There are more than 7,000 identified rare and neglected diseases, yet only about 600 treatments are available. Obstacles such as incomplete knowledge of disease natural history hinder the etiology and pathogenesis understanding of rare and neglected diseases. Emerging technologies including Artificial Intelligence (AI), advanced bioengineering, and next-generation sequencing (NGS) provide unprecedented opportunity to accelerate rare and neglected disease diagnosis and treatment development.
We welcome investigators to contribute with Original Research articles, as well as Review or Opinion articles that seek to address how emerging technology can advance rare and neglected disease diagnosis and treatment development. A particular interest will be given to papers exploring or discussing the application of the integration of AI and pharmacogenomics to advance rare and neglected disease therapy development.
Potential subtopics include, but are not limited to the following:
(1) Drug repositioning for treatment development of rare and neglected diseases.
(2) AI-based mythologies and approaches for facilitating information retrieval on rare and neglected diseases.
(3) Integrative approaches of diverse biological information for rare and neglected diseases diagnosis and treatment development.
(4) Integration of pharmacogenetics/omics for enhancing drug repositioning of rare and neglected diseases.
(5) Precision medicine for treatment development of COVID-19 for different vulnerable populations and patients with different preexisting conditions.
(6) Data standardization of rare and neglected disease terminology and ontology development.
(7) Advanced techniques for efficient utilization of high-performance computing clusters and cloud systems for powering AI for rare and neglected diseases.
Topic Editor Professor Ruth Roberts is the Chair and Director of Drug Discovery at The University of Birmingham and Co-founder ApconiX Ltd. All other Topic Editors declare no competing interests with regards to the Research Topic subject.
There are more than 7,000 identified rare and neglected diseases, yet only about 600 treatments are available. Obstacles such as incomplete knowledge of disease natural history hinder the etiology and pathogenesis understanding of rare and neglected diseases. Emerging technologies including Artificial Intelligence (AI), advanced bioengineering, and next-generation sequencing (NGS) provide unprecedented opportunity to accelerate rare and neglected disease diagnosis and treatment development.
We welcome investigators to contribute with Original Research articles, as well as Review or Opinion articles that seek to address how emerging technology can advance rare and neglected disease diagnosis and treatment development. A particular interest will be given to papers exploring or discussing the application of the integration of AI and pharmacogenomics to advance rare and neglected disease therapy development.
Potential subtopics include, but are not limited to the following:
(1) Drug repositioning for treatment development of rare and neglected diseases.
(2) AI-based mythologies and approaches for facilitating information retrieval on rare and neglected diseases.
(3) Integrative approaches of diverse biological information for rare and neglected diseases diagnosis and treatment development.
(4) Integration of pharmacogenetics/omics for enhancing drug repositioning of rare and neglected diseases.
(5) Precision medicine for treatment development of COVID-19 for different vulnerable populations and patients with different preexisting conditions.
(6) Data standardization of rare and neglected disease terminology and ontology development.
(7) Advanced techniques for efficient utilization of high-performance computing clusters and cloud systems for powering AI for rare and neglected diseases.
Topic Editor Professor Ruth Roberts is the Chair and Director of Drug Discovery at The University of Birmingham and Co-founder ApconiX Ltd. All other Topic Editors declare no competing interests with regards to the Research Topic subject.