1.1 Descriptive full-text title
Provide a descriptive title using normal language without technical terms or acronyms.
Example: “Assay to test compound-derived impairment in neurite outgrowth in human mature dopaminergic neurons (NeuriTox; UKN4).”
Template by Krebs et al. (2019), ALTEX
The ToxTemp template was developed by Krebs et al. It is not the work of the ToxTempAssistant team.
Krebs, A., Waldmann, T., Wilks, M. F., van Vugt-Lussenburg, B. M. A., van der Burg, B., et al. (2019). Template for the description of cell-based toxicological test methods to allow evaluation and regulatory use of the data. ALTEX, 36(4), 682–699. https://doi.org/10.14573/altex.1909271
The questions, notes and examples below are reproduced from that article and its supplementary material under the CC BY 4.0 license. We changed the formatting and left out notes that repeat the question. ToxTempAssistant is a separate tool that helps you draft answers to these questions.
ToxTemp turns the requirements of OECD Guidance Document 211 into guided questions, so that non-guideline, cell-based toxicological test methods are described completely and consistently. It has 70 questions in 11 sections, plus 7 sub-questions that structure the abstract.
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Provide a descriptive title using normal language without technical terms or acronyms.
Example: “Assay to test compound-derived impairment in neurite outgrowth in human mature dopaminergic neurons (NeuriTox; UKN4).”
Please write an abstract on the cell-based toxicological test method in no more than 200 words:
Provide the original/published name, as well as the potential tradename.
Provide the original deposition date of first version and date of current version.
This only applies to updated versions. If this is the original version, state 'original version'.
Normal text names often do not uniquely define the method. Therefore, each method should be assigned a clearly and uniquely defined data base name.
These are some example data base names generated in the EU-ToxRisk project: UKN1a_DART_NPC_Diff_6D_02 UKN1b_DART_NPC_Diff_4D_01 UKN2a_DART_NC_Migr_24h_04 The name is assembled (in more generic terms) from the following elements: Axa_B_C_D_E Axa: mandatory part of the identifier allowing unambiguous identification A: Abbreviation/acronym of the partner depositing the assay x: Consecutive number (referring to the partner’s assay number) a: Sub-specifier (for variants, i.e. very similar assays but e.g. different readout or medium); not mandatory, but ‘Axa’ must be specific (i.e. clearly identifying) for each assay variant.
Include affiliation.
Provide the details of the principal contact person.
For example, the principal investigator (PI) of the lab, the person who conducted the experiments, etc.
Supply number of supporting files. Describe supporting files (e.g. metadata files, instrument settings, calculation template, raw data file, etc.).
Note: This section might be redundant with section 4. It is meant to describe the procedure of generating the cells, which are eventually used in the test method. This applies, e.g., for stem cells, which have to be differentiated towards the cell type with which the method is conducted (e.g., neurons or hepatocytes derived from iPSC). See scheme for illustration. If this is not applicable to your test system, go directly to section 4. Fig. 1: Overview of test system stages and where to find/deposit corresponding information in this document
Note: Refer to overview figure to connect question number and cell culture stages.
Describe briefly whether the cells are from a commercial supplier, continuously generated by cell culture, or obtained by isolation from human/animal tissue (or other).
Note: Not all stages may be relevant / applicable for some tests, e.g., commercial cells may be thawed and used immediately for a transporter or metabolism assay. In such cases, sections such as 3.6 may not need to be filled in.
Give a brief overview of your biological source system, i.e. the source or starting cells that you use. Which cell type(s) are used or obtained (e.g. monoculture/co-culture, differentiation state, 2D/3D, etc.)? If relevant, give human donor specifications (e.g. sex, age, pool of 10 donors, from healthy tissue, etc.).
List quantitative and semi-quantitative features that define your cell source/starting cell population. For test methods that are based on differentiation, describe your initial cells, e.g. iPSC, proliferating SH-SY5Y; the differentiated cells are described in section 4. Define cell identity, e.g. by STR signature (where available), karyotype information, sex (where available and relevant), ATCC number, passage number, source (supplier), sub-line (where relevant), source of primary material, purity of the cells, etc. Describe defining biological features you have measured or that are FIRMLY established (use simple listing, limit to max. 0.5 pages), e.g. the cells express specific marker genes, have specific surface antigens, lack certain markers, have or lack a relevant metabolic or transporting capacity, have a doubling time of x hours, etc. Transgenic cell lines have particular requirements concerning the characterization of the genetic manipulation (type of transgene, type of vector, integration/deletion site(s), stability, etc.). Organoids and microphysiological systems (MPS) may need some special/additional considerations as detailed in Pamies et al. (2018) and Marx et al. (2016), e.g. ratio of cell types used, percent of normal cells in tumor spheroids created from resected tissue; derivation of cells for re-aggregating brain cultures.
Note: Each test method can only use one specific cell source. Use of another source means that a key feature of the test method has been modified, and this change usually results in a new/different test method. (
Examples: use of another transgene in a transgenic cell, or use of another cell line , or use of another mouse strain, or use of another primary cell isolation method are all likely to qualify for/require a new method description – including its characterization for performance parameters. [“Source” is not limited to a single cell type, and it also includes composite sources, i.e., combination of ≥ 2 cell populations in a co-culture or microphysiological system. Notably, change of any part of such a composite source (e.g., one of the cell populations) would be considered a change of source)].
Describe the acceptance criteria (AC) for your initial cells (i.e. the quality criteria for your proliferating cell line, tissue for isolation, organism, etc.). Which specifications do you consider to describe the material, which quality control criteria have to be fulfilled (e.g. pathogen-free)? Which functional parameters (e.g. certain biological responses to reference substances) are important? For iPSC maintenance: How do you control pluripotency? How stable are your cells over several passages? Which passage(s) are valid? For primary cells: Show stability and identity of supply; demonstrate stability of function (e.g. xenobiotic metabolism). Quantitative definitions for AC should be given based on this defining information. Exclusion criteria (features to be absent) are also important. As in 3.3., special/additional requirements apply to genetically-modified cells and microphysiological systems.
Name known causes of variability of the initial cells/source cells. Indicate critical consumables or batch effects (e.g. relevance of the plate format and supplier, batch effects of fetal calf serum (FCS) or serum replacement, critical additives like type of trypsin, apo-transferrin vs. holo-transferrin, etc.). Indicate critical handling steps and influencing factors (e.g. special care needed in pipetting, steps that need to be performed quickly, cell density, washing procedures, etc.). As in 3.3., special/additional requirements apply to genetically-modified cells and microphysiological systems, e.g. dependence on matrix chemistry and geometry, dependence on microfluidics system, consideration of surface cells vs core cells, etc. Give recommendations to increase/ensure reproducibility and performance.
Describe the principles of the selected differentiation protocol, including a scheme and graphical overview, indicating all phases, media, substrates, manipulation steps (medium change/re-plating, medium additives, etc.). Special/additional requirements apply to microphysiological systems and organoids: e.g. cell printing, self-aggregation/self-organisation process, interaction with the matrix, geometrical characterization (size/shape), etc.
Note: ‘Differentiation’ is meant here in a broad sense, involving all changes occurring to source cells until they are exposed to compounds.
Examples for such processes include: proliferation associated with contact inhibition and change of average cell cycle state, formation of monolayers associated with formation of tight junctions, baso -lateral polarization, synaptic networking, formation of bile canaliculi, self -organization in 2D or 3D, change of activation state, etc. Thus , differentiation may be directed and intentional, but also non-intentional known changes need description here.
Examples to be described in detail: primary human hepatocytes (PHH) are plated on coated plastic, or are embedded in a collagen sandwich, or are aggregated to microtissues. Primary human monocytes are purified from blood by centrifugation and left to adhere on plastic; bronchial epithelial cells are cultured on air-liquid interface (ALI) until confluence is reached, etc.
Provide the SOP of the general maintenance procedure as a database link. This should also include the following information: How are the cells maintained outside the experiment (basic cell propagation)? How pure is the cell population (average, e.g. 95% of iPSC cells Oct4-positive)? What are the quality control measures and acceptance criteria for each cell batch? Which number(s) passage(s) can be used in the test? Is Good Cell Culture Practice (GCCP) and/or Good In Vitro Method Practice (GIVIMP) followed? How long can same cell batches be used? How are frozen stocks and cell banks prepared? For primary cells: how are they obtained in general and what are they characterized for (and what are inclusion and exclusion criteria).
Note: This section refers to the stage of the test system, which is then used for the test method. See scheme for illustration. If you have cells that do not need prior differentiation, give their basic characteristics here. If your test system undergoes significant changes between the maintenance culture and the use for testing, please also fill in section 3.
Describe the test system as it is used in the test. If the generation of the test system involves differentiation steps or complex technical manipulation (e.g. formation of microtissues), this is described in 3.6. Give details on the general features/principles of the culture protocol (collagen embedding, 3D structuring, addition of mitotic inhibitors, addition of particular hormones/growth factors, etc.) of the cells that are used for the test. What is the percentage of contaminating cells; in co-cultures what is the percentage of each subpopulation? Are there subpopulations that are generally more sensitive to cytotoxicity than others, and could this influence viability measures? Is it known whether specific chemicals/chemical classes show differential cytotoxicity for the cell sub-populations used?
Note: The exact experimental procedure is covered by a separate question.
What are the endpoint(s) that you use to control that your culture(s) is/are as expected at the start of toxicity testing (e.g. gene expression, staining, morphology, responses to reference chemicals, etc.)? Describe the acceptance criteria for your test system, i.e. the quality criteria for your cells/tissues/organoids: Which endpoints do you consider to describe the cells or other source material, which parameters are important? Describe the (analytical) methods that you use to evaluate your culture (PCR, ATP measurement) and to measure the acceptance criteria (AC). Which values (e.g. degree of differentiation or cell density) need to be reached/should not be reached? Historical controls: How does your test system perform with regard to the acceptance criteria, e.g. when differentiation is performed 10 times, what is the average and variation of the values for the acceptance criteria parameters)? Indicate actions if the AC are not met. Examples: cell are > 90% viable, or > 98% of cells express marker x (e.g. AP-2), or > 80% of the cells attach, etc.
Describe the acceptance criteria for your test system, i.e. the quality criteria for your cells/tissues/organoids: Which endpoints do you consider to describe the cells or other source material, which parameters are important? Which values (e.g. degree of differentiation or cell density) need to be reached/should not be reached? Historical controls: How does your test system perform with regard to the acceptance criteria, e.g. when differentiation is performed 10 times, what is the average and variation of the values for the acceptance criteria parameters)? Indicate actions if the AC are not met. Examples: Usual neurite length is 50 ±15 μm; experiments with average neurite length below 25 μm in the negative controls (NC) are discarded. Usual nestin induction is 200 ±40 fold, experiments with inductions below 80-fold for NC are discarded.
Note: Sometimes the test system does not change significantly between the beginning and end of compound exposure. In such cases, 4.3 does not need to be answered. In other cases, drastic changes occur (e.g. proliferation, further differentiation, spontan eous death, etc.). This needs characterization here.
Give known causes of variability for final test system state. Indicate critical consumables or batch effects (e.g. plate format and supplier, batch effects of FCS or serum replacement, additives). Indicate critical handling steps, and/or influencing factors identified (e.g. special care needed in pipetting, steps that need to be performed quickly, cell density). Indicate positive and negative controls and their expected values, and accepted deviation within and between the test repeats. Give recommendations to increase/ensure reproducibility and performance.
What is known about endogenous metabolic capacity (CYP system (phase I); relevant conjugation reactions (phase II))? What is known about other pathways relevant to xenobiotic metabolism? What specific information is there on transporter activity?
Note: This paragraph is meant as a brief overview based on own experience and may differ from the general literatu re. In case of differences, information under 4.5 may, e.g., look like “normally these cells are reported to be devoid of CypIIA1 activity, but under our culture conditions, significant activity was observed.
Are there transcriptomics data or other omics data available that describe the test system (characterization of cells without compounds)? Briefly list and describe such data. Indicate the type of data available (e.g. RNASeq or proteomics data). Refer to data file, data base or publication.
Give information on where the test system differs from the mimicked human tissue and which gaps of analogy need to be considered.
Are there elements of the test system that are protected by patents or any other means?
Note: Here information can / should be added on the availability / accessibility of the test system (e.g. from a supplier or through a license agreement). This is also the place to mention potential limitations of use (imposed by the supplier or the intellectual property rights situation). Further guidance may be found at the OECD (http://www.oecd.org/chemicalsafety/testing/intellectual- property-in-oecd-testguidelines.htm) or in OECD GD 298 on availability of test system elements (Guiding Principles on Good Practices for the Availability/Distribution of Protected Elements in OECD Test Guidelines).
Note: Black boxes (missing/confidential information) are hardly acceptable for a fully valid test method description, and this situation is even more problematic for method validation (Linge and Hartung, 2007).
Fill only if section 3 has not been answered. Provide the SOP for the general maintenance procedure as a database link. This should also include the following information: How are the cells maintained outside the experiment (basic cell propagation)? How pure is the cell population (average, e.g. 95% of iPSC cells Oct4-positive)? What are the quality control measures and acceptance criteria for each cell batch? Which number(s) passage(s) can be used in the test? Is Good Cell Culture Practice (GCCP) and/or Good In Vitro Method Practice (GIVIMP) followed? How long can same cell batches be used? How are freezing stocks and cell banks prepared? For primary cells: how are they obtained in general and what are they characterized for (and what are inclusion and exclusion criteria).
Provide an exposure scheme (graphically, show timelines, addition of medium supplements and compounds, sampling, etc.), within the context of the overall cell culture scheme (e.g. freshly re-plated cells or confluent cells at start, certain coatings, etc.). Include medium changes, cell re-plating, whether compounds are re-added in cases of medium change, critical medium supplements, etc.
Note: There can only be one exposure scheme, no alternative options! See 6.8 for indicating theoretical variations.
Define the specific endpoint(s) of the test system that you use for toxicity testing (e.g. cytotoxicity, cell migration, etc.). Indicate whether cytotoxicity is the primary endpoint. What are secondary/further endpoints? Also describe here potential reference/normalization endpoints (e.g. cytotoxicity, protein content, housekeeping gene expression) that are used for normalization of the primary endpoint.
Define and describe the principle(s) of the analytical methods used. Provide here a general overview of the method’s key steps (e.g. cells are fixed or not, homogenized sample or not, etc.), sufficient for reviewers/regulators to understand what was done, but not in all detail for direct repetition. If you have two or more endpoints (e.g. viability and neurite outgrowth), do you measure both in the same well, under same conditions in parallel, or independently of each other? For imaging endpoints: Explain in general how quantification algorithm or how semi-quantitative estimates are obtained and how many cells are imaged (roughly).
Provide information on machine settings, analytical standards, data processing and normalization procedures. For imaging endpoints: provide detailed algorithm. This information should also be covered in an SOP, preferably in DB-ALM format (see link in 6.6).
Note: Details on data processing are given in a separate chapter below.
MCC are chemicals/manipulations that show biologically plausible changes of the endpoint. List such controls (up to 10), indicate why you consider them as MCC, and describe expected data on such controls. Highlight the compounds to be used for testing day-to-day test performance, i.e. for setting acceptance criteria (AC). If available, indicate MCC that each increase or decrease the activity of the relevant pathway. Do pathway inhibitions or activations correlate with the test method response?
Example 1: U0126 (ERK signaling pathway inhibitor). Neurite outgrowth in the CNS is controlled by ERK, inhibitors should therefore block this endpoint. U0126 blocks neurite growth at concentrations that block ERK activation
Example 2: Cytochalasin D (actin depolymerizer). Cell movement requires actin reorganization. Disturbance of actin structure should attenuate cell migration. Cytochalasin D inhibits cell migration at non-cytotoxic concentrations.
Example 3: BMP4 (endogenous protein, ligand of BMP receptor). Cell differentiation towards neuroectoderm is disturbed by BMP- SMAD signaling. Therefore, the test is based on SMAD inhibition by noggin (a protein scavenging/neutralizing BMP4). Addition of more BMP4 should outcompete n oggin and lead to SMAD signaling, therefore preventing neuronal differentiation. BMP4 prevents the normal differentiation this test is based on.
What chemicals/manipulations are used as positive controls? Describe the expected data on such controls (signal and its uncertainty)? How good are in vivo reference data on the positive controls? Are in vivo relevant threshold concentrations known?
Note: Positive controls (PC) are compounds that are known to affect the endpoint in man (or in a gold standard model). They are therefore also referred to as positive reference compounds. It is not necessary that the exact mechanism for the PC is known. However, for the use of a positive control (PC) in an in vitro system, it is essential to show that the compound reaches the target cell in vitro similarly to the in vivo situation. (
Example problem 1: The positive control (PC) reaches the target in vivo because of transport or because of accumulation not present in vitro;
Note: MCC and PC may overlap. MCC are often more suitable than PC in order to define acceptance criteria for the test method; PC are classically used to build the prediction model.
Note: PC (and other chemicals used as anchor for the test method performance) need specification (not just listing of names), e.g., their CAS number, purity, handling and storage (relevant also for 5.5 and 5.7).
What chemicals/manipulations are used as negative controls? Describe the expected data on such controls (signal and its uncertainty)? (Such data define the background noise of the test method) What is the rationale for the concentration setting of negative controls? Do you use unspecific controls? If yes, indicate the compounds and the respective rationale for their use and the concentration selection.
Note: Some ways to define negatives include: (i) compound only acting when metabolized, (ii) acting on another organ, (iii) known to be safe for man, (iv) being selective for another assay, (v) pairs/matches of a specific positive control (e.g. inactive m etabolite). However, this all needs background knowledge. See also 5.6 for toxicokinetics problems (
Example problems: A compound may not affect a target cell in vivo because it does not reach the cell behind a barrie r or the compound has a too short half -life (high excretion or metabolism).
Does the test system have a particular apoptosis sensitivity or resistance? Is cytotoxicity hard to capture for minor cellular subpopulations? In multicellular systems, which cell population is the most sensitive? Are specific markers known for each cell population? Are there issues with distinguishing slowed proliferation from cell death? For repeated/prolonged dosing: Is early death and compensatory growth considered? For very short-term endpoints (e.g. electrophysiology measured 30 min after toxicant exposure): Is a delayed measure of cytotoxicity provided?
Note: This paragraph is meant as a brief overview based on own experience; it may differ from the general literature. In c ase of differences, these should be specified.
Which rule do you apply to test whether a test run is within the normal performance frame? How do you document this decision? Indicate actions if the AC are not met.
Note: AC are usually defined on the base of PC or MCC or NCTM results run in parallel. MCC or NC TM have to meet , for example, certain threshold values or be in a historic range to accept the given test run. As an example, such reference compounds were discussed for developmental neurotoxicity (DNT) by Aschner et al. (2017).
Note: Reference materials (MCC, or NC TM) also play a ce ntral role to show the proficiency of a laboratory to perform a test , or they can be used to document the adequacy of a certain test implementation/variant compared to a (validated) reference method (Hartung, 2007).
Indicate 'real data points per month' (not per week/per quarter, etc.): count three working weeks per month. Each concentration is a data point. Necessary controls that are required for calibration and for acceptability criteria are NOT counted as data points. All technical replicates of one condition are counted as one single data point (see notes for explanation) Indicate possibility/extent of repeated measures (over time) from same dish. Explain your estimate.
Note: The throughput estimate refers to the test conditions available to the developer or the lab where the test is applied. It refers to the normal required number of replicates needed to obtain meaningful data (as specified by the prediction model).
Note: Technical replicates are several measurements of the same sample, e.g., five solvent samples on the same multi-well plate or in the same test run, using cells from the same cell batch. Biologica l replicates are when the test is repeated on another day or using different cells (different passage or differentiation), see also Leist et al. (2010).
Give an overview of the range of volumes, particular lab ware/instruments for dispensing, temperature/lighting considerations, particular media/buffers for dilution, decision rules for the solvent, tests of solubility as stocks and in culture medium, etc. How are compound stocks prepared (fold concentration, verification, storage, etc.)? How are dilutions prepared? What solvent is used? Is filtering used to obtain sterility? How does the final addition to the test system take place? Give details of addition of test compounds to test systems (e.g. in which compartment of compartmentalized cultures, in which volume, before after or during medium change, etc.).
Note: Strike a reasonable balance between information overview for reviewers (focus here) and techni cal detail (to be detailed in an SOP). This applies to several chapters detailed in an SOP (e.g., controls and acceptance criteria).
How are day-to-day procedures documented (type of ‘lab book’ organisation, templates)? Define lab-specific procedures used for each practical experiment on how to calculate test compound concentrations (and to document this). How are plate maps defined and reported? Detailed information should also be covered in an SOP, preferably in DB-ALM format (see link in 6.6).
Note: Lab book entries are metadata that need to be linkable to test results on demand!
How is the time plan of pipetting established, followed, and documented? How is adherence to plate maps during pipetting documented? What are the routine procedures to document intermediate steps with potential errors, mistakes and uncertainties? How are errors documented (e.g. pipetting twice in one well)? How are the plate wells used sequentially – following which pattern? Detailed information should also be included in an SOP, preferably in DB-ALM format (see link in 6.6).
How is the concentration range of test compounds defined (e.g. only single concentrations, always 1:10 serial dilutions or variable dilution factors, ten different concentrations, etc.)? Is there a rule for defining starting dilutions? For functional endpoints that may not provide full concentration-response, how is the test concentration defined? E.g. EC10 of viability data are usually tested for gene expression endpoints. Detailed information should also be included in an SOP, preferably in DB-ALM format (see link in 6.6).
What types of compounds are problematic, e.g. interference with analytical endpoint, low solubility, precipitation of medium components, etc.? What experimental variables are hard to control (e.g. because they are fluorescent)? What are critical handling steps during the execution of the assay? Robustness issues, e.g. known variations of test performance due to operator training, season, use of certain consumable or unknown causes, etc. Describe known pitfalls (or potential operator mistakes).
Ideally the SOP follows the DB-ALM or a comparable format: https://ecvam-dbalm.jrc.ec.europa.eu/home/contribute Refer to additional file(s) (containing information covered in sections 3 and 4), containing all details and explanations. Has the SOP been deposited in an accessible data base? Has the SOP been reviewed externally and if yes, how?
Does the method require specialized instrumentation that is not found in standard laboratories? Is there a need for custom-made instrumentation or material? Is there a need for equipment that is not commercially available (anymore)?
Describe possible variations, modifications and extensions of the test method: a) other endpoints, b) other analytical methods for same endpoint, c) other exposure schemes (e.g. repeated exposure, prolonged exposure, etc.), d) experimental variations (e.g. use of a specific medium, presence of an inhibitor or substrate that affects test outcome, etc.)
Note: This should not be everything that COULD be done, but only points that have been done successfully, or that have a high likelihood of being done in a defined project context and after some appropriate evaluation.
Indicate the names (and database names) of related tests and give a short description (including a brief comment on differences to the present method). If the test method has been used for high throughput transcriptomics or deep sequencing as alternative endpoint, this should be indicated.
What is the data format? Raw data: give general explanation. Upload an exemplary file of raw data (e.g. Excel file as exported out of plate reader). Provide an example of processed data at a level suitable for general display and comparison of conditions and across experiments and methods. If the file format is not proprietary or binary, include a template. This will help other users to provide their data in a similar way to the general data infrastructure. Example as used in EU-ToxRisk: Excel sheet with columns specifying line number, assay name, date of experiment, identifier for reference to partner lab book, compound, concentration (in: -log[M]), line number of corresponding control, number of replicates, endpoints, data of endpoint(s), etc.
How are outliers defined and handled? How are they documented? Provide the general frequency of outliers.
Note: If only processed data are reported, outlier information gets lost.
How are raw data processed to obtain summary data (e.g. EC50, BMC15, ratios, PoD, etc.) in your lab? Describe all processing steps from background correction (e.g. measurement of medium control) to normalization steps (e.g. if you relate treated samples to untreated controls).
How are data normally handled to obtain the overall test result (e.g. concentration response fitting using model X, determination of EC50 by method Y, use of EC50 as final data)? How do you model your concentration response curve (e.g. LL.4 parameter fit) and which software do you use (e.g. GraphPad Prism, R, etc.)? Do you usually calculate an uncertainty measure of your summary data (e.g. a 95% confidence interval for the BMC or a BMCL), and with which software? Can you give uncertainty for non-cytotoxicity or no-effect? How do you handle non-monotonic curve shapes or other curve features that are hard to describe with the usual mathematical fit model?
How and how long are raw and other related data stored? What backup procedures are used (how frequently)? How are data versions identified?
How are metadata documented and stored (lab book, Excel files, left in machine, etc.)? How are they linked to raw data? What metadata are stored/should be stored?
Give example of the metadata file (if available). If metadata or data format (see 7.1) are pre-defined in the project, state here 'as pre-defined in project xxx' (e.g. EU-ToxRisk).
What is the scientific rationale to link test method data to a relevant in vivo adverse outcome? Which toxicological target (organ, tissue, physiological/biochemical function, etc.) is modelled? Which biological process(es) (e.g. neurite outgrowth, differentiation) are modelled/reflected by your test method? Which toxicological events (e.g. oxidative stress, cell death) are modelled/reflected by your test method? To which (human) adverse outcome(s) is your test method related? Which hazard(s) do(es) your test method (potentially) predict?
Provide the statistics of your benchmark response (threshold and variance): (i) For dichotomized data, provide your prediction model. When do you consider the result as toxic or not toxic? (ii) For pseudo-dichotomized outcomes (two classes with borderline class in between): define borderline range. (iii) For multi-class or continuous outcomes: provide definitions and rationale. What is the rationale for your threshold? This can be on a mathematical (e.g. 3-fold standard deviation) or a biological basis (e.g. below 80% viability). Is there a toxicological rationale for the threshold settings and definitions of your prediction model? What are the limitations of your prediction model? What is a ‘hit’ if the test is used in screening mode (= hit definition, if different from above)?
Note: Hit definition in a screen can be different from the benchmark response in normal testing, e.g. , in a screen you can be less strict because you do not want to miss anything, whereas in hit follow up testing you may use the benchmark response threshold.
How was the prediction model set up (using which test set of chemicals to train the model; using probing with what kind of classifiers/statistical approaches)? Has the prediction model been tested (what was the test set of chemicals)? List chemicals or give n, if n > 50. Is the process documented (publication)? Does the prediction model (PM) apply to changes to both sides of controls (up/down)? If the PM is one-sided (e.g. toxicants leading to a decrease vs. control), how are data in the opposite direction handled and interpreted? If the PM is two-sided, do different rules, characteristics and interpretations apply to the two sides (e.g. is a decrease in viability or an increase in viability both interpreted as an effect/toxicity; are thresholds and performance characteristics to both sides the same?).
Note: For final values on accuracy, sensitivity and specificity, refer to 8.4.
Indicate here basic performance parameters or, if possible, preliminary estimates (label as such): Baseline variation (noise) within assays AND between assays. What is the signal/noise ratio (signal = standard positive control)? Is the z-factor determined? Give the specificity of the test method. How is it determined? Give the sensitivity of the test method. How is it determined? Give measures of the uncertainty of your test method. How are they determined? What is the detection limit (required change of endpoint to become measurable)? If available, give limit of detection (LOD) and limit of quantification (LOQ). What are inter-operator variations? Are there data of ‘historical controls’ over a longer time period?
Note: Assay parameters can only apply to one assay version. A standard version must be defined and referred to in all answers.
Describe parameters important for the determination of free compound concentrations in the medium. Indicate the lipid and protein content of the medium and the cells. Indicate the volume of the cells. Indicate volume (medium volume) and surface area of culture dish. Is there information/literature on IVIVE strategies/data in the test? Has the test been used earlier for IVIVE? Are there special considerations that are relevant for IVIVE (e.g. potential for compound accumulation due to frequent medium changes and compound re-addition, glycoprotein (MDR1) expression, capacity for xenobiotic metabolism of test system)?
Which compounds is the test likely to pick up correctly, where is it likely to fail? How does the test method react to mixtures and UVCBs? Are there areas (according to industry sector, compound chemistry, physical-chemical properties) that need to be excluded from testing, or that are particularly suitable? Which compound class cannot be detected (e.g. neurotransmitters for which the receptors are not expressed, endocrine disruptors in absence of respective pathway)? Are any compounds known to interfere with the test system (e.g. fluorescent or colored chemicals)?
Does the test fit into a test battery? If yes, into which test battery and are there any restrictions? Indicate potential strengths and weaknesses of the system in a test battery (e.g. method is a good confirmation assay, good for creating alerts, mechanistic follow-up, screening, etc.). Compare performance to similar tests. Which gaps in a known or potential battery does the test method fill? Should the test preferentially be used in the first tier or later tiers, are complementary assays required or is it a stand-alone method?
Note: Such information may not be available at early phases of test implementation and use. If it is available, it is a valuable part of the test description, as i t specifies one of the test purposes and it links the test to related tests, with overall battery outcome as secondary purpose.
Refer to published literature on the test AND indicate in detail deviations from published descriptions (e.g. plastic plate supplier, cell number, endpoint measurement, timing, etc.). Provide the most relevant publications that describe/give a comprehensive overview of (a) your test system and/or (b) your test method. Describe what aspects are covered therein. Give a prioritized (according to importance) list of further publications on the test method or its application. Give short comments on which type(s) of information can be obtained from these publications (e.g. contains test chemical lists, contains more positive/negative controls, contains validation against other tests, contains incorporation in test battery, demonstrates use by other lab, etc.).
Note: Provide links (e.g., to PubMed, doi, etc.).
Indicate whether the test method has been or could be linked to an AOP (or several AOPs) and in which form (e.g. test of KE activation). Can the test method cover an AOP MIE/KE? Reference relevant AOP and if in AOP-wiki, refer to status.
Note: See remarks in 8.7.
Indicate/summarize information on mechanistic validation, e.g. by omics approaches or by use of endpoint specific controls (MCC; section 5.5). Has it been explored in how far the system reflects human biology, signaling, tissue organization relevant to the form of toxicity to be assessed (e.g. nigrostriatal neurons should contain dopamine, liver tests relevant to cholestasis may need to contain bile canalicular structures, etc.)?
Example 1: If a test measures neurite growth, then biological signals kn own to control neurite growth and growth cone collapse should be present in the system and their modulation should affect the test endpoint.
Example 2: If a test measures DNA damage response, then DNA damage sensors should be expressed and functioning, and knockdown of DNA damage sensors should affect the test endpoint.
Indicate/summarize activities for test qualification, pre-validation or validation. Indicate e.g. ring trials, full (pre-)validations. Give an overview of compounds or libraries that have been tested.
Note: To give evaluators/regulators an overview of the test readiness, this may be the place to add a summary of test readine ss scoring. This would give an overall overview of the uncertainties associated with test readiness (different from the single uncertainty measures for test system, analytical endpoint, the prediction model , etc.). Ideally, here the measures to minimize the impact of overall test method uncertainty may be described.
Indicate whether the test method is linked to an OECD Test Guideline (how, and which) or other regulatory guidance (e.g. EMA).
What experience is required? How are new operators trained in your laboratory? How much training/experience is required for smooth assay performance?
Has the test system been transferred to other labs? Has the test method been used by various operators (over a long time period)? Has the test method been transferred to other labs? Is there data on inter-laboratory variability? What are procedures and how was the performance (experience) of the transfer?
Are there special legal requirements for running the test in your lab; are there special hazards associated with the test that may affect operators, bystanders, others (e.g. through waste).
Are the SDSs for all hazardous reagents used in the test method available? Are the SDSs for all hazardous test compounds stored? Describe where and how the SDSs are stored internally. How is safe handling ensured? Is the exposure scenario for the hazardous reagents used in the test method available?
Are special permits (e.g. genetic work, stem cells, radioactivity, etc.) required? Are special facilities required? Is special ethical approval necessary (indicate approval document).
List elements of the test method (e.g. consumables, chemicals, analytical methods, equipment) that are protected by patents or any other means. Indicate the type of protection and where the element (or license for it) may be obtained.
Note: Here information can/should be added on the availability/accessibility of the test elements (e.g. from a supplier or through a license agreement. This is also the place to mention potential limitations of use (imposed by the supplier or the intellectual property rights situation). Further guidance may be found at the OECD ( http://www.oecd.org/chemicalsafety/testing/intellectual-property- in-oecd-testguidelines.htm). Compare also 4.8 (on commercial aspects of the cell system).
Note: Sometimes such information is hard to obtain. Unless full OECD validation and acceptance is sought, information may be given only on issues and elements that are well-known (or that may be a problem upon test method transfer).