About this Research Topic
Tremendous progress has been made over the past decades in developing New Approach Methodologies (NAMs) and fostering their widespread use and acceptance. Across various industries such as cosmetics, pharmaceuticals, food, and agrochemicals, the adoption of NAMs has led to a significant shift in safety assessment practices. The European ban on animal testing for cosmetics has propelled NAMs into the spotlight, driving innovation in toxicity evaluation methods. This burgeoning ecosystem brings together stakeholders from diverse backgrounds, including companies, governmental agencies, academic groups, non-governmental organizations, and service providers, united in the shared goal of advancing pharmacological science while safeguarding human health and environmental integrity.
However, transitioning from traditional animal-based methods to NAMs presents its own set of challenges. As we navigate this new paradigm, questions arise regarding the adaptability of regulatory frameworks to accommodate emerging scientific and technological advancements. The convergence of disciplines such as artificial intelligence, computational modelling, and mechatronics adds both opportunities and complexities to the field of predictive toxicology.
This Research Topic invites submissions of original research and review papers that explore the journey of conceiving, developing, accepting, and implementing NAMs, with a particular emphasis on their pharmacological implications. Drawing parallels with the accelerated pace of biomedical research spurred by the COVID-19 pandemic, the aim is to extract valuable lessons that can inform future strategies in predictive toxicology. Join us in shaping the future of predictive toxicology and unlocking new horizons in pharmacological science.
However, transitioning from traditional animal-based methods to NAMs presents its own set of challenges. As we navigate this new paradigm, questions arise regarding the adaptability of regulatory frameworks to accommodate emerging scientific and technological advancements. The convergence of disciplines such as artificial intelligence, computational modelling, and mechatronics adds both opportunities and complexities to the field of predictive toxicology.
This Research Topic invites submissions of original research and review papers that explore the journey of conceiving, developing, accepting, and implementing NAMs, with a particular emphasis on their pharmacological implications. Drawing parallels with the accelerated pace of biomedical research spurred by the COVID-19 pandemic, the aim is to extract valuable lessons that can inform future strategies in predictive toxicology. Join us in shaping the future of predictive toxicology and unlocking new horizons in pharmacological science.
Keywords: Toxicology, New Approach Methodologies, Safety, Advancements, Machine Learning
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
