04327nas a2200673   4500000000100000000000100001008004100002260001500043653000900058653002400067653001500091653002000106653001300126653003800139653001300177653002800190100001800218700001800236700002100254700002300275700002200298700001900320700001800339700001600357700001800373700001900391700002600410700001600436700002000452700001800472700001900490700002200509700001800531700002200549700001900571700001700590700002600607700001800633700002400651700001900675700002100694700002400715700002000739700001600759700002000775700002600795700001800821700001900839700002100858700002400879700001700903700001700920245010200937856005601039300001201095490000701107520252501114022001403639       2025                            d  c2025-01-1410aFAIR10adata interpretation10adata layer10adata processing10aMetadata10aNew Approach Methodologies (NAMs)10araw data10atest method description1 aJonathan Blum1 aMarkus Brüll1 aJan G. Hengstler1 aDaniel R. Dietrich1 aAndreas J. Gruber1 aMichele Dipalo1 aUdo Kraushaar1 aIris Mangas1 aAndrea Terron1 aEllen Fritsche1 aPhilip Marx-Stoelting1 aBarry Hardy1 aAndreas Schepky1 aSylvia Escher1 aThomas Hartung1 aRobert Landsiedel1 aAlex Odermatt1 aMagdalini Sachana1 aKatharina Koch1 aArif Dönmez1 aStefan Masjosthusmann1 aKathrin Bothe1 aStefan Schildknecht1 aMario Beilmann1 aJoost B. Beltman1 aSuzanne Fitzpatrick1 aAswin Mangerich1 aMarkus Rehm1 aSilvia Tangianu1 aFranziska M. Zickgraf1 aHennicke Kamp1 aGerhard Burger1 aBob van de Water1 aNicole Kleinstreuer1 aAndrew White1 aMarcel Leist00aThe long way from raw data to NAM-based information: Overview on data layers and processing steps  uhttps://altex.org/index.php/altex/article/view/2911  a167-1800 v423 aToxicological test methods generate raw data and provide instructions on how to use these to determine a final outcome such as a classification of test compounds as hits or non-hits. The data processing pipeline provided in the test method description is often highly complex. Usually, multiple layers of data, ranging from a machine-generated output to the final hit definition, are considered. Transition between each of these layers often requires several data processing steps. As changes in any of these processing steps can impact the final output of new approach methods (NAMs), the processing pipeline is an essential part of a NAM description and should be included in reporting templates such as the ToxTemp. The same raw data, processed in different ways, may result in different final outcomes that may affect the readiness status and regulatory acceptance of the NAM, as an altered output can affect robustness, performance, and relevance. Data management, pro­cessing, and interpretation are therefore important elements of a comprehensive NAM definition. We aim to give an overview of the most important data levels to be considered during the devel­opment and application of a NAM. In addition, we illustrate data processing and evaluation steps between these data levels. As NAMs are increasingly standard components of the spectrum of toxi­cological test methods used for risk assessment, awareness of the significance of data processing steps in NAMs is crucial for building trust, ensuring acceptance, and fostering the reproducibility of NAM outcomes.
Plain language summary Toxicological test methods initially generate raw data. These need to be further processed to determine a final outcome, such as the classification of test compounds as hits or non-hits. The pro­cessing of the raw data is often highly complex and proceeds stepwise. This process generates many layers of data connected by several processing steps. Any change to these processing steps can impact the final output of new approach methods (NAMs). This means that the same raw data, processed in different ways, may result in different final outcomes. Data management, processing and interpretation are therefore considered important elements of a comprehensive NAM definition. We illustrate data processing and evaluation steps that play an important role. Awareness of the significance of data processing steps in NAMs is crucial for building trust, ensuring acceptance, and fostering the reproducibility of NAM outcomes.  a1868-8551