The Quest for Clinically Translatable Data
Research Models
Dustin Grinnell

The Quest for Clinically Translatable Data

A major challenge in preclinical research is getting preclinical data that is translatable to the clinic. When deciding whether to take the expensive and long journey of bringing a drug to market, pharmaceutical companies are always looking to improve how they select, screen and characterize compounds in the drug development process. When used in a preclinical setting, imaging technologies such as Positron Emission Tomography (PET), Computer Tomography (CT), and Magnetic Resonance (MR) modalities are helping yield more clinically translatable data to speed drug development.

To track disease progression, many clinical trials now use image-based parameters as clinical endpoints, including anatomical (size), physiological (blood flow) and functional (tissue oxygenation). Cellular and molecular processes–such as cellular proliferation and metabolism–are assessed as well. These imaging data translate well between the preclinical testing of drugs and their clinical evaluation, helping pharmaceutical companies make more informed decisions about compounds in development.

With PET for example, tissue metabolism, inflammation and cellular proliferation can all be measured, particularly in tumors, where the technology can evaluate cancer therapies. CT on the other hand, provides high-resolution images of skeletal anatomy and can be used to assess bone remodeling and/or deterioration in animal models of arthritis, for example.

Combing imaging technologies in a single study has become more common as well, as the approach can generate a wide range of physiological and functional information simultaneously. PET and CT are often combined in such a way. And many imaging labs now use MRI and PET in tandem to generate multi-faceted datasets on a drug’s mechanism of action (e.g. MRI measures tumor vascularity and PET assesses metabolism). Data from this combination approach greatly enhances lead candidate selection in many cases.

The Many Applications of Magnetic Resonance

By providing anatomical and functional data on soft-tissues, Magnetic Resonance (MR) can be used to visualize structures within the body. And for those always on the search for clinically translatable data, MR and its many modalities can be particularly useful when used in a preclinical setting.

In general, MR imaging modalities can detect tissue function, molecular changes as well as energy metabolism. Dynamic contrast-enhanced (DCE) MRI, for instance, can assess blood flow and surface area within the body. Given the many therapies which affect or target the body’s vasculature, DCE MRI provides a clinically translatable method for determining blood vessel responses to drugs. With functional MRI (fMRI) and pharmacological MRI (phMRI), two haemodynamic MRI techniques, brain activation can be measured in response to sensory or drug initiated stimuli.

Functional defects can be evaluated via diffusion weighted MRI (DW-MRI), another MR modality. By mapping the distribution of water within tissues, DW-MRI can assess ischemic stroke and traumatic brain injury (e.g. cytotoxic edema) as well as tumor responses to therapeutics (by measuring tumor density). Diffusion studies can also be extended beyond conventional methods to assess the directionality of water diffusion, such as in conditions which affect the brain’s white matter.

MR spectroscopy (MRS) measures the levels of metabolites within tissues and can help reveal physiochemical and metabolic events often lurking behind disease. For example, MRS can measure choline, which when elevated, can be associated with cancers of the breast, prostate and brain. N-Acetyl Aspartate is another commonly studied metabolite, which can be used to evaluate neuronal cell death and dysfunction in many neurodegenerative diseases.

Making More Informed Decisions

The drug discovery and development process is long (approximately 12 years) and costly (about $800 million dollars). As such, that which can both shorten the time and financial investment in getting a drug to market will be valuable to pharmaceutical companies.

When used in the preclinical space, imaging technologies such as PET, CT and the various MR modalities can help drug developers evaluate compounds more effectively and make more informed decisions, thus increasing their candidates’ chances for breaking through in the clinical studies.

For this reason, we will likely see the increased use of such imaging technologies in preclinical settings, likely earlier in the process too. Imaging biomarkers and clinical trial endpoints will likely be refined as well. And more and more, imaging technologies like the ones described here will be used in combination–all in the name of getting more clinically translatable data to bridge the gap between preclinical and clinical research.