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Wittwehr C, Clerbaux LA, Edwards S, Angrish M, Mortensen H, Carusi A, Gromelski M, Lekka E, Virvilis V, Martens M, Bonino da Silva Santos LO, Nymark P. Why adverse outcome pathways need to be FAIR. ALTEX 2024; 41:50-56. [PMID: 37528748 DOI: 10.14573/altex.2307131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 07/25/2023] [Indexed: 08/03/2023]
Abstract
Adverse outcome pathways (AOPs) provide evidence for demonstrating and assessing causality between measurable toxicological mechanisms and human or environmental adverse effects. AOPs have gained increasing attention over the past decade and are believed to provide the necessary steppingstone for more effective risk assessment of chemicals and materials and moving beyond the need for animal testing. However, as with all types of data and knowledge today, AOPs need to be reusable by machines, i.e., machine-actionable, in order to reach their full impact potential. Machine-actionability is supported by the FAIR principles, which guide findability, accessibility, interoperability, and reusability of data and knowledge. Here, we describe why AOPs need to be FAIR and touch on aspects such as the improved visibility and the increased trust that FAIRification of AOPs provides.
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Affiliation(s)
| | | | | | - Michelle Angrish
- Center for Public Health and Environmental Assessment, Chemical & Pollutant Assessment Division, U.S. Environmental Protection Agency, Washington DC, USA
| | - Holly Mortensen
- Center for Public Health and Environmental Assessment, Public Health and Integrated Toxicology Division, U.S. Environmental Protection Agency, Durham, NC, USA
| | | | - Maciej Gromelski
- Laboratory of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdańsk, Gdańsk, Poland
| | | | | | - Marvin Martens
- Department of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, Maastricht, The Netherlands
| | - Luiz Olavo Bonino da Silva Santos
- GO FAIR Foundation, Leiden, the Netherlands
- Services and Cybersecurity group, Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente - Enschede, The Netherlands
| | - Penny Nymark
- Karolinska Institutet, Institute of Environmental Medicine, Stockholm, Sweden
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Martin R, Nasir N, Carusi A. Enhancing research culture through PhD training: a systems approach to identifying leverage points for policy formation. Wellcome Open Res 2023; 8:422. [PMID: 38173561 PMCID: PMC10762290 DOI: 10.12688/wellcomeopenres.19567.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/16/2023] [Indexed: 01/05/2024] Open
Abstract
This article examines the role of PhD training programmes in identifying and implementing positive interventions in research culture in the biosciences. Using a data set consisting of transcripts from interviews and group discussions with 179 participants from 18 of the current 23 (78%) UK-based Wellcome-funded PhD programmes, we apply a systems theory methodology to the system of higher education and PhD training. Using system mapping as an investigative tool, this approach identifies points of leverage within the system where policy interventions might be best targeted to affect changes to research culture in the global higher education sector. The results of this investigation highlight the student-supervisor relationship as a nexus for these interventions and recommends the programme structure as a global policy for PhD training.
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Affiliation(s)
- Rebecca Martin
- Centre for History in Public Health, London School of Hygiene and Tropical Medicine, London, UK
| | - Nazia Nasir
- UK Research Development, Research and Innovation Services, Univresity of Leeds, Leeds, UK
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Carusi A, Filipovska J, Wittwehr C, Clerbaux LA. CIAO: a living experiment in interdisciplinary large-scale collaboration facilitated by the Adverse Outcome Pathway framework. Front Public Health 2023; 11:1212544. [PMID: 37637826 PMCID: PMC10449328 DOI: 10.3389/fpubh.2023.1212544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 07/12/2023] [Indexed: 08/29/2023] Open
Abstract
Introduction The CIAO project was launched in Spring 2020 to address the need to make sense of the numerous and disparate data available on COVID-19 pathogenesis. Based on a crowdsourcing model of large-scale collaboration, the project has exploited the Adverse Outcome Pathway (AOP) knowledge management framework built to support chemical risk assessment driven by mechanistic understanding of the biological perturbations at the different organizational levels. Hence the AOPs might have real potential to integrate data produced through different approaches and from different disciplines as experienced in the context of COVID-19. In this study, we aim to address the effectiveness of the AOP framework (i) in supporting an interdisciplinary collaboration for a viral disease and (ii) in working as the conceptual mediator of a crowdsourcing model of collaboration. Methods We used a survey disseminated among the CIAO participants, a workshop open to all interested CIAO contributors, a series of interviews with some participants and a self-reflection on the processes. Results The project has supported genuine interdisciplinarity with exchange of knowledge. The framework provided a common reference point for discussion and collaboration. The diagram used in the AOPs assisted with making explicit what are the different perspectives brought to the knowledge about the pathways. The AOP-Wiki showed up many aspects about its usability for those not already in the world of AOPs. Meanwhile their use in CIAO highlighted needed adaptations. Introduction of new Wiki elements for modulating factors was potentially the most disruptive one. Regarding how well AOPs support a crowdsourcing model of large-scale collaboration, the CIAO project showed that this is successful when there is a strong central organizational impetus and when clarity about the terms of the collaboration is brought as early as possible. Discussion Extrapolate the successful CIAO approach and related processes to other areas of science where the AOP could foster interdisciplinary and systematic organization of the knowledge is an exciting perspective.
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Affiliation(s)
| | | | - Clemens Wittwehr
- European Commission, Joint Research Centre (JRC), Joint Research Centre, Ispra, Italy
| | - Laure-Alix Clerbaux
- European Commission, Joint Research Centre (JRC), Joint Research Centre, Ispra, Italy
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Abstract
Artificial intelligence (AI) and machine learning (ML) techniques occupy a prominent role in medical research in terms of the innovation and development of new technologies. However, while many perceive AI as a technology of promise and hope-one that is allowing for more early and accurate diagnosis-the acceptance of AI and ML technologies in hospitals remains low. A major reason for this is the lack of transparency associated with these technologies, in particular epistemic transparency, which results in AI disturbing or troubling established knowledge practices in clinical contexts. In this article, we describe the development process of one AI application for a clinical setting. We show how epistemic transparency is negotiated and co-produced in close collaboration between AI developers and clinicians and biomedical scientists, forming the context in which AI is accepted as an epistemic operator. Drawing on qualitative research with collaborative researchers developing an AI technology for the early diagnosis of a rare respiratory disease (pulmonary hypertension/PH), this paper examines how including clinicians and clinical scientists in the collaborative practices of AI developers de-troubles transparency. Our research shows how de-troubling transparency occurs in three dimensions of AI development relating to PH: querying of data sets, building software and training the model The close collaboration results in an AI application that is at once social and technological: it integrates and inscribes into the technology the knowledge processes of the different participants in its development. We suggest that it is a misnomer to call these applications 'artificial' intelligence, and that they would be better developed and implemented if they were reframed as forms of sociotechnical intelligence.
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Affiliation(s)
- Peter David Winter
- School of Sociology, Politics and International Studies, University of Bristol, Bristol, UK
| | - Annamaria Carusi
- Interchange Research, London, UK
- Department of Science and Technology Studies, University College London, London, London, UK
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Carusi A, Winter PD, Armstrong I, Ciravegna F, Kiely DG, Lawrie A, Lu H, Sabroe I, Swift A. Medical artificial intelligence is as much social as it is technological. NAT MACH INTELL 2023. [DOI: 10.1038/s42256-022-00603-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
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Clerbaux LA, Amigó N, Amorim MJ, Bal-Price A, Batista Leite S, Beronius A, Bezemer GFG, Bostroem AC, Carusi A, Coecke S, Concha R, Daskalopoulos EP, De Bernardi F, Edrosa E, Edwards SW, Filipovska J, Garcia-Reyero N, Gavins FNE, Halappanavar S, Hargreaves AJ, Hogberg HT, Huynh MT, Jacobson D, Josephs-Spaulding J, Kim YJ, Kong HJ, Krebs CE, Lam A, Landesmann B, Layton A, Lee YO, Macmillan DS, Mantovani A, Margiotta-Casaluci L, Martens M, Masereeuw R, Mayasich SA, Mei LM, Mortensen H, Munoz Pineiro A, Nymark P, Ohayon E, Ojasi J, Paini A, Parissis N, Parvatam S, Pistollato F, Sachana M, Sørli JB, Sullivan KM, Sund J, Tanabe S, Tsaioun K, Vinken M, Viviani L, Waspe J, Willett C, Wittwehr C. COVID-19 through Adverse Outcome Pathways: Building networks to better understand the disease - 3rd CIAO AOP Design Workshop. ALTEX 2022; 39:322–335. [PMID: 35032963 PMCID: PMC10069302 DOI: 10.14573/altex.2112161] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 12/17/2021] [Indexed: 02/07/2023]
Abstract
On April 28-29, 2021, 50 scientists from different fields of expertise met for the 3rd online CIAO workshop. The CIAO project “Modelling the Pathogenesis of COVID-19 using the Adverse Outcome Pathway (AOP) framework” aims at building a holistic assembly of the available scientific knowledge on COVID-19 using the AOP framework. An individual AOP depicts the disease progression from the initial contact with the SARS-CoV-2 virus through biological key events (KE) toward an adverse outcome such as respiratory distress, anosmia or multiorgan failure. Assembling the individual AOPs into a network highlights shared KEs as central biological nodes involved in multiple outcomes observed in COVID-19 patients. During the workshop, the KEs and AOPs established so far by the CIAO members were presented and positioned on a timeline of the disease course. Modulating factors influencing the progression and severity of the disease were also addressed as well as factors beyond purely biological phenomena. CIAO relies on an interdisciplinary crowdsourcing effort, therefore, approaches to expand the CIAO network by widening the crowd and reaching stakeholders were also discussed. To conclude the workshop, it was decided that the AOPs/KEs will be further consolidated, integrating virus variants and long COVID when relevant, while an outreach campaign will be launched to broaden the CIAO scientific crowd.
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Affiliation(s)
| | | | | | - Anna Bal-Price
- European Commission, Joint Research Centre, Ispra, Italy
| | | | - Anna Beronius
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | | | | | | | - Sandra Coecke
- European Commission, Joint Research Centre, Ispra, Italy
| | - Rachel Concha
- Fairleigh Dickinson University, Green Neuroscience Laboratory, San Diego, CA, USA
| | | | - Francesca De Bernardi
- Division of Otorhinolaryngology, Department of Biotechnologies and Life Sciences, University of Insubria, Ospedale di Circolo e Fondazione Macchi, Varese, Italy
| | - Eizleayne Edrosa
- Green Neuroscience Laboratory, Neurolinx Research Institute, San Diego, CA, USA
| | | | | | | | - Felicity N E Gavins
- The Centre for Inflammation Research and Translational Medicine (CIRTM), Brunel University London, London, UK
| | - Sabina Halappanavar
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, Ontario, Canada
| | - Alan J Hargreaves
- School of Science and Technology, Nottingham Trent University, Nottingham, UK
| | - Helena T Hogberg
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Mylène T Huynh
- Department of Preventive Medicine and Biometrics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Daniel Jacobson
- Biosciences, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | | | - Young Jun Kim
- Korea Institute of Science and Technology Europe Forschungsgesellschaft mbH, Saarbrücken, Germany
| | - Hyun Joon Kong
- University of Illinois at Urbana-Champaign, Champaign, IL, USA
| | | | - Ann Lam
- Green Neuroscience Laboratory, Neurolinx Research Institute, San Diego, CA, USA
| | | | | | - Yong Oh Lee
- Korea Institute of Science and Technology Europe Forschungsgesellschaft mbH, Saarbrücken, Germany
| | | | | | - Luigi Margiotta-Casaluci
- The Centre for Inflammation Research and Translational Medicine (CIRTM), Brunel University London, London, UK
| | - Marvin Martens
- Department of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, Maastricht, The Netherlands
| | - Rosalinde Masereeuw
- Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
| | - Sally A Mayasich
- University of Wisconsin-Madison Aquatic Sciences Center at US EPA, Duluth, MN, USA
| | | | | | | | - Penny Nymark
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Elan Ohayon
- Green Neuroscience Laboratory, Neurolinx Research Institute, San Diego, CA, USA
| | - Joshi Ojasi
- Hiranandani College of Pharmacy, Mumbai, India
| | - Alicia Paini
- European Commission, Joint Research Centre, Ispra, Italy
| | | | - Surat Parvatam
- Centre for Predictive Human Model Systems Atal Incubation Centre - Centre for Cellular and Molecular Biology Habsiguda, Hyderabad, India
| | | | - Magdalini Sachana
- Environment Health and Safety Division, Environment Directorate, Organisation for Economic Cooperation and Development (OECD), Paris, France
| | | | | | - Jukka Sund
- European Commission, Joint Research Centre, Ispra, Italy
| | - Shihori Tanabe
- Division of Risk Assessment, Center for Biological Safety and Research, National Institute of Health Sciences, Kawasaki, Japan
| | - Katya Tsaioun
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Mathieu Vinken
- Department of Pharmaceutical and Pharmacological Sciences, Vrije Universiteit Brussel, Brussels, Belgium
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Carusi A, Davies MR, De Grandis G, Escher BI, Hodges G, Leung KMY, Whelan M, Willett C, Ankley GT. Harvesting the promise of AOPs: An assessment and recommendations. Sci Total Environ 2018; 628-629:1542-1556. [PMID: 30045572 PMCID: PMC5888775 DOI: 10.1016/j.scitotenv.2018.02.015] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Revised: 02/02/2018] [Accepted: 02/02/2018] [Indexed: 05/22/2023]
Abstract
The Adverse Outcome Pathway (AOP) concept is a knowledge assembly and communication tool to facilitate the transparent translation of mechanistic information into outcomes meaningful to the regulatory assessment of chemicals. The AOP framework and associated knowledgebases (KBs) have received significant attention and use in the regulatory toxicology community. However, it is increasingly apparent that the potential stakeholder community for the AOP concept and AOP KBs is broader than scientists and regulators directly involved in chemical safety assessment. In this paper we identify and describe those stakeholders who currently-or in the future-could benefit from the application of the AOP framework and knowledge to specific problems. We also summarize the challenges faced in implementing pathway-based approaches such as the AOP framework in biological sciences, and provide a series of recommendations to meet critical needs to ensure further progression of the framework as a useful, sustainable and dependable tool supporting assessments of both human health and the environment. Although the AOP concept has the potential to significantly impact the organization and interpretation of biological information in a variety of disciplines/applications, this promise can only be fully realized through the active engagement of, and input from multiple stakeholders, requiring multi-pronged substantive long-term planning and strategies.
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Affiliation(s)
- Annamaria Carusi
- Medical Humanities Sheffield, University of Sheffield, Medical School, Beech Hill Road, Sheffield S10 2RX, UK.
| | | | - Giovanni De Grandis
- Science, Technology, Engineering and Public Policy (STEaPP), Boston House, 36-37 Fitzroy Square, London W1T 6EY, UK.
| | - Beate I Escher
- UFZ - Helmholtz Centre for Environmental Research, 04318 Leipzig, Germany; Eberhard Karls University Tübingen, Environmental Toxicology, Centre for Applied Geosciences, 72074 Tübingen, Germany.
| | - Geoff Hodges
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK.
| | - Kenneth M Y Leung
- The Swire Institute of Marine Science and School of Biological Sciences, The University of Hong Kong, Pokfulam, Hong Kong, China.
| | - Maurice Whelan
- European Commission, Joint Research Centre (JRC), Ispra, Italy.
| | - Catherine Willett
- The Humane Society of the United States, 700 Professional Drive, Gaithersburg, MD, 20879, USA.
| | - Gerald T Ankley
- US Environmental Protection Agency, 6201 Congdon Blvd, Duluth, MN 55804, USA.
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8
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van Baalen S, Carusi A, Sabroe I, Kiely DG. A social-technological epistemology of clinical decision-making as mediated by imaging. J Eval Clin Pract 2017; 23:949-958. [PMID: 27696641 PMCID: PMC5655732 DOI: 10.1111/jep.12637] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2016] [Revised: 07/22/2016] [Accepted: 08/05/2016] [Indexed: 11/29/2022]
Abstract
In recent years there has been growing attention to the epistemology of clinical decision-making, but most studies have taken the individual physicians as the central object of analysis. In this paper we argue that knowing in current medical practice has an inherently social character and that imaging plays a mediating role in these practices. We have analyzed clinical decision-making within a medical expert team involved in diagnosis and treatment of patients with pulmonary hypertension (PH), a rare disease requiring multidisciplinary team involvement in diagnosis and management. Within our field study, we conducted observations, interviews, video tasks, and a panel discussion. Decision-making in the PH clinic involves combining evidence from heterogeneous sources into a cohesive framing of a patient, in which interpretations of the different sources can be made consistent with each other. Because pieces of evidence are generated by people with different expertise and interpretation and adjustments take place in interaction between different experts, we argue that this process is socially distributed. Multidisciplinary team meetings are an important place where information is shared, discussed, interpreted, and adjusted, allowing for a collective way of seeing and a shared language to be developed. We demonstrate this with an example of image processing in the PH service, an instance in which knowledge is distributed over multiple people who play a crucial role in generating an evaluation of right heart function. Finally, we argue that images fulfill a mediating role in distributed knowing in 3 ways: first, as enablers or tools in acquiring information; second, as communication facilitators; and third, as pervasively framing the epistemic domain. With this study of clinical decision-making in diagnosis and treatment of PH, we have shown that clinical decision-making is highly social and mediated by technologies. The epistemology of clinical decision-making needs to take social and technological mediation into account.
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Affiliation(s)
- Sophie van Baalen
- Department of Philosophy, University of Twente, Enschede, The Netherlands
| | | | - Ian Sabroe
- Department of Infection Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, UK
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Carusi A, Rodriguez B, Burrage K. Validation and models in computational biomedical sciences: Philosophy, science, engineering. Prog Biophys Mol Biol 2017; 129:1-2. [PMID: 28882254 DOI: 10.1016/j.pbiomolbio.2017.08.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Affiliation(s)
| | | | - Kevin Burrage
- Queensland University of Technology, Australia; University of Oxford, UK
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10
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Muszkiewicz A, Britton OJ, Gemmell P, Passini E, Sánchez C, Zhou X, Carusi A, Quinn TA, Burrage K, Bueno-Orovio A, Rodriguez B. Variability in cardiac electrophysiology: Using experimentally-calibrated populations of models to move beyond the single virtual physiological human paradigm. Prog Biophys Mol Biol 2015; 120:115-27. [PMID: 26701222 PMCID: PMC4821179 DOI: 10.1016/j.pbiomolbio.2015.12.002] [Citation(s) in RCA: 104] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/16/2015] [Revised: 11/24/2015] [Accepted: 12/02/2015] [Indexed: 01/13/2023]
Abstract
Physiological variability manifests itself via differences in physiological function between individuals of the same species, and has crucial implications in disease progression and treatment. Despite its importance, physiological variability has traditionally been ignored in experimental and computational investigations due to averaging over samples from multiple individuals. Recently, modelling frameworks have been devised for studying mechanisms underlying physiological variability in cardiac electrophysiology and pro-arrhythmic risk under a variety of conditions and for several animal species as well as human. One such methodology exploits populations of cardiac cell models constrained with experimental data, or experimentally-calibrated populations of models. In this review, we outline the considerations behind constructing an experimentally-calibrated population of models and review the studies that have employed this approach to investigate variability in cardiac electrophysiology in physiological and pathological conditions, as well as under drug action. We also describe the methodology and compare it with alternative approaches for studying variability in cardiac electrophysiology, including cell-specific modelling approaches, sensitivity-analysis based methods, and populations-of-models frameworks that do not consider the experimental calibration step. We conclude with an outlook for the future, predicting the potential of new methodologies for patient-specific modelling extending beyond the single virtual physiological human paradigm.
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Affiliation(s)
- Anna Muszkiewicz
- Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, United Kingdom
| | - Oliver J Britton
- Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, United Kingdom
| | - Philip Gemmell
- Clyde Biosciences Ltd, West Medical Building, University of Glasgow, Glasgow G12 8QQ, United Kingdom
| | - Elisa Passini
- Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, United Kingdom
| | - Carlos Sánchez
- Center for Computational Medicine in Cardiology (CCMC), Institute of Computational Science, Università della Svizzera italiana, Lugano, Switzerland
| | - Xin Zhou
- Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, United Kingdom
| | | | - T Alexander Quinn
- Department of Physiology and Biophysics, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Kevin Burrage
- Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, United Kingdom; Mathematical Sciences, Queensland University of Technology, Queensland 4072, Australia; ACEMS, ARC Centre of Excellence for Mathematical and Statistical Frontiers, Queensland University of Technology, Queensland 4072, Australia
| | - Alfonso Bueno-Orovio
- Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, United Kingdom
| | - Blanca Rodriguez
- Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, United Kingdom.
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Rodriguez B, Carusi A, Abi-Gerges N, Ariga R, Britton O, Bub G, Bueno-Orovio A, Burton RAB, Carapella V, Cardone-Noott L, Daniels MJ, Davies MR, Dutta S, Ghetti A, Grau V, Harmer S, Kopljar I, Lambiase P, Lu HR, Lyon A, Minchole A, Muszkiewicz A, Oster J, Paci M, Passini E, Severi S, Taggart P, Tinker A, Valentin JP, Varro A, Wallman M, Zhou X. Human-based approaches to pharmacology and cardiology: an interdisciplinary and intersectorial workshop. Europace 2015; 18:1287-98. [PMID: 26622055 PMCID: PMC5006958 DOI: 10.1093/europace/euv320] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2015] [Accepted: 08/20/2015] [Indexed: 12/12/2022] Open
Abstract
Both biomedical research and clinical practice rely on complex datasets for the physiological and genetic characterization of human hearts in health and disease. Given the complexity and variety of approaches and recordings, there is now growing recognition of the need to embed computational methods in cardiovascular medicine and science for analysis, integration and prediction. This paper describes a Workshop on Computational Cardiovascular Science that created an international, interdisciplinary and inter-sectorial forum to define the next steps for a human-based approach to disease supported by computational methodologies. The main ideas highlighted were (i) a shift towards human-based methodologies, spurred by advances in new in silico, in vivo, in vitro, and ex vivo techniques and the increasing acknowledgement of the limitations of animal models. (ii) Computational approaches complement, expand, bridge, and integrate in vitro, in vivo, and ex vivo experimental and clinical data and methods, and as such they are an integral part of human-based methodologies in pharmacology and medicine. (iii) The effective implementation of multi- and interdisciplinary approaches, teams, and training combining and integrating computational methods with experimental and clinical approaches across academia, industry, and healthcare settings is a priority. (iv) The human-based cross-disciplinary approach requires experts in specific methodologies and domains, who also have the capacity to communicate and collaborate across disciplines and cross-sector environments. (v) This new translational domain for human-based cardiology and pharmacology requires new partnerships supported financially and institutionally across sectors. Institutional, organizational, and social barriers must be identified, understood and overcome in each specific setting.
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Affiliation(s)
- Blanca Rodriguez
- Department of Computer Science, University of Oxford, Oxford, UK
| | | | - Najah Abi-Gerges
- AnaBios Corporation, San Diego Science Center, San Diego, CA 92109, USA
| | - Rina Ariga
- Radcliffe Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Oliver Britton
- Department of Computer Science, University of Oxford, Oxford, UK
| | - Gil Bub
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
| | | | - Rebecca A B Burton
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
| | | | | | - Matthew J Daniels
- Radcliffe Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | | | - Sara Dutta
- Department of Computer Science, University of Oxford, Oxford, UK
| | - Andre Ghetti
- AnaBios Corporation, San Diego Science Center, San Diego, CA 92109, USA
| | - Vicente Grau
- Department of Engineering Science, University of Oxford, Oxford, UK
| | - Stephen Harmer
- William Harvey Heart Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, UK
| | - Ivan Kopljar
- Discovery Sciences, Dis&Dev Research, Janssen Pharmaceutical NV, Beerse, Belgium
| | - Pier Lambiase
- Institute of Cardiovascular Science, University College London, Bars Heart Centre, London, UK
| | - Hua Rong Lu
- Discovery Sciences, Dis&Dev Research, Janssen Pharmaceutical NV, Beerse, Belgium
| | - Aurore Lyon
- Department of Computer Science, University of Oxford, Oxford, UK
| | - Ana Minchole
- Department of Computer Science, University of Oxford, Oxford, UK
| | - Anna Muszkiewicz
- Department of Computer Science, University of Oxford, Oxford, UK
| | - Julien Oster
- Department of Engineering Science, University of Oxford, Oxford, UK
| | - Michelangelo Paci
- Department of Electronics and Communications Engineering, Tampere University of Technology, BioMediTech, Tampere, Finland
| | - Elisa Passini
- Department of Computer Science, University of Oxford, Oxford, UK
| | - Stefano Severi
- Department of Electrical, Electronic and Information Engineering, University of Bologna, Cesena 47521, Italy
| | - Peter Taggart
- Institute of Cardiovascular Science, University College London, Bars Heart Centre, London, UK
| | - Andy Tinker
- William Harvey Heart Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, UK
| | | | | | | | - Xin Zhou
- Department of Computer Science, University of Oxford, Oxford, UK
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Carusi A. Validation and variability: dual challenges on the path from systems biology to systems medicine. Stud Hist Philos Biol Biomed Sci 2014; 48 Pt A:28-37. [PMID: 25262024 DOI: 10.1016/j.shpsc.2014.08.008] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2014] [Revised: 08/21/2014] [Accepted: 08/22/2014] [Indexed: 06/03/2023]
Abstract
Systems biology is currently making a bid to show that it is able to make an important contribution to personalised or precision medicine. In order to do so, systems biologists need to find a way of tackling the pervasive variability of biological systems that is manifested in the medical domain as inter-subject variability. This need is simultaneously social and epistemic: social as systems biologists attempt to engage with the interests and concerns of clinicians and others in applied medical research; epistemic as they attempt to develop new strategies to cope with variability in the validation of the computational models typical of systems biology. This paper describes one attempt to develop such a strategy: a trial with a population-of-models approach in the context of cardiac electrophysiology. I discuss the development of this approach against the background of ongoing tensions between mathematically and experimentally inclined modellers on the one hand, and attempts to forge new collaborations with medical scientists on the other. Apart from the scientific interest of the population-of-models approach for tackling variability, the trial also offers a good illustration of the epistemology of experiment-facing modelling. I claim that it shows the extent to which experiment-facing modelling and validation require the establishment of criteria for comparing models and experiments that enable them to be linked together. These 'grounds of comparability' are the broad framework in which validation experiments are interpreted and evaluated by all the disciplines in the collaboration, or being persuaded to participate in it. I claim that following the process of construction of the grounds of comparability allows us to see the establishment of epistemic norms for judging validation results, through a process of 'normative intra-action' (Rouse, 2002) that shape the social and epistemic evolution of systems approaches to biomedicine.
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Affiliation(s)
- Annamaria Carusi
- Centre for Medical Science and Technology Studies, University of Copenhagen, Denmark.
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Carusi A, Burrage K, Rodríguez B. Bridging experiments, models and simulations: an integrative approach to validation in computational cardiac electrophysiology. Am J Physiol Heart Circ Physiol 2012; 303:H144-55. [PMID: 22582088 DOI: 10.1152/ajpheart.01151.2011] [Citation(s) in RCA: 60] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Computational models in physiology often integrate functional and structural information from a large range of spatiotemporal scales from the ionic to the whole organ level. Their sophistication raises both expectations and skepticism concerning how computational methods can improve our understanding of living organisms and also how they can reduce, replace, and refine animal experiments. A fundamental requirement to fulfill these expectations and achieve the full potential of computational physiology is a clear understanding of what models represent and how they can be validated. The present study aims at informing strategies for validation by elucidating the complex interrelations among experiments, models, and simulations in cardiac electrophysiology. We describe the processes, data, and knowledge involved in the construction of whole ventricular multiscale models of cardiac electrophysiology. Our analysis reveals that models, simulations, and experiments are intertwined, in an assemblage that is a system itself, namely the model-simulation-experiment (MSE) system. We argue that validation is part of the whole MSE system and is contingent upon 1) understanding and coping with sources of biovariability; 2) testing and developing robust techniques and tools as a prerequisite to conducting physiological investigations; 3) defining and adopting standards to facilitate the interoperability of experiments, models, and simulations; 4) and understanding physiological validation as an iterative process that contributes to defining the specific aspects of cardiac electrophysiology the MSE system targets, rather than being only an external test, and that this is driven by advances in experimental and computational methods and the combination of both.
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Abstract
Volunteer computing projects (VCPs) have been set up by groups of scientists to recruit members of the public who are asked to donate spare capacity on their personal computers to the processing of scientific data or computationally intensive models. VCPs serve two purposes: to acquire significant computing capacity and to educate the public about science. A particular challenge for these scientists is the retention of volunteers as there is a very high drop-out rate. This paper develops recommendations for scientists and software engineers setting up or running VCPs regarding which strategies to pursue in order to improve volunteer retention rates. These recommendations are based on a qualitative study of volunteers in a VCP (climateprediction.net). A typology of volunteers has been developed, and three particularly important classes of volunteers are presented in this paper: for each type of volunteer, the particular benefits they offer to a project are described, and their motivations for continued participation in a VCP are identified and linked to particular strategies. In this way, those setting up a VCP can identify which types of volunteers they should be particularly keen to retain, and can then find recommendations to increase the retention rates of their target volunteers.
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Affiliation(s)
- Peter Darch
- Computing Laboratory, University of Oxford, Wolfson Building, Parks Road, Oxford OX1 3QD, UK.
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Albaladejo P, Carusi A, Apartian A, Lacolley P, Safar ME, Bénétos A. Effect of chronic heart rate reduction with ivabradine on carotid and aortic structure and function in normotensive and hypertensive rats. J Vasc Res 2003; 40:320-8. [PMID: 12891001 DOI: 10.1159/000072696] [Citation(s) in RCA: 38] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2002] [Accepted: 04/08/2003] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND A reduction of heart rate (HR) by surgical means or pharmacological agents affects the progression and/or regression of atherosclerotic lesions. Nevertheless, the effect of bradycardia per se on large artery structure and function has never been investigated in rat models of hypertension. METHODS Four groups of Wistar-Kyoto (WKY) rats and spontaneously hypertensive rats (SHRs) were treated for 28 days either by placebo or by the selective HR-reducing agent ivabradine (8.4 mg/kg/day), a novel compound devoid of inotropic or vasodilating effects and without direct action on the autonomic nervous system. At the end of the follow-up period, intra-arterial blood pressure, carotid pulsatile arterial hemodynamics (echo tracking techniques) and the medial cross-sectional area (MCSA) of the aorta and the carotid artery were determined. RESULTS In conscious animals, chronic administration of ivabradine significantly reduced HR by 26-30% with no change in tail systolic blood pressure. In anesthetized animals, the decrease in HR and the subsequent increase in the diastolic period were responsible for a decrease in diastolic blood pressure. At the site of the large arteries, ivabradine produced a decrease in the MCSA of the thoracic but not of the abdominal aorta, as well as an increase in pulsatile change of the carotid diameter without change in the isobaric distensibility and MCSA. The changes in pulsatile diameter were significantly larger in WKY rats than in SHRs. CONCLUSION In normotensive and mainly in SHRs, selective chronic HR reduction by ivabradine is associated with alterations in large arteries involving an aortic antihypertrophic effect.
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Affiliation(s)
- P Albaladejo
- Department of Anesthesiology, Hôpital Beaujon, Clichy, France
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