| description abstract | New approach methodologies, nonanimal methods, and novel alternative methods are all used to define the acronym for NAMs. While there may not be consensus on the words that made the acronym, there is certainly consensus on what NAMs can accomplish. Namely, that they can help reduce, refine, or replace animal models used in research. These “3R's” of NAMs are at the heart of this Special Issue.NAMs have been thrust into the national spotlight recently as minimizing the use of animals in research has become a priority of funding and regulatory agencies [1,2]. The push toward innovation in this space is obvious from new funding opportunities [3] and the promise of a forthcoming office at the NIH [4], and attention from the National Academies [5].Biomechanical engineering as a discipline was built on animal models, from foundational studies in the composition of tendons [6] to modern-day use of animal models to evaluate bone healing or implant success. Alongside those animal models, our community has long pursued alternatives, from computational models that are now moving toward digital twins to mechanobiology studies that now use ex vivo tissue or engineered tissue constructs. These alternatives to animal models have been in our community all along; the papers in this Special Issue highlight connections between the tried-and-true work in biomechanical engineering and the 3R's of NAMs.We have deliberately taken a broad view of NAMs in this special issue by highlighting the vast efforts in musculoskeletal, neuronal, and cardiovascular systems. All work builds on foundational biomechanical engineering principles and has the potential to reduce, refine, or replace animal models in research.Toward NAMs of the skeletal system, Nguyen et al. [7] developed a finite element algorithm to simulate fatigue damage in metatarsals that closely predicts ex vivo values of bone stiffness and deformation. Similarly, Cameron et al. [8] demonstrate that patient-specific, finite element analysis using computed tomography (CT) images can predict fracture risk in benign knee tumors, potentially enabling individualized pre-operative planning for orthopedic surgery. For bone healing, Bahrami et al. [9] translated a finite element model for tibial fracture healing from sheep to humans using CT-based digital twins, enabling noninvasive assessment of callus biomechanics without direct human testing. In the analysis of bone microstructure, Cox et al. [10] introduced a metric of structural organization of plate-like and rod-like trabeculae to a finite element model to improve predictions of yield strain and provide insights into damage mechanisms. For future efforts in mechanobiology, Meyer et al. [11] showed that endothelin-1 inhibits bone adaptation to mechanical load in ex vivo human trabecular samples.Toward connective tissue NAMs, Almeida and Middendorf [12] conducted multi-axial compressive–tensile tests on annulus fibrosus and showed that incorporating fiber reorientation and interlamellar interactions greatly improves constitutive model accuracy for spine biomechanics. In a departure from animal models, Frantz et al. [13] used digital image correlation of cadaver tissue to spatially map the strains in the tendon at the rotator cuff to examine how shoulder muscles transmit forces directly through the shoulder. To further reduce the reliance on animal models, Stephenson et al. [14] developed a scaffold-free engineered tissue using stem cells and myoblasts to study early tendon–muscle formation under biochemical and mechanical cues.For the neuronal system NAMs, Zhao and Ji [15] enhanced a deep learning surrogate of a validated finite element brain model to rapidly predict individualized head impact strains, bridging macroscale tissue deformation and microscale axonal injury modeling while reducing reliance on animal or human testing for biomechanical applications.Relevant to NAMs for the cardiovascular system, Bahmani et al. [16] developed a patient-specific computational fluid dynamics model of the pulmonary artery using MRI data to characterize hemodynamics in pulmonary hypertension, demonstrating the potential of NAMs to reduce animal testing and enable personalized cardiovascular insights. For the ventricles of the heart, Li et al. [17] used a patient-specific biventricular finite element model to compare different modes of external, artificial loads to assist the pumping function of the heart. At the cellular level, Telle et al. [18] used a spatial computational model to investigate how cardiac fibrosis affects active and passive biomechanics of myocardial tissue, which could be adapted to physiologically relevant models of the whole heart. Potter et al. [19] developed a 3D engineered heart tissue platform that mimics the heterogeneous mechanical environment of the myocardium after an infarct, enabling in vitro studies of myocardial remodeling and therapeutic screening while reducing reliance on animal models. Finally, Goldstein et al. [20] created CRISPR-edited engineered heart tissues lacking dystrophin to model cardiomyopathy related to Duchenne muscular dystrophy, revealing impaired contractility, altered calcium handling, and structural changes, providing a human-relevant platform for mechanistic studies and therapeutic testing that has the potential to replace the reliance on animal models for this disease.Taken together, this collection of work illustrates how biomechanical engineering research is poised to lead the societal push to reduce, refine, and replace animals in research. All papers in this issue explicitly address their relevance to the 3R's, which we hope will catalyze discussion within our community. This collection of papers sets the stage for our community to consider the use of animal models in research alongside these emerging technologies, and to choose the best model for the research question.Generating dialogue around NAMs in biomechanical engineering was our goal when pursuing this special issue. To help us all continue the conversation, we are delighted to provide an interactive crossword puzzle about NAMs, artfully crafted by former JBME co-editor Victor Barocas (Fig. 1). The solutions are available as Supplemental Materials on the ASME Digital Collection. We hope that you will share it with your colleagues and students as appropriate, and join us in recognizing all of the NAMs work that has been in our community all along.We close with many thanks. To our fearless editors, Vicky Nguyen and Ross Ethier, for having the foresight to agree that the topic of NAMs merited a Special Issue. This issue would not have been possible without the outstanding scientific contributions from our community, including those who submitted papers and those who joined the dialogue as reviewers. And of course, we give thanks to Victor Barocas for his eagerness to merge his passion and acumen for creating crosswords with the theme of NAMs. The science in this Special Issue is so exciting that it kept us encouraged and motivated through some trying times. It is our hope that these connections around NAMs continue to grow this work in our biomechanical engineering community. | |
