Reproducibility of research in biophysics

Improving Replicability, Reproducibility, And Reliability In Preclinical Research: A Shared Responsibility

Reproducible and reliable scientific investigation depends on the identification and consideration of various intrinsic and extrinsic factors that may affect the model system used. The impact of these factors must be managed during all phases of a study: planning, execution, and reporting. The value of in vivo (animal) research has come under increasing scrutiny over the past decade because of multiple reports documenting poor translatability to human studies. These failures have been attributed to various causes, including poor study design and execution as well as deficiencies in reporting. It is important to recognize that achieving reproducible and reliable preclinical research results is a joint responsibility that requires a partnership between the investigative team and the animal care and use program staff. The myriad of intrinsic factors, such as species, strain/substrain, age, sex, physiologic and health status, and extrinsic factors, including temperature, humidity, lighting, housing system, and diet, need to be recognized and managed during study planning and execution, as they can influence animal physiology and biological response. Of equal importance is the need to document and report these details. The ARRIVE and PREPARE guidelines were developed by concerned scientists, veterinarians, statisticians, journal editors, and funding agencies to assist investigative teams and scientific journals manage and report on intrinsic and extrinsic factors to improve reproducibility and reliability. This issue of the ILAR Journal will focus on the various extrinsic factors that have been recognized to confound animal research.

Perspectives on Sharing Models and Related Resources in Computational Biomechanics Research

The role of computational modeling for biomechanics research and related clinical care will be increasingly prominent. The biomechanics community has been developing computational models routinely for exploration of the mechanics and mechanobiology of diverse biological structures. As a result, a large array of models, data, and discipline-specific simulation software has emerged to support endeavors in computational biomechanics. Sharing computational models and related data and simulation software has first become a utilitarian interest, and now, it is a necessity. Exchange of models, in support of knowledge exchange provided by scholarly publishing, has important implications. Specifically, model sharing can facilitate assessment of reproducibility in computational biomechanics and can provide an opportunity for repurposing and reuse, and a venue for medical training. The community's desire to investigate biological and biomechanical phenomena crossing multiple systems, scales, and physical domains, also motivates sharing of modeling resources as blending of models developed by domain experts will be a required step for comprehensive simulation studies as well as the enhancement of their rigor and reproducibility. The goal of this paper is to understand current perspectives in the biomechanics community for the sharing of computational models and related resources. Opinions on opportunities, challenges, and pathways to model sharing, particularly as part of the scholarly publishing workflow, were sought. A group of journal editors and a handful of investigators active in computational biomechanics were approached to collect short opinion pieces as a part of a larger effort of the IEEE EMBS Computational Biology and the Physiome Technical Committee to address model reproducibility through publications. A synthesis of these opinion pieces indicates that the community recognizes the necessity and usefulness of model sharing. There is a strong will to facilitate model sharing, and there are corresponding initiatives by the scientific journals. Outside the publishing enterprise, infrastructure to facilitate model sharing in biomechanics exists, and simulation software developers are interested in accommodating the community's needs for sharing of modeling resources. Encouragement for the use of standardized markups, concerns related to quality assurance, acknowledgement of increased burden, and importance of stewardship of resources are noted. In the short-term, it is advisable that the community builds upon recent strategies and experiments with new pathways for continued demonstration of model sharing, its promotion, and its utility. Nonetheless, the need for a long-term strategy to unify approaches in sharing computational models and related resources is acknowledged. Development of a sustainable platform supported by a culture of open model sharing will likely evolve through continued and inclusive discussions bringing all stakeholders at the table, e.g., by possibly establishing a consortium.

Reproducible Research Using Biomodels

Like other types of computational research, modeling and simulation of biological processes (biomodels) is still largely communicated without sufficient detail to allow independent reproduction of results. But reproducibility in this area of research could easily be achieved by making use of existing resources, such as supplying models in standard formats and depositing code, models, and results in public repositories.

Moving Toward Model Reproducibility and Reusability

This paper provides a brief history of the U.S. funding initiatives associated with promoting multiscale modeling of the physiome since 2003. An effort led in the United States is the Interagency Modeling and Analysis Group (IMAG) Multiscale Modeling (MSM) Consortium. Though IMAG and the MSM Consortium have generated much interest in developing MSM models of the physiome, challenges associated with model and data sharing in biomedical, biological, and behavioral systems still exist. Since 2013, the IEEE EMBS Technical Committee on Computational Biology and the Physiome (CBaP TC) has supported discussions on promoting model reproducibility through publications. This special issue on model sharing and reproducibility is a realization of the CBaP TC discussions. Though open questions remain on how we can further facilitate model reproducibility, accessibility, and reuse by the worldwide community for different biomedical domain applications, this special issue provides a unique demonstration of both the challenges and opportunities for publishing reproducible computational models.