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Covid-19 Is derailing cancer clinical trials. Is new technology required to get them back on track?

It is time to make it our collective mission to bring data automation to patient recruiting for clinical trials and not wait for a resolution of the pandemic to manage clinical trial disruption.

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The coronavirus pandemic has affected every aspect of American healthcare. Some have postponed medical, dental or vision appointments for themselves or family members out of fear of contracting the virus. Many providers have deferred nonessential visits to slow the pandemic’s spread and keep critical staff available to treat patients with Covid-19.

The clinical trial cycle is also experiencing significant disruption. One leading oncology practice publication notes that new cancer diagnoses are down 37% since the pandemic began, and IQVIA data shows that “22 million people postponed cancer screening tests and 80,000 patients delayed or missed diagnoses.” (Editor’s Note: IQVIA is an investor in Inteliquet).

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A Deep-dive Into Specialty Pharma

A specialty drug is a class of prescription medications used to treat complex, chronic or rare medical conditions. Although this classification was originally intended to define the treatment of rare, also termed “orphan” diseases, affecting fewer than 200,000 people in the US, more recently, specialty drugs have emerged as the cornerstone of treatment for chronic and complex diseases such as cancer, autoimmune conditions, diabetes, hepatitis C, and HIV/AIDS.

How do we ensure that the right patient can still access the right drug at the right time, at a time when many oncology clinical trials which would provide a much-needed treatment option have been delayed?

A Cancer Diagnosis Has Never Been More Terrifying
Even if the prognosis is excellent, the specter of Covid-19 looms over the decision-making process for patients and their families. Nevertheless, they still deserve as many options as possible for their care. In some cases, clinical trials are the only way to deliver cutting-edge medicine that offers hope for extended lives, and even survival. The backlog of needy patients is a serious concern.

Not surprisingly, we have seen a return to the older standard of cancer care as opposed to targeted therapies. Even before the coronavirus pandemic, the work of clinical trial patient matching at cancer centers has been a complex, manual and labor-intensive process. In fact, the leading cause of missed clinical trial deadlines is the patient recruitment process, with patient enrollment being the most time-consuming aspect, taking up an estimated 30% of the clinical timeline. Pre-pandemic, only three to five percent of oncology patients took part in clinical trials. Under the best of conditions, this is simply not enough.

Patient Recruitment Through Electronic Medical File (EMR) Interrogation — Effective, But Challenging
The implementation of automatic EMR screening can efficiently boost clinical trial recruitment, but only 60 percent of the data needed to match patients to an oncology clinical trial is found in EMRs. As much as 80 percent of that data is unstructured, including notes, lab reports, images and files. Manual assessment of patient feasibility can delay or even curtail patient enrollment.

Data around diagnostics, biomarkers, and genomic sequencing holds the key to improving the practice of oncology through more targeted therapies. Technology can help tap the vast amount of data available on individual patients that already exists. Technical tools like AI, algorithms, natural language processing can help find a more complete match between researchers’ needs and potential patient candidates. Additionally, technology and clinical collaboration can help researchers reach patients from broad geographies and diverse origins and backgrounds, fulfilling important criteria for ethical research.

Reaching patients beyond a consortium of facilities who might benefit from a clinical trial is a strength of using new technologies. Understanding patient populations also better allows sponsors to reprioritize their pipelines and figure out which trials they stop or restart. Some have been on top of the modification to a virtual or hybrid model, and others have not, so we have an interesting degree of flexibility right now.

An Unexpected Crisis Spurs Changes
Before the pandemic, adopting new technology and digital health solutions may not have been determined “mission-critical.” Covid-19 changed everything. We’re finding cancer centers using screening and matching tools have doubled down on automating patient identification and are continuing to match patients to trials—some more effectively than ever before.

Consider one small community oncology center in a clinical research consortium. When the coronavirus pandemic hit, the center adjusted quickly by implementing a clinical trial software platform. From March to June 2020, the center enrolled three times as many patients in clinical trials as it had using traditional methods during the previous five months.

Cancer Isn’t Waiting for a Resolution to the Pandemic
It is time to make it our collective mission to bring data automation to patient recruiting for clinical trials. Thanks to better data analytics and clinical support, it is currently possible to make connections between researchers and patients in less than 24 hours. The ability to quickly and efficiently match patients to clinical trials gives physicians, patients and their families what they want and need — more treatment options, and more hope.

Photo: FotografiaBasica, Getty Images


Marie E. Lamont is President and COO of Inteliquet, a patient matching software company for clinical trials. Before Inteliquet, Lamont was President of the patient services business unit of Dohmen Life Science Services, and previous to this global head of business strategy and commercial operations for rare diseases at Genzyme.

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