Pandemic has provided lessons on continuing research during a crisis

COVID-19 has been a tragic wrecking ball on several fronts, but something that isn’t mentioned much is clinical research.

Long a linchpin at CHOC and, moving forward, poised to become even more central as CHOC evolves into a leading pediatric health system, clinical research has had to quickly readjust under the strain of the pandemic.

But out of these dark days have emerged several lessons on not only how to continue research during a crisis, but how to keep it thriving.

That was a key message delivered by Phuong Dao, director of Research Operations at CHOC, during a recent webinar beamed around the country.

Phuong Dao, director of research operations at CHOC

“There’s a renewed sense of energy and purpose to use science to solve problems that are important to our patients and the public,” Phuong said during a panel discussion that was part of a two-week summit on rare diseases hosted by Global Genes, an Aliso Viejo-based non-profit that advocates for the rare disease community.

“I think we can really harness and leverage this shared renewed energy and translate that to the conducting of rare-disease trials,” Phuong said.

The panel, speaking on “Proactive Planning for Continuity of Research During a Crisis,” also featured moderator Nina Wachsman, founder and president of Augur Health, a New York-based clinical research recruitment firm, and Gerald Mosely, founder and principal of CP&P Development, a Sacramento-based specialty consulting firm focused on pharmaceutical sales and operations.

Wachsman laid out some realities hospitals face during COVID-19:

  • Less access to doctors and inpatient visits
  • Less interest in research into rare diseases
  • An explosion in telehealth visits
  • E-signatures for informed consent
  • Nurse home visits
  • Lab tests done remotely

As for clinical research, Wachsman said, challenges include a lack of available capital, a lack of access to enough clinical trial participants and the ability to retain them, and getting the attention of the FDA at a time when COVID-related studies dominate.

And in a world of virtual meetings, Mosely noted, effective teamwork can be a challenge.

“The people aspect is what can make or break things,” Mosely said. “Successful outcomes can be affected more by interpersonal than technical skills.”

But bright spots abound, Phuong said.

COVID-19 studies can serve as a template for clinical research well beyond the end of the pandemic. “We have seen study teams form quickly and multi-disciplinary teams mobilize,” she said.

The contracting and budgeting processes for COVID-19 studies have accelerated and teams involved in “master trial protocol” studies involving multiple hospitals have readily shared resources, when in the past there were more hurdles.

“This focus on leaner and faster clinical trials can be leveraged in the rare disease space as well,” Phuong said.

Other positive changes introduced during the pandemic that can affect all clinical trials moving forward include:

  • Fast tracking by the Institutional Review Board (IRB)
  • The acceptability, and patient popularity, of telehealth
  • Home-based testing and monitoring technologies
  • Curbside/courier pick-up and delivery of participant samples and investigational products
  • Digital data collecting tools
  • Remote Site Initiation Visits (SIVs) and monitoring
  • Less reliance of participants having to be on site

Phuong noted that clinical trials involving kids impact entire families, one of the things that makes pediatric research different from studies involving adults.

The consenting process is unique, she added, and some teenagers who still are minors sometimes have a different opinion from their parents when it comes to treatment plans.

Moving forward with telehealth, Phuong said, clinicians need to think about how to engage with study participants in the languages they understand best.

And there are other questions that need to be addressed, including:

  • How research should be structured to adapt to new realities
  • How to keep motivation high to conduct clinical studies into rare diseases
  • How virtual meetings and healthcare visits affect productivity

“I hope that we sustain the gains we have made to move toward more efficiently and that we are able to approach clinical research in ways that are more streamlined and modernized,” Phuong said.

To learn more about CHOC’s Research Institute, click here.

Artificial intelligence seen as critical tool in helping to diagnose rare diseases

Machine learning algorithms could make a dramatic difference when it comes to diagnosing children with rare diseases, two CHOC Children’s doctors said in a recent webinar.

Although the use of artificial intelligence (AI) in diagnosing medical conditions is in its infancy stages, the potential is huge, said Dr. Jose Abdenur and Dr. Terence Sanger, speaking on a panel during a two-week summit on rare diseases hosted by Global Genes, an Aliso Viejo-based non-profit that advocates for the rare disease community.

“Human decision making is very, very good,” said Dr. Sanger, vice president for research and chief scientific officer at CHOC. “But we’re not very good at incorporating tens of thousands of pieces of information into making these decisions.”

That’s where machine learning could be of immense value, he and Dr. Abdenur said in the one-hour discussion on Sept. 22, which can be viewed in its entirety here.

Machine learning involves the use of computer algorithms that improve automatically by building mathematical models based on reams of data. This makes AI particularly valuable for improving the rare disease diagnosis process, which remains far from perfect, says Abdenur, chief of the division of metabolic disorders at CHOC and director of CHOC’s metabolic laboratory.

Although great strides are being made in diagnosing rare diseases through such processes as rapid whole genome sequencing, 40 percent of families with sick children still do not have diagnoses, Dr. Abdenur said.

“We’re doing better, but we’re definitely not good enough,” he said. “We hope in the future that artificial intelligence and machine learning will help us (reach diagnoses faster).”

In diagnosing patients, clinicians consider a list of possible conditions or diseases that could be causing symptoms – what’s known as making a differential diagnosis. They consider such things as a patient’s symptoms, his or her medical history, basic lab results, and a physical examination.

With AI, a virtually limitless amount of information beyond that – such as similar symptoms that have occurred in patients around the world, the environment they live in, etc. – could be factored into helping make differential diagnoses.

Dr. Sanger compared the benefits of using AI in diagnosing patients to a standard camera – what’s used now – to a wide-angel lens that can take in much more information, which machine learning would provide.

“If you have an avalanche of information, (physicians) can’t take all of it in themselves,” Dr. Abdenur noted.

But a sophisticated machine-learning program could, he and other panelists said.

An algorithm that gets smarter over time would lead to faster, simpler, accurate, and earlier diagnoses, said panel member Annastasiah Mhaka, co-founder of the Alliance for AI in Healthcare.

“Data is at the heart of (learning more about rare childhood diseases), and AI would help along every step of the way,” said another panelist, Sebastien Lefebvre, an analyst with Alexion Pharmaceuticals.

Both Dr. Abdenur and Dr. Sanger agreed that AI could be used to augment a clinician’s decision, but never replace it.

“(AI) never makes a decision for you,” Sanger said. “It just assists in the decision making.”

Newly emerging technologies such as machine learning in healthcare could lead to lower healthcare costs and better treatment, Mhaka said.

“Diagnosis needs are huge and unmet in the (rare disease) population,” she noted.

Learn more about rare disease research at CHOC.