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TZID:Europe/Berlin
TZUNTIL:20270328T010000Z
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DTSTART:20241027T030000
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RDATE:20251026T030000
RDATE:20261025T030000
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DTSTAMP:20260726T190301Z
DESCRIPTION:Data driven approaches are becoming increasingly important for 
 the environmental risk assessment of chemicals and other pollutants. While
  traditional approaches are largely based on standard experiments conducte
 d with few surrogate test species under controlled and artificial conditio
 ns in the lab\, new methods are now envisioned that ideally allow to relia
 bly extrapolate from lab to field\, from in vitro to in vivo tests\, from 
 tested species to untested ones and from tested to untested pollutants. Ma
 jor aims of these computational approaches are to reduce animal testing an
 d accelerate the identification of likely problematic pollutants at an ear
 ly stage. While comparably sophisticated methods are in use for the regula
 tory assessment of pesticides and many other chemical pollutants\, newer c
 ontaminants including micro- and nanoplastic particles lack a regulatory f
 ramework so far and data bases for the training of predictive models are l
 argely lacking to date. In addition to new computational approaches and de
 velopments in microplastics risk assessments\, traditional regulatory ecot
 oxicology currently faces a transition in the statistical approaches used 
 for the analysis of the generated data. Several initiatives have been laun
 ched working on the renewal of statistics guidance documents on a European
  and global level which all aim at improving the reliability of regulatory
  decisions. In this talk I will introduce new trait-based approaches to th
 e risk assessment of micro- and nanoplastic particles and discuss the impo
 rtance and availability of adequate data sources for predictive modelling.
  I will show advances we made in the development of microplastic databases
  as a new basis for predictive modelling\, show how machine learning model
 s can be used in the future to speed up ecotoxicity testing to improve dat
 a coverage and give examples on how existing microplastic effects database
 s can be used for risk assessment purposes. In addition\, I will demonstra
 te how statistical research can create direct policy impact on a regulator
 y level and discuss novel developments in this field.\n&nbsp\;
DTSTART;TZID=Europe/Berlin:20250710T123000
DTEND;TZID=Europe/Berlin:20250710T140000
LOCATION:H6\, Geo
SUMMARY:Dr. Magdalena Mair\, Statistical Ecotoxicology\, BayCEER (Homepage)
 : Data-driven approaches to the environmental risk assessment of chemicals
  and microplastic particles
TRANSP:TRANSPARENT
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