The IDG Administrative Core (AC) relies on the extensive management experience of the Oprea, Sklar and Simeonov, and also the UNMCMD program and project management infrastructure. We discuss the AC structure and personnel, the composition of an External Target Panel and External Scientific Panel, and the facilitation of communications throughout the Center and with NIH staff. This plan takes into account many years of PI/PD experience with NIH programs involving technology integration, program and project management. The plan addresses ongoing evaluation of software development progress, communications, group meetings and teleconferences, presentation and publication of data, transmission of information, as well as tracking deliverables and milestones, such as through the use of a Gantt chart. Through our participation in BARD, we are accustomed to engagement and monthly meetings with NIH program managers and external scientific review panels regarding the identification and resolution of problems. The decade of experience with the MLPCN has strengthened our ability to successfully collaborate with multiple investigators, both within and outside the United States. Our problem-solving skills, the ability to coordinate, and tele-collaborate are supported by the number of chemical probes, investigator-initiated clinical trials, as well as patented technologies and publications from our team. We have managed consortia (subcontracts) through regular communications such as periodic meetings and conference calls. Documentation of research experiments and their results will be reviewed using extensive experience. The budget process manages research-related travel through approval both at the Center and Institutional levels. The AC partners with UNM on compliance with Federal regulations, policies, and guidelines for human subject research, evaluation of risks and protections, ethical oversight, and data and safety monitoring as appropriate.
The KMC will combine unrelated informational elements from biology, chemistry and clinical sciences, and distill them into knowledge, associating diseases and proteins, to rank proteins for druggability using facts, inferences and predictions. The results, captured in the