Nuclear medicine is the second largest source of medical radiation exposure to the general population after computed tomography imaging. Imaging modalities utilizing nuclear medicine produce a more detailed view of internal structure and function and are most commonly used to diagnose diseases such as heart disease, Alzheimer’s and brain disorders. They are used to visualize tumors, abscesses due to infection or abnormalities in abdominal organs.

Drug delivery technologies have long claimed the ability to selectively deliver therapeutic cargo to target cells. Despite advances in nanomedicine and drug delivery systems, there are no targeted nanoscale drug delivery technologies on the market. Thus, there is still tremendous potential in improved therapeutic efficacy when targeted drug delivery is achieved. 

Traumatic brain injury (TBI) is a major health problem.  Between 3.2 and 5.3 million people live with long-term disabilities resulting from TBI, and thus, contribute to the need to develop therapies that treat TBI-induced cellular damage. Researchers at the National Institute of Child Health and Human Development (NICHD) have developed a device that simulates the pressure waves resulting from explosions.

Rhabdomyosarcoma (RMS) is the most common type of soft tissue sarcoma in children and makes up 3% of all childhood cancers. Aveloar Rhabdomyosarcoma is the most aggressive subtype and is primarily established through a chromosomal translocation resulting in the fusion protein PAX3-FOXO1. Despite aggressive therapy, the 5-year survival rate for patients with high risk or recurrent Fusion Positive RMS (FP-RMS) is low (~30% and ~17%, respectively). Therefore, new therapies targeting the PAX3-FOXO1 oncogenic driver are urgently needed.  

There are no effective treatments for Alzheimer’s disease (AD), a progressive brain disease that slowly destroys a person’s memory, cognitive skills and ability to carry out the simplest tasks. AD affects more than 5 million individuals in the United States and ranks as the sixth leading cause of death. The ε4 allele of the apolipoprotein-E (APOE) gene is the strongest genetic risk factor for sporadic or late-onset AD. Heterozygous carriers of the ε4 allele are at three-to-four times greater risk; homozygous carriers are at ten times greater risk.

Due to the large degree of homology among dopamine D2-like receptors, discovering ligands capable of discriminating between the D2, D3, and D4 receptor subtypes remains a significant challenge. The development of subtype-selective pharmaceutical small molecules to activate (agonists) signals regulated by D2-like receptors has been especially difficult. 

Computer and imaging technologies led to the development of digital pathology and the capture and storage of pathological specimens as digitally formatted images. The use of artificial intelligence (AI) in digital pathology, such as in three-dimensional (3D) reconstruction, requires analyses of high volumes of data. This results in increased demands for processing and acquisition of digital images of pathology samples. Increased usage cannot be met by the time-consuming, manual, and laborious methods currently used.

There are no analgesics to ameliorate chronic pain without adverse side-effects (e.g., respiratory depression, gastrointestinal effects, tolerance, dependence), thus forcing patients into a difficult choice of negative impacts on quality of life. Most of the analgesics used for chronic and acute pain are drugs such as oxycodone, morphine, oxymorphone, and codeine. All of these opioids have been subject to misuse; prescription drug abuse is a severe problem worldwide, causing high mortality and greatly increased emergency room visits.

The available system is the Human Research Information System (HuRIS), an integrated advanced clinical/research informatics series of systems—that is, an intelligent electronic environment for the collection, organization and retrieval of information in clinical/scientific decision support—which enables data and resource sharing in real time among authorized users at our clinics. (Individual systems or subsystems may be licensable.)

Computer and imaging technologies led to the development of digital pathology and the capture and storage of pathological specimens as digitally formatted images. The use of artificial intelligence (AI) in digital pathology, such as in three-dimensional (3D) reconstruction, requires analyses of high volumes of data. This resulted in increased demands for processing and acquisition of digital images of pathology samples. Increased usage cannot be met by the time-consuming, manual, and laborious methods currently used.