It isn’t often that People for the Ethical Treatment of Animals (PETA) offers praise for NIH. More typically, the organization accuses the agency of conducting or funding studies that “torment” animals; in the recent past, PETA branded former Director Francis Collins “an apologist” and “an animal experimentation enthusiast who oversaw a spending spree of nearly half the agency’s budget on archaic animal experiments.”
But last month, PETA offered its gratitude to NIH and new Director Monica Bertagnolli while taking some credit for the strategies developed over the past several years that she embraced, which are aimed at reducing animals used in research.[1] A working group reporting to the NIH Advisory Committee to the Director (ACD) studied rigor and reproducibility in animal research from 2019 to 2021; a second focused on strategies NIH could employ to catalyze the development and use of novel alternative methods (NAMs). In related news, NIH created a new NAMs program within the Common Fund, planned to be funded at $350 to $400 million over 10 years. This program, however, defines NAMs as “new approach methodologies.”[2]
After Bertagnolli’s announcement, Emily R. Trunnell, director of PETA’s Science Advancement and Outreach Division, said in a statement that NIH’s “plan to prioritize non-animal research methods could eventually save millions of lives—both human and animal. Scientists at PETA are relieved to see many of our recommendations reflected in the steps outlined by the director, and we look forward to seeing them speedily implemented.”[3]
On Feb. 1, Bertagnolli accepted the NAMs recommendations approved by the ACD at its December meeting.
“After careful review and consideration of the report, NIH accepts these recommendations and is committed to continuing its investment in building a robust suite of tools for researchers to study human biology and disease,” Bertagnolli said. “These recommendations build on an existing foundation of NIH investment in NAMs projects. This foundation includes complex lab-based systems like cells and tissues grown on chips and 3D cultures of cells that can replicate some features of organs.”
Bertagnolli noted that “computer and machine learning/AI models for neurodegenerative disease, wound healing, learning and behavior, SARS-CoV-2 propagation and many other conditions” are in use. NAMs include “biochemical screening and other assays such as those for skin irritation and eye toxicity.”
