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It is well established that personalized medicine can overcome some limitations of a one-size-fits-all approach to healthcare. In research and practice, personalized medicine is being increasingly utilized. For example, it is playing an increased role in efficacy studies for biomarker-driven therapies and informs treatment.

However, for the field to evolve further, the development of highly characterized pre-clinical models is essential in order to evaluate new targeted therapies and increase the scope of actionable mutations in the clinic. One such model, which helps bridge the preclinical research and the clinic, is the patient-derived xenografts (PDX) - where tissue from a patient's tumor is implanted into an immunodeficient or humanized mouse. 

Using PDX models in research means that mutations seen in the clinic can be factored into the discovery pipeline from the earliest phases of a research program, in the preclinical setting. Andrew Brown, Global Product Manager at Inotiv explains how this approach could transform the future of cancer treatments:

"PDX models allow us to work backwards from the clinic, so that development phases can target the mutations seen in patients. We can then go on to screen for those mutations in other patients, offering the opportunity to pair up an individual with the treatment that's been targeted to a true representation of their tumor."

How are PDX models generated, and why are they so different from traditional approaches?

Cancer research has traditionally been dependent on cell lines and later cell-derived xenografts (CDXs), the latter of which are developed by first expanding the tumor cells in-vitro. These methods have been the vanguards of preclinical drug development, and have greatly enhanced our knowledge of cancer biology. However, CDX models do not fully reflect the properties of human tumors, and therefore their use hasn't always translated into successful treatments. Viktoria Hyddmark, Senior Scientist at Inotiv, explains: 

"Growing cells on plastic petri dishes cause a host of oCF gene expression changes and selections in the cell population. This results in a loss of the heterogeneity that's present in patient tumors, and it's this heterogeneity that's critical for determining whether a particular patient is going to respond to a particular treatment."

As such, using tumor tissue from real patients, as in PDX models, allows researchers to recapitulate what is seen in the clinic (or in a clinical setting). Indeed, recent research from Inotiv demonstrates the potential for PDX models to change the standard of practice. Using models generated from Washington University, they were able to further show that PDX models selectively resistant to different doses of standard-of-care drugs, such as Palbociclib, can be generated. This gives a researcher unprecedented flexibility to compare the therapies in development - either alone or in combination with lower doses of available treatments - against the standard of care. 

How is the industry and scientific community working together to accelerate breakthroughs?

To ensure these powerful translational research tools can be widely utilized, Inotiv has partnered with Washington University to curate and license the Washington University Human in Mouse (WHIM) PDX collection and with Wistar Institute to license the Wistar Melanoma (WM) PDX collection. These collaborations mean that Inotiv offers a continuously growing resource for the research community. 

Andrew Brown explains why these partnerships between industry and academia are so important for ensuring that PDX models remain relevant to changing clinical needs: "As new standard-of-care and first-line drugs are developed and implemented, our collaboration with Washington University and the Wistar Institute means that our customers will have access to new tumor material that represents the changes seen in the ongoing treatment landscape."

In summary, PDX models are a game-changing innovation that will bring further personalized medicine to the treatment of patients. They faithfully recapitulate the complexity of tumor heterogeneity, which is a primary contributor to the currently high failure rate of therapeutics in oncology clinical studies. Inotiv's project managers are available to provide more information for researchers interested in using these models in their next preclinical cancer study. 

Please contact us to learn more about our PDX models and related services. 


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