Strategies For Developing Biomarkers Using Preclinical Animal Models

There are several strategies that can be employed for the development of biomarkers using preclinical animal models. This often involves utilization of existing information about the pathogenesis of a given disease in relevant models. However, in most cases this requires basic research designed to understand what biomarkers correlate with the development of disease and if these biomarkers can be modulated by therapy in a meaningful way.

When considering animal models for biomarker development, it is important to distinguish between the types of models available. The best-case scenario is to utilize (or develop) a model that mimics the major and minor factors that drive the development of disease in humans. The identification of these factors as the cause of disease in these models allows for the ability to monitor and correlate them with disease severity. It then becomes important to determine if these factors respond to standard therapy known to reduce disease in humans. This is the best-case scenario moving forward if searching for new, improved therapeutic agents through head-to-head testing with standard therapies can be achieved.

However, it is most often the case that therapeutic agents are being developed for a disease for which there is no current treatment and/or there are no biomarkers of disease pathogenesis. In these situations, basic research is required for biomarker identification. The current approaches are varied and not uniform. Often, a good starting point for this initiative involves thorough research of the existing scientific literature to understand what serum or tissue factors are increased or decreased in patients who manifest disease and whether these factors are predictive of disease or disease severity. In addition, it is important to understand if these factors are a driving force in disease pathogenesis. If this is the case, these factors could be good candidates as useful biomarkers to monitor the efficacy of potential therapeutic agents.

As cited above, TNFa and IL-6 are cytokines that are generally increased in sera taken from patients with RA [4]. These peptides are proinflammatory cytokines that appear early in the cascade of cytokines that ultimately lead to joint inflammation and the pathogenesis of this disease. The ability of drugs known to have a therapeutic effect on RA to decrease the levels of these cytokines in preclinical animal models demonstrated their value as biomarkers for the testing of new therapies. This highlights the usefulness of identifying serum biomarkers that play a central role in the pathogenesis of disease, as their levels typically increase in a manner that correlates with disease progression.

In cases where there is no literature to support biomarker identification, the development of genomic and proteomic techniques has created the opportunity for de novo biomarker discovery. If good animal models are available, genome-wide microarray analysis of cells or tissues obtained during the onset or progression of disease could lead to the identification of genes that are up-or down- r egulated. These data need to be confirmed with additional pro-teomic studies to validate the potential role of the identified gene products, while additional structure-function studies in animal models need to be done to determine if these gene products correlate with disease progression and/or play a central role in disease pathogenesis. Finally, studies need to be performed to determine if these biomarkers respond to therapies known to affect the disease in animal models.

Once these basic research studies are performed in animal models, the identification of potential biomarkers needs to be validated in humans. This can be done in clinical trials in the patient target population using similar molecular techniques. The biomarkers selected need to be amenable to identification in easy-to-obtain clinical specimens such as serum or peripheral blood cells. However, once validated in humans, these biomarkers can serve as a very important tool in the value chain, leading to the testing and evaluation of novel therapeutic agents.

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