12 research outputs found
Prospectus, April 10, 1985
https://spark.parkland.edu/prospectus_1985/1009/thumbnail.jp
The SFA Business Review Vol. 3 No. 1
https://scholarworks.sfasu.edu/busreview/1004/thumbnail.jp
AI is a viable alternative to high throughput screening: a 318-target study
: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery
A protocol for the Heart Matters stepped wedge cluster randomised trial: The effectiveness of heart attack education in regions at highest-risk
Aim: To describe the Heart Matters (HM) trial which aims to evaluate the effectiveness of a community heart attack education intervention in high-risk areas in Victoria, Australia. These local government areas (LGAs) have high rates of acute coronary syndrome (ACS), out-of-hospital cardiac arrest (OHCA), cardiovascular risk factors, and low rates of emergency medical service (EMS) use for ACS. Methods: The trial follows a stepped-wedge cluster randomised design, with eight clusters (high-risk LGAs) randomly assigned to transition from control to intervention every four months. Two pairs of LGAs will transition simultaneously due to their proximity. The intervention consists of a heart attack education program delivered by trained HM Coordinators, with additional support from opportunistic media and a geo-targeted social media campaign. The primary outcome measure is the proportion of residents from the eight LGAs who present to emergency departments by EMS during an ACS event. Secondary outcomes include prehospital delay time, rates of OHCA and heart attack awareness. The primary and secondary outcomes will be analysed at the patient/participant level using mixed-effects logistic regression models. A detailed program evaluation is also being conducted. The trial was registered on August 9, 2021 (NCT04995900). Results: The intervention was implemented between February 2022 and March 2023, and outcome data will be collected from administrative databases, registries, and surveys. Primary trial data is expected to be locked for analysis by October 31st 2023, with a follow-up planned until March 31st 2024. Conclusion: The results from this trial will provide high-level evidence the effectiveness of a community education intervention targeting regions at highest-risk of ACS and low EMS use