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Personalized Medicine - Scientific & Commercial Aspects

  • ID: 4748160
  • Report
  • June 2021
  • Region: Global
  • 1163 Pages
  • Jain PharmaBiotech
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. Biomarkers play an important role in personalized medicine. Diagnosis is integrated with therapy for selection of treatment as well for monitoring the results. There is emphasis on early detection and prevention of disease in modern medicine. Biochip/microarray technologies and next generation sequencing are also important. The concept of personalized medicine described in this report remains remains the best way to integrate new technologies such as nanobiotechnology for improving healthcare. 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 2023.

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 2020-2030.

Profiles of 298 companies involved in developing technologies for personalized medicines, along with 583 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 88 tables and 50 figures.
Note: Product cover images may vary from those shown

Part I: Technologies & Applications

Executive Summary

1. Basic Aspects

  • Definition of personalized medicine
  • History of medical concepts relevant to personalized medicine 
  • Evolution of modern personalized medicine 
  • Molecular biological basis of personalized medicine
  • The human genome 
  • ENCODE  
  • Chromosomes 
  • Genes 
  • The genetic code 
  • Gene expression 
  • DNA sequences and structure
  • Genetic variations in the human genome  
  • Single nucleotide polymorphisms
  • Copy number variations in the human genome
  • Insertions and deletions in the human genome
  • Large scale variation in human genome 
  • Structural variations in the human genome  
  • Mapping and sequencing of structural variation from human genomes
  • 1000 Genomes Project  
  • Role of DNA sequencing in the development of personalized medicine
  • Human Variome Project
  • Interconnected genetic and genomic patterns in human diseases
  • Mitochondrial tRNA and personalized medicine
  • Molecular pathology 
  • Basics technologies for developing personalized medicine  
  • Definitions of technologies relevant to personalized medicine  
  • Problems with the ICH definitions of pharmacogenomics and pharmacogenetics
  • ‘Omics’ and personalized medicine  
  • Relationship of various technologies to personalized medicine
  • Conventional medicine versus personalized medicine
  • Personalized medicine and evidence-based medicine  
  • Role of genetics in future approaches to healthcare
  • Genetic medicine 
  • Human disease and genes 
  • Genetic and environmental interactions in etiology of human diseases  
  • Role of genetics in development of personalized medicines
  • Genetic databases
  • Clinical Genomic Database
  • Genetic epidemiology
  • Limitations of medical genetics 
  • Role of epigenetics in personalized medicine
  • Role of systems biology in personalized medicine 
  • Systems pharmacology 
  • Systems medicine  
  • Synthetic biology and development of personalized medicines
  • Personalized digital medicine  
  • Artificial intelligence in personalized medicine
  • Machine learning and personalized medicine 
  • Algorithms based on machine learning  
  • Bioelectronics and personalized medicine  
  • A personalized approach to environmental factors in disease 
  • Role of animal models in development of personalized medicine
  • Animal models for supplementing research on human genomes 
  • Mouse models for personalized medicine 
  • Promise and limitations of animal models for personalized medicine
  • Role of pets with naturally occuring diseases
  • Cancer in dogs  
  • Reclassification of diseases
  • Translational science and personalized medicine
  • Genome to phenome translation  
  • Personalization of multimodal therapies  

2. Molecular Diagnostics in Personalized Medicine

  • Introduction
  • Molecular diagnostic technologies 
  • PCR-based methods 
  • DirectLinear™ Analysis  
  • Denaturing high-performance liquid chromatography
  • Multiplex Allele-Specific Diagnostic Assay
  • Representational oligonucleotide microarray analysis
  • Restriction fragment length polymorphism (RFLP)
  • Real-time PCR for detection of CNVs
  • Non-PCR methods  
  • Arrayed primer extension (APEX)
  • Enzymatic Mutation Detection (EMD) 
  • DNA sequencing
  • Sanger-sequencing technology 
  • ABI PRISM® 310 Genetic Analyzer  
  • High-throughput paired end transcriptome sequencing  
  • Emerging sequencing technologies 
  • 4300 DNA analyzer 
  • Apollo 100 
  • Cyclic array sequencing
  • CEQ™ 8000  
  • DeepCAGE sequencing 
  • Electron microscope-based DNA sequencing
  • IBS sequencing technology
  • Illumina’s sequencing technology
  • Ion Torrent's sequencing technology
  • Life Technologies 3500 series Genetic Analyzer
  • MegaBACE 500
  • Microdroplet-based PCR for large-scale targeted sequencing
  • Multiplex amplification of human DNA sequences  
  • Nanoscale sequencing 
  • Next generation sequencing based on Lightning Terminators  
  • Polonator sequencer  
  • RainStorm™ microdroplet technology  
  • Roche GL-FLEX sequencing
  • Sequential DEXAS
  • SOLiD technology  
  • Sequencing by hybridization 
  • Whole genome sequencing
  • Bioinformatic tools for analysis of genomic sequencing data 
  • Clinical Genomicist Workspace for managing NGS-based clinical tests  
  • Detection of single molecules in real time
  • Direct observation of nucleotide incorporation  
  • Molecular Combing
  • Nanopore sequencing
  • DNA sequence by use of nanoparticles
  • Zero-mode waveguide nanostructure arrays
  • Future prospects of sequencing
  • Role of DNA sequencing in development of personalized medicine 
  • Role of RNA sequencing in development of personalized medicine 
  • Biochips and microarrays
  • Role of biochip/microarray technology in personalized medicine 
  • Applications of biochip/microarray technology in personalized medicine
  • Standardizing the microarrays
  • Biochip technologies 
  • GeneChip
  • AmpliChip CYP450
  • Microfluidics  
  • Lab-on-a-chip 
  • Micronics' microfluidic technology
  • LabCD
  • Microfluidic automated DNA analysis using PCR
  • Integrated microfluidic bioassay chip 
  • Electronic detection of nucleic acids on microarrays
  • Strand displacement amplification on a biochip  
  • Rolling circle amplification on DNA microarrays  
  • Universal DNA microarray combining PCR and ligase detection reaction
  • Protein biochips
  • ProteinChip  
  • LabChip for protein analysis 
  • TRINECTIN proteome chip  
  • Protein expression microarrays 
  • Microfluidic devices for proteomics-based diagnostics
  • New developments in protein biochips/microarrays 
  • Protein biochips/microarrays for personalized medicine  
  • SNP genotyping 
  • Genotyping and haplotyping
  • Haplotype Specific Extraction
  • Computation of haplotypes
  • HapMap project
  • Haplotyping for whole genome sequencing 
  • Predictingdrug response with HapMap
  • Companies developing haplotyping technology
  • Technologies for SNP analysis  
  • Biochip and microarray-based detection of SNPs
  • SNP genotyping by MassARRAY
  • BeadArray technology
  • SNP-IT primer-extension technology 
  • Use of NanoChip for detection of SNPs
  • Electrochemical DNA probes
  • Laboratory Multiple Analyte Profile 
  • PCR-CTPP (confronting two-pair primers)  
  • TaqMan real-time PCR
  • Locked nucleic acid  
  • Molecular inversion probe based assays  
  • Pyrosequencing 
  • Smart amplification process version 2
  • Zinc finger proteins  
  • Mitochondrial SNPs
  • Limitations of SNP in genetic testing 
  • Concluding remarks on SNP genotyping  
  • Companies involved in developing technologies/products for SNP analysis  
  • Impact of SNPs on personalized medicine 
  • Detection of copy number variations
  • CNVer algorithm for CNV detection
  • CNVnator for discovery of CNVs and genotyping  
  • Study of rare variants in pinpointing disease-causing genes
  • Optical Mapping
  • Proteomics in molecular diagnosis
  • Proteomic strategies for biomarker identification  
  • Proteomic technologies for detection of biomarkers in body fluids
  • Protein patterns 
  • Layered Gene Scanning
  • Comparison of proteomic and genomic approaches in personalized medicine 
  • Role of nanobiotechnology in molecular diagnostics  
  • Cantilevers for personalized medical diagnostics  
  • Role of biomarkers in personalized medicine
  • Role of biosensors in personalized medicine  
  • Biomarkers for diagnostics
  • Biomarkers for drug development  
  • Gene expression profiling  
  • DNA microarrays  
  • Analysis of single-cell gene expression.
  • Gene expression profiling based on alternative RNA splicing  
  • Whole genome expression array
  • Tangerine™ expression profiling
  • Gene expression analysis on biopsy samples 
  • Profiling gene expression patterns of white blood cells  
  • Serial analysis of gene expression (SAGE) 
  • Multiplexed Molecular Profiling 
  • Gene expression analysis using competitive PCR and MALDI TOF MS  
  • Companies involved in gene expression analysis  
  • Monitoring in vivo gene expression by molecular imaging
  • Molecular imaging and personalized medicine 
  • Combination of diagnostics and therapeutics
  • Use of molecular diagnostics for stratification in clinical trials
  • Companion diagnostics
  • Companies involved in companion diagnostics
  • Point-of-care diagnosis  
  • Companies developing point-of-care diagnostic technologies
  • Point-of-care diagnosis of infections 
  • Advantages versus disadvantages of point-of-care diagnosis
  • Future prospects of point-of-care diagnosis
  • Genetic testing for disease predisposition
  • Preventive genetics by early diagnosis of mitochondrial diseases 
  • Direct-to-consumer genetic services 
  • Personalized polygenic risk scores  
  • Role of diagnostics in integrated healthcare  
  • Concept of integrated healthcare 
  • Components of integrated healthcare
  • Screening  
  • Disease prediction 
  • Early diagnosis 
  • Prevention
  • Therapy based on molecular diagnosis 
  • Monitoring of therapy  
  • Advantages and limitations of integrated healthcare
  • Commercially available systems for integrated healthcare
  • Future of molecular diagnostics in personalized medicine

3. Pharmacogenetics

  • Basics of pharmacogenetics 
  • Role of molecular diagnostics in pharmacogenetics 
  • Role of pharmacogenetics in pharmaceutical industry 
  • Study of the drug metabolism and pharmacological effects 
  • Causes of variations in drug metabolism
  • Enzymes relevant to drug metabolism
  • Pharmacogenetics of phase I metabolism
  • CYP450  
  • CYP2D6 inhibition by selective serotonin reuptake inhibitors
  • CYP2D6 genotype and codeine pharmacokinetics
  • Cytochrome P450 polymorphisms and response to clopidogrel  
  • Lansoprazole and cytochrome P450 
  • Glucose-6-phosphate dehydrogenase
  • Pharmacogenetics of phase II metabolism
  • N-Acetyltransferase
  • Uridine diphosphate-glucuronosyltransferase  
  • Measurement of CYP isoforms 
  • Polymorphism of drug transporters
  • Genetic variation in drug targets
  • Polymorphisms of kinase genes
  • Effect of genetic polymorphisms on disease response to drugs  
  • Ethnic differences in drug metabolism
  • Gender differences in pharmacogenetics
  • Role of pharmacogenetics in drug safety
  • Adverse drug reactions
  • Adverse drug reactions in children
  • Adverse drug reactions related to toxicity of chemotherapy  
  • Genetically determined adverse drug reactions 
  • Malignant hyperthermia 
  • Pharmacogenetics of clozapine-induced agranulocytosis 
  • Role of pharmacogenetics in warfarin therapy
  • Role of pharmacogenetics in antiplatelet therapy
  • Role of pharmacogenetics in carbamazepine therapy 
  • Role of pharmacogenetics in statin therapy
  • FDA consortium linking genetic biomarkers to serious adverse events 
  • Therapeutic drug monitoring, phenotyping, and genotyping  
  • Applications of therapeutic drug monitoring
  • Phenotyping 
  • Genotyping
  • Genotyping vs phenotyping  
  • Phenomics  
  • Limitations of genotype-phenotype association studies
  • Molecular toxicology in relation to personalized medicines
  • Toxicogenomics  
  • Biomarkers of drug toxicity  
  • Drug-induced mitochondrial toxicity  
  • Companies involved in molecular toxicology 
  • Gene expression studies  
  • Pharmacogenetics in clinical trials  
  • Postmarketing pharmacogenetics 
  • Clinical implications of pharmacogenetics
  • Application of CYP450 genotyping in clinical practice 
  • Genotype-based drug dose adjustment  
  • Pharmacogenomic biomarker information in drug labels 
  • Standardized terminology for clinical pharmacogenetic test results
  • Use of pharmacogenetics in clinical pharmacology
  • Application of CYP2C19 pharmacogenetics for personalized medicine
  • Genotyping for identifying responders to sulfasalazine
  • HLA alleles associated with lumiracoxib-related liver injury  
  • Pharmacogenetic basis of thiopurine toxicity  
  • Tranilast-induced hyperbilirubinemia due to gene polymorphism 
  • Linking pharmacogenetics with pharmacovigilance 
  • Genetic susceptibility to ADRs
  • Linking genetic testing to postmarketing ADR surveillance 
  • Recommendations for the clinical use of pharmacogenetics 
  • Limitations of pharmacogenetics 
  • Pharmacoepigenomics vs pharmacogenetics in drug safety  
  • Future role of pharmacogenetics in personalized medicine 

4. Pharmacogenomics 

  • Introduction  
  • Basics of pharmacogenomics
  • Pharmacogenomics and drug discovery
  • Preclinical prediction of drug efficacy  
  • Role of pharmacogenomics in drug discovery and drug delivery
  • Next generation sequencing and pharmacogenomics
  • Pharmacogenomics and clinical trials
  • Impact of genetic profiling on clinical studies 
  • Limitations of the pharmacogenomic-based clinical trials
  • Pharmacogenomic aspects of major therapeutic areas  
  • Oncogenomics
  • Oncogenes
  • Tumor suppressor genes  
  • Cardiogenomics 
  • Neuropharmacogenomics  
  • Pharmacogenomics of Alzheimer's disease
  • Pharmacogenomics of depression  
  • Pharmacogenomics of bipolar disorder 
  • Pharmacogenomics of schizophrenia  
  • Companies involved in neurogenomics-based drug discovery
  • Current state and future of pharmacogenomics

5. Role of Pharmacoproteomics

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

6. Role of Metabolomics in Personalized Medicine

  • Metabolomics and metabonomics  
  • Metabolomics bridges the gap between genotype and phenotype
  • Metabolomics, biomarkers and personalized medicine  
  • Metabolomic technologies
  • Urinary profiling by capillary electrophoresis
  • Lipid profiling  
  • Role of metabolomics in biomarker identification and pattern recognition
  • Pharmacometabonomics
  • Metabonomic technologies for toxicology studies  
  • Metabonomics/metabolomics and personalized nutrition  
  • Metabolomics for personalized medicine 

7. Personalized Biological Therapies

  • Introduction  
  • Recombinant human proteins
  • Therapeutic monoclonal antibodies 
  • Cell therapy 
  • Autologous tissue and cell transplants
  • Stem cells 
  • iPSCs for personalized cell therapy
  • Role of stem cells derived from unfertilized embryos 
  • Cloning and personalized cell therapy
  • Use of stem cells for drug testing 
  • Gene therapy
  • Gene editing by CRISPR/Cas9 system
  • Personalized gene therapy for cancer
  • Stem cell-based personalized gene therapy for cancer
  • Personalized vaccines
  • Personalized vaccines for viral diseases  
  • Personalized cancer vaccines
  • Antisense therapy  
  • RNA interference  
  • MicroRNAs  

8. Personalized complementary & Alternative Therapies  

  • Introduction  
  • Ayurveda as a personalized healthcare system
  • Taditional Chinese medicine  
  • Personalized acupuncture therapy
  • Personalized hyperbaric oxygen therapy 
  • Personalized nutrition.
  • Nutrigenomics
  • Evolutionary basis of nutrigenomics  
  • Genomics of vitamin D and calcium supplementation 
  • Nutrigenomics and functional foods 
  • Nutrigenomics and personalized medicine  
  • Nutriproteomics  
  • Nutrigenetics and personalized medicine
  • Personalized diet prescription
  • Personalized nutrition and aging 
  • Personalized diet for diabetics
  • Role of systems medicine in personalized nutrition 
  • Companies involved in personalized nutrition  
  • Personalized physical exercise  
  • Aerobic exercise response variations in individuals 
  • Exercise-induced muscle hypertrophy and strength variations 
  • Personalized exercise for prevention of functional decline in the elderly  

9. Personalized Medicine in Major Therapeutic Areas 

  • Introduction  
  • Personalized management of infections
  • Genetic susceptibility to infections 
  • Personalized use of antibiotics 
  • Personalized management of sepsis 
  • Role of nanobiotechnology in personalized management of infections
  • Personalized management of viral infections 
  • Genomic epidemiology of viral diseases
  • Management of HIV
  • CD4 counts as a guide to drug therapy for AIDS
  • Drug-resistance in HIV
  • Genetics of human susceptibility to HIV infection
  • Measurement of Replication Capacity
  • Personalized vaccine for HIV
  • Prevention of adverse reactions to antiviral drugs 
  • Pharmacogenetics and HIV drug safety  
  • Pharmacogenomics of antiretroviral agents
  • Role of diagnostic testing in management of HIV
  • Role of genetic variations in susceptibility to HIV-1
  • Role of personalized HIV therapy in controlling drug resistance
  • PhenoSense® to test HIV drug resistance  
  • Sequencing for detecting mutations to personalize HIV therapy
  • Personalized treatment of hepatitis B
  • Personalized treatment of hepatitis C
  • Responders vs non-responders to treatment for hepatitis C  
  • Drug resistance in hepatitis C 
  • Challenges for personalized management of hepatitis C 
  • Personalized management of COVID-19  
  • Molecular diagnosis of COVID-19  
  • Genomics of coronaviruses 
  • Genetic susceptibility for severity of COVID-19 
  • Risk factors for cardiac complications of COVID-19  
  • Strategies for developing therapies for COVID-19 
  • Antivirals for COVID-19 
  • Cell/gene therapy for COVID-19 
  • Personalized approach to passive antibody therapy for COVID-19
  • Personalized vaccines for COVID-19  
  • Personalized management of tuberculosis 
  • Personalized management of fungal infections
  • Psychiatric disorders
  • Introduction
  • Role of amygdala in personalized psychiatry
  • Gene polymorphisms as basis of personalized approach to psychiatric disorders  
  • Psychopharmacogenetics/psychopharmacodynamics
  • Serotonin genes  
  • Calcium channel gene  
  • Dopamine receptor genes
  • COMT genotype and response to amphetamine 
  • Methylenetetrahydrofolate reductase
  • Genetic loci associated with risk of major depressive disorder 
  • Role of gene mutations in ADHD 
  • Genotype and response to methylphenidate in children with ADHD 
  • GeneSight tests for individualized therapy of psychiatric disorders
  • Personalized antipsychotic therapy for schizophrenia
  • Pharmacogenetics for personalizing antipsychotic therapy
  • Patient-derived stem cells for personalizing drugs for schizophrenia  
  • Personalized therapy of bipolar disorder  
  • Personalized antidepressant therapy  
  • Pharmacogenetics/pharmacogenomics of antidepressant therapy  
  • Biomarkers of response to antidepressant treatment 
  • EEG biomarkers for predicting safety and efficacy of antidepressants
  • GeneSight pharmacogenomic test
  • Individualization of SSRI treatment 
  • Role of protein sFRP3 in predicting response to antidepressants
  • Treatment resistant depression
  • Vilazodone with a test for personalized treatment of depression
  • Personalized management of alcohol use disorder
  • Personalized management of autism spectrum disorders 
  • Neurological disorders 
  • Introduction to personalized neurology 
  • Individuality of the human brain as a basis of personalized neurology.
  • Gender differences in neurological disorders 
  • Measuring brain health across life span  
  • AI for personalized neurology
  • Wearable devices for personalized neurology  
  • Role of neuroinformatics in personalized neurology
  • Personalized management of Alzheimer's disease
  • Personalized management of Parkinson's disease
  • Atremorine as personalized dopaminergic therapy for PD
  • Brain imaging for diagnosis of neurodegenerative parkinsonism
  • Direct-to-consumer genetic testing in PD 
  • Disease modification in PD 
  • Discovery of subgroup-selective drug targets in PD
  • Personalized cell therapy for PD
  • Pharmacogenetics of PD
  • Use of wearable sensors to monitor PD response to levodopa therapy 
  • Personalized selection of targets for deep brain stimulation  
  • Personalized management of Huntington disease
  • Personalized management of amyotrophic lateral sclerosis
  • Personalized management of epilepsy
  • Adverse effects of AEDs 
  • An algorithm for personalized management of epilepsy
  • Biomarkers of epilepsy
  • Changes in seizure evolution with circadian timescale  
  • Drug resistance in epilepsy
  • Genetics/genomics of epilepsy  
  • Pharmacogenomics of epilepsy
  • Rasmussen’s encephalitis
  • Selection of the right AED
  • Status epilepticus.
  • Future of management of epilepsy
  • Personalized management of migraine
  • Individualization of use of triptans for migraine  
  • Multitarget therapeutics for personalized treatment of headache 
  • Personalized strategy for prevention of migraine attacks  
  • Personalized management of intracranial aneurysms
  • Personalized management of cerebral vasospasm following SAH 
  • Personalized management of stroke 
  • Biomarkers of stroke 
  • Management of a patient with carotid stenosis a risk for stroke
  • Anticoagulation for stroke prevention
  • Management of acute ischemic stroke 
  • Application of proteomics for personalizing stroke management
  • Brain imaging for personalized management of stroke
  • Deep learning for prediction of final ischemic stroke lesion from MRI
  • Intravenous thrombolysis and revascularization in acute stroke
  • Personalized management of intracerebral hemorrhage 
  • Revascularization procedures in chronic post-stroke stage 
  • Personalized cell therapy for management of stroke
  • Management of stroke according to stage  
  • Personalized treatment of multiple sclerosis
  • Autologous bone marrow stem cell therapy for multiple sclerosis  
  • Fusokine method of personalized cell therapy of multiple sclerosis
  • Immunopathological patterns of demyelination for assessing therapy
  • Personalizing mitoxantrone therapy of multiple sclerosis  
  • Pharmacogenomics of IFN-β therapy in multiple sclerosis
  • Personalizing therapy of MS by use of biomarkers 
  • Preclinical detection of multiple sclerosis in children
  • Predictive models of individual treatment response in MS
  • T cell-based personalized vaccine for MS
  • Targeting MS therapy to cell type of lesion
  • Personalized management of traumatic brain injury
  • Biomarkers of TBI 
  • Comparative effectiveness research for management of TBI
  • CT scores for prognosis and risk stratification of TBI
  • Management of cerebral edema/raised intracranial pressure in TBI 
  • Personalized management of myasthenia gravis  
  • Personalized management of tinnitus
  • Personalized management of pain  
  • Genetic factors in response to pain
  • Genetic mutations with loss of pain 
  • Genetic mutations and painful conditions 
  • Mechanism-specific management of pain 
  • Gene expression biomarkers for personalizing pain management  
  • Pharmacogenetics/pharmacogenomics of pain
  • Personalized management of pain with opioids 
  • Personalized opioid therapy for noncancer pain 
  • Pharmacogenetics of NSAIDs
  • Mechanism-specific management of pain 
  • Preoperative testing to tailor postoperative analgesic requirements 
  • Personalized analgesics.
  • Prediction of response to an analgesic by in vitro iPSC based testing
  • Signature of pain on brain imaging
  • Concluding remarks on personalized management of pain
  • Personalized management of sleep disorders 
  • Personalized therapy of insomnia  
  • Future of personalized neurology 
  • Personalized management of ophthalmic disorders 
  • Proteomics-based personalized management of uveitis
  • Combining cell and gene therapies for retinal disorders
  • Cardiovascular disorders 
  • Role of diagnostics in personalized management of cardiovascular disease  
  • Cardiovascular disorders with a genetic component
  • Gene mutations associated with risk of coronary heart disease
  • Gene variant as a risk factor for sudden cardiac death
  • KIF6 gene test as a guide to management of heart disease  
  • NGS sequencing for management of cardiovascular disorders 
  • Personalized antiplatelet therapy after PCI
  • Assessing patients with coronary heart disease
  • Assessing coronary artery disease for percutaneous coronary interventions..
  • Companion diagnostics for therapy of cardiovascular disorders  
  • Biomarkers and personalized management of cardiovascular disorders 
  • Clinical biomarkers  
  • Laboratory biomarkers
  • Pharmacogenomics of cardiovascular disorders
  • Nanotechnology-based personalized therapy of cardiovascular diseases  
  • Personalized management of chronic myocardial ischemia
  • Management of chronic angina pectoris
  • Inflammation as a target for therapy of myocardial ischemia
  • Personalized management of myocardial infarction  
  • Management of heart failure
  • β-blockers  
  • Bucindolol  
  • BiDil  
  • Cell therapy for cardiac repair 
  • Management of atrial fibrillation..
  • Treatment targets based on genetic variants  
  • Selection of personalized therapy for AF
  • Management of hypertension
  • Adjusting therapy of hypertension to fluctuations of blood pressure
  • Choice of drugs for hypertension 
  • Control of blood pressure with vagal nerve stimulation
  • Correction of causes and risk factors of hypertension  
  • Genes and hypertension  
  • Guideline for management of HPN
  • Improving management of HPN by targeting new pathways
  • Individualized therapy of HPN based on risk factors of heart disease
  • Personalized management of hypertensive patients with diabetes
  • Personalized management of hypertensive patients with albuminuria
  • Personalized management of hypertension in the elderly
  • Personalized management of hypertension in women  
  • Pharmacogenomics of diuretic drugs
  • Pharmacogenomics of ACE inhibitors
  • Prediction of antihypertensive activity of rostafuroxin  
  • Role of pharmacogenetics in management of hypertension 
  • Scheme for management of hypertension by personalized approach  
  • Personalized lipid-lowering therapies  
  • NIR spectroscopy of plaques to guide cholesterol-lowering therapy 
  • Polymorphisms in genes involved in cholesterol metabolism
  • Role of eNOS gene polymorphisms
  • Prediction of response to statins 
  • Personalized management of women with hyperlipidemia
  • Therapeutic alternatives in patients with statin intolerance 
  • Treatment of familial hypercholesterolemia
  • PCSK9 inhibitors
  • Concluding remarks on the personalized cholesterol management
  • Thrombotic disorders
  • Factor V Leiden mutation
  • Anticoagulant therapy
  • Antiplatelet therapy
  • Personalized management of aortic aneurysms
  • Clinical trials of personalized therapy of cardiovascular diseases
  • Project euHeart for personalized management of heart disease
  • Modification of life style factors in management of cardiovascular disorders
  • Multimorbidity in patients with cardiovascular disease  
  • Systems biology approach to personalized cardiology 
  • Concluding remarks on personalized management of cardiovascular diseases  
  • Personalized management of pulmonary disorders 
  • Role of genetic ancestory in lung function 
  • Targeted drug delivery for personalized management of pulmonary disorders
  • Personalized therapy of asthma
  • Asthma phenotyping for improving therapeutic precision
  • Biomarkers for predicting response to corticosteroid therapy
  • Genetic polymorphism and response to β2-adrenergic agonists
  • Genotyping in asthma
  • IgE as guide to dosing of omalizumab for asthma 
  • Lebrikizumab for personalised treatment of asthma
  • Personalized management of chronic obstructive pulmonary disease  
  • Biomarker-guided treatment of COPD
  • Molecular phenotype-based treatment of COPD  
  • Personalized management of idiopathic pulmonary fibrosis.
  • Personalized management of skin disorders  
  • Genetic testing for personalized skin care 
  • Management of hair loss based on genetic testing
  • Personalized urology
  • Personalized approaches in immunology 
  • Immunological tests in personalized medicine..
  • Antibody profiles
  • Role of Mannose-binding lectin testing in personalized medicine 
  • Pharmacogenetics and pharmacogenomics of immunosuppressive agents 
  • Personalized management of patients with lupus erythematosus.
  • Personalized therapy of rheumatoid arthritis
  • Biomarkers and diagnostics for personalizing therapy of rheumatoid arthritis  
  • DIATSTAT™ anti-cyclic citrullinated peptides in rheumatoid arthritis 
  • Genetics and epigenetic aspects of rheumatoid arthritis
  • Personalization of COX-2 inhibitor therapy  
  • Personalized biological therapy of RA  
  • Personalization of infliximab therapy  
  • Personalized therapy of RA guided by anti-citrullinated protein antibodies 
  • Variations in the effectiveness of therapies for RA
  • Personalized management of obesity
  • Basics of obesity  
  • Genetics of obesity as a basis for personalized management
  • Limitations of personalized approach to management of obesity
  • Personalized management of diabetes  
  • Biomarkers in the management of diabetes
  • Closed loop control of type1 DM
  • Personalized prediction of postprandial glycemic response.
  • Personalized management of monogenic diabetes 
  • Selection from multiple options for treatment of T2DM
  • Stratification of diabetes into 5 subgroups and personalized medicine.
  • Management of genetic disorders  
  • Personalized treatment of cystic fibrosis
  • Personalized management of Prader-Willi syndrome
  • Personalized management of gastrointestinal disorders 
  • Role of microbiome in personalized management of gastrointestinal disorders
  • Personalized therapy of inflammatory bowel disease
  • Personalized management of lactose intolerance  
  • Personalized approaches to improve organ transplantation  
  • Personalization of kidney transplantation
  • Cell-based bioengineered kidney transplant
  • Personalization of cardiac transplantation
  • Cell-based regeneration of heart for personalized transplantation 
  • Prediction of rejection for personalizig anti-rejection treatment  
  • Personalized immunosuppressant therapy in organ transplants  
  • Role of immunological biomarkers in monitoring grafted patients 
  • Improved matching of blood transfusion
  • Personalized approaches to addiction
  • Reversal of cocaine-evoked synaptic plasticity
  • Pharmacogenetics of drug addiction 
  • Genetic polymorphism and management of alcoholism
  • Personalized therapy for smoking cessation
  • Antidepressant therapy for smoking cessation
  • DNA methylation-based test for monitoring smoking 
  • Effectiveness of nicotine patches in relation to genotype  
  • Sex differences in smoking as response to stress
  • Personalized geriatrics  
  • Chronological vs biological age  
  • Pharmacogenetics and adverse drug reactions
  • Role of biomarkers and ageotyping
  • Systems pharmacology approach to disorders of aging
  • Personalized pediatrics  
  • WGS for personalized management of genetic disorders in critically ill infants 
  • Personalized nephrology.
  • Personalized management of chronic kidney disease
  • Genes and chronic kidney disease
  • MicroRNAs and chronic kidney disease 
  • Metabolomics and chronic kidney disease 
  • TGF-β1 as a target for therapy of chronic kidney disease
  • Proteomics and chronic kidney disease  
  • Personalized management of renal disease associated with hypertension
  • ACE inhibitors as renoprotective agents in hypertension
  • Gene associated with end-stage renal disease and hypertension 
  • Personalized approach to type I primary hyperoxaluria
  • Personalized gynecology 
  • Female sexual dysfunction
  • Hormone replacement therapy in women 
  • Lower urinary tract disorders in women  
  • Personalized surgery
  • Personalized approaches to miscellaneous problems
  • Personalized treatment of malaria  
  • Personalized management of osteoporosis  
  • Personalized care of trauma patients  
  • Personalized medical care of astronauts during space flights
  • Personalized management of motion sickness 
  • Personalized treatment of rare diseases  
  • Development of individualized biological therapies for rare diseases  
  • Personalized management of DNA repair disorders 
  • Personalized preventive medicine
  • Personalized surgery

10. Personalized Therapy of Cancer

  • Introduction  
  • Epidemiology of cancer
  • Development of personalized therapy in cancer 
  • Molecular biology of cancer as basis for personalized management
  • Cancer epigenetics/epigenomics and personalized therapy 
  • Cell division and mitotic spindles 
  • Chromosomes and cancer
  • Chromosomal instability 
  • Extrachromosomal DNA and cancer 
  • DNA damage, repair and cancer
  • Gene mutations and cancer  
  • Telomeres and cancer 
  • Challenges of cancer classification  
  • Role of staging in personalized management of cancer
  • Systems biology of cancer
  • Relationships of technologies for personalized management of cancer
  • Role of molecular diagnostics on the management of cancer..
  • A universal NGS-based oncology test system  
  • Analysis of RNA splicing events in cancer
  • Analysis of chromosomal alterations in cancer cells  
  • Cancer classification using microarrays 
  • Cancer gene panel for detection of genetic alterations  
  • Companion diagnostics for cancer  
  • Circulating tumor cells isolation and characterization
  • Circulating cell-free DNA for monitoring personalized cancer therapy  
  • Detection of loss of heterozygosity
  • Detection of rare mutations to guide cancer therapy
  • Diagnostics for detection of minimal residual disease
  • DNA repair biomarkers
  • DNA sequencing for prognosis of cutaneous T cell lymphoma
  • Fluorescent in situ hybridization
  • Gene expression profiling  
  • Gene expression profiling in hematological cancers
  • Gene expression profiling in prostate cancer 
  • Gene expression profiles predict chromosomal instability in tumors 
  • OnkoMatch tumor genotyping 
  • Synthetic lethality
  • GPS Cancer test 
  • Liquid biopsy 
  • Targeted digital sequencing  
  • Modulation of CYP450 activity for cancer therapy
  • NanoFlares for detection of CTCs 
  • Pathway-based analysis of cancer  
  • Conversion of gene-level information into pathway-level information
  • Personalized therapies based on oncogenic pathways signatures 
  • Quantum dot-based test for DNA methylation  
  • Role of molecular imaging in personalized therapy of cancer
  • Functional diffusion MRI 
  • FDG-PET/CT for personalizing cancer treatment  
  • Image-guided personalized drug delivery in cancer
  • Optoacoustic imaging and nanoparticles in cancer management 
  • Tumor imaging and elimination by targeted gallium corrole  
  • Future of molecular imaging in management of cancer
  • Unraveling the genetic code of cancer
  • Cancer prognosis 
  • Personalized cancer prevention
  • Detection of mutations for cancer risk assessment and prevention
  • Impact of biomarkers on management of cancer 
  • Biomarker-based assays for predicting response to anticancer therapeutics
  • HER-2/neu oncogene as a biomarker for cancer 
  • L-asparaginase treatment of cancer guided by a biomarker 
  • miRNA biomarkers for personalized management of cancer 
  • Oncogene GOLPH3 as a cancer biomarker 
  • Predictive biomarkers for efficacy of anticancer therapy
  • Sequencing to discover biomarkers to personalize cancer treatment 
  • Swiss molecular tumor board for individualized, biomarker-based decisions
  • VeraTag™ assay system for cancer biomarkers
  • Determination of response to therapy 
  • Ex vivo testing of tumor biopsy for chemotherapy sensitivity
  • Genomic approaches to predict response to anticancer agents 
  • Gene expression patterns to predict response of cancer to therapy 
  • Genetic therapy of cancer
  • Genomic analysis of tumor biopsies 
  • Genotype-dependent efficacy of pathway inhibition in cancer 
  • Mutation detection at molecular level
  • Predicting response to checkpoint inhibitors 
  • RNA Disruption Assay™ 
  • Non-genetic factors for variations in response of cancer cells to drugs
  • Profiling of cancer therapy in zebrafish xenografts to predict response
  • Proteomic analysis of tumor biopsies to predict response to treatment 
  • Real-time apoptosis monitoring
  • Serum nucleosomes as indicators of sensitivity to chemotherapy 
  • Targeted microbubbles to tumors for monitoring anticancer therapy 
  • PET imaging for determining response to chemotherapy 
  • PET imaging with tyrosine kinase inhibitors
  • Concluding remarks about predicting response to anticancer therapy
  • Molecular diagnostics combined with cancer therapeutics..
  • Aptamers for combined diagnosis and therapeutics of cancer
  • Combining diagnosis and therapy of metastatic cancer
  • Detection and destruction of CTCs with nanoparticles and X-rays 
  • Molecular profiling of cancer  
  • Targeted cancer therapies
  • Targeting angiogenesis in cancer 
  • Targeting glycoproteins on cell surface 
  • Targeting pathways in cancer
  • Targeted personalized anticancer medicines in clinical use
  • Immunotherapy of cancer
  • Monoclonal antibodies for personalized management of cancer  
  • Targeted MAb-based immune therapy of cancer 
  • MAbs targeted to alpha fetaprotein receptor 
  • MAbs targeted to tumor blood vessels 
  • MAbs that selectively target cancer 
  • Velociximab
  • MAbs for immune activation  
  • Functional MAb-based therapies
  • Immunotherapy of dormant cancer
  • Combined use of MAbs and cytokines
  • Antibody-drug conjugates for personalized therapy of cancer
  • Combining diagnostics with therapeutics based on MAbs 
  • Radiolabeled antibodies for detection and targeted therapy of cancer
  • Cancer immunotherapy based on suppression of enzymes
  • Personalized cancer vaccines..
  • Antigen-specific vaccines  
  • Active immunotherapy based on antigen specific to the tumor  
  • Tumor-derived vaccines
  • FANG vaccine
  • MyVax 
  • OncoVAX 
  • Tumor cells treated with dinitrophenyl 
  • Prophage 
  • Melacine
  • Patient-specific cell-based vaccines
  • Dendritic cell-based vaccines
  • Adoptive cell therapy
  • Combination of antiangiogenic agents with ACT  
  • Genetically targeted T cells for treating B cell malignancies  
  • Genetic engineering of tumor cells
  • Hybrid cell vaccination
  • Personalized peptide cancer vaccines 
  • Targeting core mutations in cancer
  • Current status and future of personalized cancer vaccines
  • Personalized radiation therapy  
  • Peptide receptor radionuclide therapy
  • Use of radiation sensitivity biomarkers in personalized radiotherapy 
  • Use of imaging to monitor radioimmunotherapy of non-Hodgkin lymphoma..
  • Role of nanobiotechnology in personalized management of cancer 
  • Design of future personalized cancer therapies
  • Personalized therapy of cancer based on cancer stem cells
  • Role of CRISPR-Cas9 in personalized cancer gene therapy
  • Role of epigenetics in development of personalized cancer therapies  
  • Cancer epigenetics and immunotherapy
  • Selective destruction of cancer cells while sparing normal cells  
  • Sphingolipids  
  • Hyperbaric oxygen as adjunct to radiotherapy
  • Targeting response to transformation-induced oxidative stress
  • Targeting enzymes to prevent proliferation of cancer cells.
  • Tissue systems biology approach to personalized management of cancer
  • Role of oncoproteomics in personalized therapy of cancer
  • Cancer tissue proteomics  
  • Proteomics technologies to guide targeted drug selection for cancer 
  • LC-MS/MS proteomics as a companion diagnostic 
  • Personalized cancer therapy based on targeted proteomics  
  • Role of metabolomics in personalized therapy of cancer 
  • Manipulation of tumor metabolism for personalizing antitumor effect  
  • Role of sequencing in personalized therapy of cancer 
  • Pharmacogenomic-based chemotherapy 
  • Whole genome technology to predict drug resistance 
  • Anticancer drug selection based on molecular characteristics of tumor
  • Testing microsatellite-instability for response to chemotherapy  
  • Pharmacogenetics of cancer chemotherapy 
  • CYP 1A2
  • Thiopurine methyltransferase
  • Dihydropyrimidine dehydrogenase
  • UGT1A1 test as guide to irinotecan therapy
  • Computers and digital technologies for personalized oncology  
  • Artificial intelligence in personalized management of cancer  
  • Computational models of kinetically tailored treatment
  • Mathematical modeling of tumor microenvironments
  • Modeling signaling pathways to reposition anticancer drugs  
  • Personalized computational oncology  
  • Therapy resistance in cancer
  • Mechanism of therapy resistance in cancer  
  • Cancer stem cells and radioresistance 
  • Expression of P-glycoprotein gene by tumor 
  • Overexpression of multidrug resistance gene  
  • P53 mutations
  • Role of splice variants in resistance to cancer therapy
  • Detection of drug resistance  
  • Anaplastic lymphoma kinase..
  • CRISPR for studying mechanism of drug-resistance in cancer 
  • Metabolic profiling of cancer
  • Management of drug resistance in cancer 
  • Chemogenomic approach to drug resistance 
  • Determination of chemotherapy response by topoisomerase levels
  • Patient-derived xenograft mouse models in drug resistant cancer
  • Resistance to vaccines in cancer recurrence after surgery
  • Systems biology approach to drug-resistant cancer
  • Personalized therapy of cancer metastases 
  • Technologies for analysis of CTCs 
  • Microfluidic technologies  
  • BEAMing technology for analysis of circulating tumor DNA.
  • Technologies for detection of interplay of environments and CTCs
  • Systemic antitumor effect of localized radiotherapy for cancer metastases  
  • Diagnosis of cancer of an unknown primary..
  • Personalized management of cancers of various organs/systems
  • Personalized management of bladder cancer 
  • Biomarkers of bladder cancer 
  • Selection of optimal anticancer agents for bladder cancer
  • Personalized management of brain tumors  
  • Aptamers for selective targeting of tumor initiating cells in GBM 
  • Bioinformatic approach to personalizing treatment of GBM 
  • Biosimulation approach to personalizing treatment of brain cancer
  • Brain cancer chip for personalized drug screening 
  • Combination of gene therapy and CAR-T cell therapy for GBM  
  • Drug resistance in GBM.
  • Genetics and genomics of GBM
  • Genomic analysis as a guide to personalized therapy of GBM
  • Induced neural stem cells for personalized therapy of GBM  
  • Molecular diagnostics for personalized management of GBM
  • Personalized vaccine for GBM 
  • Personalized chemotherapy of GBM 
  • Sex differences in GBM for guiding management
  • Personalized therapy of oligodendroglial tumors  
  • Personalized therapy of neuroblastomas
  • Personalized therapy of medulloblastomas
  • Personalized management of germ cell brain tumors 
  • Personalized management of meningiomas
  • Supratentorial hemispheric diffuse low-grade gliomas  
  • Targeted therapy of BRAF V600E mutant papillary craniopharyngioma
  • Future prospects of personalized therapy of malignant brain tumors  
  • Personalized management of breast cancer
  • Biomarker-guided decisions for breast cancer therapy
  • Developing personalized drugs for breast cancer
  • Gene expression plus conventional predictors of breast cancer
  • Her2 testing in breast cancer as a guide to treatment  
  • HER2/neu-derived peptide vaccine for breast cancer 
  • Prediction of cell signaling pathways from gene expression patterns  
  • Trends in treatment patterns and outcomes for DCIS  
  • Molecular diagnostics in breast cancer 
  • Molecular classification of infiltrating breast cancer 
  • Monitoring of circulating tumor cells in breast cancer 
  • Gene therapy of breast cancer  
  • Pharmacogenetics of breast cancer 
  • Proteomics-based personalized management of breast cancer  
  • Predicting response to chemotherapy in breast cancer
  • Adjuvant endocrine therapy in premenopausal breast cancer
  • Prediction of resistance to chemotherapy in breast cancer
  • Prediction of adverse reaction to radiotherapy in breast cancer
  • Prediction of recurrence in breast cancer for personalizing therapy
  • Prognostic tests for breast cancer
  • Racial factors in the management of breast cancer  
  • RATHER consortium to study personalized approach to breast cancer
  • Ribociclib as first-line therapy for HR-positive breast cancer
  • TAILORx (Trial Assigning Individualized Options for Treatment)
  • Tamoxin therapy for ER-positive breast cancer 
  • Triple negative breast cancer
  • Treatment resistance in hormone receptor-positive breast cancer
  • Current trends and future of breast cancer research
  • Understanding tumor diversity in mouse mammary cancer model
  • Personalized management of ovarian cancer 
  • Early diagnosis of ovarian cancer  
  • Determining response to chemotherapy in ovarian cancer
  • Personalized PARP therapy of ovarian cancer  
  • Prognosis of ovarian cancer based on CLOVAR
  • Recurrent and drug-resistant ovarian cancer  
  • Pathway targeted therapies for ovarian cancer 
  • Repurposing auranofin for treatment of ovarian cancer
  • Subtype-specific therapies for epithelial ovarian cancer 
  • Targeting hematogenous metastasis of ovarian cancer
  • Vynfinit ® for platinum-resistant ovarian cancer
  • Personalized management of head and neck cancer
  • Molecular characterization of head and neck cancer using omics 
  • Relevance of biomarkers of HPV-related head and neck cancer
  • Molecular targeted therapies for HNSCC..
  • Personalized management of hematological malignancies
  • B cell malignancies  
  • Personalized management of acute lymphoblastic leukemia
  • Personalized management of chronic lymphocytic leukemia  
  • Personalized management of acute myeloid leukemia  
  • Personalized management of chronic myeloid leukemia 
  • Personalized management of multiple myeloma  
  • Personalized management of myelodysplastic syndrome  
  • Personalized management B cell lymphomas  
  • Personalized vaccine for follicular lymphoma  
  • Pharmacoproteomics approach to diffuse large B cell lymphoma 
  • Companion diagnostic for treatment of lymphoma with Adcentris™ 
  • Management of drug resistance in leukemia 
  • Personalized management of gastrointestinal tumors 
  • Personalized management of esophageal cancer
  • Personalized management of gastric cancer 
  • Personalized management of gastroesophageal cancer
  • Personalized management of gastrointestinal stromal tumors 
  • Personalized management of colorectal cancer
  • Developing personalized therapies for CRC
  • Molecular diagnosis for guiding personalized management of CRC
  • Role of staging of CRC in prognosis and management decisions
  • Role of biomarkers in personalized management of CRC  
  • Role of miRNA modeling in personalized management of CRC 
  • Resistance to targeted EGFR blockade in CRC
  • Sequencing for personalized management of colorectal cancer
  • Systems biology approach to drug resistance in colorectal cancer
  • Personalized management of liver cancer
  • Prognosis of HCC in relation to management  
  • Prediction of recurrence of hepatocellular carcinoma 
  • Prediction of survival of patients with fibrolamellar HCC 
  • Personalized management of lung cancer
  • ALK inhibitors for personalized management of NSCLC
  • Bronchial genomic classifier for diagnostic of lung cancer
  • Companion diagnosis for NSCLC therapeutics
  • Copy number variations as a diagnostic tool for lung cancer
  • Development of resistance to EGFR inhibitors
  • EGFR mutations for predicting response to drugs in lung cancer 
  • Molecular subtyping of lung cancer
  • miRNA classifiers as diagnostic/prognostic tools in lung cancer
  • Predicting response of NSCLC to drug therapy
  • Predicting recurrence of lung cancer for prevention
  • Proteomics for discovery of metabolic biomarkers of lung cancer  
  • Role of a new classification system in the management of lung cancer 
  • Selecting therapy of cancer arising from respiratory papillomatosis 
  • Sequencing the genomes of SCLC
  • Testing for response to chemotherapy in lung cancer  
  • Testing for prognosis of lung cancer  
  • Testing for recurrence of lung cancer
  • Personalized management of malignant melanoma  
  • Inhibitors of BRAF mutation for metastatic melanoma
  • Management of drug-resistant metastatic melanoma 
  • Vaccine for malignant melanoma based on heat shock protein  
  • Personalized management of endocrine tumors 
  • Adosterone producing tumors 
  • Neuroendocrine tumors 
  • Parathyroid tumors
  • Personalized management of pheochromocytoma and paraganglioma 
  • Personalized management of osteosarcoma
  • Personalized management of pancreatic cancer 
  • Biomarkers of pancreatic cancer 
  • Histone modifications predict treatment response in pancreatic cancer  
  • Transport properties of pancreatic cancer and gemcitabine delivery  
  • Personlized management of prostate cancer
  • Assessing susceptibility to prostate cancer by genotyping
  • Diagnostics for guiding therapy of prostate cancer  
  • Detection of prostate cancer metastases
  • Early detection of cancer recurrence and guiding treatment
  • Effects of lifestyle changes shown by gene expression studies 
  • Epigenetics-based assays for guiding the decision to biopsy prostate  
  • Genomic patterns of aggressiveness of prostate cancer 
  • Personalized peptide vaccine for prostate cancer
  • Selection of prostate cancer patients responsive to rucaparib therapy 
  • Personalized management of thyroid cancer
  • Current trends and future of personalized oncology  
  • Challenges for developing personalized cancer therapies 
  • Personalizing anticancer drug combinations
  • Cancer Genome Atlas 
  • Cancer Moonshot
  • Blood Profiling Atlas
  • NCI collaborations 
  • COLTHERES consortium
  • Computer and imaging technologies for personalizing cancer treatment  
  • Genomic Cancer Care Alliance 
  • Integrated genome-wide analysis of cancer for personalized therapy  
  • International Cancer Genome Consortium 
  • National Cancer Institute of US  
  • Catalog of cancer genes for personalized therapy
  • NCI-designated Comprehensive Cancer Centers  
  • Role of NCI Genomic Data Commons in personalized cancer therapy
  • Precision Oncology Decision Support at MD Anderson Cancer Center  
  • PREDICT Consortium
  • Quebec Clinical Research Organization in Cancer
  • The San Antonio 1000 Cancer Genomes Project 
  • Companies involved in developing personalized oncology

Tables 
Table 1-1: Selected terms relevant to the concept of personalized medicine
Table 1-2: Landmarks in the historical development of personalized medicine
Table 1-3: Genetic variations in the human genome
Table 1-4: Examples of systems medicine-based diagnostic/therapeutic approaches
Table 2-1: Molecular diagnostic technologies used for personalized medicine  
Table 2-2: Applications of biochip technology relevant to personalized medicine  
Table 2-3: Companies developing haplotying technology  
Table 2-4: Technologies for SNP analysis
Table 2-5: A sampling of companies involved in technologies for SNP genotyping  
Table 2-6: Comparison of proteomic and genomic approaches in personalized medicine
Table 2-7: Selected methods for gene expression profiling  
Table 2-8: A selection of companies with gene expression technologies
Table 2-9: Drugs requiring biomarker/companion diagnostic information in the label
Table 2-10: Companies involved in companion diagnostics  
Table 2-11: Applications of point-of-care diagnosis
Table 2-12: Companies developing point-of-care diagnostic tests
Table 2-13: Companies offering genetic screening tests directly to consumers  
Table 3-1: Pharmacogenetic vs. pharmacogenomic studies
Table 3-2: Enzymes relevant to drug metabolism  
Table 3-3: Examples of mutation of the enzyme CYP450
Table 3-4: Frequency distribution of drugs metabolized by major isoforms of CYP450. 
Table 3-5: Commonly prescribed medications, which are metabolized by CYP2D6  
Table 3-6: Polymorphisms in drug target genes that can influence drug response  
Table 3-7: Effect of genetic polymorphisms on disease response to drugs
Table 3-8: Examples of genetically determined adverse reactions to drugs 
Table 3-9: Examples of genotyping and phenotyping in some diseases
Table 3-10: Companies with novel molecular toxicology technology
Table 3-11: Pharmacogenomic biomarkers in drug labeling
Table 4-1: Role of pharmacogenomics in variable therapy targets
Table 4-2: Role of pharmacogenomics in clinical trials
Table 4-3: Examples of pharmacogenomics-based clinical studies
Table 4-4: Tumor suppressor genes, their chromosomal location, function and associated tumors.  
Table 4-5: Gene polymorphisms relevant to cardiovascular disease management  
Table 4-6: Companies involved in cardiovascular genomics
Table 4-7: SNPs in genes implicated in response of bipolar disorder to lithium
Table 4-8: A sampling of companies involved in neuropharmacogenomics
Table 5-1: Applications of pharmacoproteomic biomarkers in personalized medicine  
Table 8-1: Companies involved in personalized nutrition
Table 9-1: Important therapeutic areas for personalized medicine 
Table 9-2: Enzymes that metabolize antipsychotics
Table 9-3: Enzymes that metabolize antidepressants
Table 9-4: Biomarkers of response to antidepressant treatment  
Table 9-5: Brain imaging for diagnosis of neurodegenerative parkinsonism 
Table 9-6: Biomarkers of epilepsy
Table 9-7: Influence of gene polymorphisms on efficacy of antiepileptic drugs 
Table 9-8: Biomarkers of stroke  
Table 9-9: Role of cell therapy in management of stroke according to stage  
Table 9-10: Gene expression as biomarker of response to IFN-β in multiple sclerosis
Table 9-11: Biomarkers of traumatic brain injury 
Table 9-12: P450 isoforms in the metabolism of drugs used in the management of pain
Table 9-13: Personalized management of neuropathic pain based on mechanism  
Table 9-14: Genes that cause cardiovascular diseases
Table 9-15: Classification of diabetes into 5 clusters  
Table 9-16: Genetic influences on pharmacotherapy of alcoholism 
Table 10-1: Factors that drive the development of personalized therapy in cancer
Table 10-2: Impact of molecular diagnostics on the management of cancer  
Table 10-3: FDA-approved companion diagnostics for cancer  
Table 10-4: Marketed anticancer personalized medicines
Table 10-5: Monoclonal antibodies for cancer approved by the FDA
Table 10-6: Clinical trials of personalized cancer vaccines 
Table 10-7: Future developments in oncology relevant to personalized management
Table 10-8: Selected companies involved in developing personalized oncology  

Figures 
Figure 1-1: Relation of personalized medicine to other technologies 
Figure 1-2: Relation of systems pharmacology to personalized medicine
Figure 2-1: Role of sequencing in personalized medicine 
Figure 2-2: Role of biochip/microarray technology in personalized medicine  
Figure 2-3: Application of biochips/microarrays in personalized therapy  
Figure 2-4: Affymetrix GeneChip technology 
Figure 2-5: Role of CYP450 genotyping in development of personalized medicine
Figure 2-6: Role of SNPs in personalized medicine 
Figure 2-7: A scheme of integrated healthcare and personalized medicine
Figure 3-1: Pharmacogenetics as a link between genotype and phenotype
Figure 3-2: Role of pharmacogenetic technologies in personalized medicine  
Figure 4-1: Impact of new technologies at various stages of the drug discovery process
Figure 4-2: Steps in the application of pharmacogenomics in clinical trials
Figure 7-1: Role RNAi in development of personalized medicine 
Figure 8-1: A scheme of various factors in personalized nutrition
Figure 9-1: Pathogen sequencing as guide to personalized management viral infections
Figure 9-2: An integrated approach to viral diseases  
Figure 9-3: Workflow of genotypic resistance analysis for personalized HIV therapy 
Figure 9-4: Gene-environment interactions leading to an increased risk of cardiac death in COVID-19
Figure 9-5: Components of multimodal therapy for neurological disorders
Figure 9-6: Scheme of iPSCs use for personalized cell therapy of Parkinson disease 
Figure 9-7: Antisense approaches for personalized therapy of Huntington disease
Figure 9-8: An algorithm for personalized management of epilepsy  
Figure 9-9: Interacting risk factors for stroke
Figure 9-10: Decision for medical vs surgical treatment of carotid occlusive disease 
Figure 9-11: Algorithm for anticoagulant therapy to prevent stroke in atrial fibrillation 
Figure 9-12: Spot sign of extravasation and expansion of intracerebral hematoma
Figure 9-13: A scheme of personalized therapy of multiple sclerosis
Figure 9-14: Personalized targeting of therapeutic agents to lesions of multiple sclerosis
Figure 9-15: Essential components of personalized management of pain  
Figure 9-16: Genetic and non-genetic factors affecting efficacy and side effects of opioids  
Figure 9-17: Role of opioid therapy in management of noncancer pain
Figure 9-18: An algorithm for personalized management of pain
Figure 9-19: Assessment of stable coronary artery disease
Figure 9-20: Flow chart of personalized approach to management of atrial fibrillation
Figure 9-21: A scheme of personalized approach to management of chronic hypertension  
Figure 9-22: Statins for management of blood cholesterol to reduce risk of CVD
Figure 9-23: Basis of personalized approach to idiopathic pulmonary fibrosis (IPF)
Figure 9-24: Steps in growing a new heart in vitro for transplantation  
Figure 10-1: Relationships of technologies for personalized management of cancer
Figure 10-2: Integration of technologies for personalized prevention of cancer 
Figure 10-3: CRISPR-Cas9 in personalized cancer gene therapy  
Figure 10-4: Use of LC-MS/MS to select appropriate targeted therapy for cancer 
Figure 10-5: Personalized cancer therapy based on targeted proteomics
Figure 10-6: Applications of NCI Genomic Data Commons  
Figure 10-7: Workflow for development of gene pages for personalized cancer therapy  

Part II: Development, Ethics, Regulation, Markets & Companies

11. Development of Personalized Medicine 

  • Introduction  
  • Non-genomic factors in the development of personalized medicine  
  • Personalized medicine based on circadian rhythms 
  • Cytomics as a basis for personalized medicine 
  • Intestinal microflora 
  • Gut microbiome compared to human genome 
  • Metabolic interactions of the host and the intestinal microflora 
  • Role of drug delivery in personalized medicine 
  • Personalized approach to clinical trials  
  • Adaptive clinical trials
  • Bayesian approach in biomarker-based clinical trials
  • Clinical trials of therapeutics and companion diagnostics
  • Clinical trials on selected subpopulations of patients  
  • Clinical trials networks 
  • Creative clinical trial design
  • Individualzing risks and benefits in clinical trials 
  • Players in the development of personalized medicine  
  • Personalized Medicine Coalition
  • Role of pharmaceutical industry 
  • Repositioning of drugs for personalized medicine  
  • Discovery of personalized medicines
  • Personalized drug delivery
  • Production and distribution of personalized medicines
  • Role of biotechnology companies
  • Role of life sciences industries
  • Role of biomedical engineering in wearable devices for personalized healthcare
  • Role of molecular imaging in personalized medicine 
  • Molecular imaging for personalized drug development in oncology  
  • Molecular imaging and CNS drug development
  • Companies involved in molecular imaging
  • Role of the clinical laboratories
  • Role of the US government in personalized medicine  
  • Precision Medicine Initiative 
  • Department of Health and Human Services and personalized medicine
  • Agency for Healthcare Research and Quality
  • Comparative effectiveness research
  • Role of the US Government agencies in personalized medicine
  • NIH's Roadmap Initiative for Medical Research
  • NIH and personalized medicine 
  • NIH collaboration with the FDA 
  • NIH and Genetic Testing Registry
  • National Human Genome Research Institute
  • National Institute of General Medical Sciences  
  • National Institute of Standards and Technology
  • Role of the Centers for Disease Control
  • Role of academic institutions and health centers in the US  
  • Baylor College of Medicine 
  • California Initiative to Advance Precision Medicine
  • Children’s Hospital of Los Angeles 
  • Clinical Proteomics Program of NCI & FDA
  • Coriell Personalized Medicine Collaborative™
  • Delaware Valley Personalized Medicine Project  
  • Duke University’ Center for Genomic and Computational Biology
  • Evaluation of genetic tests and genomic applications
  • Indiana University Institute for Personalized Medicine
  • Inova Center for Personalized Health 
  • Institute of Medicine’s role in personalized medicine  
  • Jackson Laboratory for Genomic Medicine
  • Johns Hopkins Center for Personalized Cancer Medicine Research 
  • Mayo Clinic’s Centers for Individualized Medicine  
  • Mt. Sinai Medical Center’s Personalized Medicine Research Program
  • North Shore University’s Center for Personalized Medicine  
  • P4 Medicine Institute
  • Personalized Medicine Partnership of Florida
  • Personalized oncology at Massachusetts General Hospital  
  • Personalized oncology at Oregon Health & Science University
  • Pharmacogenetics Research Network and Knowledge Base
  • Southeast Nebraska Cancer Center's Personalized Medicine Network 
  • Spectrum Health Center for personalized cancer care
  • Stanford Center for Genomics and Personalized Medicine 
  • UAB-HudsonAlpha Center for Genomic Medicine
  • University of Colorado’s Center for Personalized Medicine 
  • UNC Institute for Pharmacogenomics and Individualized Therapy
  • Weill Cornell’s Englander Institute for Precision Medicine
  • Wisconsin Genomics Initiative.
  • Role of academic collaborations with companies
  • New York Genome Center  
  • Role of healthcare organizations  
  • Role of the medical profession
  • The American Medical Association and personalized medicine
  • Education of the physicians
  • Off-label prescribing and personalized medicine
  • Medical education
  • Role of patients
  • Consumer genomics  
  • Monitoring of patient compliance with therapy  
  • Public attitude towards personalized medicine  
  • Patient participation in disease management decisions  
  • Patient engagement in clinical trials of personalized medicine
  • Role of genetic banking systems and databases  
  • Role of biobanks in development of personalized medicine  
  • UK Biobank 
  • Biobanking and development of personalized medicine in EU 
  • BBMRI-ERIC
  • CARTaGENE for biobanks in Canada
  • Personalized medicine based on PhysioGenomics™ technology
  • Role of bioinformatics in development of personalized medicine
  • Biosimulation techniques for developing personalized medicine
  • Biosensing and wearable devices for monitoring of health 
  • Devices for detection of digital biomarkers 
  • Clinical decision support systems
  • Digitalized medicine 
  • Genomic data analysis
  • Integration of omics data by deep learning
  • Exploration of disease-gene relationship 
  • Health information management  
  • Electronic health records
  • Analysis of -omic and EHR data of the patient
  • Cost of EHR and savings on healthcare expenses in the US
  • EHRs and genome-wide studies  
  • Linking patient medical records and genetic information
  • Management of personal genomic data
  • Use of EHRs for improving safety of new medicines 
  • Use of EHRs for genetic research
  • Use of EHRs for personalized drug discovery and development 
  • Personalized prognosis of disease
  • Integration of technologies for personalized medicine
  • Global scope of personalized medicine
  • Global Alliance for Genomics and Health 
  • Precision medicine project of World Economic Forum  
  • Personalized medicine in Canada
  • Personalized medicine at Ontario Institute for Cancer Research 
  • Personalized Medicine Partnership for Cancer in Quebec
  • Quebec Center of Excellence in Personalized Medicine
  • Personalized medicine in the EU  
  • European Personalized Medicine Diagnostics Association
  • European Ubiquitous Pharmacogenomics project
  • UK National Health Service and medical genetics
  • UK’s 100,000 Genomes project
  • UK's Precision Medicine Catapult  
  • Personalized medicine in France 
  • Personalized medicine in Germany  
  • Personalized medicine in Israel 
  • Personalized medicine in Japan 
  • Biobanks in Japan  
  • Companion diagnostics in Japan  
  • Cost-effectiveness of personalized medicine in Japan
  • Genetic testing in Japan  
  • Initiative on rare and undiagnosed diseases  
  • Personalized medicine in the developing countries  
  • Personalized medicine in the Middle East
  • Personalized medicine in China 
  • Personalized medicine in India
  • Personalized medicine in Africa 
  • Advantages of personalized medicine  
  • Limitations of personalized medicine 
  • Non-genomic factors in response to drugs
  • Incidental findings in genetic screening and clinical sequencing 
  • Future of personalized medicine  
  • Personal Genome Project
  • Genome-wide association studies
  • NHGRI’s genomics vision for 2020 
  • Genomics of aging in a genetically homogeneous population  
  • Translational science and personalized medicine
  • Translation of genomic research into genetic testing for healthcare
  • Long-term behavioral effects of personal genetic testing
  • Personalized predictive medicine  
  • Connected health and personalized medicine
  • Opportunities and challenges for personalized medicine  
  • Comparative-effectiveness research and personalized medicine  
  • Genetic testing and concerns about equality of healthcare 
  • Impact of molecular diagnostics on personalized medicine
  • Initiative for delivery for precision medicine
  • IGNITE network - implementing personalized medicine in clinical care
  • Prospects and limitations of genetic testing  
  • Personalized medicine and public health  
  • Pharmacotyping
  • Medicine in the year 2025  
  • Concluding remarks about the future of personalized medicine

12. Ethical, Legal and Regulatory Aspects of Personalized Medicine 

  • Introduction to ethical issues  
  • Ethical issues of pharmacogenetics  
  • Ethical aspects of genetic information 
  • Ethical issues of whole genome analysis  
  • Privacy issues in personalized medicine 
  • Genetic Information Nondiscrimination Act in the US
  • UNESCO and ethical aspects of personalized medicine 
  • Genotype-specific clinical trials
  • Ethical issues in the use of digital technologies for personalized medicine 
  • Social issues in personalized medicine  
  • Race and personalized medicine 
  • Legal issues of personalized medicine
  • Gene patents and personalized medicine
  • Regulatory aspects  
  • FDA and personalized medicine 
  • FDA and molecular diagnostics in relation to personalized medicine
  • CLSI guideline for the use of RNA controls in gene expression assays
  • Evaluation of companion diagnostics/therapeutic
  • FDA oversight of laboratory developed tests 
  • FDA guidelines for the role of IVD in personalized medicine  
  • FDA oversight of NGS for diagnosis in personalized medicine
  • FDA’s Clinical Databases Guidance
  • Analytical Validation Guidance  
  • IVD device and drug co-development
  • FDA guidelines for personalized oncology 
  • Regulatory aspects of pharmacogenetics
  • Regulation of direct-to-consumer genetic testing
  • Need for regulatory oversight of DTC
  • FDA and pharmacogenomics
  • FDA guidance for pharmacogenomic data submissions
  • Joint guidelines of the FDA and EU regulators for pharmacogenomics
  • Pharmacogenomic (PGx) information in drug labels
  • FDA guidelines for pharmacogenomics-based dosing 
  • FDA and validation of biomarkers  
  • FDA and predictive medicine

13. Markets for Personalized Medicine  

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

14. Companies Involved in Developing Personalized Medicine  

  • Introduction  
  • Profiles  
  • Collaborations

15. References

Tables 
Table 11-1: Bayesian versus frequentist approaches in clinical trials  
Table 11-2: Players in the development of personalized medicine  
Table 11-3: Members of the Personalized Medicine Coalition
Table 11-4: Biobanks relevant to personalized medicine 
Table 11-5: Role of bioinformatics in the development of personalized medicine  
Table 11-6: Advantages of personalized medicine for the biopharmaceutical industry 
Table 11-7: Advantages of personalized medicine for the patients
Table 11-8: Advantage of personalized medicine for the physicians
Table 11-9: Advantage of personalized medicine for the healthcare providers
Table 11-10: Limitations of personalized medicine 
Table 11-11: Recommendations of the Association for Molecular Pathology on incidental findings  
Table 11-12: Methods of translational science that are relevant to personalized medicine 
Table 11-13: Companies involved in predictive healthcare
Table 11-14: Delivery for precision medicine 
Table 12-1: Drugs with pharmacogenomic information in their labels 
Table 13-1: Drivers for the development of personalized medicine 
Table 13-2: Growth of markets relevant to personalized medicine 2020-2030 
Table 13-3: Markets for personalized medicine according to therapeutic area 2020-2030
Table 13-4: Markets for personalized medicine in major regions 2020-2030  
Table 13-5: Lack of efficacy in current therapy  
Table 13-6: Impact of personalized medicine on other industries
Table 13-7: Strategies to develop personalized medicine
Table 13-8: Role of the Internet in the development of personalized medicine
Table 14-1: Top five pharmaceutical companies involved in personalized medicine
Table 14-2: Selected collaborations of companies in personalized medicine 

Figures
Figure 13-1: Cost of sequencing per genome
Figure 13-2: Evolution of personalized medicine as a market driver

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