麻豆传媒

In developing therapeutic agents for COVID-19, researchers learned from the lessons of past viruses, from HIV to Ebola to even flu, experts at an NIH webinar said.

Clinical agents in development for SARS-CoV-2 include antivirals and host targeted/immunomodulators, as well as neutralizing monoclonal antibodies. And randomized trials are still the best way to determine whether they work, experts said.

The (ACTIV) series of trials are public-private partnerships. ACTIV-1 studies host-targeted immune modulators, ACTIV-2 and ACTIV-3 concentrates on neutralizing antibodies and oral antivirals, ACTIV-4 targets anticoagulants and antiplatelet drugs, and ACTIV-5 (the "Big Effect Trial"), a phase II proof of concept study looks at "multiple promising treatments."

But antivirals are still desperately needed, as only remdesivir (Veklury) has been approved by the FDA to treat COVID-19.

Anthony Fauci, MD, director of the National Institute of Allergy and Infectious Diseases (NIAID), discussed prior experience in studying the replication cycle for the HIV virus. He added that discovering "all vulnerable points of intervention" eventually led to a host of antiretroviral therapies against the disease, including nucleoside/nucleotide reverse transcriptase inhibitors, non-nucleoside reverse transcriptase inhibitors, and integrase inhibitors.

While acknowledging that chronic HIV infection was different from acute infection with SARS-CoV-2, he said the replication cycle was comparable and each virus can "provide vulnerable targets in the replication cycle" for which to develop drugs.

Fauci also reviewed the "windows of opportunity" to treat SARS-CoV-2, noting that treatment appears most effective during a patient's pre-symptomatic period.

"A lot of emphasis has been put on monoclonal antibodies, which are in various levels of clinical trials," he said.

NIH researchers gave an overview of SARS-CoV-2 antibody trials currently in progress, noting that both the cocktails from Eli Lilly and Regeneron have shown effectiveness in treating viral load and symptoms in non-hospitalized patients. While Regeneron's product trended towards reducing medical visits, Eli Lilly's product was unlikely to help hospitalized COVID-19 patients recover from this advanced stage of their disease. Eli Lilly that its monoclonal antibody trial was on hold.

Fauci also emphasized the importance of conducting randomized clinical trials during COVID-19, saying "the core principles of science and ethics in conducting research during an epidemic does not change."

"This was shown very clearly during the Ebola outbreak in Africa with the PALM trial, which examined several Ebola therapies," he said. Among these were Regeneron's recently approved monoclonal antibody cocktail, and the then-investigational antiviral remdesivir.

Hilary Marston, MD, also of NIAID, also noted the importance of generating data in clinical trials during outbreaks, noting that researchers have made "significant strides in this area."

"It's not only ethical, but preferable to conduct randomized trials in the midst of outbreaks," Marston said.

She explained that at the beginning of outbreaks, researchers generally start with non-specific treatments like interferon, "but as we go on, we have things far more targeted."

"It's helpful to have adaptive designs into which we can feed additional agents as the outbreak goes on," she said, adding that it "gives us the most interpretable evidence about safety and efficacy of drugs in order to benefit patients of the future."

Indeed, this approach seems fairly new, as it was not generally used in the 2009 H1N1 influenza pandemic, said Frederick Hayden, MD, of the University of Virginia in Charlottesville.

"One of the problems of the 2009 pandemic response was that there were no robust clinical trials completed. We didn't learn anything new in terms of how to treat severe influenza infections," he said.

Hayden added that some efforts were put in place, but there were practical problems, such as that the researchers were unable to enroll sufficient numbers of subjects.

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