Safe and Sustainable by Design Workflows supporting Product Design and Decision Making

Traditional product safety assessment processes frequently rely on lengthy animal testing and may fail to accurately predict and manage impacts during product design and innovation on  human and environmental health and their interactions, highlighting the urgent need for a move toward more effective and timely assessment methods.

Within our framework, New Approach Methods (NAMs), such as high-throughput screening, in silico and in vitro methods, and omics technologies, are integrated into tiered strategies involving Safe and Sustainable by Design (SSbD),  Integrated Approaches to Testing and Assessment, and Next Generation Risk Assessment, to incorporate function, safety and sustainability into product design from the start of the innovation and development process. 

Our developed methodology is founded on knowledge integration of data, models and supporting evidence incorporated into a workflow system implementing and documenting SSbD tasks and decisions with trusted integrity and reproducibility.

We will explain how a tiered  iterative workflow approach enables users to use SSbD methods and tools effectively, hence improving their ability to integrate the concepts and calculations into daily operations and product decisions.  Through application to a variety of industrial case studies, we demonstrate how this approach works in real-world scenarios, guiding early product design decisions ensuring that products are optimised for function, safety and human and environmental health impacts. 

We discuss the use of modelling and AI techniques to assist the collection, generation and use of evidence as a critical strategic NAM methodology supporting SSbD goals. Valuable assistance is obtained from resources that use data and scientific techniques to obtain and organise relevant knowledge embedded into SSbD decision-making workflows. To achieve this goal, full use of existing data, models and knowledge should be leveraged into providing relevant information supporting assessment and decision goals between alternatives in early stage innovation. Such data needs to be integrated with evidence-weighting and scoring schemes, including uncertainty, to reach initial decisions on alternatives and to plan for subsequent refinement phases. The findings may include recommendations for generating the most meaningful and useful data to address gaps and uncertainty. We will demonstrate the methodology followed and questions arising from current case study work applying SSbD to chemicals, polymers and advanced materials.

ACCORDs (grant  agreement  n°  101092796), SSbD4Chem (grant  agreement  n°  101138475), Biophenom (grant  agreement  n°  101135107)   projects  have  received  funding  from  the  European  Union’s  Horizon  Europe research  and  innovation  programme.  UK participants of projects  are  supported by UKRI.  CH participants project receive funding from the Swiss State Secretariat for Education, Research and Innovation (SERI).