hepatitis C 172
• Personalized management of tuberculosis 173
• Psychiatric disorders 174
• Psychopharmacogenetics 174
• COMT genotype and response to amphetamine 175
• Genotype and response to methylphenidate in children with ADHD 175
• Personalized antipsychotic therapy 175
• Personalized antidepressant therapy 178
• Pretreatment EEG to predict adverse effects to antidepressants 178
• Individualization of SSRI treatment 179
• Vilazodone with a test for personalized treatment of depression 180
• Neurological disorders 180
• Personalized management of Alzheimer' s disease 180
• Personalized management of Parkinson' s disease 182
• Discovery of subgroup-selective drug targets in PD 182
• Personalized management of Epilepsy 183
• Choice of the right AED 183
• Pharmacogenetics of epilepsy 183
• Pharmacogenomics of epilepsy 183
• Drug resistance in epilepsy 184
• Future prospects for management of epilepsy 185
• Personalized management of migraine 186
• Personalized treatment of multiple sclerosis 186
• MBP8298 187
• Pharmacogenomics of IFN-β therapy in multiple sclerosis 187
• Cardiovascular disorders 188
• Role of diagnostics in personalized management of cardiovascular disease 189
• Testing in coronary heart disease 189
• SNP genotyping in cardiovascular disorders 189
• Cardiovascular disorders with a genetic component 190
• Gene variant as a risk factor for sudden cardiac death 191
• SNP Chip for study of cardiovascular diseases 192
• Pharmacogenomics of cardiovascular disorders 192
• Modifying the genetic risk for myocardial infarction 192
• Management of heart failure 193
• β blockers 193
• Bucindolol 193
• BiDil 194
• Management of hypertension 194
• Pharmacogenomics of diuretic drugs 195
• Pharmacogenomics of ACE inhibitors 195
• Management of hypertension by personalized approach 195
• Pharmacogenetics of lipid-lowering therapies 196
• Polymorphisms in genes involved in cholesterol metabolism 197
• Role of eNOS gene polymorphisms 197
• The STRENGTH study 198
• Personalized management of women with hyperlipidemia 199
• Thrombotic disorders 199
• Factor V Leiden mutation 199
• Anticoagulant therapy 200
• Nanotechnology-based personalized therapy of cardiovascular diseases 200
• Project euHeart for personalized management of cardiovascular diseases 201
• Concluding remarks 201
• Personalized management of skin disorders 202
• Personalized therapy of rheumatoid arthritis 202
• DIATSTAT™ anti-cyclic citrullinated peptides in rheumatoid arthritis 203
• Personalization of COX-2 inhibitor therapy 203
• Personalization of infliximab therapy 204
• Personalized therapy of asthma 204
• Genetic polymorphism and response to β -adrenergic agonists 204
• Genotyping in asthma 205
• Personalized approaches in immunology 205
• Role of Mannose-binding lectin in personalized medicine 206
• Pharmacogenetics and pharmacogenomics of immunosuppressive agents 206
• Personalized immunosuppressant therapy in organ transplants 206
• Personalized management of pain 207
• Pharmacogenetics/pharmacogenomics of pain 208
• Mechanism-specific management of pain 209
• Preoperative testing to tailor postoperative analgesic requirements 209
• Personalized analgesics 210
• Management of genetic disorders 210
• Personalized treatment of cystic fibrosis 210
• Personalized management of gastrointestinal disorders 211
• Personalized therapy of inflammatory bowel disease 211
• Personalized management of lactose intolerance 211
• Personalized approach to addiction 212
• Genetic polymorphism and management of alcoholism 212
• Personalized therapy for smoking cessation 212
• Antidepressant therapy for smoking cessation 212
• Effectiveness of nicotine patches in relation to genotype 213
• Personalized approach to drug addiction 213
• Personalized approaches to miscellaneous problems 213
• Hormone replacement therapy in women 213
• Personalized treatment of malaria 214
• Personalized management of renal disease 214
• Personalization of organ transplantation 215
• Personalization of kidney transplantation 215
• Personalization of cardiac transplantation 215
• Prediction of rejection to tailor anti-rejection medications 216
• Role of immunological biomarkers in monitoring grafted patients 216
• Improved matching of blood transfusion 217
• Personalized care of trauma patients 217
• Personalized anticoagulation 218
• Personalized Hyperbaric oxygen therapy 218
• Personalized preventive medicine 219
• Personalized nutrition 219
• Nutrigenomics 220
• Nutrigenomics and functional foods 220
• Nutrigenomics and personalized medicine 221
• Nutrition and proteomics 221
• Personalized diet prescription 221

9. Personalized Therapy of Cancer 223

• Introduction 223
• Challenges of cancer classification 223
• Relationships of technologies for personalized management of cancer 223
• Impact of molecular diagnostics on the management of cancer 224
• Analysis of RNA splicing events in cancer 225
• Analysis of chromosomal alterations in cancer cells 225
• Cancer classification using microarrays 225
• Detection of loss of heterozygosity 226
• Diagnosis of cancer of an unknown primary 226
• Diagnostics for detection of minimal residual disease 227
• Fluorescent in situ hybridization 227
• Gene expression profiling 227
• Gene expression profiles predict chromosomal instability in tumors 229
• Isolation and characterization of circulating tumor cells 229
• Modulation of CYP450 activity for cancer therapy 230
• Personalized therapies based on oncogenic pathways signatures 230
• Role of molecular imaging in personalized therapy of cancer 231
• Functional diffusion MRI 231
• Role of FDG-PET/CT in personalizing cancer treatment 231
• Tumor imaging and elimination by targeted gallium corrole 232
• Future prospects of molecular imaging in management of cancer 232
• Unraveling the genetic code of cancer 233
• Cancer prognosis 233
• Detection of mutations for risk assessment and prevention 234
• Impact of biomarkers on management of cancer 234
• VeraTag"! assay system for cancer biomarkers 234
• Predictive biomarkers for cancer 234
• HER-2/neu oncogene as a biomarker for cancer 235
• L-asparaginase treatment of cancer guided by a biomarker 235
• Determination of response to therapy 235
• ChemoFx cell culture assay for predicting anticancer drug response 236
• Ex vivo testing of tumor biopsy for chemotherapy sensitivity 236
• Genomic approaches to predict response to anticancer agents 236
• Gene expression patterns to predict response of cancer to therapy 236
• Genomic analysis of tumor biopsies 237
• Mutation detection at molecular level 237
• Role of genetic variations in susceptibility to anticancer drugs 238
• Non-genetic factors for variations in response of cancer cells to drugs 238
• Proteomic analysis of tumor biopsies to predict response to treatment 238
• Real-time apoptosis monitoring 239
• Serum nucleosomes as indicators of sensitivity to chemotherapy 239
• Targeted microbubbles to tumors for monitoring anticancer therapy 240
• PET imaging for determining response to chemotherapy 240
• Tissue systems biology approach to personalized management of cancer 240
• Targeted cancer therapies 241
• Targeting glycoproteins on cell surface 241
• Targeting pathways in cancer 241
• Functional antibody-based therapies 241
• Personalized radiation therapy 243
• Molecular diagnostics combined with cancer therapeutics 244
• Aptamers for combined diagnosis and therapeutics of cancer 244
• Role of nanobiotechnology in personalized management of cancer 245
• Design of future cancer therapies 245
• Screening for personalized anticancer drugs 246
• Role of epigenetics in development of personalized cancer therapies 246
• Personalized therapy of cancer based on cancer stem cells 246
• Role of oncoproteomics in personalized therapy of cancer 247
• Cancer tissue proteomics 247
• Pharmacogenomic-based chemotherapy 247
• Whole genome technology to predict drug resistance 247
• Anticancer drug selection based on molecular characteristics of tumor 248
• Testing microsatellite-instability for response to chemotherapy 248
• Pharmacogenetics of cancer chemotherapy 249
• CYP 1A2 249
• Thiopurine methyltransferase 250
• Dihydropyrimidine dehydrogenase 250
• UGT1A1 test as guide to irinotecan therapy 251
• Role of computational models in personalized anticancer therapy 251
• A computational model of kinetically tailored treatment 251
• Mathematical modeling of tumor mivroenvironments 252
• Molecular profiling of cancer 252
• Drug resistance in cancer 253
• Detection of drug resistance in cancer by metabolic profiling 253
• Determination of chemotherapy response by topoisomerase levels 254
• A systems biology approach to drug resistance in colorectal cancer 254
• Management of drug resistance in leukemia 254
• Overexpression of multidrug resistance gene 255
• P53 mutations 255
• A chemogenomic approach to drug resistance 256
• Examples of personalized management of cancer 256
• Personalized management of breast cancer 256
• Genetic testing in breast cancer as a guide to treatment 256
• Pharmacogenetics of breast cancer 257
• Molecular diagnostics in breast cancer 258
• Racial factors in the management of breast cancer 259
• Proteomics-based personalized management of breast cancer 259
• Tests for prognosis of breast cancer 260
• Developing personalized drugs for breast cancer 262
• Developing personalized drugs for triple-negative breast cancer 262
• Predicting response to chemotherapy in breast cancer 262
• Prediction of resistance to therapy in breast cancer 265
• Prediction of adverse reaction to radiotherapy in breast cancer 265
• Prediction of recurrence in breast cancer for personalizing therapy 265
• TAILORx (Trial Assigning Individualized Options for Treatment) 267
• Gene expression plus conventional predictors of breast cancer 267
• Future development of gene expression microarrays for breast cancer 268
• Personalized management of ovarian cancer 268
• Personalized management of hematological malignancies 270
• Personalized management of acute leukemias 270
• Personalized management of chronic lymphocytic leukemia 271
• Personalized management of multiple myeloma 272
• Personalized management B cell lymphomas 273
• Personalized vaccine for follicular lymphoma 273
• Personalized management of myelodysplasia 274
• Personalized management of malignant melanoma 274
• Personalized management of gastrointestinal cancer 274
• Personalized management of esophageal cancer 274
• Personalized management of colorectal cancer 275
• Personalized management of lung cancer 277
• Determination of outcome of EGFR tyrosine kinase inhibitor treatment 277
• Testing for response to chemotherapy in lung cancer 279
• Testing for prognosis of NSCLC 279
• Testing for recurrence of lung cancer 280
• Role of a new classification system in the management of lung cancer 280
• Personlized management of prostate cancer 280
• Benefit of lifestyle changes shown by gene expression studies 281
• Personalized management of brain cancer 281
• Genetics and genomics of brain cancer 282
• Molecular diagnostics for personalized management of brain cancer 283
• Personalized chemotherapy of brain tumors 284
• Biosimulation approach to personalizing treatment of brain cancer 285
• Personalized therapy of oligodendroglial tumors (OTs) 286
• Personalized therapy of neuroblastomas 286
• Personalized management of germ cell brain tumors 287
• Future of cancer therapy 287
• Challenges for developing personalized cancer therapies 288
• The Cancer Genome Atlas 288
• Role of the International Cancer Genome Consortium 288
• Using computer and imaging technologies to personalize cancer treatment 289
• Integrated genome-wide analysis of cancer for personalized therapy 290
• Companies involved in developing personalized cancer therapy 290

10. Development of Personalized Medicine 293

• Introduction 293
• Non-genomic factors in the development of personalized medicine 293
• Personalized medicine based on circadian rhythms 293
• Cytomics as a basis for personalized medicine 294
• Intestinal microflora 294
• Gut microbiome compared to human genome 294
• Metabolic interactions of the host and the intestinal microflora 295
• Role of drug delivery in personalized medicine 295
• Personalized approach to clinical trials 295
• Use of Bayesian approach in clinical trials 295
• Individualzing risks and benefits in clinical trials 296
• Clinical trials of therapeutics and companion diagnostics 296
• Players in the development of personalized medicine 297
• Personalized Medicine Coalition 297
• Role of pharmaceutical industry 298
• Production and distribution of personalized medicines 298
• Role of biotechnology companies 299
• Role of life sciences industries 300
• Role of molecular imaging in personalized medicine 300
• Molecular imaging for personalized drug development in oncology 300
• Molecular imaging and CNS drug development 302
• Companies involved in molecular imaging 303
• Role of the clinical laboratories 303
• Role of the US government 304
• Role of the US Government agencies in personalized medicine 305
• NIH' s Roadmap Initiative for Medical Research 305
• NIH and personalized medicine 305
• National Institute of General Medical Sciences 306
• National Institute of Standards and Technology 307
• Role of academic institutons in the US 307
• Clinical Proteomics Program 307
• Coriell Personalized Medicine Collaborative"! 307
• Delaware Valley Personalized Medicine Project 308
• Evaluation of genetic tests and genomic applications 308
• Genomic-Based Prospective Medicine Project 309
• Personalized oncology at Massachusetts General Hospital 310
• Pharmacogenetics Research Network and Knowledge Base 310
• Quebec Center of Excellence in Personalized Medicine 310
• Southeast Nebraska Cancer Center' s Personalized Medicine Network 311
• Wisconsin Genomics Initiative 311
• Role of healthcare organizations and hospitals 311
• Signature Genetics 311
• The Mayo Clinic genetic database 312
• Research center for personalized medicine at Mt. Sinai Medical Center 312
• Role of the medical profession 312
• Education of the physicians 312
• Off-label prescribing and personalized medicine 313
• Medical education 313
• Public attitude towards personalized medicine 314
• Role of genetic banking systems and databases 314
• Role of biobanks in development of personalized medicine 314
• UK Biobank 315
• Biobanking and development of personalized medicine in EU 315
• CARTaGENE for biobanks in Canada 316
• Personalized medicine based on PhysioGenomics"! technology 316
• Role of bioinformatics in development of personalized medicine 317
• Exploration of disease-gene relationship 318
• Biosimulation techniques for developing personalized medicine 318
• Health information management 318
• Electronic health records 319
• Linking patient medical records and genetic information 319
• Management of personal genomic data 320
• Personalized prognosis of disease 320
• Integration of technologies for development of personalized medicine 321
• Global scope of personalized medicine 321
• Personalized medicine in the developed countries 321
• Personalized medicine in the US 322
• Personalized medicine in the EU 322
• UK National Health Service and medical genetics 323
• Personalized medicine in the developing countries 323
• Advantages and limitations of personalized medicine 324
• Future of personalized medicine 326
• Ongoing genomic projects 326
• Understanding the genetic basis of diseases 326
• Personal Genome Project 326
• Genome-wide association studies 327
• The 1000 Genomes Project 328
• Genomics of aging in a genetically homogeneous population 328
• Translational science and personalized medicine 329
• Translation of genomic research into genetic testing for healthcare 329
• Long-term behavioral effects of personal genetic testing 330
• Personalized predictive medicine 330
• Opportunities and challenges 331
• Prospects and limitations of genetic testing 331
• Pharmacotyping 332
• Comparative-effectiveness research and personalized mediine 332
• Medicine in the year 2013 333
• Concluding remarks about the future of personalized medicine 333

11. Ethical and Regulatory Aspects of Personalized Medicine 335

• Introduction to ethical issues 335
• Ethical issues of pharmacogenetics 335
• Ethical aspects of genetic information 335
• Ethical issues of whole genome analysis 335
• Ethical aspects of direct-to-consumer genetic services 336
• Privacy issues in personalized medicine 338
• Genetic Information Nondiscrimination Act in the US 338
• Genotype-specific clinical trials 338
• Social issues in personalized medicine 339
• Race and personalized medicine 339
• Regulatory aspects 341
• CLSI guideline for the use of RNA controls in gene expression assays 341
• MicroArray Quality Control Project 342
• Regulatory aspects of pharmacogenetics 343
• Regulation of direct-to-consumer genetic testing 343
• FDA and pharmacogenomics 344
• FDA guidance for pharmacogenomic data submissions 344
• Joint guidelines of the FDA and EU regulators for pharmacogenomics 345
• Pharmacogenomic information in drug labels 345
• FDA guidelines for pharmacogenomics-based dosing 345
• FDA and validation of biomarkers 346
• FDA and predictive medicine 347
• FDA regulation of multivariate index assays 347
• Evaluation of companion diagnostics/therapeutic for cancer 348

12. Commercial Aspects of Personalized Medicine 349

• Introduction 349
• Perceived financial concerns 349
• Personalized medicine and orphan drug syndrome 349
• Commercial aspects of pharmacogenomics 349
• Cost of DNA testing 349
• Cost of sequencing the human genome 350
• Cost of genotyping 352
• Cost of pharmacogenomics-based clinical trials 352
• Business development of pharmacogenomic companies 353
• Cost of personalized healthcare 353
• Cost of genetic testing 353
• Economics of CYP genotyping-based pharmacotherapy 354
• Cost of personalized medicines 354
• The rising healthcare costs in the US 354
• Lowering the cost of healthcare 355
• Cost effectiveness of HIV genotyping 355
• Lowering the high costs of cancer chemotherapy 355
• Reducing the cost incurred by adverse drug reactions 356
• Overall impact of personalized medicine on healthcare 356
• Drivers for the development of personalized medicine 356
• Evolution of medicine as a driver for personalized therapy markets 357
• Collaboration between the industry and the academia 358
• Personalized medicine and drug markets 358
• Impact on drug markets 358
• Growth of markets relevant to personalized medicine 359
• SNP market 359
• Pharmacogenomics 360
• Pharmacogenetics 360
• Pharmacoproteomics 360
• Biochips 360
• Point-of-Care 360
• Markets for personalized medicines according to therapeutic areas 360
• Markets for personalized medicines according to geographical regions 361
• Market opportunities for personalization of medicine 361
• Impact of personalized medicine on other industries 362
• Strategies for developing and marketing personalized medicine 363
• Education of the public 363
• Role of the Internet in development of personalized medicine 363
• Marketing companion diagnostics for personalized medicine 364

13. References 365

Tables

• Table 1 1: Selected terms relevant to the concept of personalized medicine 19
• Table 1 2: Landmarks in the historical development of personalized medicine 20
• Table 2 1: Molecular diagnostic technologies used for personalized medicine 39
• Table 2 2: Applications of biochip technology relevant to personalized medicine 49
• Table 2 3: Companies developing haplotying technology 64
• Table 2 4: Technologies for SNP analysis 65
• Table 2 5: A sampling of companies involved in technologies for SNP genotyping 74
• Table 2 6: Comparison of proteomic and genomic approaches in personalized medicine 81
• Table 2 7: Selected methods for gene expression profiling 82
• Table 2 8: A selection of companies with gene expression technologies 88
• Table 2 9: Companies combining molecular diagnostics and therapeutics 91
• Table 2 10: Applications of point-of-care diagnosis 92
• Table 2 11: Companies developing point-of-care diagnostic tests 93
• Table 2 12: Companies offering genetic screening tests directly to consumers 97
• Table 3 1: Pharmacogenetic vs. pharmacogenomic studies 104
• Table 3 2: Enzymes relevant to drug metabolism 106
• Table 3 3: Examples of mutation of the enzyme CYP450 107
• Table 3 4: Frequency distribution of drugs metabolized by major isoforms of CYP450. 107
• Table 3 5: Commonly prescribed medications, which are metabolized by CYP2D6 107
• Table 3 6: Polymorphisms in drug target genes that can influence drug response 112
• Table 3 7: Effect of genetic polymorphisms on disease response to drugs 113
• Table 3 8: Examples of genetically determined adverse reactions to drugs 116
• Table 3 9: Examples of genotyping and phenotyping in some diseases 122
• Table 3 10: Companies with novel molecular toxicology technology 124
• Table 4 14 2: Role of pharmacogenomics in variable therapy targets 133
• Table 4 3: Role of pharmacogenomics in clinical trials 137
• Table 4 4: Examples of pharmacogenomics-based clinical studies 137
• Table 4 5: Tumor suppressor genes, their chromosomal location, function and associated tumors. 140
• Table 4 6: Gene polymorphisms relevant to cardiovascular disease management 141
• Table 4 7: Companies involved in cardiovascular genomics 143
• Table 4 8: A sampling of companies involved in neuropharmacogenomics 145
• Table 8 1: Important therapeutic areas for personalized medicine 167
• Table 8 2: Enzymes that metabolize antipsychotics 177
• Table 8 3: Enzymes that metabolize antidepressants 178
• Table 8 4: Biomarkers of response to interferon-β in multiple sclerosis 188
• Table 8 5: Genes that cause cardiovascular diseases 190
• Table 9 1: Factors that drive the development of personalized therapy in cancer 223
• Table 9 2: Impact of molecular diagnostics on the management of cancer 224
• Table 9 3: Selected companies involved in developing personalized cancer therapies 290
• Table 10 1: Players in the development of personalized medicine 297
• Table 10 2: Members of the Personalized Medicine Coalition 297
• Table 10 3: Biobanks relevant to personalized medicine 314
• Table 10 4: Role of bioinformatics in the development of personalized medicine 317
• Table 10 5: Advantages of personalized medicine for the biopharmaceutical industry 324
• Table 10 6: Advantages of personalized medicine for the patients 324
• Table 10 7: Advantage of personalized medicine for the physicians 324
• Table 10 8: Limitations of personalized medicine 325
• Table 10 9: Methods of translational science that are relvant to personalized medicine 329
• Table 10 10: Companies involved in predictive healthcare 330
• Table 12 1: Drivers for the development of personalized medicine 356
• Table 12 2: Growth of markets relevant to personalized medicine 2008-2018 359
• Table 12 3: Markets for personalized medicine according to therapeutic area 2008-2018 361
• Table 12 4: Markets for personalized medicine in major regions 2008-2018 361
• Table 12 5: Lack of efficacy in current therapy 362
• Table 12 6: Impact of personalized medicine on other industries 362
• Table 12 7: Strategies to develop personalized medicine 363
• Table 12 8: Role of the Internet in development of personalized medicine 364

Figures

• Figure 1 1: Relation of personalized medicine to other technologies 31
• Figure 1 2: Relation of systems pharmacology to personalized medicine 36
• Figure 2 1: Role of biochips/microarrays in personalized medicine 50
• Figure 2 2: Affymetrix GeneChip technology 51
• Figure 2 3: Role of CYP450 genotyping in development of personalized medicine 54
• Figure 2 4: Role of SNPs in personalized medicine 61
• Figure 2 5: A scheme of integrated healthcare and personalized medicine 98
• Figure 3 1: Pharmacogenetics as a link between genotype and phenotype 103
• Figure 3 2: Role of pharmacogenetic technologies in personalized medicine 104
• Figure 4 1: Impact of new technologies at various stages of the drug discovery process 135
• Figure 4 2: Steps in the application of pharmacogenomics in clinical trials 137
• Figure 7 1: Role RNAi in development of personalized medicine 166
• Figure 8 1: A scheme of personalized approach to management of hypertension 196
• Figure 8 2: A scheme of personalized management of pain 208
• Figure 9 1: Relationships of technologies for personalized management of cancer 224
• Figure 10 1: Integration of technologies for the development of personalized medicine 321
• Figure 12 1: Evolution of personalized medicine as a market driver 357