The growing prevalence of AI systems in society, has also prompted a growth of AI systems in the public sector. There are however ethical concerns over the impact of AI on society and how this technology can impact public values. Previous works do not connect public values and the development of AI. To address this, a method is required to ensure that developers and public servants can signal possible ethical implications of an AI system and are assisted in creating systems that adhere to public values. Using the Research pathway model and Value Sensitive Design, we will develop a toolbox to assist in these challenges and gain insight into how public values can be embedded throughout the development of AI systems.
For almost fifteen years, the availability and regulatory acceptance of new approach methodologies (NAMs) to assess the absorption, distribution, metabolism and excretion (ADME/biokinetics) in chemical risk evaluations are a bottleneck. To enhance the field, a team of 24 experts from science, industry, and regulatory bodies, including new generation toxicologists, met at the Lorentz Centre in Leiden, The Netherlands. A range of possibilities for the use of NAMs for biokinetics in risk evaluations were formulated (for example to define species differences and human variation or to perform quantitative in vitro-in vivo extrapolations). To increase the regulatory use and acceptance of NAMs for biokinetics for these ADME considerations within risk evaluations, the development of test guidelines (protocols) and of overarching guidance documents is considered a critical step. To this end, a need for an expert group on biokinetics within the Organisation of Economic Cooperation and Development (OECD) to supervise this process was formulated. The workshop discussions revealed that method development is still required, particularly to adequately capture transporter mediated processes as well as to obtain cell models that reflect the physiology and kinetic characteristics of relevant organs. Developments in the fields of stem cells, organoids and organ-on-a-chip models provide promising tools to meet these research needs in the future.
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