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BACKGROUND: Older adults with multimorbidity are under-represented in clinical drug trials. Their inclusion will not increase unless they are willing and able to participate. Data on motivators and barriers to participation in trials of new medications of older adults with multimorbidity are needed. METHODS: Cross-sectional internet and telephone survey of a nationally representative sample of adults ≥65 years with ≥3 chronic conditions (NORC University of Chicago Amerispeak Panel) conducted from March-April, 2023 to determine motivators and barriers to drug trial participation, described graphically and using statistics. RESULTS: Surveyed 1318 (1142 Internet, 176 phone) with mean age 72.3 ± 6.3 (SD), 52% women; race: 83% White, 10% Black or African American, 5% Hispanic or Latino, 1.1% Asian; 4.4 ± 1.9 chronic conditions (of 16 queried), taking 7.5 ± 3.3 medications. Barriers included fear of side effects (48%), taking too many medications (44%), placebo (44%), mobility (33%), bathroom needs (25%), hearing (19%), eyesight (15%), video visits (33%; higher in women, Black or African-American respondents, and those ≥80 years). Sixty-five percent would join all in-person trials, 49% would join all-video trials. Travel >1 h was difficult for 66%, most difficult for women. Trust was a concern in 25% of Black respondents. Caregiving responsibilities or lack of time were not obstacles. Participants were most likely to consider a drug trial for a problem they have (63%) versus prevention (44%) and if invited by a physician (80%) or University healthcare system (58%). Getting better care was ranked very important (79%) followed by helping others (57%). CONCLUSIONS: Major concerns of older patients with multimorbidity about participation in drug trials are potential side effects, taking too many medicines, and video visits. Physicians have the greatest influence on decisions and in-person visits are preferred. Proposed changes in trial design to increase enrollment of under-represented older adults may not align with patient-reported preferences.

Visapult is a prototype application and framework for remote visualization oflarge scientific datasets. We approach the technical challenges of tera-scalevisualization with a unique architecture that employs high speed WANs andnetwork data caches for data staging and transmission. This architecture allowsfor the use of available cache and compute resources at arbitrary locations onthe network. High data throughput rates and network utilization are achieved byparallelizing I/O at each stage in the application, and by pipelining thevisualization process. On the desktop, the graphics interactivity iseffectively decoupled from the latency inherent in network applications. Wepresent a detailed performance analysis of the application, and improvementsresulting from field-test analysis conducted as part of the DOE CombustionCorridor project.