The Problem

Healthcare has evolved from traditional medicine based on a patient’s symptoms, diagnosis and treatment, to a healthcare model called precision medicine, an innovative approach that uses a patient’s clinical data to deliver and monitor targeted and personalized treatment. Cancer care has also transitioned at a time of extraordinary innovation in drug development with an increasing cost burden. An essential key in the delivery of precision medicine is the ability to accurately assess therapeutic response to avoid the costs associated with ineffective treatments or prolonged toxicity exposure to sub-optimal therapy. Cancer treatment, including the costs associated with managing the side effects, contribute to the overall financial toxicity of the nation’s healthcare system.

Precision medicine requires precision imaging that provides quantitative information involving all disease sites. Cancer heterogeneity impacts the variability of therapeutic response and resistance. Just as not all patients respond the same to a given therapy, not all disease sites within a patient respond the same. Current methods used to assess treatment response are subjective, manual, select a limited number of lesions and often focus on the larger disease sites rather than a lesion by lesion response. Without an effective tool to better understand the heterogenic, lesion-specific metrics for each metastatic site during cancer therapy, it is a constant challenge for clinicians to effectively and optimally manage patient outcomes.  Empowering the cancer care team with timely and actionable intelligence could avoid continuing ineffective high-cost therapies, reduce toxicities including the costs to manage the toxicities and provide critical information to selectively add, subtract or discontinue ineffective treatment.

The Solution

For over two decades, AIQ co-founders, Glenn Liu, M.D., a medical oncologist and Robert Jeraj, Ph.D., a medical physicist combined research efforts and led the drug and imaging biomarker development at the University of Wisconsin-Madison. They understood the significant impact of heterogeneity on therapy resistance but lacked an established way to calculate a biomarker for assessing treatment response that could quantify the disease burden as well as quantify response for each disease site.  From 2009 to 2015, Dr. Liu and Dr.Jeraj leveraged $8M in funding to develop the response assessment technology, integrated today within AIQ’s products. In 2015, AIQ was incorporated and in 2017, signed an exclusive license agreement with the Wisconsin Alumni Research Foundation covering AIQ’s patents.

Today, AIQ has developed a medical device technology platform, based on advanced analytics, including artificial intelligence that automatically provides quantitative, lesion by lesion treatment response information.  

The Company

AIQ was founded and dedicated for the purpose of designing and developing medical device software platforms based on advanced analytics, to revolutionize the evaluation of treatment response in patients with complex diseases. AIQ generates and delivers Treatment Response Assessments to pharmaceutical and medical professionals seeking to understand how individual patients respond to clinical therapies. This proven technology leads to positive changes in prescribed therapies and better outcomes for patients. AIQ’s reports are powered by an FDA 510(k) cleared and patented software platform designed to measure and quantify total disease burden across time, leveraging artificial intelligence. With this innovative technology, AIQ provides clinicians with deeper knowledge in the treatment decision process.

Eric Horler is the president and chief executive officer of AIQ with 14 years of experience in medical product development, marketing, sales and management. He leads a team of experts in software engineering, research, marketing, business development, regulatory management and reimbursement strategies. AIQ is guided by a dedication to provide early, automated, quantitative, and actionable intelligence to assess treatment response and resistance to response, and offers the precision medicine community, a powerful tool in improving the management of patients, improving outcomes, and contributing to the reduction of healthcare costs.

Per the US FDA, AIQ technology is indicated for use in the identification, quantification, and evaluation of Regions of Interest (ROIs) from digital medical images, including PET and CT. Any other applications of AIQ technology are for research purposes only.