Genomics in Drug Discovery and Development introduces readers to the biomarker, pharmacogenomic, pharmacogenetic, and toxicogenomic toolboxes, four promising and rapidly growing areas of genomics research that have begun opening the door to personalized medicine solutions. The authors thoroughly review and analyze all relevant technologies and analytical methods necessary for the competent design and execution of biomarker, pharmacogenomic, pharmacogenetic, and toxicogenomic studies. Moreover, by emphasizing the synergies among these areas, they arm pharmaceutical discovery scientists and drug development professionals with state–of–the–art strategies for reducing drug development time and costs, expediting a drug′s approval, and improving its life cycle. Academic researchers will find in this book authoritative and integrated coverage of these rapidly developing and popular areas of genomic research.
Readers involved in laboratory, clinical, or modeling studies who are seeking to assess the toxicity and efficacy of drug candidates as early as possible can rely on this book to help guide their experiments. Topics include:
Weighing the relative advantages and disadvantages of available genomic technology platforms
Using pharmacogenomics and pharmacogenetics to position drug studies in the context of clinical trials
Identifying and validating biomarkers
Predicting and characterizing the toxicity of drugs
Applying study findings to improve the productivity of drug discovery
Today′s pharmaceutical industry is characterized by exponentially rising R&D costs and a steadily decreasing percentage of approved drugs. Pharmaceutical discovery scientists therefore should take advantage of this book′s unique integrated coverage of biomarkers, toxicogenomics, and pharmacogenomics in order to make their own discovery efforts as fruitful as possible.
Chapter 1: Introduction: Genomics and Personalized Medicine (Dimitri Semizarov).
1.1. Fundamentals of genomics.
1.2. The concept of personalized medicine.
1.3. Genomics technologies in drug discovery.
1.4. Scope of this book.
Chapter 2: Genomics Technologies as Tools in Drug Discovery (Dimitri Semizarov).
2.1. Introduction to genomics technologies.
2.2. Gene expression microarrays: technology.
2.2.1. Standard microarray protocol.
2.2.2. Monitoring the quality of RNA for microarray experiments.
2.2.3. Specialized microarray protocols for archived and small samples.
2.2.4. Quality of microarray data and technical parameters of microarrays.
2.2.5. Reproducibility of expression microarrays and cross–platform comparisons.
2.2.6. Microarray databases and annotation of microarray data.
2.3. Gene expression microarrays: data analysis.
2.3.1. Identification of significant gene expression changes.
2.3.2. Sample classification and class prediction using expression microarrays.
2.3.3. Pathway analysis with gene expression microarrays.
2.3.4. Common problems affecting the validity of microarray studies.
2.4. Comparative genomic hybridization: technology.
2.5. Comparative genomic hybridization: data analysis.
2.6. Microarray–based DNA methylation profiling.
2.7. Microarray–based microRNA profiling.
2.8. Technical issues in genomics experiments and regulatory submissions of microarray data.
2.8.1. Study of a drug s mechanism of action by gene expression profiling.
2.8.2. Early assessment of drug toxicity in model systems.
2.8.3. Biomarker identification in discovery and early development.
2.8.4. Patient stratification in clinical trials using gene expression signatures.
2.8.5. Genotyping of patients in clinical studies to predict drug response.
Chapter 3: Genomic Biomarkers (Dimitri Semizarov).
3.1. Introduction into genomic biomarkers.
3.2. DNA biomarkers.
3.2.1. DNA copy number alterations.
220.127.116.11. DNA copy alterations in cancer.
18.104.22.168. DNA copy number alterations in other diseases.
22.214.171.124. Identification of DNA copy number biomarkers in drug discovery.
126.96.36.199. p53 mutations.
188.8.131.52. K–ras mutations.
184.108.40.206. EGFR mutations.
220.127.116.11. Bcr–abl and KIT mutations.
3.2.3. Epigenetic markers.
3.3. RNA biomarkers.
3.3.1. Gene expression biomarkers validated as diagnostic tests.
3.3.2. Other examples of gene expression biomarkers.
3.4. Clinical validation of genomic biomarkers.
Chapter 4: Fundamental Principles of Toxicogenomics (Eric Blomme).
4.2. Fundamentals of toxicogenomics.
4.2.1. Principle of toxicogenomics.
4.2.2. Technical reproducibility.
4.2.3. Biological reproducibility.
4.2.4. Species extrapolation.
4.3. Analysis of toxicogenomics data.
4.3.1. Compound–induced gene expression changes.
4.3.2. Visualization tools.
4.3.3. Class prediction.
4.3.4. Network and pathway analysis.
4.4. Practical and logistic aspects of toxicogenomics.
4.4.1. Species considerations.
4.4.2. Toxicogenomics studies.
18.104.22.168. Sample considerations.
22.214.171.124. Experimental design in toxicogenomics studies.
4.5. Toxicogenomics reference databases.
4.5.1. The utility of reference databases in toxicogenomics.
4.5.2. Design and development of toxicogenomics reference databases.
4.5.3. Existing toxicogenomics databases.
Chapter 5: Toxicogenomics: Applications to In Vivo Toxicology (Eric Blomme).
5.1. The value of toxicogenomics in drug discovery and development.
5.2. Basic principles of toxicology in drug discovery and development.
5.2.1. Preclinical safety assessment.
5.2.2. Discovery toxicology.
5.3. Toxicogenomics in predictive toxicology.
5.3.1. Prediction of hepatotoxicity.
5.3.2. Prediction of nephrotoxicity.
5.3.3. Prediction of in vivo carcinogenicity.
5.3.4. Gene expression–based biomarkers in other tissues and the promise of hemogenomics.
5.3.5. Integration of toxicogenomics in discovery toxicogology.
5.4. Toxicogenomics in mechanistic toxicology.
5.4.1. Toxicogenomics to investigate mechanisms of hepatotoxicity.
5.4.2. Intestinal toxicity and Notch signaling.
5.4.3. Cardiac toxicity.
5.4.4. Testicular toxicity.
5.5. Toxicogenomics and target–related toxicity.
5.5.1. Target expression in normal tissues.
5.5.2. Target modulation.
5.6. Predicting species–specific toxicity.
5.7. Evaluation of idiosyncratic toxicity with toxicogenomics.
Chapter 6: Toxicogenomics: Applications in In Vitro Systems (Eric Blomme).
6.1. Introductory remarks on in vitro toxicology.
6.2. Overview of the current approaches to in vitro toxicology.
6.3. Toxicogenomics in in vitro systems: technical considerations.
6.3.2. Genomic classifiers.
6.3.3. Testing concentrations.
6.3.4. Throughput and cost.
6.4. Proof–of–concept studies using primary rat hepatocytes.
6.5. Use of gene expression profiling to assess genotoxicity.
6.5.1. Toxicogenomics can differentiate genotoxic carcinogens from non–genotoxic carcinogens.
6.5.2. Toxicogenomics can differentiate DNA reactive from non–DNA reactive compounds positive in the in vitro mammalian cell–based genotoxicity assays.
6.5.3. Toxicogenomics assays may be less sensitive than the standard battery of in vitro genetic toxicity tests.
6.6. Application of gene expression profiling for the in vitro detection of phopholipidosis.
6.7. Toxicogenomics in the assessment of idiosyncratic hepatotoxicity.
6.8. Do peripheral blood mononuclear cells represent a useful alternative in vitro model?
6.9. Current and future use of in vitro toxicogenomics.
6.9.1 Improved gene expression platforms.
6.9.2. Standardization of protocols and experimental approaches.
6.9.3. Performance accuracy.
6.9.4. Battery of gene expression signatures.
6.9.5. Clear actionable data points.
Chapter 7: Germ Line Polymorphisms and Drug Response (Dimitri Semizarov).
7.1. Introduction into germline polymorphisms.
7.2. Polymorphisms and drug response in oncology.
7.2.1. UGT1A1 polymorphism and response to irinotecan.
7.2.2. FGFR4 polymorphism and response to chemotherapy.
7.2.3. Mdr–1 polymorphism and response to paclitaxel.
7.2.4. DPD polymorphisms and response to 5 –fluorouracil.
7.2.5. TPMT variants and response to thiopurines.
7.2.6. MTHFR polymorphisms and response to chemotherapy.
7.2.7. Tandem repeat polymorphisms in the TS gene and response to drugs targeting thymidylate synthase.
7.2.8. Use of cancer cell lines to identify predictive SNPs.
7.3. Polymorphisms and response to anticoagulants.
7.4. Polymorphisms in neuroscience.
7.5. Polymorphisms and drug response in immunology.
7.6. Polymorphisms and response to antiviral agents.
7.6.1. Anti–HIV drugs.
7.6.2. Interferon therapy in hepatitis B treatment.
7.7. Gene copy number polymorphisms.
7.8. Conclusions: approaches to identification of polymorphisms as predictors of drug response.
7.8.1. Candidate gene approach.
7.8.2. Genome–wide approach.
7.8.3. Pathway approach.
7.8.4. Use of model systems in the identification of predictive pharmacogenetic markers.
7.8.5. Comparison of the methodologies in the context of drug discovery.
Chapter 8: Pharmacogenetics of Drug Disposition (Anahita Bhathena).
8.2. Genes and polymorphisms affecting drug disposition.
8.2.1. Drug metabolizing enzymes.
8.2.2. Drug transport proteins.
8.3. Genomic biomarkers for PK studies.
8.4. Utility of PG––PK studies in early clinical trials.
8.5. Limitations of PG––PK studies.
8.6. Genotyping technologies.
Chapter 9: Overview of Regulatory Developments and Initiatives Related to the Use of Genomic Technologies in Drug Discovery and Development (Eric Blomme).
9.1. Introduction into recent regulatory developments in the genomic area.
9.2. FDA guidance on pharmacogenomic data submission.
9.2.1. Voluntary genomic data submission (VGDS).
9.2.2. Pharmacogenomic data submission.
9.2.3. International harmonization.
9.3. Pharmacogenomic data submission: draft companion guidance.
9.4. Drug–diagnostic co–development concept paper.
9.5. Regulations for in vitro diagnostic assays.
9.5.1. General overview of regulatory pathways for devices in the U.S.A.
9.5.2. Draft guidance for industry, clinical laboratories, and FDA staff on in vitro diagnostic multivariate index assays.
9.6. Biomarker qualification.
9.7. Current initiatives relevant to pharmacogenomics.
9.8. Future impact of genomic data on drug development.