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Early Stage Drug Safety Strategies and Risk Management: Maximizing Opportunities Towards Achieving Clinical Success
Description:
Declining industrial productivity has forced companies to urgently address the areas of drug development that are most likely to lead to the failure of a new compound. Innovations are required that can support the earlier termination of drugs which will be toxic in humans and cause rare events that are unlikely to be identified in clinical trials. Major pharma companies have subsequently begun to implement an array of new technologies for drug safety prediction into the discovery phases of research.
‘Early Stage Drug Safety Strategies and Risk Management’ is a report that identifies the new predictive technologies which can facilitate the earlier termination of potentially unsuccessful compounds. Emerging approaches in key areas such as hepatotoxicity, nephrotoxicity and cardiotoxicity are examined, and the collaborative efforts of academia and technology developers in driving the discovery of safety predictive methods and biomarkers are reviewed. This report evaluates the latest innovative predictive technologies being introduced into pre-clinical and early clinical development phases and also explores the potential cost savings and challenges associated with their implementation.
Key Findings
Future improvements in drug discovery will include the modelling of a wider range of toxicities, such as hepatotoxicity, and formations of reactive metabolites that might lead to idiosyncratic toxicity. Developments in high-throughput technologies, systems biology and bioinformatics have also enabled virtual modelling for whole organs.
High-content screening is increasingly important for identifying toxicity endpoints in a drug discovery setting. The methods use automated microscopy with image analysis to measure the effects of compounds on cell health. Improvements are required in the cell types used and the number of toxicity endpoints that can be studied reliably.
Novel in vivo models are now available including zebrafish screens, which are suited for use at the lead optimization stage or earlier. Humanized rodent models, in which key enzymes responsible for metabolism have been replaced by their human counterparts, may also be suitable for use in candidate selection.
Pharmacometric modeling and simulation and novel study methods such as adaptive designs are increasingly being applied in drug development to make the most of the data collected and to guide the choice of dose for clinical application.
Use this report to
-Assess key technologies for predicting drug safety in the earliest stages of discovery and clinical development with this report’s comprehensive analysis of emerging approaches across in silico, in vitro and in vivo preclinical technologies.
-Identify which companies are leading the field in safety prediction for new drugs, understand the strategic implementations for large pharma companies and examine the role of public-private consortia in solving key issues within this field of predictive safety.
-Discover the extent to which predictive safety technologies can provide potential cost savings and improvements in attrition rates and assess the challenges and risks associated with the implementation.
-Understand the latest strategies to improve safety evaluation in early clinical development with this report’s analysis of the latest approaches in exploratory and Phase I clinical trials.
Explore issues including
The impact of failure; Declining productivity in the pharma industry has intensified the need to create innovative solutions to reduce new compound failures. The current likelihood of a project progressing from Phase 1 to approval is roughly 20%, although in some therapeutic areas this may be as low as 8%.
The importance of collaboration; Sharing information and expertise across companies can drive the field forward in a way that is impossible for these organizations individually. Biomarker data from some of the major consortia has been submitted to regulators, and this represents significant progress, most notably within the field of renal toxicity.
Better predictive animal models; Rodent and non-rodent models used in drug development are expensive and the results do not always translate well to the human situations. A survey carried out in 1999 reported a true positive concordance rate between animal and human data of 71% for rodent and non-rodent species (63% for non-rodents and 43% for rodents alone).
The need for early assessment of key clinical attributes; Exploratory trials are particularly useful for gaining early insight into human ADME characteristics including mass balance, metabolite and absolute bioavailability parameters that would not traditionally be collected until Phase 2 or later. These studies use microdoses and can explore more candidates at a lower cost than a traditional ‘First in Man’ study.
Discover
-Which technologies are leading the way in predicting potential safety problems in the earliest stages of drug discovery and development as possible?
-What are the contributions of in silico, in vitro, and in vivo methods in the non-clinical stages of drug development?
-What are the goals of public-private consortia in driving the discovery of methods and biomarkers and how much have they achieved to date?
-How can the data collected in early human clinical trials be improved to better inform decision-making about potentially safe candidates?
‘Early Stage Drug Safety Strategies and Risk Management’ is a report that identifies the new predictive technologies which can facilitate the earlier termination of potentially unsuccessful compounds. Emerging approaches in key areas such as hepatotoxicity, nephrotoxicity and cardiotoxicity are examined, and the collaborative efforts of academia and technology developers in driving the discovery of safety predictive methods and biomarkers are reviewed. This report evaluates the latest innovative predictive technologies being introduced into pre-clinical and early clinical development phases and also explores the potential cost savings and challenges associated with their implementation.
Key Findings
Future improvements in drug discovery will include the modelling of a wider range of toxicities, such as hepatotoxicity, and formations of reactive metabolites that might lead to idiosyncratic toxicity. Developments in high-throughput technologies, systems biology and bioinformatics have also enabled virtual modelling for whole organs.
High-content screening is increasingly important for identifying toxicity endpoints in a drug discovery setting. The methods use automated microscopy with image analysis to measure the effects of compounds on cell health. Improvements are required in the cell types used and the number of toxicity endpoints that can be studied reliably.
Novel in vivo models are now available including zebrafish screens, which are suited for use at the lead optimization stage or earlier. Humanized rodent models, in which key enzymes responsible for metabolism have been replaced by their human counterparts, may also be suitable for use in candidate selection.
Pharmacometric modeling and simulation and novel study methods such as adaptive designs are increasingly being applied in drug development to make the most of the data collected and to guide the choice of dose for clinical application.
Use this report to
-Assess key technologies for predicting drug safety in the earliest stages of discovery and clinical development with this report’s comprehensive analysis of emerging approaches across in silico, in vitro and in vivo preclinical technologies.
-Identify which companies are leading the field in safety prediction for new drugs, understand the strategic implementations for large pharma companies and examine the role of public-private consortia in solving key issues within this field of predictive safety.
-Discover the extent to which predictive safety technologies can provide potential cost savings and improvements in attrition rates and assess the challenges and risks associated with the implementation.
-Understand the latest strategies to improve safety evaluation in early clinical development with this report’s analysis of the latest approaches in exploratory and Phase I clinical trials.
Explore issues including
The impact of failure; Declining productivity in the pharma industry has intensified the need to create innovative solutions to reduce new compound failures. The current likelihood of a project progressing from Phase 1 to approval is roughly 20%, although in some therapeutic areas this may be as low as 8%.
The importance of collaboration; Sharing information and expertise across companies can drive the field forward in a way that is impossible for these organizations individually. Biomarker data from some of the major consortia has been submitted to regulators, and this represents significant progress, most notably within the field of renal toxicity.
Better predictive animal models; Rodent and non-rodent models used in drug development are expensive and the results do not always translate well to the human situations. A survey carried out in 1999 reported a true positive concordance rate between animal and human data of 71% for rodent and non-rodent species (63% for non-rodents and 43% for rodents alone).
The need for early assessment of key clinical attributes; Exploratory trials are particularly useful for gaining early insight into human ADME characteristics including mass balance, metabolite and absolute bioavailability parameters that would not traditionally be collected until Phase 2 or later. These studies use microdoses and can explore more candidates at a lower cost than a traditional ‘First in Man’ study.
Discover
-Which technologies are leading the way in predicting potential safety problems in the earliest stages of drug discovery and development as possible?
-What are the contributions of in silico, in vitro, and in vivo methods in the non-clinical stages of drug development?
-What are the goals of public-private consortia in driving the discovery of methods and biomarkers and how much have they achieved to date?
-How can the data collected in early human clinical trials be improved to better inform decision-making about potentially safe candidates?
Contents:
Early Stage Drug Safety Strategies and Risk
Management: Maximizing opportunities towards achieving clinical success. Executive Summary
Introduction
Modeling and simulation in drug discovery
Novel in vitro technologies for predictive safety testing
Novel in vivo methods in for non-clinical safety assessment
Current initiatives in preclinical drug safety
Strategies to improve safety evaluation in early clinical development
Challenges and cost saving opportunities
Chapter 1 Introduction
Summary
State of the industry
Drug attrition
Innovation in drug safety
Report outline
Chapter 2 Modelling and simulation in drug discovery
Summary
Introduction
Molecular modeling
Structure-toxicity relationships
Epix Pharmaceuticals’ in silico discovery platform
Chemoinformatic methods
Collaborative projects
Biosimulation
Virtual models of whole organs
Conclusions
Chapter 3 Novel in vitro technologies for predictive safety testing
Summary
Introduction
Toxicogenomics and systems biology
Commercial platforms
Cell-based assays
Stem cells
Conclusions
Chapter 4 Novel in vivo methods in for nonclinical safety assessment 68
Summary
Introduction
Zebrafish
Whole animal imaging and microscopy
Humanized rodent models
Conclusions
Chapter 5 Current initiatives in preclinical drug safety
Summary
Introduction
The Predictive Safety Testing Consortium
The International Life Sciences – Health and Environmental Sciences
Institute
The InnoMed PredTox project
The Innovative Medicines Initiative
Additional consortia
The Chemical Effects in Biological Systems Database
The Japanese Toxicogenomics Project
Liver Toxicity Biomarker Study
Consortium for Metabonomic Toxicology
Other European funded initiatives
ACuteTox
Reprotec
Predictomics
CarcinoGenomics
Conclusions
Chapter 6 Strategies to improve safety evaluation in early clinical development
Summary
Introduction
Exploratory clinical trials
Other applications of AMS
Industry uptake
Regulatory status
The future for AMS-based studies
Technologies
Linking pharmacology data to microdose studies
Improving safety evaluation in Phase
Biomarkers in Phase 1 clinical trials
Pharmacogenomics and rare, idiosyncratic adverse events
Pharmacometrics – modeling and simulation to improve Phase 1 safety
Optimizing early clinical trial design
QT in Phase 1
The Thorough QT Study
Timing of the TQT study
Intensive QT studies in early Phase 1
Costs and decision making
Conclusions
Chapter 7 Challenges and cost saving opportunities
Summary
Introduction
Implementation of new technologies
New technologies, new risks
Qualifying biomarkers
Translational medicine
‘Fail early, fail often’
Conclusions
Chapter 8 Appendix
Primary research methodology
Acknowledgments
Index
Glossary
Glossary
Bibliography
Endnotes
List of Figures
Figure 1.1: Pharma industry productivity decline (1995-2007)
Figure 1.2: Reasons for drug attrition
Figure 1.3: The place of innovative safety evaluation strategies in drug discovery and development
Figure 1.4: Serious adverse events: research priorities
Figure 2.5: In silico methods contribute to the earliest stages of drug discovery
Figure 2.6: The Safety Intelligence Program from BioWisdom
Figure 2.7: Examples of assertions in the Safety Intelligence Program from BioWisdom
Figure 3.8: Novel in vitro methods and their use in drug discovery and development
Figure 3.9: A typical toxicogenomics workflow in the pharma industry
Figure 4.10: Novel in vivo methods and their use in drug discovery and development
Figure 4.11: Whole body microPET images through a rat showing 18F-FDG distribution
Figure 5.12: Study design and investigations used in the InnoMed PredTox project
Figure 6.13: The ‘learn and confirm’ model of drug development
Figure 6.14: The place of innovative technologies in early clinical safety assessment
Figure 6.15: Comparison of midazolam pharmacokinetics at microdose and therapeutic dose levels in the CREAM study
Figure 6.16: Proposed decision tree for integration of pharmacogenetic studies in early drug development
Figure 6.17: Information utilized in model-based drug development
Figure 6.18: Key attributes of a thorough QT study
Figure 7.19: Success rate improvements from increasing investment in technologies for early safety prediction 139
List of Table
Table 1.1: Failure rates at each stage of clinical drug development
Table 1.2: Drugs withdrawn from the market in the US between 1998 and April 2008
Table 3.3: Examples of companies providing platforms for toxicogenomics
Table 3.4: Examples of companies offering integrated software suites for the analysis of toxicogenomic data
Table 3.5: Examples of contract laboratories offering HCA cytotoxicity screening
Table 3.6: Examples of companies offering stem cells for toxicity testing
Table 4.7: Advantages and disadvantages of zebrafish for toxicity screening
Table 4.8: Companies offering zebrafish toxicity screening products and services
Table 4.9: Advantages of molecular imaging of whole animals for preclinical studies
Table 4.10: Manufacturers of molecular imaging equipment and probes
Table 4.11: Companies developing transgenic models for ADMET testing
Table 5.12: Biomarker candidates identified by the InnoMed PredTox project
Table 6.13: Companies offering AMS services
Table 6.14: Advantages and disadvantages of AMS-based microdosing studies
Table 6.15: Advantages and disadvantages of using AMS for mass balance and absolute bioavailability studies
Table 6.16: Core list of validated genomic biomarkers involved in ADME
Table 6.17: Examples of valid genomic biomarkers in drug labels
Table 6.18: Pharmacometric consultancies
Table 7.19: Definitions and examples of safety biomarkers with different levels of qualification
Table 7.20: Success rate improvements from increasing investment in technologies for early safety prediction
Table 7.21: Success rate improvements from increasing investment in technologies for early safety prediction
Management: Maximizing opportunities towards achieving clinical success. Executive Summary
Introduction
Modeling and simulation in drug discovery
Novel in vitro technologies for predictive safety testing
Novel in vivo methods in for non-clinical safety assessment
Current initiatives in preclinical drug safety
Strategies to improve safety evaluation in early clinical development
Challenges and cost saving opportunities
Chapter 1 Introduction
Summary
State of the industry
Drug attrition
Innovation in drug safety
Report outline
Chapter 2 Modelling and simulation in drug discovery
Summary
Introduction
Molecular modeling
Structure-toxicity relationships
Epix Pharmaceuticals’ in silico discovery platform
Chemoinformatic methods
Collaborative projects
Biosimulation
Virtual models of whole organs
Conclusions
Chapter 3 Novel in vitro technologies for predictive safety testing
Summary
Introduction
Toxicogenomics and systems biology
Commercial platforms
Cell-based assays
Stem cells
Conclusions
Chapter 4 Novel in vivo methods in for nonclinical safety assessment 68
Summary
Introduction
Zebrafish
Whole animal imaging and microscopy
Humanized rodent models
Conclusions
Chapter 5 Current initiatives in preclinical drug safety
Summary
Introduction
The Predictive Safety Testing Consortium
The International Life Sciences – Health and Environmental Sciences
Institute
The InnoMed PredTox project
The Innovative Medicines Initiative
Additional consortia
The Chemical Effects in Biological Systems Database
The Japanese Toxicogenomics Project
Liver Toxicity Biomarker Study
Consortium for Metabonomic Toxicology
Other European funded initiatives
ACuteTox
Reprotec
Predictomics
CarcinoGenomics
Conclusions
Chapter 6 Strategies to improve safety evaluation in early clinical development
Summary
Introduction
Exploratory clinical trials
Other applications of AMS
Industry uptake
Regulatory status
The future for AMS-based studies
Technologies
Linking pharmacology data to microdose studies
Improving safety evaluation in Phase
Biomarkers in Phase 1 clinical trials
Pharmacogenomics and rare, idiosyncratic adverse events
Pharmacometrics – modeling and simulation to improve Phase 1 safety
Optimizing early clinical trial design
QT in Phase 1
The Thorough QT Study
Timing of the TQT study
Intensive QT studies in early Phase 1
Costs and decision making
Conclusions
Chapter 7 Challenges and cost saving opportunities
Summary
Introduction
Implementation of new technologies
New technologies, new risks
Qualifying biomarkers
Translational medicine
‘Fail early, fail often’
Conclusions
Chapter 8 Appendix
Primary research methodology
Acknowledgments
Index
Glossary
Glossary
Bibliography
Endnotes
List of Figures
Figure 1.1: Pharma industry productivity decline (1995-2007)
Figure 1.2: Reasons for drug attrition
Figure 1.3: The place of innovative safety evaluation strategies in drug discovery and development
Figure 1.4: Serious adverse events: research priorities
Figure 2.5: In silico methods contribute to the earliest stages of drug discovery
Figure 2.6: The Safety Intelligence Program from BioWisdom
Figure 2.7: Examples of assertions in the Safety Intelligence Program from BioWisdom
Figure 3.8: Novel in vitro methods and their use in drug discovery and development
Figure 3.9: A typical toxicogenomics workflow in the pharma industry
Figure 4.10: Novel in vivo methods and their use in drug discovery and development
Figure 4.11: Whole body microPET images through a rat showing 18F-FDG distribution
Figure 5.12: Study design and investigations used in the InnoMed PredTox project
Figure 6.13: The ‘learn and confirm’ model of drug development
Figure 6.14: The place of innovative technologies in early clinical safety assessment
Figure 6.15: Comparison of midazolam pharmacokinetics at microdose and therapeutic dose levels in the CREAM study
Figure 6.16: Proposed decision tree for integration of pharmacogenetic studies in early drug development
Figure 6.17: Information utilized in model-based drug development
Figure 6.18: Key attributes of a thorough QT study
Figure 7.19: Success rate improvements from increasing investment in technologies for early safety prediction 139
List of Table
Table 1.1: Failure rates at each stage of clinical drug development
Table 1.2: Drugs withdrawn from the market in the US between 1998 and April 2008
Table 3.3: Examples of companies providing platforms for toxicogenomics
Table 3.4: Examples of companies offering integrated software suites for the analysis of toxicogenomic data
Table 3.5: Examples of contract laboratories offering HCA cytotoxicity screening
Table 3.6: Examples of companies offering stem cells for toxicity testing
Table 4.7: Advantages and disadvantages of zebrafish for toxicity screening
Table 4.8: Companies offering zebrafish toxicity screening products and services
Table 4.9: Advantages of molecular imaging of whole animals for preclinical studies
Table 4.10: Manufacturers of molecular imaging equipment and probes
Table 4.11: Companies developing transgenic models for ADMET testing
Table 5.12: Biomarker candidates identified by the InnoMed PredTox project
Table 6.13: Companies offering AMS services
Table 6.14: Advantages and disadvantages of AMS-based microdosing studies
Table 6.15: Advantages and disadvantages of using AMS for mass balance and absolute bioavailability studies
Table 6.16: Core list of validated genomic biomarkers involved in ADME
Table 6.17: Examples of valid genomic biomarkers in drug labels
Table 6.18: Pharmacometric consultancies
Table 7.19: Definitions and examples of safety biomarkers with different levels of qualification
Table 7.20: Success rate improvements from increasing investment in technologies for early safety prediction
Table 7.21: Success rate improvements from increasing investment in technologies for early safety prediction
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