Testing Services
- FHAIVE´s staff has over 20 years experience in in vitro methods. FHAIVE is committed to high-quality research and testing and operates under GLP regulations. FHAIVE offers testing services using FHAIVE´s validated routine test methods. Tests can be performed as GLP or non-GLP studies (Contact your local authorities to insure requirements in your application).
- We also offer comprehensive computational services for predictive and systems toxicology and pharmacology
Contact persons:
jack.morikka@tuni.fi (In vitro)
michele.fratello@tuni.fi (In silico)
angela.serra@tuni.fi (Mechanistic and integrative)
Or contact fhaiveinfo@lists.tuni.fi
Available in vitro tests
Test/service
Principle
We offer
Acute cytotoxicity test
Acute cell toxicity means adverse effects resulting from interference with structures or processes that are essential for cell survival (e.g. cell membrane integrity, mitochondrial energy metabolism) after a single chemical exposure for 24-48 hours.
Applications
- Predicting acute toxicity of chemicals (pharmaceuticals, cosmetics, industrial chemicals, biocides etc.) and their mixtures, and medical device
- Predicting acute oral dose for rodent test
- Acute toxicity testing using mouse BALB 3T3 fibroblasts and Neutral Red Uptake Assay in compliance with OECD GD 129.
- Acute toxicity testing using human BJ fibroblasts and Neutral Red Uptake Assay. Using human cells instead of mouse cells gives better prediction of human effects1. The protocol is in line with OECD GD 129 and has been intra-laboratory validated in FICAM.
Performance of BJ NRU cytotoxicity test [YouTube video] - Both GLP and non-GLP testing service available
1Mannerström et al. 2017: Basic Clin Pharmacol Toxicol, 121 Suppl 3:109-115
EpiDerm™ skin corrosion test
Skin corrosion means irreversible damage (loss of cell viability) of the skin following the application of a test substance for up to four hours.
EpiDermTM. Skin corrosion test is performed using human cell based three-dimensional highly differentiated keratinocyte cultures (EpiDermTM) in compliance with OECD TG 431. The potential of chemical to induce skin corrosion is an important consideration in establishing procedures for the safe handling, packing and transport of chemicals.
- Evaluation of skin corrosion potential of chemicals (drugs, cosmetics,
industrial chemicals, biocides) and mixtures of chemicals - Both GLP and non–GLP testing service available!
EpiDerm™ skin irritation test
Skin irritation means production of reversible damage (local inflammatory reaction) to the skin following the application of a test chemical for up to 4 hours.
EpiDermTM skin irritation test is performed using human cell based three-dimensional highly differentiated keratinocyte cultures (EpiDermTM) in compliance with OECD TG 439. The potential of chemical to induce skin irritation is an important consideration in establishing procedures for the safe handling, packing and transport of chemicals.
- Evaluation of skin irritation potential of chemicals (drugs, cosmetics,
industrial chemicals, biocides) and mixtures of chemicals - Both GLP and non–GLP testing service available!
ISO 10993-5:2009 “Biological evaluation of medical devices: tests for in vitro cytotoxicity”
Cytotoxicity testing is a part of biological evaluation process of medical devices. The purpose of the BJ NRU cytotoxicity test method is to evaluate the acute toxicity induced by the medical device materials.
- Cytotoxicity testing using human BJ fibroblasts and Neutral Red Uptake Assay in compliance with ISO 10993-5:2009
- Extraction of test materials is included in the service
- Both GLP and non-GLP testing service available
Test method validation
Test method validation is a part of the regulatory acceptance process of the test method and has to be performed in GLP in compliance with OECD GD 34.
- test method optimization and validation
- consultation on test method validation (and GLP)
- FHAIVE is a NETVAL laboratory and can act as a reference laboratory in inter-laboratory test method validations
In silico
Test/service
Principle
We offer
QSAR
QSAR is an analytic approach to modeling chemical activities based on a numeric representation of their structure. It is most suited in situations where a large collection of heterogeneous chemicals is available.
Development of machine learning predictive models of chemical compounds properties, activities and toxicity based on large scale datasets.
Virtual Screening
Virtual Screening is a chemical discovery methodology to search through a collection of small molecules to identify structures with defined desirable properties, such as binding to a specific receptor.
Exploration of the space of structurally diverse chemicals to identify compounds likely to have the desired properties; alternatively, we can search a chemical library for chemicals structurally similar to a query compound.
Read-across
Read-across is used to quantify an unknown property of a compound (e.g. toxicity) based on a set of a few analogous compounds.
We build the analog series of compounds and exploit the known information to fill the gap for an unknown target compound.
Mechanistic
Test/service
Principle
We offer
Design of toxicogenomics studies
A careful experimental design is the first step towards effective and reliable omics data analysis. Experimental and technical effects are a common issue in experimentation and can lead to biased results.
We design omics experiments by taking into account the biological requirements, optimal sample size, careful sample randomization and technical parameters.
Definition of chemicals mechanism of action (MOA) from toxicogenomics data
The mechanism of action (MOA) of a compound comprises all the molecular alterations induced by its exposure. The characterization of the MOA can be performed by comparing transcriptomics or epigenomics data between the sample groups and identifying the differences induced by the exposure.
We apply standardized pipelines for quality check and preprocessing of microarray and RNASeq data. We perform chemical mechanism of action characterization in terms of differentially expressed molecules and their functional enrichment.
Dose-dependent modelling of toxicogenomics data
One of the main goals of toxicity assessment is the study of exposure-response relationships that describe the strength of the response of an organism as a function of exposure to a stimulus. These relationships can be described as dose-response curves from which a benchmark dose (BMD) value is calculated as the dose (or concentration) that produces a given amount of change in the response.
We perform modelling of microarray gene expression data with well standardized pipelines to identify the portion of MOA that has a dose-dependent behaviour. For each dose-dependent molecular alteration we identify the point of departure as the benchmark dose (BMD) and its lower (BMDL) and upper (BMDU) values.
Identification of predictive biomarkers
Biomarkers are valuable indicators of the state of a biological system. Omics technology has been extensively used to identify biomarkers and build computational predictive models for disease prognosis, drug sensitivity and toxicity evaluations. Biomarker detection from microarray data requires several considerations both from the biological and computational points of view.
We apply machine learning based feature selection strategy to identify biomarkers from single and multi omics data.
Integrative
Test/service
Principle
We offer
QSMART
Classical QSAR analysis aims to study the correlation between chemical structures and a particular property. QSMART analysis identifies connections between a chemical property and both chemical structure and its induced molecular alterations.
We perform integrative modelling of cheminformatics and omics data to create hybrid QSAR predictive modelling. We aim at identifying the smallest set of predictive features with the best applicability domain.
Multi-omics MOA modelling
Different types of omics data have become available allowing the measurement of multiple omics data layers for the same set of samples. These data usually provide potentially complementary information and assess different parts of the same complex biological process.
We apply classical and cutting edge machine learning methodology for the analysis of multi-omics data. We offer comprehensive reconstruction of MOA models involving multiple molecular districts possibly affected by a chemical perturbation.
Knowledge graph-based integrated analysis
High volume data analysis can help to identify relationships and correlations between data points, counteract biases, dilutes mistakes and can improve decision making overall. The diverse set of biological data is modeled in a linked data structure to generate a detailed view of complex biological processes.
We apply knowledge discovery methodology to a graph structured knowledge base. This facilitates the discovery of new connections between chemical exposures and health phenotypes. This can be used for chemical safety assessment and drug design alike.