Title:Neural Networks of Knowledge: Ontologies Pioneering Precision Medicine in Neurodegenerative Diseases
Volume: 23
Issue: 14
Author(s): Pooja Mittal, Rupesh Kumar Gautam*, Himanshu Sharma, Rajat Goyal, Garima, Ramit Kapoor, Dileep Kumar, Mohammad Amjad Kamal*, Shafiul Haque and Siva Nageswara Rao Gajula
Affiliation:
- Department of Pharmacology, Indore Institute of Pharmacy, IIST Campus, Rau, Indore, India
- Department of Pharmaceutical
Sciences, College of Pharmacy, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia
- Department of
Pharmacy, Faculty of Allied Health Sciences, Daffodil International University, Dhaka, Bangladesh
- Centre for Global
Health Research, Saveetha Medical College and Hospital, Saveetha Institute of Medical and Technical Sciences,
Chennai, Tamil Nadu, India
- Department of Health Sciences, Faculty of Science, Novel Global Community Educational
Foundation, Hebersham, New South Wales, Australia
Keywords:
Neurodegenerative, ontologies, precision medicine, Alzheimer's, Parkinson's, Huntington's.
Abstract: The review focuses on the ways that ontologies are revolutionising precision medicine in
their effort to understand neurodegenerative illnesses. Ontologies, which are structured frameworks
that outline the relationships between concepts in a certain field, offer a crucial foundation for
combining different biological data. Novel insights into the construction of a precision medicine
approach to treat neurodegenerative diseases (NDDs) are given by growing advancements in the area
of pharmacogenomics. Affected parts of the central nervous system may develop neurological
disorders, including Alzheimer's, Parkinson's, autism spectrum, and attention-deficit/hyperactivity
disorder. These models allow for standard and helpful data marking, which is needed for crossdisciplinary
study and teamwork. With case studies, you can see how ontologies have been used to
find biomarkers, understand how sicknesses work, and make models for predicting how drugs will
work and how the disease will get worse. For example, problems with data quality, meaning variety,
and the need for constant changes to reflect the growing body of scientific knowledge are discussed
in this review. It also looks at how semantic data can be mixed with cutting-edge computer methods
such as artificial intelligence and machine learning to make brain disease diagnostic and prediction
models more exact and accurate. These collaborative networks aim to identify patients at risk,
identify patients in the preclinical or early stages of illness, and develop tailored preventative
interventions to enhance patient quality of life and prognosis. They also seek to identify new, robust,
and effective methods for these patient identification tasks. To this end, the current study has been
considered to examine the essential components that may be part of precise and tailored therapy
plans used for neurodegenerative illnesses.
