Marta Bertolaso and Miles MacLeod are editors of Issue 30 (April 2016) of Humana.Mente — Journal of Philosophical Studies, entitled “In Silico Modeling: the Human Factor”. The issue reflects on the human dimensions inherent to bio-medical and social applications of in silico modelling, as well as on general issues pertaining the relationship between in silico modelling technologies and the human factor (HF). In fact, the challenges related to in silico modeling ask for a reflection on the intrinsic relationship among new technologies, which allow us to manage big data and to model biological functions, and the HF in bio-medical practice.
We understand the HF in three dimensions: a) the HF as a crucial factor in the process of scientific understanding, b) the HF as intrinsic feature of the object of in silico models (human physiology and its biological complexity) and c) the HF as part of a decisional process in using and applying in silico modeling in human contexts, for example in medicine (drug development, devices and clinical trials) or in the social world.
In silico modelling promises to overcome both the limitations of the in vitro and in vivo experimental models – like animal models – we use to represent human biological systems, but also the limits on our cognitive capacities to store, analyse and represent the enormous amount of information needed to reliably and accurately capture systems complexity and variability.
In silico modelling methods in biology and biomedicine use a range of different computational tools, resources and simulations including databases, quantitative structure-activity relationships, dynamic pathway models, machine learning and data-mining techniques, to develop and test hypotheses about the relationships amongst biological components and the behaviour of biological systems; and predict the results of intervening on these systems for medical or other purposes. To what extent big data and intensive computational modelling methods sacrifice mechanistic understanding in favour of computational pattern recognition and estimation algorithms, and what might be the benefits and risks of doing so? What epistemological issues arise and need to be taken into account when replacing in vitro and in vivo trials of human systems (such as those using human cells or animal models) with in silico trials? How well does computational integration of biological data (e.g. bio-ontologies) serve to represent the knowledge of individual biologists and communities of researchers? How well are estimations of model reliability being integrated into the ways in which in silico modelling is used to inform clinical practices and research funding? In general what is the proper role for in silico modelling to take with respect to the established framework of practices for both generating biological knowledge through experiment and other established means and for clinical decision-making? How well does in silico modelling provide platforms to overcome the human constraints that restrict the possibilities of genuine interdisciplinary collaboration and interaction, which is required for multi-scale and multi-field modelling?
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