Safe innovation approach: Towards an agile system for dealing with innovations

Nanotechnologies are characterized by a growing legacy of already marketed and novel manufactured nanomaterials (MNMs) and nano-enabled products with a lack of a coherent risk governance system to address their safety effectively. In response to this situation, a proactive system is needed to minimize the gap between the pace of innovation and the pace of developing nano-specific risk governance. With the Safe Innovation Approach (SIA), we seek to enhance the ability of all stakeholders to address the safety assessment of innovations in a robust yet agile manner. The SIA is an approach that combines a) the Safe-by-Design (SbD) concept, which recommends industry to integrate safety considerations as early as possible into the innovation process, and b) the Regulatory Preparedness (RP) concept which aims to improve anticipation of regulators in order that they can facilitate the development of adaptable (safety) regulation that can keep up with the pace of knowledge generation and innovation of MNMs and MNM-enabled products. SIA promotes a safe and responsible approach for industry when developing innovative products and materials, and stimulates a proactive attitude amongst policymakers and regulators to minimize the time gap between appearance and approval of innovation and appropriate legislation. Here we introduce a SIA framework consisting of creating SIA awareness, developing a SIA methodology (SbD scenarios, SbD methodology including information needs, functionality, and grouping, SIA Toolbox and a nano-specific database), bringing the Trusted Environment and RP concept into an operational level, and the development of novel business for industry and novel governance models for regulators. The SIA framework once implemented will result in a system for MNMs and nano-enabled products that is agile and robust. Current international efforts such as in the OECD are now trying to bring this concept to practice. © 2019 Elsevier Ltd

[1]  Eugenia Valsami-Jones,et al.  A strategy for grouping of nanomaterials based on key physico-chemical descriptors as a basis for safer-by-design NMs , 2014 .

[2]  Trevor Kletz Inherently Safer Design—Its Scope and Future , 2003 .

[3]  Georgia Tsiliki,et al.  The eNanoMapper database for nanomaterial safety information , 2015, Beilstein journal of nanotechnology.

[4]  Evan S. Michelson “The Train Has Left the Station”: The Project on Emerging Nanotechnologies and the Shaping of Nanotechnology Policy in the United States , 2013 .

[5]  Nastassja A. Lewinski,et al.  Nanocuration workflows: Establishing best practices for identifying, inputting, and sharing data to inform decisions on nanomaterials , 2015, Beilstein journal of nanotechnology.

[6]  G. Schmid The Nature of Nanotechnology , 2010 .

[7]  Hermann M. Bolt Grouping of nanomaterials for risk assessment , 2014, Archives of Toxicology.

[8]  David H. Guston,et al.  The Anticipatory Governance of Emerging Technologies , 2010 .

[9]  Hedwig M Braakhuis,et al.  Grouping nanomaterials to predict their potential to induce pulmonary inflammation. , 2016, Toxicology and applied pharmacology.

[10]  Robert G. Cooper,et al.  Perspective: The Stage‐Gate® Idea‐to‐Launch Process—Update, What's New, and NexGen Systems* , 2008 .

[11]  Riego Sintes Juan,et al.  NANoREG harmonised terminology for environmental health and safety assessment of nanomaterials , 2016 .

[12]  Iseult Lynch,et al.  How safe are nanomaterials? , 2015, Science.

[13]  Tsuyoshi Murata,et al.  {m , 1934, ACML.

[14]  Antonio Marcomini,et al.  Grouping and Read-Across Approaches for Risk Assessment of Nanomaterials , 2015, International journal of environmental research and public health.

[15]  Pekka Kohonen,et al.  Toxic and Genomic Influences of Inhaled Nanomaterials as a Basis for Predicting Adverse Outcome. , 2018, Annals of the American Thoracic Society.

[16]  Katarzyna Odziomek,et al.  Decision tree models to classify nanomaterials according to the DF4nanoGrouping scheme , 2018, Nanotoxicology.

[17]  Andreas Luch,et al.  Systems Biology to Support Nanomaterial Grouping. , 2017, Advances in experimental medicine and biology.

[18]  Finn Verner Jensen,et al.  Bayesian networks , 1998, Data Mining and Knowledge Discovery Handbook.

[19]  William L. Jorgensen,et al.  Journal of Chemical Information and Modeling , 2005, J. Chem. Inf. Model..

[20]  Arthur N. Mayeno,et al.  Computational Toxicology , 2013, Methods in Molecular Biology.

[21]  Pantelis Sopasakis,et al.  Jaqpot Quattro: A Novel Computational Web Platform for Modeling and Analysis in Nanoinformatics , 2017, J. Chem. Inf. Model..

[22]  Evan S. Michelson Emerging technologies and the role of NGOs. , 2017, Nature nanotechnology.

[23]  ScienceDirect,et al.  Toxicology and Applied Pharmacology , 1959, Nature.

[24]  S. Thompson Advances in experimental medicine and biology , 1996 .

[25]  Seyed Hamed Mousavi,et al.  Process Safety and Environmental Protection , 2015 .

[26]  Christian Micheletti,et al.  Implementation of Safe-by-Design for Nanomaterial Development and Safe Innovation: Why We Need a Comprehensive Approach , 2018, Nanomaterials.

[27]  Tomasz Puzyn,et al.  How should the completeness and quality of curated nanomaterial data be evaluated? , 2016, Nanoscale.

[28]  Deutsche Gesellschaft für experimentelle und klinische Phar Toxikologie. Archives of toxicology , 1974 .

[29]  T. Schimmel Beilstein Journal of Nanotechnology , 2010, Beilstein journal of nanotechnology.

[30]  Milind Kandlikar,et al.  Expert Views on Regulatory Preparedness for Managing the Risks of Nanotechnologies , 2013, PloS one.

[31]  L. Christophorou Science , 2018, Emerging Dynamics: Science, Energy, Society and Values.

[32]  Ola Spjuth,et al.  Toward the Replacement of Animal Experiments through the Bioinformatics-driven Analysis of ‘Omics’ Data from Human Cell Cultures , 2015, Alternatives to laboratory animals : ATLA.

[33]  Sharon Munn,et al.  The Adverse Outcome Pathway approach in nanotoxicology , 2017 .

[34]  D. Rebholz-Schuhmann,et al.  Journal of Biomedical Semantics , 2017 .

[35]  Egon L. Willighagen,et al.  eNanoMapper: harnessing ontologies to enable data integration for nanomaterial risk assessment , 2015, Journal of Biomedical Semantics.

[36]  Vidar Skaug,et al.  Criteria for grouping of manufactured nanomaterials to facilitate hazard and risk assessment, a systematic review of expert opinions , 2018, Regulatory toxicology and pharmacology : RTP.

[37]  Yi-Ming Wei,et al.  Author's Personal Copy China's Carbon Emissions from Urban and Rural Households during 1992e2007 , 2022 .

[38]  S. Buck,et al.  Solving reproducibility , 2015, Science.

[39]  Gregory Morose,et al.  The 5 principles of “Design for Safer Nanotechnology” , 2010 .

[40]  Paul Anastas,et al.  Green chemistry: principles and practice. , 2010, Chemical Society reviews.