Personalized Medicine - scientific & commercial aspects

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 38

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 53
• Lab-on-a-chip 54
• Micronics' microfluidic technology 54
• LabCD 54
• Microfluidic automated DNA analysis using PCR 54
• Integrated microfluidic bioassay chip 55
• Electronic detection of nucleic acids on microarrays 55
• Strand displacement amplification on a biochip 55
• Rolling circle amplification on DNA microarrays 56
• Universal DNA microarray combining PCR and ligase detection reaction 56
• Protein biochips 56
• ProteinChip 57
• LabChip for protein analysis 58
• TRINECTIN proteome chip 58
• Protein expression microarrays 58
• Microfluidic devices for proteomics-based diagnostics 59
• New developments in protein chips 59
• Protein chips for personalized medicine 60
• SNP genotyping 60
• Haplotyping 61
• Haplotype Specific Extraction 62
• Computation of haplotypes 62
• HapMap project 62
• Predictingdrug response with HapMap 63
• Companies developing haplotyping technology 63
• Technologies for SNP analysis 64
• Biochip and microarray-based detection of SNPs 65
• SNP genotyping by MassARRAY 65
• Biochip combining BeadArray and ZipCode technologies 65
• SNP-IT primer-extension technology 66
• OmniScan SNP genotyping 66
• Affymetrix Variation Detection Arrays 66
• Use of NanoChip for detection of SNPs 66
• DNA sequencing 67
• Electrochemical DNA probes 67
• Single base extension-tag array 68
• Laboratory Multiple Analyte Profile 68
• PCR-CTPP (confronting two-pair primers) 68
• SNP genotyping on a genome-wide amplified DOP-PCR template 69
• TaqMan real-time PCR 69
• Non-Enzymatic Amplification Technology 69
• SNP genotyping with gold nanoparticle probes 70
• Locked nucleic acid 70
• Molecular inversion probe based assays 70
• Pyrosequencing 70
• Reversed enzyme activity DNA interrogation test 71
• Smart amplification process version 2 72
• Zinc finger proteins 72
• UCAN method (Takara Biomedical) 72
• Mitochondrial SNPs 72
• Limitations of SNP in genetic testing 73
• Concluding remarks on SNP genotyping 73
• Companies involved in developing technologies/products for SNP analysis 73
• Impact of SNPs on personalized medicine 75
• Optical Mapping 75
• Role of nanobiotechnology in molecular diagnostics 76
• Cantilevers for personalized medical diagnostics 76
• Nanopore-based technology for single molecule identification 77
• Role of biomarkers in personalized medicine 77
• Biomarkers for diagnostics 78
• Biomarkers for drug development 78
• Application of proteomics in molecular diagnosis 78
• Proteomic strategies for biomarker identification 79
• Proteomic technologies for detection of biomarkers in body fluids 79
• Protein patterns 79
• Layered Gene Scanning 80
• Comparison of proteomic and genomic approaches in personalized medicine 81
• Gene expression profiling 81
• DNA microarrays 82
• Analysis of single-cell gene expression 82
• Gene expression profiling based on alternative RNA splicing 83
• Whole genome expression array 84
• Tangerine"! expression profiling 84
• Gene expression analysis on biopsy samples 85
• Profiling gene expression patterns of white blood cells 85
• Serial analysis of gene expression (SAGE) 85
• Multiplexed Molecular Profiling 86
• Gene expression analysis using competitive PCR and MALDI TOF MS 86
• Monitoring in vivo gene expression by magnetic resonance imaging 87
• Companies involved in gene expression analysis 87
• Monitoring in vivo gene expression by molecular imaging 88
• Molecular imaging and personalized medicine 88
• Glycomics-based diagnostics 89
• Combination of diagnostics and therapeutics 89
• Companies combining diagnostics and therapeutics 90
• Point-of-care diagnosis 91
• Companies developing point-of-care diagnostic technologies 92
• Point-of-care diagnosis of infections 94
• Advantages versus disadvantages of point-of-care diagnosis 95
• Future prospects of point-of-care diagnosis 95
• Genetic testing for disease predisposition 96
• Preventive genetics by early diagnosis of mitochondrial diseases 96
• Personal genetic service 96
• Role of diagnostics in integrated healthcare 97
• Concept of integrated healthcare 97
• 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 114
• Gender differences in pharmacogenetics 114
• Role of pharmacogenetics in drug safety 115
• Adverse drug reactions 115
• Adverse drug reactions in children 115
• Adverse drug reactions related to toxicity of chemotherapy 116
• Genetically determined adverse drug reactions 116
• Malignant hyperthermia 117
• Pharmacogenetics of clozapine-induced agranulocytosis 118
• Role of pharmacogenetics in warfarin therapy 118
• Role of pharmacogenetics in carbamazepine therapy 119
• 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 121
• Genotyping 122
• Genotyping vs phenotyping 122
• Phenomics 123
• Limitations of genotype-phenotype association studies 123
• Molecular toxicology in relation to personalized medicines 124
• Toxicogenomics 124
• Companies involved in molecular toxicology 124
• Gene expression studies 125
• Genomics and the prediction of xenobiotic toxicity 126
• Pharmacogenetics in clinical trials 126
• Postmarketing pharmacogenetics 127
• 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 128
• 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 130
• Pharmacoepigenomics vs pharmacogenetics in drug safety 130
• Academic research in pharmacogenetics 131
• 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
• Multipeptide cancer vaccines 164
• Personalized melanoma vaccines 165
• Antisense therapy 165
• RNA interference 166
• MicroRNAs 167

8. Personalized Medicine in Major Therapeutic Areas 169

• Introduction 169
• Management of infections 170
• Management of HIV 170
• Genetics of human susceptibility to HIV infection 170
• Pharmacogenomics of antiretroviral agents 170
• Role of diagnostic testing in HIV 171
• CD4 counts as a guide to drug therapy for AIDS 171
• Drug-resistance in HIV 171
• Measurement of Replication Capacity 173
• Prevention of adverse reactions to antiviral drugs 173
• Role of genetic variations in susceptibility to HIV-1 173
• Pharmacogenetics and HIV drug safety 174
• Treatment of hepatitis B 174
• Treatment of hepatitis C 174
• Personalized management of tuberculosis 175
• Psychiatric disorders 176
• Psychopharmacogenetics 176
• COMT genotype and response to amphetamine 177
• Genotype and response to methylphenidate in children with ADHD 177
• Personalized antipsychotic therapy 177
• Personalized antidepressant therapy 180
• Pretreatment EEG to predict adverse effects to antidepressants 180
• Individualization of SSRI treatment 181
• Vilazodone with a test for personalized treatment of depression 182
• Neurological disorders 182
• Personalized management of Alzheimer' s disease 182
• Personalized management of Parkinson' s disease 184
• Discovery of subgroup-selective drug targets in PD 184
• Personalized management of Epilepsy 185
• Choice of the right AED 185
• Pharmacogenetics of epilepsy 185
• Pharmacogenomics of epilepsy 185
• Drug resistance in epilepsy 186
• Future prospects for management of epilepsy 187
• Personalized management of migraine 188
• Individualization of use of triptans for migraine 188
• Personalized treatment of multiple sclerosis 188
• Immunopathological patterns of demyelination for assessing therapy 189
• Personalizing mitoxantrone therapy of multiple sclerosis 189
• Fusokine method of personalized cell therapy of multiple sclerosis 190
• MBP8298 190
• Pharmacogenomics of IFN-β therapy in multiple sclerosis 191
• Cardiovascular disorders 192
• Role of diagnostics in personalized management of cardiovascular disease 192
• Testing in coronary heart disease 192
• SNP genotyping in cardiovascular disorders 193
• Cardiovascular disorders with a genetic component 193
• Gene variant as a risk factor for sudden cardiac death 195
• KIF6 gene test as a guide to management of congestive heart failure 195
• SNP Chip for study of cardiovascular diseases 196
• Pharmacogenomics of cardiovascular disorders 196
• Modifying the genetic risk for myocardial infarction 196
• Management of heart failure 197
• β blockers 197
• Bucindolol 197
• BiDil 197
• Management of hypertension 198
• Pharmacogenomics of diuretic drugs 198
• Pharmacogenomics of ACE inhibitors 199
• Management of hypertension by personalized approach 199
• Pharmacogenetics of lipid-lowering therapies 200
• Polymorphisms in genes involved in cholesterol metabolism 201
• Role of eNOS gene polymorphisms 201
• The STRENGTH study 202
• Personalized management of women with hyperlipidemia 203
• Thrombotic disorders 203
• Factor V Leiden mutation 203
• Anticoagulant therapy 204
• Antiplatelet therapy 204
• Nanotechnology-based personalized therapy of cardiovascular diseases 204
• Project euHeart for personalized management of cardiovascular diseases 205
• Concluding remarks 205
• Personalized management of pulmonary disorders 206
• Personalized therapy of asthma 206
• Biomarkers for predicting response to corticosteroid therapy 206
• Genetic polymorphism and response to β -adrenergic agonists 207
• Genotyping in asthma 207
• IgE as guide to dosing of omalizumab for asthma 208
• Personalized management of chronic obstructive pulmonary disease 208
• Personalized management of skin disorders 209
• Genetic testing for personalized skin care 209
• Management of hair loss based on genetic testing 209
• Personalized therapy of rheumatoid arthritis 209
• DIATSTAT"! anti-cyclic citrullinated peptides in rheumatoid arthritis 210
• Personalization of COX-2 inhibitor therapy 211
• Personalization of infliximab therapy 211
• Personalized approaches in immunology 211
• Role of Mannose-binding lectin in personalized medicine 212
• Pharmacogenetics and pharmacogenomics of immunosuppressive agents 212
• Personalized immunosuppressant therapy in organ transplants 212
• Personalized management of pain 213
• Pharmacogenetics/pharmacogenomics of pain 214
• Mechanism-specific management of pain 215
• Preoperative testing to tailor postoperative analgesic requirements 215
• Personalized analgesics 215
• Management of genetic disorders 216
• Personalized treatment of cystic fibrosis 216
• Personalized management of gastrointestinal disorders 217
• Personalized therapy of inflammatory bowel disease 217
• Personalized management of lactose intolerance 217
• Personalized approach to addiction 218
• Genetic polymorphism and management of alcoholism 218
• Personalized therapy for smoking cessation 218
• Antidepressant therapy for smoking cessation 218
• Effectiveness of nicotine patches in relation to genotype 219
• Personalized approach to drug addiction 219
• Personalized approaches to miscellaneous problems 219
• Hormone replacement therapy in women 219
• Personalized treatment of malaria 219
• Personalized management of renal disease 220
• Gene associated with end-stage renal disease 221
• Personalization of organ transplantation 221
• Personalization of kidney transplantation 221
• Personalization of cardiac transplantation 222
• Prediction of rejection to tailor anti-rejection medications 222
• Role of immunological biomarkers in monitoring grafted patients 223
• Improved matching of blood transfusion 223
• Personalized care of trauma patients 223
• Personalized anticoagulation 224
• Personalized Hyperbaric oxygen therapy 224
• Personalized preventive medicine 225
• Personalized nutrition 226
• Nutrigenomics 226
• Nutrigenomics and functional foods 227
• Nutrigenomics and personalized medicine 227
• Nutrition and proteomics 227
• Personalized diet prescription 228

9. Personalized Therapy of Cancer 229

• Introduction 229
• Challenges of cancer classification 229
• Relationships of technologies for personalized management of cancer 229
• Impact of molecular diagnostics on the management of cancer 230
• Analysis of RNA splicing events in cancer 231
• Analysis of chromosomal alterations in cancer cells 231
• Cancer classification using microarrays 231
• Detection of loss of heterozygosity 232
• Diagnosis of cancer of an unknown primary 232
• Diagnostics for detection of minimal residual disease 233
• Fluorescent in situ hybridization 233
• Gene expression profiling 233
• Gene expression profiles predict chromosomal instability in tumors 235
• Isolation and characterization of circulating tumor cells 235
• Modulation of CYP450 activity for cancer therapy 236
• Personalized therapies based on oncogenic pathways signatures 236
• Quantum dot-based test for DNA methylation 237
• Role of molecular imaging in personalized therapy of cancer 237
• Functional diffusion MRI 237
• Role of FDG-PET/CT in personalizing cancer treatment 238
• Tumor imaging and elimination by targeted gallium corrole 238
• Future prospects of molecular imaging in management of cancer 239
• Unraveling the genetic code of cancer 239
• Cancer prognosis 239
• Detection of mutations for risk assessment and prevention 240
• Impact of biomarkers on management of cancer 240
• VeraTag"! assay system for cancer biomarkers 240
• Predictive biomarkers for cancer 241
• HER-2/neu oncogene as a biomarker for cancer 241
• Oncogene GOLPH3 as a cancer biomarker 241
• L-asparaginase treatment of cancer guided by a biomarker 242
• Determination of response to therapy 242
• ChemoFx cell culture assay for predicting anticancer drug response 242
• Ex vivo testing of tumor biopsy for chemotherapy sensitivity 242
• Genomic approaches to predict response to anticancer agents 243
• Gene expression patterns to predict response of cancer to therapy 243
• Genomic analysis of tumor biopsies 243
• Mutation detection at molecular level 244
• Role of genetic variations in susceptibility to anticancer drugs 244
• Non-genetic factors for variations in response of cancer cells to drugs 245
• Proteomic analysis of tumor biopsies to predict response to treatment 245
• Real-time apoptosis monitoring 245
• Serum nucleosomes as indicators of sensitivity to chemotherapy 246
• Targeted microbubbles to tumors for monitoring anticancer therapy 246
• PET imaging for determining response to chemotherapy 247
• Tissue systems biology approach to personalized management of cancer 247
• Targeted cancer therapies 247
• Targeting glycoproteins on cell surface 248
• Targeting pathways in cancer 248
• Functional antibody-based therapies 248
• Personalized radiation therapy 249
• Molecular diagnostics combined with cancer therapeutics 250
• Aptamers for combined diagnosis and therapeutics of cancer 251
• Role of nanobiotechnology in personalized management of cancer 251
• Design of future cancer therapies 252
• Screening for personalized anticancer drugs 252
• Role of epigenetics in development of personalized cancer therapies 253
• Personalized therapy of cancer based on cancer stem cells 253
• Role of oncoproteomics in personalized therapy of cancer 253
• Cancer tissue proteomics 253
• Pharmacogenomic-based chemotherapy 254
• Whole genome technology to predict drug resistance 254
• Anticancer drug selection based on molecular characteristics of tumor 254
• Testing microsatellite-instability for response to chemotherapy 255
• Pharmacogenetics of cancer chemotherapy 255
• CYP 1A2 256
• Thiopurine methyltransferase 256
• Dihydropyrimidine dehydrogenase 257
• UGT1A1 test as guide to irinotecan therapy 257
• Role of computational models in personalized anticancer therapy 258
• A computational model of kinetically tailored treatment 258
• Mathematical modeling of tumor mivroenvironments 258
• Molecular profiling of cancer 259
• Drug resistance in cancer 259
• Detection of drug resistance in cancer by metabolic profiling 260
• Determination of chemotherapy response by topoisomerase levels 260
• A systems biology approach to drug resistance in colorectal cancer 261
• Management of drug resistance in leukemia 261
• Overexpression of multidrug resistance gene 262
• P53 mutations 262
• A chemogenomic approach to drug resistance 262
• Systems biology approach to personalizing therapy for drug-resistant cancer 262
• Examples of personalized management of cancer 263
• Personalized management of breast cancer 263
• Developing personalized drugs for breast cancer 263
• Gene expression plus conventional predictors of breast cancer 264
• Genetic testing in breast cancer as a guide to treatment 265
• Molecular diagnostics in breast cancer 266
• Pharmacogenetics of breast cancer 267
• Proteomics-based personalized management of breast cancer 267
• Predicting response to chemotherapy in breast cancer 268
• Prediction of resistance to therapy in breast cancer 271
• Prediction of adverse reaction to radiotherapy in breast cancer 271
• Prediction of recurrence in breast cancer for personalizing therapy 271
• Prognosistic tests for breast cancer 272
• Racial factors in the management of breast cancer 274
• TAILORx (Trial Assigning Individualized Options for Treatment) 275
• Trends and future prospects of breast cancer research 275
• Understanding tumor diversity in mouse mammary cancer model 276
• Personalized management of ovarian cancer 276
• Personalized management of hematological malignancies 278
• Personalized management of acute leukemias 278
• Personalized management of chronic lymphocytic leukemia 279
• Personalized management of multiple myeloma 279
• Personalized management B cell lymphomas 281
• Personalized vaccine for follicular lymphoma 281
• Personalized management of myelodysplasia 281
• Personalized management of hepatocellular carcinoma 282
• Personalized management of malignant melanoma 282
• Personalized management of gastrointestinal cancer 282
• Personalized management of esophageal cancer 282
• Personalized management of gastric cancer 283
• Personalized management of colorectal cancer 283
• Personalized management of lung cancer 286
• Determination of outcome of EGFR tyrosine kinase inhibitor treatment 286
• Testing for response to chemotherapy in lung cancer 288
• Testing for prognosis of NSCLC 288
• Testing for recurrence of lung cancer 288
• Role of a new classification system in the management of lung cancer 289
• Personlized management of prostate cancer 289
• Benefit of lifestyle changes shown by gene expression studies 290
• Personalized management of brain cancer 290
• Genetics and genomics of brain cancer 290
• Prognosis of glioblastoma multiforme based on its genetic landscape 292
• Molecular diagnostics for personalized management of brain cancer 292
• Personalized chemotherapy of brain tumors 293
• Biosimulation approach to personalizing treatment of brain cancer 294
• Personalized therapy of oligodendroglial tumors (OTs) 295
• Personalized therapy of neuroblastomas 295
• Personalized therapy of medulloblastomas 296
• Personalized management of germ cell brain tumors 297
• Future of cancer therapy 297
• Challenges for developing personalized cancer therapies 297
• The Cancer Genome Atlas 297
• Role of the International Cancer Genome Consortium 298
• Using computer and imaging technologies to personalize cancer treatment 299
• Integrated genome-wide analysis of cancer for personalized therapy 299
• Companies involved in developing personalized cancer therapy 300

10. evelopment of Personalized Medicine 303

• Introduction 303
• Non-genomic factors in the development of personalized medicine 303
• Personalized medicine based on circadian rhythms 303
• Cytomics as a basis for personalized medicine 304
• Intestinal microflora 304
• Gut microbiome compared to human genome 304
• Metabolic interactions of the host and the intestinal microflora 305
• Role of drug delivery in personalized medicine 305
• Personalized approach to clinical trials 306
• Use of Bayesian approach in clinical trials 306
• Individualzing risks and benefits in clinical trials 306
• Clinical trials of therapeutics and companion diagnostics 307
• Players in the development of personalized medicine 307
• Personalized Medicine Coalition 307
• Role of pharmaceutical industry 308
• Production and distribution of personalized medicines 309
• Role of biotechnology companies 310
• Role of life sciences industries 310
• Role of molecular imaging in personalized medicine 310
• Molecular imaging for personalized drug development in oncology 311
• Molecular imaging and CNS drug development 312
• Companies involved in molecular imaging 313
• Role of the clinical laboratories 314
• Role of the US government 314
• Department of Health and Human Services and personalized medicine 315
• Comparative effectiveness research 316
• Role of the US Government agencies in personalized medicine 317
• NIH' s Roadmap Initiative for Medical Research 317
• NIH and personalized medicine 317
• National Institute of General Medical Sciences 318
• National Institute of Standards and Technology 318
• Role of academic institutons in the US 319
• Clinical Proteomics Program 319
• Coriell Personalized Medicine Collaborative"! 319
• Delaware Valley Personalized Medicine Project 320
• Evaluation of genetic tests and genomic applications 320
• Genomic-Based Prospective Medicine Project 321
• Personalized oncology at Massachusetts General Hospital 321
• Pharmacogenetics Research Network and Knowledge Base 322
• Quebec Center of Excellence in Personalized Medicine 322
• Southeast Nebraska Cancer Center' s Personalized Medicine Network 322
• Wisconsin Genomics Initiative 323
• Role of healthcare organizations and hospitals 323
• Signature Genetics 323
• The Mayo Clinic genetic database 323
• Research center for personalized medicine at Mt. Sinai Medical Center 324
• Role of the medical profession 324
• Education of the physicians 324
• Off-label prescribing and personalized medicine 325
• Medical education 325
• Public attitude towards personalized medicine 325
• Role of genetic banking systems and databases 326
• Role of biobanks in development of personalized medicine 326
• UK Biobank 327
• Biobanking and development of personalized medicine in EU 327
• CARTaGENE for biobanks in Canada 328
• Personalized medicine based on PhysioGenomics"! technology 328
• Role of bioinformatics in development of personalized medicine 328
• Exploration of disease-gene relationship 330
• Biosimulation techniques for developing personalized medicine 330
• Health information management 330
• Electronic health records 330
• Linking patient medical records and genetic information 331
• Management of personal genomic data 332
• Personalized prognosis of disease 332
• Integration of technologies for development of personalized medicine 332
• Global scope of personalized medicine 333
• Personalized medicine in the developed countries 333
• Personalized medicine in the US 334
• Personalized medicine in the EU 334
• UK National Health Service and medical genetics 335
• Personalized medicine in the developing countries 336
• Advantages and limitations of personalized medicine 336
• Future of personalized medicine 338
• Ongoing genomic projects 338
• Understanding the genetic basis of diseases 338
• Personal Genome Project 339
• Genome-wide association studies 339
• The 1000 Genomes Project 340
• Genomics of aging in a genetically homogeneous population 340
• Translational science and personalized medicine 341
• Translation of genomic research into genetic testing for healthcare 341
• Long-term behavioral effects of personal genetic testing 342
• Personalized predictive medicine 342
• Opportunities and challenges 343
• Prospects and limitations of genetic testing 343
• Pharmacotyping 344
• Comparative-effectiveness research and personalized mediine 345
• Medicine in the year 2013 345
• Concluding remarks about the future of personalized medicine 346

11. Ethical and Regulatory Aspects of Personalized Medicine 347

• Introduction to ethical issues 347
• Ethical issues of pharmacogenetics 347
• Ethical aspects of genetic information 347
• Ethical issues of whole genome analysis 347
• Ethical aspects of direct-to-consumer genetic services 348
• Privacy issues in personalized medicine 350
• Genetic Information Nondiscrimination Act in the US 350
• Genotype-specific clinical trials 350
• Social issues in personalized medicine 351
• Race and personalized medicine 351
• Regulatory aspects 353
• CLSI guideline for the use of RNA controls in gene expression assays 353
• MicroArray Quality Control Project 354
• Regulatory aspects of pharmacogenetics 355
• Regulation of direct-to-consumer genetic testing 355
• FDA and pharmacogenomics 356
• FDA guidance for pharmacogenomic data submissions 356
• Joint guidelines of the FDA and EU regulators for pharmacogenomics 357
• Pharmacogenomic/pharmacogenetic information in drug labels 357
• FDA guidelines for pharmacogenomics-based dosing 358
• FDA and validation of biomarkers 358
• FDA and predictive medicine 359
• FDA regulation of multivariate index assays 359
• Evaluation of companion diagnostics/therapeutic for cancer 360

12. Commercial Aspects of Personalized Medicine 363

• Introduction 363
• Perceived financial concerns 363
• Personalized medicine and orphan drug syndrome 363
• Commercial aspects of pharmacogenomics 363
• Cost of DNA testing 363
• Cost of sequencing the human genome 364
• Cost of genotyping 366
• Cost of pharmacogenomics-based clinical trials 366
• Business development of pharmacogenomic companies 367
• Cost of personalized healthcare 367
• Cost of genetic testing 367
• Economics of CYP genotyping-based pharmacotherapy 368
• Cost of personalized medicines 368
• The rising healthcare costs in the US 368
• Lowering the cost of healthcare 369
• Cost effectiveness of HIV genotyping 369
• Lowering the high costs of cancer chemotherapy 369
• Reducing the cost incurred by adverse drug reactions 370
• Overall impact of personalized medicine on healthcare 370
• Drivers for the development of personalized medicine 370
• Evolution of medicine as a driver for personalized therapy markets 371
• Collaboration between the industry and the academia 372
• Personalized medicine and drug markets 372
• Impact on drug markets 372
• Growth of markets relevant to personalized medicine 373
• SNP market 373
• Pharmacogenomics 374
• Pharmacogenetics 374
• Pharmacoproteomics 374
• Biochips 374
• Point-of-Care 374
• Markets for personalized medicines according to therapeutic areas 374
• Markets for personalized medicines according to geographical regions 375
• Market opportunities for personalization of medicine 375
• Impact of personalized medicine on other industries 376
• Strategies for developing and marketing personalized medicine 377
• Education of the public 377
• Role of the Internet in development of personalized medicine 377
• Marketing companion diagnostics for personalized medicine 378

13. References 379

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 64
• 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 87
• Table 2 9: Companies combining molecular diagnostics and therapeutics 90
• Table 2 10: Applications of point-of-care diagnosis 91
• Table 2 11: Companies developing point-of-care diagnostic tests 92
• 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 113
• 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 123
• Table 3 10: Companies with novel molecular toxicology technology 125
• Table 4 1: Role of pharmacogenomics in variable therapy targets 133
• Table 4 2: Role of pharmacogenomics in clinical trials 137
• Table 4 3: Examples of pharmacogenomics-based clinical studies 137
• Table 4 4: Tumor suppressor genes, their chromosomal location, function and associated tumors. 140
• Table 4 5: Gene polymorphisms relevant to cardiovascular disease management 141
• Table 4 6: Companies involved in cardiovascular genomics 143
• Table 4 7: A sampling of companies involved in neuropharmacogenomics 145
• Table 8 1: Important therapeutic areas for personalized medicine 169
• Table 8 2: Enzymes that metabolize antipsychotics 179
• Table 8 3: Enzymes that metabolize antidepressants 180
• Table 8 4: Biomarkers of response to interferon-β in multiple sclerosis 191
• Table 8 5: Genes that cause cardiovascular diseases 194
• Table 9 1: Factors that drive the development of personalized therapy in cancer 229
• Table 9 2: Impact of molecular diagnostics on the management of cancer 230
• Table 9 3: Selected companies involved in developing personalized cancer therapies 300
• Table 10 1: Players in the development of personalized medicine 307
• Table 10 2: Members of the Personalized Medicine Coalition 307
• Table 10 3: Biobanks relevant to personalized medicine 326
• Table 10 4: Role of bioinformatics in the development of personalized medicine 329
• Table 10 5: Advantages of personalized medicine for the biopharmaceutical industry 336
• Table 10 6: Advantages of personalized medicine for the patients 337
• Table 10 7: Advantage of personalized medicine for the physicians 337
• Table 10 8: Limitations of personalized medicine 337
• Table 10 9: Methods of translational science that are relvant to personalized medicine 341
• Table 10 10: Companies involved in predictive healthcare 343
• Table 12 1: Drivers for the development of personalized medicine 370
• Table 12 2: Growth of markets relevant to personalized medicine 2008-2018 373
• Table 12 3: Markets for personalized medicine according to therapeutic area 2008-2018 375
• Table 12 4: Markets for personalized medicine in major regions 2008-2018 375
• Table 12 5: Lack of efficacy in current therapy 376
• Table 12 6: Impact of personalized medicine on other industries 376
• Table 12 7: Strategies to develop personalized medicine 377
• Table 12 8: Role of the Internet in development of personalized medicine 378

Figures

• Figure 1 1: Relation of personalized medicine to other technologies 31
• Figure 1 2: Relation of systems pharmacology to personalized medicine 37
• Figure 2 1: Role of biochips/microarrays in personalized medicine 50
• Figure 2 2: Affymetrix GeneChip technology 52
• Figure 2 3: Role of CYP450 genotyping in development of personalized medicine 53
• 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 200
• Figure 8 2: A scheme of personalized management of pain 213
• Figure 9 1: Relationships of technologies for personalized management of cancer 230
• Figure 10 1: Integration of technologies for the development of personalized medicine 333
• Figure 12 1: Evolution of personalized medicine as a market driver 371