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AIQ’s medical device technology platform, driven by artificial intelligence, revolutionizes the evaluation of treatment response in patients with complex diseases. This technology allows researchers to better understand disease and clinicians to more effectively manage patients, ultimately helping improve patient outcomes and reduce healthcare system costs.
Understand and target treatment resistance, which drives therapy outcomes.
Unique information provided at the right time to support treatment decisions.
Avoid unnecessary costs associated with
ineffective patient therapies.
The scientific community has long appreciated the impact of heterogeneity of treatment response between patients: not all patients respond the same to a given therapy. However, heterogeneity of treatment response within an individual patient, intra-patient heterogeneity, is under-recognized. This intra-patient heterogeneity of treatment response can be spatial—treatment response that differs by anatomical location—and/or temporal—treatment response that changes over time. A 2017 multi-site study demonstrated a high degree of intra-patient treatment response heterogeneity, as shown in the figure within this section. The percentage of lesions that are responding, stable, and resistant varies considerably within each patient, as do the relative percentages among patients.
Using AIQ's technology, a 2017 multi-site clinical study found that treatment response, calculated as functional burden for each individual lesion, proved the highest single predictor for Progression-Free Survival (PFS). In addition, the changes in functional burden showed stronger correlation to PFS than did the change in number of lesions.
Further analysis using AIQ's technology, demonstrates how intra-patient treatment response heterogeneity drives clinical outcomes. The graphs on the left show that a very small fraction of resistant lesions strongly correlates with negative clinical outcomes. Specifically, the analysis found that patients with more than 31% of lesions classified as responding had longer PFS time, however, patients with only 5% or more of their lesions classified as resistant had shorter PFS time.
Although response improves benefit, overall outcome is predominantly driven by resistance. A focus on minimizing treatment resistance would then help optimize overall patient outcome. Only by quantifying treatment response for each individual lesion, can the clinician or researcher identify and understand treatment resistance.
The AIQ medical device technology platform, developed by experts in oncology, medical physics, and clinical research, was created to address how intra-patient heterogeneity of treatment response impacts patient outcomes. AIQ delivers informative data no other company can, so that better decisions can be made for patients and for clinical studies. AIQ delivers a three dimensional, quantitative spatiotemporal treatment response assessment for every lesion within each patient. These response assessments provide actionable information to help understand how the treatment is working, to help optimize therapy and to improve patient outcomes.
Learn more about how AIQ delivers Actionable Intelligence to our customers.
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This document contains claims that have not been reviewed by the FDA. For information about applications in commercial distribution for patient management, see www.aiq-solutions.com/customers/hospitals
