Knowledge Engineering for PharmacoGenomic Molecular Imaging of the Brain

Schizophrenia, Alzheimer’s disease, Parkinson’s disease, and other neuropsychiatric degenerative disorders and dementias impose an enormous economic and psychosocial burden on society, communities, and families. In order to gain a better understanding of gene-brain-behavior relationships, improve treatment, and find cures for these diseases, translational research must be conducted with clinical trials of new drugs and other interventions followed by genotyping and imaging biomarkers for patients with these neuropyschiatric degenerative disorders. This research, involving pharmacogenomic molecular imaging of the brain, will be extremely costly in many ways. Therefore, knowledge engineering with effective software tools and applications built upon a semantic-enabled informatics infrastructure remains a necessary prerequisite to facilitate a reduction of those research costs by maximizing the benefit obtained from existing data and minimizing the cost of generating new data. A knowledge engineering framework that serves this goal must operate in a cross-disciplinary manner that integrates data from diverse biomedical fields while at the same time incorporating the relevant computational mathematics, statistics, and informatics analyses for productive data mining.