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Article ; Online: Predicting DNA-Reactivity of N-Nitrosamines: A Quantum Chemical Approach.

Wenzel, Jan / Schmidt, Friedemann / Blumrich, Matthias / Amberg, Alexander / Czich, Andreas

2022 Volume 35, Issue 11, Page(s) 2068–2084

Abstract: ... ...

Abstract	N
MeSH term(s)	Humans ; Nitrosamines/metabolism ; Carcinogens/metabolism ; Mutagens ; DNA ; Pharmaceutical Preparations
Chemical Substances	Nitrosamines ; Carcinogens ; Mutagens ; DNA (9007-49-2) ; Pharmaceutical Preparations
Language	English
Publishing date	2022-10-27
Publishing country	United States
Document type	Journal Article
ZDB-ID	639353-6
ISSN	1520-5010 ; 0893-228X
ISSN (online)	1520-5010
ISSN	0893-228X
DOI	10.1021/acs.chemrestox.2c00217
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Article ; Online: Nonclinical safety evaluation of a novel ionizable lipid for mRNA delivery.

Broudic, Karine / Amberg, Alexander / Schaefer, Markus / Spirkl, Hans-Peter / Bernard, Marie-Clotilde / Desert, Paul

Toxicology and applied pharmacology

2022 Volume 451, Page(s) 116143

Abstract: mRNA vaccines hold tremendous potential in disease control and prevention for their flexibility with respect to production, application, and design. Recent breakthroughs in mRNA vaccination would have not been possible without major advances in lipid ... ...

Abstract	mRNA vaccines hold tremendous potential in disease control and prevention for their flexibility with respect to production, application, and design. Recent breakthroughs in mRNA vaccination would have not been possible without major advances in lipid nanoparticles (LNPs) technologies. We developed an LNP containing a novel ionizable cationic lipid, Lipid-1, and three well known excipients. An in silico toxicity hazard assessment for genotoxicity, a genotoxicity assessment, and a dose range finding toxicity study were performed to characterize the safety profile of Lipid-1. The in silico toxicity hazard assessment, utilizing two prediction systems DEREK and Leadscope, did not find any structural alert for mutagenicity and clastogenicity, and prediction in the statistical models were all negative. In addition, applying a read-across approach a structurally very similar compound was tested negative in two in vitro assays confirming the low genotoxicity potential of Lipid-1. A dose range finding toxicity study in rabbits, receiving a single intramuscular injection of either different doses of an mRNA encoding Influenza Hemagglutinin H3 antigen encapsulated in the LNP containing Lipid-1 or the empty LNP, evaluated local tolerance and systemic toxicity during a 2-week observation period. Only rabbits exposed to the vaccine were able to develop a specific IgG response, indicating an appropriate vaccine take. The vaccine was well tolerated up to 250 μg mRNA/injection, which was defined as the No Observed Adverse Effect Level (NOAEL). These results support the use of the LNP containing Lipid-1 as an mRNA delivery system for different vaccine formulations and its deployment into clinical trials.
MeSH term(s)	Animals ; Lipids/chemistry ; Lipids/toxicity ; Liposomes ; Nanoparticles/chemistry ; Nanoparticles/toxicity ; RNA, Messenger/genetics ; Rabbits
Chemical Substances	Lipid Nanoparticles ; Lipids ; Liposomes ; RNA, Messenger
Language	English
Publishing date	2022-07-16
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	204477-8
ISSN	1096-0333 ; 0041-008X
ISSN (online)	1096-0333
ISSN	0041-008X
DOI	10.1016/j.taap.2022.116143
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Article ; Online: In silico

Keller, Douglas A / Bassan, Arianna / Amberg, Alexander / Burns Naas, Leigh Ann / Chambers, Jon / Cross, Kevin / Hall, Frances / Jahnke, Gloria D / Luniwal, Amarjit / Manganelli, Serena / Mestres, Jordi / Mihalchik-Burhans, Amy L / Woolley, David / Tice, Raymond R

Frontiers in toxicology

2023 Volume 5, Page(s) 1234498

Abstract: ... In ... ...

Abstract	In silico
Language	English
Publishing date	2023-11-13
Publishing country	Switzerland
Document type	Journal Article
ISSN	2673-3080
ISSN (online)	2673-3080
DOI	10.3389/ftox.2023.1234498
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Article ; Online: Toward implementing virtual control groups in nonclinical safety studies.

Golden, Emily / Allen, David / Amberg, Alexander / Anger, Lennart T / Baker, Elizabeth / Baran, Szczepan W / Bringezu, Frank / Clark, Matthew / Duchateau-Nguyen, Guillemette / Escher, Sylvia E / Giri, Varun / Grevot, Armelle / Hartung, Thomas / Li, Dingzhou / Lotfi, Laura / Muster, Wolfgang / Snyder, Kevin / Wange, Ronald / Steger-Hartmann, Thomas

ALTEX

2023 Volume 41, Issue 2, Page(s) 282–301

Abstract: Historical data from control groups in animal toxicity studies is currently mainly used for comparative purposes to assess validity and robustness of study results. Due to the highly controlled environment in which the studies are performed and the ... ...

Abstract	Historical data from control groups in animal toxicity studies is currently mainly used for comparative purposes to assess validity and robustness of study results. Due to the highly controlled environment in which the studies are performed and the homogeneity of the animal collectives it has been proposed to use the historical data for building so-called virtual control groups, which could replace partly or entirely the concurrent control. This would constitute a substantial contribution to the reduction of animal use in safety studies. Before the concept can be implemented, the prerequisites regarding data collection, curation and statistical evaluation together with a validation strategy need to be identified to avoid any impairment of the study outcome and subsequent consequences for human risk assessment. To further assess and develop the concept of virtual control groups the transatlantic think tank for toxicology (t⁴) sponsored a workshop with stakeholders from the pharmaceutical and chemical industry, academia, FDA, pharmaceutical, contract research organizations (CROs), and non-governmental organizations in Washington, which took place in March 2023. This report summarizes the current efforts of a European initiative to share, collect and curate animal control data in a centralized database and the first approaches to identify optimal matching criteria between virtual controls and the treatment arms of a study as well as first reflections about strategies for a qualification procedure and potential pitfalls of the concept.
MeSH term(s)	Animals ; Control Groups ; Pharmaceutical Preparations ; Research
Chemical Substances	Pharmaceutical Preparations
Language	English
Publishing date	2023-12-01
Publishing country	Germany
Document type	Journal Article
ZDB-ID	165707-0
ISSN	1868-8551 ; 1018-4562 ; 0946-7785
ISSN (online)	1868-8551
ISSN	1018-4562 ; 0946-7785
DOI	10.14573/altex.2310041
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Article ; Online: Toward implementing virtual control groups in nonclinical safety studies

Golden, Emily / Allen, David / Amberg, Alexander / Anger, Lennart T. / Baker, Elizabeth / Baran, Szczepan W. / Bringezu, Frank / Clark, Matthew / Duchateau-Nguyen, Guillemette / Escher, Sylvia / Giri, Varun / Grevot, Armelle / Hartung, Thomas / Li, Dingzhou / Lotfi, Laura / Muster, Wolfgang / Snyder, Kevin / Wange, Ronald / Steger-Hartmann, Thomas

2024

Abstract: 282 ... 301 ... Historical data from control groups in animal toxicity studies is currently mainly used for comparative purposes to assess validity and robustness of study results. Due to the highly controlled environment in which the studies are performed ... ...

Abstract	282 301 Historical data from control groups in animal toxicity studies is currently mainly used for comparative purposes to assess validity and robustness of study results. Due to the highly controlled environment in which the studies are performed and the homogeneity of the animal collectives it has been proposed to use the historical data for building so-called virtual control groups, which could replace partly or entirely the concurrent control. This would constitute a substantial contribution to the reduction of animal use in safety studies. Before the concept can be implemented, the prerequisites regarding data collection, curation and statistical evaluation together with a validation strategy need to be identified to avoid any impairment of the study outcome and subsequent consequences for human risk assessment. To further assess and develop the concept of virtual control groups the transatlantic think tank for toxicology (t4) sponsored a workshop with stakeholders from the pharmaceutical and chemical industry, academia, FDA, pharmaceutical, contract research organizations (CROs), and non-governmental organizations in Washington, which took place in March 2023. This report summarizes the current efforts of a European initiative to share, collect and curate animal control data in a centralized database and the first approaches to identify optimal matching criteria between virtual controls and the treatment arms of a study as well as first reflections about strategies for a qualification procedure and potential pitfalls of the concept. 41 2
Subject code	390
Language	English
Publishing country	de
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Introducing the concept of virtual control groups into preclinical toxicology testing.

Steger-Hartmann, Thomas / Kreuchwig, Annika / Vaas, Lea / Wichard, Jörg / Bringezu, Frank / Amberg, Alexander / Muster, Wolfgang / Pognan, Francois / Barber, Chris

ALTEX

2020 Volume 37, Issue 3, Page(s) 343–349

Abstract: Sharing legacy data from in vivo toxicity studies offers the opportunity to analyze the variability of control groups stratified for strain, age, duration of study, vehicle and other experimental conditions. Historical animal control group data may lead ... ...

Abstract	Sharing legacy data from in vivo toxicity studies offers the opportunity to analyze the variability of control groups stratified for strain, age, duration of study, vehicle and other experimental conditions. Historical animal control group data may lead to a repository, which could be used to construct virtual control groups (VCGs) for toxicity studies. VCGs are an established concept in clinical trials, but the idea of replacing living beings with virtual data sets has so far not been introduced into the design of regulatory animal studies. The use of VCGs has the potential of a 25% reduction in animal use by replacing the control group animals with existing randomized data sets. Prerequisites for such an approach are the availability of large and well-structured control data sets as well as thorough statistical evaluations. the foundation of data sharing has been laid within the Innovative Medicines Initiatives projects eTOX and eTRANSAFE. For a proof of principle participating companies have started to collect control group data for subacute (4-week) GLP studies with Wistar rats (the strain preferentially used in Europe) and are characterizing these data for its variability. In a second step, the control group data will be shared among the companies and cross-company variability will be investigated. In a third step, a set of studies will be analyzed to assess whether the use of VCG data would have influenced the outcome of the study compared to the real control group.
MeSH term(s)	Databases, Factual ; Drug Evaluation, Preclinical/methods ; Information Dissemination ; Knowledge Bases ; Research Design ; Toxicity Tests/methods
Language	English
Publishing date	2020-03-31
Publishing country	Germany
Document type	Journal Article
ZDB-ID	165707-0
ISSN	1868-596X ; 1018-4562 ; 0946-7785
ISSN	1868-596X ; 1018-4562 ; 0946-7785
DOI	10.14573/altex.2001311
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Article: Hepatotoxicity prediction by systems biology modeling of disturbed metabolic pathways using gene expression data.

Carbonell, Pablo / Lopez, Oriol / Amberg, Alexander / Pastor, Manuel / Sanz, Ferran

ALTEX

2016 Volume 34, Issue 2, Page(s) 219–234

Abstract: The present study applies a systems biology approach for the in silico predictive modeling of drug toxicity on the basis of high-quality preclinical drug toxicity data with the aim of increasing the mechanistic understanding of toxic effects of compounds ...

Abstract	The present study applies a systems biology approach for the in silico predictive modeling of drug toxicity on the basis of high-quality preclinical drug toxicity data with the aim of increasing the mechanistic understanding of toxic effects of compounds at different levels (pathway, cell, tissue, organ). The model development was carried out using 77 compounds for which gene expression data for treated primary human hepatocytes is available in the LINCS database and for which rodent in vivo hepatotoxicity information is available in the eTOX database. The data from LINCS were used to determine the type and number of pathways disturbed by each compound and to estimate the extent of disturbance (network perturbation elasticity), and were used to analyze the correspondence with the in vivo information from eTOX. Predictive models were developed through this integrative analysis, and their specificity and sensitivity were assessed. The quality of the predictions was determined on the basis of the area under the curve (AUC) of plots of true positive vs. false positive rates (ROC curves). The ROC AUC reached values of up to 0.9 (out of 1.0) for some hepatotoxicity endpoints. Moreover, the most frequently disturbed metabolic pathways were determined across the studied toxicants. They included, e.g., mitochondrial beta-oxidation of fatty acids and amino acid metabolism. The process was exemplified by successful predictions on various statins. In conclusion, an entirely new approach linking gene expression alterations to the prediction of complex organ toxicity was developed and evaluated.
MeSH term(s)	Animal Testing Alternatives ; Animals ; Databases, Factual ; Drug Evaluation, Preclinical/methods ; Drug-Related Side Effects and Adverse Reactions/genetics ; Gene Expression Regulation/genetics ; Hepatocytes/drug effects ; Humans ; In Vitro Techniques ; Liver/drug effects ; Metabolic Networks and Pathways/drug effects ; Metabolic Networks and Pathways/genetics ; Models, Statistical ; Rats ; Sensitivity and Specificity
Language	English
Publishing date	2016-09-30
Publishing country	Germany
Document type	Journal Article
ZDB-ID	165707-0
ISSN	1868-596X ; 1018-4562 ; 0946-7785
ISSN	1868-596X ; 1018-4562 ; 0946-7785
DOI	10.14573/altex.1602071
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Article ; Online: NMR and MS Methods for Metabolomics.

Amberg, Alexander / Riefke, Björn / Schlotterbeck, Götz / Ross, Alfred / Senn, Hans / Dieterle, Frank / Keck, Matthias

Methods in molecular biology (Clifton, N.J.)

2017 Volume 1641, Page(s) 229–258

Abstract: Metabolomics, also often referred as "metabolic profiling," is the systematic profiling of metabolites in biofluids or tissues of organisms and their temporal changes. In the last decade, metabolomics has become more and more popular in drug development, ...

Abstract	Metabolomics, also often referred as "metabolic profiling," is the systematic profiling of metabolites in biofluids or tissues of organisms and their temporal changes. In the last decade, metabolomics has become more and more popular in drug development, molecular medicine, and other biotechnology fields, since it profiles directly the phenotype and changes thereof in contrast to other "-omics" technologies. The increasing popularity of metabolomics has been possible only due to the enormous development in the technology and bioinformatics fields. In particular, the analytical technologies supporting metabolomics, i.e., NMR, UPLC-MS, and GC-MS, have evolved into sensitive and highly reproducible platforms allowing the determination of hundreds of metabolites in parallel. This chapter describes the best practices of metabolomics as seen today. All important steps of metabolic profiling in drug development and molecular medicine are described in great detail, starting from sample preparation to determining the measurement details of all analytical platforms, and finally to discussing the corresponding specific steps of data analysis.
MeSH term(s)	Gas Chromatography-Mass Spectrometry ; Magnetic Resonance Spectroscopy/methods ; Metabolome ; Metabolomics/methods
Language	English
Publishing date	2017
Publishing country	United States
Document type	Journal Article
ISSN	1940-6029
ISSN (online)	1940-6029
DOI	10.1007/978-1-4939-7172-5_13
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Computational Models for Human and Animal Hepatotoxicity with a Global Application Scope.

Mulliner, Denis / Schmidt, Friedemann / Stolte, Manuela / Spirkl, Hans-Peter / Czich, Andreas / Amberg, Alexander

Chemical research in toxicology

2016 Volume 29, Issue 5, Page(s) 757–767

Abstract: Hepatic toxicity is a key concern for novel pharmaceutical drugs since it is difficult to anticipate in preclinical models, and it can originate from pharmacologically unrelated drug effects, such as pathway interference, metabolism, and drug ... ...

Abstract	Hepatic toxicity is a key concern for novel pharmaceutical drugs since it is difficult to anticipate in preclinical models, and it can originate from pharmacologically unrelated drug effects, such as pathway interference, metabolism, and drug accumulation. Because liver toxicity still ranks among the top reasons for drug attrition, the reliable prediction of adverse hepatic effects is a substantial challenge in drug discovery and development. To this end, more effort needs to be focused on the development of improved predictive in-vitro and in-silico approaches. Current computational models often lack applicability to novel pharmaceutical candidates, typically due to insufficient coverage of the chemical space of interest, which is either imposed by size or diversity of the training data. Hence, there is an urgent need for better computational models to allow for the identification of safe drug candidates and to support experimental design. In this context, a large data set comprising 3712 compounds with liver related toxicity findings in humans and animals was collected from various sources. The complex pathology was clustered into 21 preclinical and human hepatotoxicity endpoints, which were organized into three levels of detail. Support vector machine models were trained for each endpoint, using optimized descriptor sets from chemometrics software. The optimized global human hepatotoxicity model has high sensitivity (68%) and excellent specificity (95%) in an internal validation set of 221 compounds. Models for preclinical endpoints performed similarly. To allow for reliable prediction of "truly external" novel compounds, all predictions are tagged with confidence parameters. These parameters are derived from a statistical analysis of the predictive probability densities. The whole approach was validated for an external validation set of 269 proprietary compounds. The models are fully integrated into our early safety in-silico workflow.
MeSH term(s)	Animals ; Area Under Curve ; Computer Simulation ; Dose-Response Relationship, Drug ; Humans ; Liver/drug effects ; Toxicity Tests
Language	English
Publishing date	2016-05-16
Publishing country	United States
Document type	Journal Article ; Validation Studies
ZDB-ID	639353-6
ISSN	1520-5010 ; 0893-228X
ISSN (online)	1520-5010
ISSN	0893-228X
DOI	10.1021/acs.chemrestox.5b00465
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Book ; Thesis: Biotransformation und Toxikokinetik der Benzinadditive Methyl-tert.-butylether (MTBE), Ethyl-tert.-butylether (ETBE) und tert.-Amyl-methylether (TAME) in Menschen und Ratten

Amberg, Alexander

2000

Author's details	von Alexander Amberg
Language	German
Size	2 Mikrofiches, graph. Darst
Document type	Book ; Thesis
Thesis / German Habilitation thesis	Univ., Diss.--Würzburg, 2000
Database	Former special subject collection: coastal and deep sea fishing

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