Quantitative image analysis provides confidence in drug development

By Samantha Black, PhD, ScienceBoard editor in chief

May 14, 2021 -- Clinical trials are increasingly dependent on sophisticated tools to help determine the physiological effects of various therapeutic candidates, understand the molecular underpinnings of human diseases, and decrease the number of patients needed in experimental designs. Olga Kubassova, PhD, CEO of Image Analysis Group, spoke with ScienceBoard.net about how computational analysis is improving clinical trial imaging.

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As part of her doctorate program in computer science, Kubassova worked on analyzing medical images, specifically magnetic resonance imaging (MRI) scans with rheumatoid arthritis and inflammatory diseases with a focus on determining which tissues are inflamed versus which are normal. By the end of her studies, she had developed a "book of algorithms" which included the quantitative methodologies for data analysis of the images she worked with. She used this information as the basis to start Image Analysis Group (IAG) to help translate real-world data into clinical practice and clinical trials.

During the discussion, Kubassova explained the importance of pairing the proper imaging modality (x-ray, histopathology, MRI, computed tomography, ultrasound, single-photon emission computed tomography, and positron emission tomography) with the appropriate therapeutic strategy in order to effectively assess the effect of a specific drug. In a clinical trial setting, quantitative imaging approaches can provide confirmation that the expected drug effects match the actual physiological effects.

With IAG's cloud-based technology platform, called Dynamika, researchers can track drug responses in different locations throughout the body and also over time. The company is focused in the inflammatory disease space, but is also exploring the use of quantitative imaging methodologies for oncology and neurology indications.

As more complex therapies are being developed, the research community needs to be sure that the strategy behind efficacy assessment of these therapies is the right strategy, Kubassova said. Quantitative analysis can provide an objective way to explain clinical trial data, she said.

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