Characterizing perceptions of an abbreviated ISMP Medication Safety Self Assessment for community pharmacies.

OBJECTIVES: This study sought to characterize users' perceptions of, and identify the average time needed to complete a newly abbreviated version of the Institute for Safe Medication Practices Medication Safety Self Assessment for Community and Ambulatory Pharmacy (MSSA-CAP). METHODS: This study took place within a large, national, nonprofit, faith-based health system. An abbreviated version of ISMP's MSSA-CAP was developed through an iterative process by researchers and the health system's medication safety officers (MSOs, i.e., the assessment tool's 'users'). Retained items included those with nonoverlapping (1) bolded or keywords; (2) "quick asks," answerable without external information; or (3) were relevant to community pharmacy practice (i.e., nonambulatory care-specific). During site visits, MSOs assessed the organization's community pharmacies with the abbreviated tool. Users completed pre- and post-visit surveys asking their perceptions of and time spent using the full and abbreviated versions of the MSSA-CAP. Results were analyzed using descriptive statistics. RESULTS: Sixty of the original MSSA-CAP's 216 items were retained. Between August to December 2019, six MSO users assessed 59 community pharmacies across 10 states with the abbreviated assessment tool. On the average, users reported needing 86.1 ± 35.4 minutes to complete the abbreviated assessment. Sixty-seven percent of users agreed or strongly agreed that the abbreviated assessment was of a good length, compared with only 17% for the original full assessment. Collectively, assessed community pharmacies scored highest on MSSA-CAP items related to Physical Environment and Prescription Labels, and lowest on Hard Stops and Proactive Risk Assessments. CONCLUSION: Streamlining items in medication safety assessment tools may be useful in overcoming time barriers to implementation in community pharmacies.

Small molecule scaffolds that disrupt the Rev1-CT/RIR protein-protein interaction.

Translesion synthesis (TLS) is a DNA damage tolerance mechanism that allows replicative bypass of DNA lesions, including DNA adducts formed by cancer chemotherapeutics. Previous studies demonstrated that suppression of TLS can increase sensitivity of cancer cells to first-line chemotherapeutics and decrease mutagenesis linked to the onset of chemoresistance, marking the TLS pathway as an emerging therapeutic target. TLS is mediated by a heteroprotein complex consisting of specialized DNA polymerases, including the Y-family DNA polymerase Rev1. Previously, we developed a screening assay to identify the first small molecules that disrupt the protein-protein interaction between the C-terminal domain of Rev1 (Rev1-CT) and the Rev1-interacting region (RIR) present in multiple DNA polymerases involved in TLS. Herein we report additional hit scaffolds that inhibit this key TLS PPI. In addition, through a series of biochemical, computational, and cellular studies we have identified preliminary structure-activity relationships and determined initial pharmacokinetic parameters for our original hits.

A review of the peak-end rule in mental health contexts.

The peak-end rule, a memory heuristic in which the most emotionally salient part of an experience (i.e., peak) and conclusion of an experience (i.e., end) are weighted more heavily in summary evaluations, has been understudied in mental health contexts. The recent growth of intensive longitudinal methods has provided new opportunities for examining the peak-end rule in the retrospective recall of mental health symptoms, including measures often used in measurement-based care initiatives. Additionally, principles of the peak-end rule have significant potential to be applied to exposure-based therapy procedures. Additional research is needed to better understand the contexts in which, and persons for whom, the peak-end rule presents a greater risk of bias, to ultimately improve assessment strategies and clinical care.

Intensive longitudinal assessment following index trauma to predict development of PTSD using machine learning.

There are significant challenges to identifying which individuals require intervention following exposure to trauma, and a need for strategies to identify and provide individuals at risk for developing PTSD with timely interventions. The present study seeks to identify a minimal set of trauma-related symptoms, assessed during the weeks following traumatic exposure, that can accurately predict PTSD. Participants were 2185 adults (Mean age=36.4 years; 64% women; 50% Black) presenting for emergency care following traumatic exposure. Participants received a 'flash survey' with 6-8 varying symptoms (from a pool of 26 trauma symptoms) several times per week for eight weeks following the trauma exposure (each symptom assessed ∼6 times). Features (mean, sd, last, worst, peak-end scores) from the repeatedly assessed symptoms were included as candidate variables in a CART machine learning analysis to develop a pragmatic predictive algorithm. PTSD (PCL-5 ≥38) was present for 669 (31%) participants at the 8-week follow-up. A classification tree with three splits, based on mean scores of nervousness, rehashing, and fatigue, predicted PTSD with an Area Under the Curve of 0.836. Findings suggest feasibility for a 3-item assessment protocol, delivered once per week, following traumatic exposure to assess and potentially facilitate follow-up care for those at risk.

Virtual Pharmacophore Screening Identifies Small-Molecule Inhibitors of the Rev1-CT/RIR Protein-Protein Interaction.

Translesion synthesis (TLS) has emerged as a mechanism through which several forms of cancer develop acquired resistance to first-line genotoxic chemotherapies by allowing replication to continue in the presence of damaged DNA. Small molecules that inhibit TLS hold promise as a novel class of anticancer agents that can serve to enhance the efficacy of these front-line therapies. We previously used a structure-based rational design approach to identify the phenazopyridine scaffold as an inhibitor of TLS that functions by disrupting the protein-protein interaction (PPI) between the C-terminal domain of the TLS DNA polymerase Rev1 (Rev1-CT) and the Rev1 interacting regions (RIR) of other TLS DNA polymerases. To continue the identification of small molecules that disrupt the Rev1-CT/RIR PPI, we generated a pharmacophore model based on the phenazopyridine scaffold and used it in a structure-based virtual screen. In vitro analysis of promising hits identified several new chemotypes with the ability to disrupt this key TLS PPI. In addition, several of these compounds were found to enhance the efficacy of cisplatin in cultured cells, highlighting their anti-TLS potential.