A tool for multi-scale modelling of the renal nephron

Reframing acute kidney injury as a pathophysiological continuum of disrupted renal excretory function

Surrogate measures of glomerular filtration rate (GFR) continue to serve as pivotal determinants of the incidence, severity, and management of acute kidney injury (AKI), as well as the primary reference point underpinning knowledge of its pathophysiology. However, several clinically important deficits in aspects of renal excretory function during AKI other than GFR decline, including acid-base regulation, electrolyte and water balance, and urinary concentrating capacity, can evade detection when diagnostic criteria are built around purely GFR-based assessments. The use of putative markers of tubular injury to detect "sub-clinical" AKI has been proposed to expand the definition and diagnostic criteria for AKI, but their diagnostic performance is curtailed by ambiguity with respect to their biological meaning and context specificity. Efforts to devise new holistic assessments of overall renal functional compromise in AKI would foster the capacity to better personalize patient care by replacing biomarker threshold-based diagnostic criteria with a shift to assessment of compromise along a pathophysiological continuum. The term AKI refers to a syndrome of sudden renal deterioration, the severity of which is classified by precise diagnostic criteria that have unquestionable utility in patient management as well as blatant limitations. Particularly, the absence of an explicit pathophysiological definition of AKI curtails further scientific development and clinical handling, entrapping the field within its present narrow GFR-based view. A refreshed approach based on a more holistic consideration of renal functional impairment in AKI as the basis for a new diagnostic concept that reaches beyond the boundaries imposed by the current GFR threshold-based classification of AKI, capturing broader aspects of pathogenesis, could enhance AKI prevention strategies and improve AKI patient outcome and prognosis.

The Human Physiome: how standards, software and innovative service infrastructures are providing the building blocks to make it achievable

Reconstructing and understanding the Human Physiome virtually is a complex mathematical problem, and a highly demanding computational challenge. Mathematical models spanning from the molecular level through to whole populations of individuals must be integrated, then personalized. This requires interoperability with multiple disparate and geographically separated data sources, and myriad computational software tools. Extracting and producing knowledge from such sources, even when the databases and software are readily available, is a challenging task. Despite the difficulties, researchers must frequently perform these tasks so that available knowledge can be continually integrated into the common framework required to realize the Human Physiome. Software and infrastructures that support the communities that generate these, together with their underlying standards to format, describe and interlink the corresponding data and computer models, are pivotal to the Human Physiome being realized. They provide the foundations for integrating, exchanging and re-using data and models efficiently, and correctly, while also supporting the dissemination of growing knowledge in these forms. In this paper, we explore the standards, software tooling, repositories and infrastructures that support this work, and detail what makes them vital to realizing the Human Physiome.

Integrating knowledge representation and quantitative modelling in physiology

A wealth of potentially shareable resources, such as data and models, is being generated through the study of physiology by computational means. Although in principle the resources generated are reusable, in practice, few can currently be shared. A key reason for this disparity stems from the lack of consistent cataloguing and annotation of these resources in a standardised manner. Here, we outline our vision for applying community-based modelling standards in support of an automated integration of models across physiological systems and scales. Two key initiatives, the Physiome Project and the European contribution - the Virtual Phsysiological Human Project, have emerged to support this multiscale model integration, and we focus on the role played by two key components of these frameworks, model encoding and semantic metadata annotation. We present examples of biomedical modelling scenarios (the endocrine effect of atrial natriuretic peptide, and the implications of alcohol and glucose toxicity) to illustrate the role that encoding standards and knowledge representation approaches, such as ontologies, could play in the management, searching and visualisation of physiology models, and thus in providing a rational basis for healthcare decisions and contributing towards realising the goal of of personalized medicine.

The Virtual Physiological Human

The Virtual Physiological Human is synonymous with a programme in computational biomedicine that aims to develop a framework of methods and technologies to investigate the human body as a whole. It is predicated on the transformational character of information technology, brought to bear on that most crucial of human concerns, our own health and well-being.