Drug repurposing is the application of approved drugs to treat diseases separate and distinct from their original indications. Herein, we define the scope of all practical precision drug repurposing using DrugBank, a publicly available database of pharmacological agents, and BioVU, a large, de-identified DNA repository linked to longitudinal electronic health records at Vanderbilt University Medical Center. We present a method of repurposing candidate prioritization through integration of pharmacodynamic and marketing variables from DrugBank with quality control thresholds for genomic data derived from the DNA samples within BioVU. Through the synergy of delineated “target-action pairs,” along with target genomics, we identify ∼230 “pairs” that represent all practical opportunities for genomic drug repurposing. From this analysis, we present a pipeline of 14 repurposing candidates across 7 disease areas that link to our repurposability platform and present high potential for randomized controlled trial startup in upcoming months.

Fiducial markers are reference points used in the registration of image space(s) with physical (patient) space. As applied to interactive, image-guided surgery, the registration of image space with physical space allows the current location of a surgical tool to be indicated on a computer display of patient-specific preoperative images. This intrasurgical guidance information is particularly valuable in surgery within the brain, where visual feedback is limited. The accuracy of the mapping between physical and image space depends upon the accuracy with which the fiducial markers were located in each coordinate system. To effect accurate space registration for interactive, image-guided neurosurgery, the use of permanent fiducial markers implanted into the surface of the skull is proposed in this paper. These small cylindrical markers are composed of materials that make them visible in the image sets. The challenge lies in locating the subcutaneous markers in physical space. This paper presents an ultrasonic technique for transcutaneously detecting the location of these markers. The technique incorporates an algorithm based on detection of characteristic properties of the reflected A-mode ultrasonic waveform. The results demonstrate that ultrasound is an appropriate technique for accurate transcutaneous marker localization. The companion paper to this article describes an automatic, enhanced implementation of the marker-localization theory described in this article.

No abstract

Registration of image space and physical space lies at the heart of any interactive, image-guided neurosurgery system. This paper, in conjunction with the previous companion paper [1], describes a localization technique that enables bone-implanted fiducial markers to be used for the registration of these spaces. The nature of these subcutaneous markers allows for their long-term use for registration which is desirable for surgical follow-up, monitoring of therapy efficacy, and performing fractionated stereotactic radiosurgery. The major challenge to using implanted markers is determining the location of the markers in physical space after implantation. The A-mode ultrasonic technique described here is capable of determining the three-dimensional (3-D) location of small implanted cylindrical markers. Accuracy tests were conducted on a phantom representing a human head. The accuracy of the system was characterized by comparing the location of a marker analogue as determined with an optically tracked pointer and the location as determined with the ultrasonic localization. Analyzing the phantom in several orientations revealed a mean system accuracy of 0.5 mm with a +/- 0.1-mm 95% confidence interval. These tests indicate that transcutaneous localization of implanted fiducial markers is possible with a high degree of accuracy.

Objective To describe content domains and applications of the IeDEA Data Exchange Standard, its development history, governance structure, and relationships to other established data models, as well as to share open source, reusable, scalable, and adaptable implementation tools with the informatics community. Methods In 2012, the International Epidemiology Databases to Evaluate AIDS (IeDEA) collaboration began development of a data exchange standard, the IeDEA DES, to support collaborative global HIV epidemiology research. With the HIV Cohorts Data Exchange Protocol as a template, a global group of data managers, statisticians, clinicians, informaticians, and epidemiologists reviewed existing data schemas and clinic data procedures to develop the HIV data exchange model. The model received a substantial update in 2017, with annual updates thereafter. Findings The resulting IeDEA DES is a patient-centric common data model designed for HIV research that has been informed by established data models from US-based electronic health records, broad experience in data collection in resource-limited settings, and informatics best practices. The IeDEA DES is inherently flexible and continues to grow based on the ongoing stewardship of the IeDEA Data Harmonization Working Group with input from external collaborators. Use of the IeDEA DES has improved multiregional collaboration within and beyond IeDEA, expediting over 95 multiregional research projects using data from more than 400 HIV care and treatment sites across seven global regions. A detailed data model specification and REDCap data entry templates that implement the IeDEA DES are publicly available on GitHub. Conclusions The IeDEA common data model and related resources are powerful tools to foster collaboration and accelerate science across research networks. While currently directed towards observational HIV research and data from resource-limited settings, this model is flexible and extendable to other areas of health research.