The field of transcriptomics has expanded rapidly during the last decades. This methodology provides an exceptional framework to study not only molecular changes underlying the adverse effects of a given compound, but also to understand its Mode of Action (MoA). However, the implementation of transcriptomics-based tests within the regulatory arena is not a straightforward process. One of the major obstacles in their regulatory implementation is still the interpretation of this new class of data and the judgment of the level of confidence of these tests. A key element in the regulatory acceptance of transcriptomics-based tests is validation, which still represents a major challenge. Although important advances have been made in the development and standardisation of such tests, to date there is limited experience with their validation. Taking into account the experience acquired so far, this chapter describes those aspects that were identified as important in the validation process of transcriptomics-based tests, including the assessment of standardisation, reliability and relevance. It also critically discusses the challenges posed to validation in relation to the specific characteristics of these approaches and their application in the wider context of testing strategies.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/978-3-319-33826-2_10 | DOI Listing |
Front Plant Sci
September 2024
Cotton Biotechnology, Agriculture and Food, CSIRO, Canberra, ACT, Australia.
Cultivated cotton plants are the world's largest source of natural fibre, where yield and quality are key traits for this renewable and biodegradable commodity. The cotton genome contains ~80K protein-coding genes, making precision breeding of complex traits a challenge. This study tested approaches to improving the genomic prediction (GP) accuracy of valuable cotton fibre traits to help accelerate precision breeding.
View Article and Find Full Text PDFNPJ Precis Oncol
August 2024
Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA.
In this study, we leveraged machine-learning tools by evaluating expression of genes of pharmacological relevance to standard-AML chemotherapy (ara-C/daunorubicin/etoposide) in a discovery-cohort of pediatric AML patients (N = 163; NCT00136084 ) and defined a 5-gene-drug resistance score (ADE-RS5) that was predictive of outcome (high MRD1 positivity p = 0.013; lower EFS p < 0.0001 and OS p < 0.
View Article and Find Full Text PDFNat Rev Cardiol
September 2024
BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Assessing atherosclerosis severity is essential for precise patient stratification. Specifically, there is a need to identify patients with residual inflammation because these patients remain at high risk of cardiovascular events despite optimal management of cardiovascular risk factors. Molecular imaging techniques, such as PET, can have an essential role in this context.
View Article and Find Full Text PDFToxicol Mech Methods
September 2024
ScitoVation, Durham, NC, USA.
Background: The TGx-DDI biomarker identifies transcripts specifically induced by primary DNA damage. Profiling similarity of TGx-DDI signatures can allow clustering compounds by genotoxic mechanism. This transcriptomics-based approach complements conventional toxicology testing by enhancing mechanistic resolution.
View Article and Find Full Text PDFJ Exp Med
May 2024
Department of Hematology, Leiden University Medical Center, Leiden, Netherlands.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!