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Using patient- relevant models to enhance cancer drug development
March 2011
by Sue Watson, PRECOS  |  Email the author

Cancer drugs entering into clinical trials must demonstrate safety, medical efficacy and be cost-effective. Although many new cancer drugs enter into clinical trials each year, the attrition rate is high due to preclinical models not accurately predicting efficacy and/or toxicity. According to a recent publication, 77 percent of 800 cancer drugs that entered into Phase I clinical trials between 1995 and 2007 failed to reach the market1. In the United States, only 8 percent of oncology drugs that entered into drug development between the early 1990s and mid-2000s received approval from the U.S. Food and Drug Administration (FDA)2.  
As a consequence, there is a growing need within the pharmaceutical and biotech industries for more "challenging" preclinical modeling for cancer drug development. It is essential to use patient- relevant models to evaluate the cancer medicines of the future in order to ensure that preclinical efficacy assessment is predictive of how the drug is likely to behave in clinical trials with cancer patients. This is particularly important as new molecular-targeted cancer drugs, with fewer potential side effects, are coming through the drug discovery pipeline.
Inefficient preclinical models  
Traditionally, most of the large pharmaceutical and biotech companies have used a limited and basic range of cancer models for the development of anti-cancer medications. The majority of these models are typically based on the use of animal cells or tissue, which in most cases are not relevant to the human situation. In general, oncology is one of the areas of drug development in which animal models are not very predictive of the true human pathophysiology.
For example, one modeling type that has been extensively used by many pharmaceutical companies is basic xenograft models, whereby a tumor cell line that may have little relevance to the patient's tumor is injected into a non-human model. This method is vulnerable to flaws due to the immunology of the non-human model not resembling the immunology of the human target and the artificial location of the tumor offering no real resemblance to what happens in man during disease progression.
These conventional models do not enable continuous measurement of response and are not capable of optimally modeling the biology of the cancer. As a consequence, these models cannot be used to effectively challenge new cancer drugs to the same degree as in the patient, resulting in a number of false positive drugs entering into clinical trials.
To facilitate effective cancer drug development, it is vital to maximize preclinical information and ensure that the drug is challenged in models reflective of the patient. In that way, it can be ensured that results are patient-relevant and thus meaningful.   New technology is now being developed in an attempt to create patient-relevant models to enable reliable preclinical efficacy assessment, thereby increasing drug development efficiency and reducing attrition rates.  
The advent of patient-relevant models  
Innovative new approaches have targeted the urgent requirement to improve the efficacy of cancer modeling by expanding the utility of reporter systems and applying them to complex multi-cellular in vitro- and in vivo-based systems.
An established approach is the development of cancer models from cells derived from patients' tumor tissue. This approach is being further developed by modeling the human tumor microenvironment in three-dimensional multicellular systems that challenge the new therapeutic entity to the greatest degree by incorporating relevant cell types, including those associated with the tumor stroma. This is opposed to evaluation in monolayer single cell cultures, which are standards within the pharma and biotech industries, and while predictive of the biology and mechanism of action, may not be as predictive of clinical efficacy. These 3D models with established human stromal epithelial interactions can then be transplanted in vivo.  
Real-time imaging of cell growth enables continuous temporal information from a single experimental model resulting in improved efficiency. In addition, lower costs are incurred due to more robust statistical analysis from fewer experimental repetitions. For example, optimal timing of drug administration can be determined based on the micro-environmental signals measured. The technology also limits the need for post-test procedures such as histology, and therefore reduced timeframes and costs. Use of medium-throughput, 3D in-vitro model screens may reduce the need for larger-scale in-vivo models, due to their capacity for modeling the tumor micro-environment more effectively—particularly in the discovery phase, potentially resulting in a more streamlined drug development process.
A second new approach allows the monitoring of the tumor microenvironment and biological changes within cells in real-time in the presence of a cancer drug. This approach is facilitated by the development of innovative new technology that involves bioluminescent/fluorescent biological reporters. These biological reporters are expressed in human cancer cells so that they emit light or fluorescence in response to different environmental stimuli. The reporters also emit light in response to changes and progression of the disease in response to drugs. For example, it is possible to monitor the presence of hypoxia (low oxygen levels) and blood vessel formation, as well as cell proliferation and cell death.
Additionally, this approach can be used to evaluate genes up-regulated in response to radiotherapy or similar insult, intra-cellular signaling activated by ligand binding to cell surface receptors, cells with cancer stem cell-like properties and that are undergoing epithelial/mesenchymal transition, a phenotype linked to cell invasion and metastasis. These reporter systems therefore cover a number of key tumor properties, including prediction of secondary spread and resistance to standard-of-care treatments. 

Both of these new approaches have been developed within an academic setting, ensuring that they remain "cutting-edge." Overall, they offer the unique advantage of reducing the need for additional monitoring and post-test procedures and the use of expensive supporting technology. In addition, these new approaches have the potential to ensure maximum data over a short timeframe with associated cost benefits.  
The outsourcing trend
Global sales of cancer drugs have been forecasted to grow at a compounded annual rate of 12 to 15 percent, reaching $75 billion to $80 billion by 2012, according to IMS Health3. Based on an estimated 18 percent of domestic sales spent on R&D4, the potential R&D spend on anti-cancer therapies is currently $7 billion, with approximately one quarter of this spend devoted to preclinical R&D ($1.75 billion). An estimated 25 percent of this is outsourced, with outsourcing predicted to expand significantly further by 2015.  
It is now becoming common practice to outsource the development of patient-relevant models to specialized service providers. Advantages of such outsourcing to specialist providers include time and cost efficiency in addition to independent validation of "in-house" data, which as a result generates a stronger preclinical package for regulatory submission by pharma and biotech organizations. Innovative technologies developed by specialist providers can quickly and cost-effectively be applied across all cancer types, benefiting the wider scientific community and vitally enabling new cancer drugs to reach patients sooner.  
Parting thoughts  
The need for patient-relevant models is driven by increasing regulatory and scientific rigor and the pressure to reduce ever-increasing cancer drug attrition rates and R&D costs through outsourcing, thereby identifying potential lead candidates as early as possible. New technology has been developed to create patient-relevant models specifically designed to fast-track new agents into the clinic. These innovative approaches are superior to traditional cancer preclinical models in that they provide maximum data over a short time frame together with associated cost benefits. The unique patient-relevant models closely reflect the patient's situation for each aspect of cancer progression encompassing pre-cancerous lesions, primary tumors and metastasis.
In an attempt to achieve time and cost efficiencies and facilitate regulatory approval of new drug candidates, large pharmaceutical and biotech companies are increasingly outsourcing the development and application of patient-relevant models to specialized service providers. These providers offer expert support to direct cancer drug development projects from concept to clinic, ensuring that preclinical efficacy assessment is predictive of how the drug is likely to behave in clinical trials with cancer patients.  
Sue Watson is principal founder and chief scientific officer at Preclinical Oncology Services (PRECOS), a preclinical research and development service provider with a specific focus on oncology, as well as head of preclinical oncology at the University of Nottingham. She has worked in the field of cancer pharmacology for 23 years with more than 85 peer-reviewed publications, and was awarded the National Research Medal from the British Society of Gastroenterology in 2002 for her contributions to gastrointestinal cancer research. Watson is currently part of a National Cancer Research Institute (NCRI) committee tasked with updating and rewriting national guidelines for in-vivo cancer research, and is a member of the Cancer Research UK discovery committee, the Yorkshire Cancer Research scientific committee and the European Association of Cancer Research Council. She is also part of the European Framework Programme (FP) 7 consortium tasked with deriving new cancer drugs from Chinese herbal medicines and is ethical advisor for a second cancer hypoxia-focused FP7 program on in-vivo research.

1. Fricker, et al. Lancet Oncology, 2008.
2. 2nd Annual Cancer Drug Discovery Symposium:
3. IMS Health Forecasts Continued Double-Digit Annual Growth of Cancer Therapeutics: Global Sales Expected to Exceed $75 Billion by 2012: vgnextoid=6e0f5e878e205210VgnVCM100000ed152ca2RCRD&vgnextchannel=41a67900b55a5110VgnVCM10000071812ca2RCRD&vgnextfmt=default 4. PhRMA news release, Jan. 22, 2004.  



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