Why Imaging Biomarkers Represent the Next Generation of Personalized Drug Development

By Rose Higgins

April 30, 2021 | Much of the healthcare industry is familiar with genetic biomarkers—which use molecular data to help predict certain health conditions—and have led to critical advances toward a new era of “personalized” medicine. These biomarkers can help frontline clinicians enhance patient care in ways that lead to preventive measures, such as predicting the likelihood of developing certain types of breast cancer, but they also hold benefits for life science organizations, such as helping to find the research study candidates who are most predisposed to success when given a particular therapy.

For example, drug developers may use biomarkers at the beginning of a clinical trial to narrow the field of patients to those most likely to benefit from that particular therapy, enabling them to save time in a trial’s early stages and reach Phase 3 with better chances of success.

Less appreciated in the industry is the role that imaging biomarkers, which are generated through the science of radiomics (think: advanced imaging analytics), are likely to play in the future of personalized drug development. Today, private industry and academia are collaborating on research to discover and develop new imaging biomarkers to add a new layer to the personalization of medicine. Prior to exploring what the future may hold for imaging biomarkers, it’s helpful to understand the basics of radiomics.

Radiomics 101: The quick version Traditionally, when viewing images of lesions or tumors, radiologists’ view has been restricted to only two dimensions: the long and short axes. Consequently, the primary method clinicians have employed to evaluate the progress of lesions was to measure the vertical and horizontal axes with digital calipers to discover any changes, an approach that unfortunately misses a significant amount of important information.

However, in reality, lesions and tumors possess multiple dimensions, in addition to numerous other structural and physical characteristics that define them. In particular, many different forms of cancer exhibit substantial structural differences that advanced medical imaging analytics are capable of noninvasively quantifying.

Radiomics, which leverages artificial intelligence to collect and quantify medical-imaging data, enables drug developers to discover patterns and similarities that would otherwise be unobtainable by profiling patients’ tumors and lesions across multiple dimensions.

Imaging Biomarkers Research: Two Overarching Goals

As a result of advanced imaging analytics data, radiomics researchers are today investigating at a deep level what is happening in the cellular structure of lesions and tumors. This research has two overarching goals.

First, researchers are endeavoring to identify the unique attributes of a tumor or lesion’s biology. Once this data has been obtained, researchers can identify patterns that may indicate how a patient will respond to a specific treatment. Though this data is challenging to develop, its impact is substantial.

Second, researchers are looking to find real-world imaging evidence that predictions and outcomes for certain diseases are tied directly to specific biomarkers. As more imaging biomarkers are identified, researchers will need to perform additional analytics to ascertain that the perceived relationship is true in all cases, as opposed to being coincidental or valid only under certain conditions.

Now, for a reality check: Reaching this point will not be simple and straightforward, but it will yield real benefits. Genetic biomarkers today offer a starting point for personalization by identifying patients more genetically predisposed to certain conditions. Imaging biomarkers can go a step further, indicating whether a recommended treatment is likely to generate the desired results.

Combined, radiomic and genomic biomarkers will deliver significant and positive changes related to how clinical trials are structured and managed. Coupled together, these two types of biomarkers will enable drug developers to substantially improve targeting of which patients to select to receive a specific treatment, saving time and money at each stage of a clinical trial.

A future of better personalization through radiomics is in sight: Now, it is simply a matter of where the research leads.


Rose Higgins serves as Chief Executive Officer of HealthMyne, a pioneer in applied radiomics, which is the cutting-edge field of extracting novel data and biomarkers from medical images. She can be reached at rose@healthmyne.com.

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