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Digitizing the Oncology Specialty: Treatment

This is the second of a two-part series highlighting the impact of technology in the management and treatment of cancers. Part I looked at how technology is disrupting the diagnosis of cancers.


Management and Treatment


Cancer is a highly individualized disease. The more we can tease out from the interplay of genetics, environment, and other clinical factors, the better we can tailor our treatment strategies and the more confident we become in predicting how the disease course may progress in that specific individual.


The uncertainty that surrounds the diagnosis of cancer becomes magnified when it comes to management and treatment. We are now looking at using artificial intelligence (and other technologies) to support the patient throughout their healthcare journey, whereas in diagnostics, it was largely used to assist the clinician. Chemotherapy drugs not only involve convoluted regimens due to the erratic nature of cancer cells, but they are also notorious for their adverse effects. Disruption in this area by digital health should prioritize optimizing drug dosing, reducing unexpected adverse effects for patients or offering continual support for managing those adverse effects, and finally, decreasing disease burden for both patients and their caregivers.


We have made significant progress within the field of oncology. The attitude towards cancer has been shifted from largely a deadly diagnosis to a chronic condition. Affected patients are living longer, but that means as healthcare professionals, we need to ensure that the care continuum is, in fact, maintained for those patients. There is no doubt that we recognize this in the oncology field and that is why we have looked to using technology as a source of remote monitoring and support for our patients. Positive results have come from clinical trials exploring the influence of technology-based tools on symptom reduction, quality of life, likelihood of relapse, and other measures that are particularly important in cancer patients.


Let me highlight a few examples below.


In a multicentre, Phase III trial, based in France, patients with advanced-stage lung cancer were randomly assigned to weekly symptom monitoring by a web-based algorithm (experimental arm), or traditional follow-up with computed tomography (CT) scans at 3-6 months (control arm). The electronic follow-up application used in the experimental arm provided an individualized schedule for imaging based on each patient's unique symptoms. At the end of the study, these patients demonstrated an improved overall survival as a result of early relapse detection and better performance status at relapse. Not only that, but they also required fewer imaging tests for the duration of the study, which speaks to potential cost-savings in the long term.


The National University of Singapore and the University of California Los Angeles developed a machine learning application, called CURATE.AI, with a goal of optimizing drug dosages for cancer patients. It follows the patient’s response to drug doses over time and continually makes suggestions based on the data it receives. Recommendations would be made based on the application’s evaluation of the patient’s condition and biomarkers; the clinical team would subsequently either accept or override CURATE.AI’s recommendation based on their holistic overview of the patient. In one case, for example, CURATE.AI recommended a novel combination of enzalutamide and an investigational drug, ZEN-3694, to a patient with metastatic prostate cancer, which proved to be beneficial. This partnership between CURATE.AI and the healthcare team was tremendous and successfully interrupted disease progression of the cancer in this patient. Although these cases are currently far and few among oncology and medicine, they illustrate the value of marrying our clinical experience with the objective pattern recognition capabilities of technology.


Yet another move to improve treatment options in this field involves the transition from intravenous (IV) chemotherapy to oral chemotherapy, otherwise known as oncolytics. In 2017, 8 of the 14 new oncology drugs were oral therapies. The switch to oncolytics allows patients to stay in the comfort of their own homes, prevents risk of infection from an IV insertion, and eliminates the need for the patient to have to travel to a clinic to receive their medication, which often takes hours at a time once they are at the clinic!


What we have to keep in mind, however, is that while in most other cases, stepping down from IV to oral means simplifying the regimen, in oncology, the oral dosing regimen remains a challenge.


And this is where digital therapeutics comes in.


Proteus Digital Health is a company contributing to the Digital Therapeutics space; their Proteus Discover technology incorporates an ingestible sensor into oral medications, allowing for adherence to be tracked electronically. An example would be the Abilify MyCite, as mentioned in an earlier blogpost about Digital Therapeutics. Now, Proteus has collaborated with Fairview Health Services and the University of Minnesota Health System to trial its technology in chemotherapy medications, the first of which to be digitized is capecitabine, commonly used to treat breast and gastrointestinal cancers. Beyond monitoring adherence, this technology will enable the collection of data surrounding oncolytics, which Proteus has announced will be consolidated into an oral oncolytic medication registry.


Oncology is a demanding field of medicine to navigate, for both patients and their healthcare providers. As with all chronic conditions, beyond the physiological toll, there is an added emotional burden, that is often perceived to be much harder to overcome. I believe that technology plays a big role in easing some of the stress involved; whether it be through enhanced support in the form of symptom monitoring or giving patients the option to stay at home, these are non-trivial improvements that will make a true difference.


As Eric Topol mentions in his latest book, Deep Medicine, "As machines get smarter and take on suitable tasks, humans might actually find it easier to be more humane." Empathy and emotional intelligence have fallen by the wayside in this industry. We are all guilty of it. Maybe more important than anything else technology is capable of doing, it will help to restore humanity and caring to medicine.


Thanks for reading, as always!

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© 2020 by Christy Cheung
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