Preclinical Models: Innovative Solutions to Accelerate Drug Discovery and Development
Scripp Business Insights, February 2010, Pages: 131
Preclinical models are developed to test lead compounds for toxicity and efficacy. They are valuable tools to minimize development costs and reduce failures prior to commencement of human trials. Problems with traditional animal models such as cost, ethics, and suitability has prompted researchers to develop new models and systems to overcome such disadvantages. Alternative approaches include new vertebrate, nonvertebrate, computer-based and imaging models that offer new perspectives and utility to aid the drug discovery and development process.
This report explores novel preclinical models that show promise to expedite and improve the target validation and lead optimization timeline and discusses the various advantages and disadvantages of ADMET screening technologies to provide insight on which models or systems may enhance the R&D function of pharmaceutical and biotechnology organisations.
Additionally, the report provides an outlook for preclinical testing over the next decade and how pharmaceutical companies may need to adjust to new systems and models to improve their efficiencies. It uniquely focuses on more than 60 companies that are involved in using or developing ADMET technologies to advance preclinical research and provides an update on recent company activities and developments where new models and systems are employed to accelerate the discovery and development process.
Key features of this report
- Analysis of current developments in preclinical ADMET research for drug discovery and development
- Evaluation of the drivers behind innovation in preclinical research.
- Identifies the current trends in ADMET research and how technology companies are developing new models to improve and accelerate discovery and development.
- Analysis of current in-vivo, in-vitro, in-silico, and systems biology models that are advancing toxicity prediction in early drug discovery.
Scope of this report
- Understand the basis to ADMET testing and why it is a necessary and important component of preclinical research
- Up-to-date information on the preclinical models and systems currently used in drug discovery and development.
- Evaluation of the key recent developments and activities of companies who are developing and licensing new ADMET technologies.
- Identifies existing models and how new ones are being developed to improve productivity and knowledge.
Key Market Issues
- Established preclinical models correlate poorly with human in-vivo biological responses therefore innovation is needed to approximate more accurately the human response.
- Technology and software providers are developing novel models to expand the ADMET market in order to accelerate drug discovery and development.
- In-vivo, in-vitro, and in-silico models are increasingly becoming more sophisticated and a push for integration is creating demand for highly efficient centralized platforms to expedite predictive ADMET insight.
Key findings from this report
- Innovation in preclinical research is rapidly changing the landscape for ADMET testing and new models are accelerating decision-making in discovery and development.
- Novel in-vivo, in-vitro, in-silico and systems biology models are accelerating the discovery and development timeline for pharmaceutical companies.
- Demand to reduce in-vivo whole-organism ADMET testing has stimulated in-silico research but novel animal models and in-vitro screens will be needed to complement and correlate in-silico prediction.
- New vertebrate and invertebrate whole organism preclinical models include humanized rodents and zebrafish that provide disease-state environments, which better predict biological responses to investigational compounds.
Key questions answered
- What are preclinical models and how are they important to the pharmaceutical industry?
- What are the advantages and disadvantages of preclinical models in ADMET screening?
- What are the innovations in preclinical models?
- What are the trends in preclinical research?
- How are in-vivo, in-vitro, in-silico and systems biology models being developed for ADMET?
- How are companies building ADMET capabilities?
Preclinical models
Executive summary
Preclinical models in drug discovery and development
In vivo models in preclinical research
In vitro models in preclinical research
In silico models in preclinical research
Systems biology models in drug discovery
Chapter 1 Preclinical models in drug discovery and development
Summary
Introduction: importance of preclinical models for toxicity screening in drug development
Preclinical ADMET testing systems
The challenge: reducing drug attrition rates in preclinical screening
Importance of ADMET screening
Applying of ADMET to the drug discovery and development process
Importance of in vivo models
Established in vivo and in vitro ADMET tools to screen compounds
Toxicity and genotoxicity screening
Predicting toxicity with paracellular markers
In vitro ADMET screening in preclinical drug development
Advantages and disadvantages of conventional ADME screening tools in preclinical drug development
Oral absorption prediction
Metabolism prediction
In vivo ADMET animal models
Established ADMET study methods in animal models
Radiolabels
Cassette dosing
Semi-simultaneous dosing
Conclusion
Limitations of traditional in vitro and in vivo ADMET screening methods
New approaches to predict ADMET in preclinical development
Metabolomics
Advantages of metabolomics in drug discovery and development
Lead prioritization using metabolomics
Metabolomics and ADMET studies
Strengths and limitations of metabolomics for preclinical research
Metabolomics and “systems biology” – a unified approach to preclinical
ADMET screening
Company focus: Merrimack Pharmaceuticals
Other emergent technologies used in preclinical drug discovery and development
Nanotechnologies in preclinical studies
Novel imaging systems
Preclinical research and recent multinational pharmaceutical company activities
Bayer AG and Nimbus Biotechnology
Pfizer/Johnson and Johnson and WuXi Pharma Tech
Roche
Sanofi-Aventis
UCB Pharma
Chapter 2 In vivo models in preclinical research
Summary
Vertebrate animal models in preclinical discovery and development
Assessment of predictive value of animal models
Rodent models
The need for improved small animal models
Humanized rodent models
Advantages and disadvantages of zebrafish models in preclinical research
Recent progress with vertebrate models
ADMET screens and zebrafish models: company developments and technologies
Discovery Genomics
Evotec AG
Phylonix
Summit
ZF Biolabs
Zygogen
ADMET screens in rodent models: selected company developments and technologies
Lexicon Pharmaceuticals
Taconic
Xenogen’s (now part of Caliper)
Sigma-Aldrich
Invertebrate animal models in preclinical discovery and development
Drosophila melanogaster (fruit fly)
Aktogen
En Vivo Pharmaceuticals
Exelixis
Medros Pharmaceuticals
Caenorhadbitis elegans (nematode)
Novel in vivo/ex-vivo focus: Locusta migratoria (locust)
Chapter 3 In vitro models in preclinical research
Summary
Importance of in vitro models in preclinical toxicity testing
In vitro technologies for drug discovery and development
Recent company developments
Affymetrix
Beckman Coulter
Covance
Gene Logic
HemoGenix
Recent developments in drug transport and metabolism
Qualyst
Xenobiotic Laboratories
Progress in cell-based in vitro assays
Use of cultured cells for ADMET studies in preclinical research
In vitro distribution
In vitro solubility
In vitro ADMET assays and cell-type selection
Recent developments in cell-based platforms for preclinical drug screening
Cell-based assays and liver toxicity
Stem cells in drug discovery and development
Stem cells and ADMET in drug discovery and development
Novel in vitro technologies in preclinical research
Nanotechnologies and ADMET in drug discovery and development
Chapter 4 In silico models in preclinical research
Summary
In silico models in drug discovery and development
Molecular modeling in silico
Computer models to predict ADMET
Methodological approaches to in silico models
Recent commercial developments and activities
Accelrys
Advanced Chemistry Development
Aureus Pharma
Chemical Computing Group
Entelos
Gene Network Sciences
Leadscope
Life Technologies Corporation
Molecular Discovery
Molecular Networks
Noray Bioinformatics
Schrödinger
Simcyp
Simulations Plus
TerraBase
Tripos
Chapter 5 Systems biology models in drug discovery
Summary
Systems biology: integrative science for drug discovery
Predictive biosimulation platforms to aid preclinical research
Virtual organs and patients
Pathway biology systems: recent commercial developments and activities
Ariadne Genomics
GeneGo
Genomatix
Genstruct
Ingenuity Systems
Merrimack Pharmaceuticals
Physiomics
Considerations for preclinical models in drug discovery and development
Key points and recommendations
Appendix
Abbreviations and acronyms
Primary research methodology
References
Other sources
Index
List of Figures
Figure 1.1: Established preclinical ADMET systems and models for drug discovery and development
Figure 1.2: Common reasons for a drug candidate’s failure
Figure 1.3: Key advantages & disadvantages of animal models in preclinical drug development
Figure 1.4: Animal models (%) used in preclinical ADMET studies
Figure 2.5: Advantages and disadvantages of zebrafish for preclinical ADMET screening in drug discovery and development
Figure 2.6: Preclinical ADMET screen types offered by Evotec AG
Figure 2.7: Rationale for use of Drosophila as preclinical model for neurobiological disease
Figure 4.8: Factors limiting the use of in silico ADMET models
Figure 5.9: Drivers of systems biology in pharmaceutical R&D
List of Tables
Table 1.1: Routine screens to assess ADME of drug candidates in discovery
Table 2.2: Key advantages of Drosophila in preclinical drug discovery and development
Table 3.3: Commonly used cultured cells for in-vitro permeability assays
- Ariadne Genomics
- GeneGo
- Genomatix
- Genstruct
- Ingenuity Systems
- Merrimack Pharmaceuticals
- Physiomics
- Accelrys
- Advanced Chemistry Development
- Aureus Pharma
- Chemical Computing Group
- Entelos
- Gene Network Sciences
- Leadscope
- Life Technologies Corporation
- Molecular Discovery
- Molecular Networks
- Noray Bioinformatics
- Schrödinger
- Simcyp
- Simulations Plus
- TerraBase
- Tripos
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