About this Research Topic
Respiratory diseases represent a high and growing epidemiological burden worldwide and have relevant implications in terms of mortality, morbidity and health care costs.
Respiratory diseases are very heterogeneous diseases. However, the endotypes, that is the disease molecular mechanisms, underlying this heterogeneity are largely unknown.
The current evidence-based, one-fits-all, pharmacotherapeutic approach is not suitable to predict drug effects at the individual level.
Molecular phenotyping of respiratory diseases, a top priority in this research area, aims to identify subgroups of persons with poorer prognosis and frequent exacerbations who require more intense and earlier pharmacological intervention, and responders to pharmacotherapy to avoid unnecessary drug exposure and reduce health care costs.
The combination of multi-omics platforms with artificial intelligence techniques, including machine learning algorithms, and their application to biomedical research, has been improving our understanding of disease pathways and represent a powerful tool for endotyping of respiratory diseases, paving the way for personalised pharmacotherapeutic strategies.
This Research Topic aims to present and discuss innovative diagnostic approaches and the pharmacological implications of molecular phenotyping and endotyping of respiratory diseases, including asthma, chronic obstructive pulmonary disease (COPD), interstitial lung disease, and lung cancer. New targeted therapies, including biologics and small molecules, and unbiased integrated multidimensional approaches to pinpoint disease pathways and discover potential new targets for the development of innovative personalised pharmacotherapies in respiratory disease, will be presented.
We welcome Original Research articles, Review articles, Case Studies, and other scholarly contributions that push the boundaries of knowledge and address unmet needs in this research area.
Respiratory diseases are very heterogeneous diseases. However, the endotypes, that is the disease molecular mechanisms, underlying this heterogeneity are largely unknown.
The current evidence-based, one-fits-all, pharmacotherapeutic approach is not suitable to predict drug effects at the individual level.
Molecular phenotyping of respiratory diseases, a top priority in this research area, aims to identify subgroups of persons with poorer prognosis and frequent exacerbations who require more intense and earlier pharmacological intervention, and responders to pharmacotherapy to avoid unnecessary drug exposure and reduce health care costs.
The combination of multi-omics platforms with artificial intelligence techniques, including machine learning algorithms, and their application to biomedical research, has been improving our understanding of disease pathways and represent a powerful tool for endotyping of respiratory diseases, paving the way for personalised pharmacotherapeutic strategies.
This Research Topic aims to present and discuss innovative diagnostic approaches and the pharmacological implications of molecular phenotyping and endotyping of respiratory diseases, including asthma, chronic obstructive pulmonary disease (COPD), interstitial lung disease, and lung cancer. New targeted therapies, including biologics and small molecules, and unbiased integrated multidimensional approaches to pinpoint disease pathways and discover potential new targets for the development of innovative personalised pharmacotherapies in respiratory disease, will be presented.
We welcome Original Research articles, Review articles, Case Studies, and other scholarly contributions that push the boundaries of knowledge and address unmet needs in this research area.
Keywords: respiratory diseases, pharmacology, omics, artificial intelligence, machine learning, targeted pharmacotherapies, personalised pharmacotherapies, drug development
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
