Standardization of key performance indicators and metrics for investigational drug services (IDS): Consensus recommendations among IDS specialists.

DISCLAIMER: In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. PURPOSE: There are currently no consensus guidelines on establishing metrics for investigational drug services (IDS). Because of the complexity of research protocols, it remains difficult for sites to track pharmacy productivity and create a baseline for IDS growth within the institution, as well as to perform benchmarking with peer institutions. The goal of this study was to help establish practical guidance for IDS metrics and site utility as applicable. METHODS: This was a survey-based project conducted by the metrics subgroup of the Hematology/Oncology Pharmacy Association (HOPA) IDS special interest group (SIG), which was formed specifically for this analysis. Three surveys developed by the metrics subgroup were sent to members of the IDS HOPA SIG to gather metrics. The first survey included questions about what metrics IDS sites currently collect. The identified metrics were then condensed into categories. Through a consensus-based approach, standardized definitions were established and applied to future surveys. The 2 subsequent surveys sent to HOPA SIG members helped create a list of top recommended metrics that are recommended for every IDS site to track. RESULTS: A total of 3 surveys were sent to 75 recipients, with the response rate ranging from 24% to 38%. From these surveys and consensus with the metrics subgroup, 5 top recommended metrics were identified: (1) active protocols; (2) dispenses; (3) new clinical trials initiated; (4) patients treated; and (5) clinical interventions. CONCLUSION: These recommended metrics should serve as guidance and allow for standardization to help ensure adequate resources are available for IDS pharmacy staff. These recommendations should serve as a basis for standardization and benchmarking with peer institutions.

Identification of GDC-1971 (RLY-1971), a SHP2 Inhibitor Designed for the Treatment of Solid Tumors.

Protein tyrosine phosphatase SHP2 mediates RAS-driven MAPK signaling and has emerged in recent years as a target of interest in oncology, both for treating with a single agent and in combination with a KRAS inhibitor. We were drawn to the pharmacological potential of SHP2 inhibition, especially following the initial observation that drug-like compounds could bind an allosteric site and enforce a closed, inactive state of the enzyme. Here, we describe the identification and characterization of GDC-1971 (formerly RLY-1971), a SHP2 inhibitor currently in clinical trials in combination with KRAS G12C inhibitor divarasib (GDC-6036) for the treatment of solid tumors driven by a KRAS G12C mutation.

Mollack: a web server for the automated creation of conformational ensembles for intrinsically disordered proteins.

UNLABELLED: Intrinsically disordered proteins (IDPs) play central roles in many biological processes. Consequently, an accurate description of the disordered state is an important step towards a comprehensive understanding of a number of important biological functions. In this work we describe a new web server, Mollack, for the automated construction of unfolded ensembles that uses both experimental and molecular simulation data to construct models for the unfolded state. An important aspect of the method is that it calculates a quantitative estimate of the uncertainty in the constructed ensemble, thereby providing an objective measure of the quality of the final model. Overall, Mollack facilitates structure-function studies of disordered proteins. AVAILABILITY AND IMPLEMENTATION: http://cmstultz-mollack.mit.edu CONTACT: cmstultz@mit.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Analyzing Ensembles of Amyloid Proteins Using Bayesian Statistics.

Intrinsically disordered proteins (IDPs) are notoriously difficult to study experimentally because they rapidly interconvert between many dissimilar conformations during their biological lifetime, and therefore cannot be described by a single structure. The importance of studying these systems, however, is underscored by the fact that they form toxic aggregates that play a role in the pathogenesis of many disorders. The first step towards a comprehensive understanding of the aggregation mechanism of these proteins involves a description of their thermally accessible states under physiologic conditions. The resulting conformational ensembles correspond to coarse-grained descriptions of their energy landscapes, where the number of structures in the ensemble is related to the resolution in which one views the free energy surface. Here, we provide step-by-step instructions on how to use experimental data to construct a conformational ensemble for an IDP using a Variational Bayesian Weighting (VBW) algorithm. We further discuss how to leverage this Bayesian approach to identify statistically significant ensemble-wide observations that can form the basis of further experimental studies.

Brief communication: correcting overestimation when determining two-dimensional occlusal area in human molars.

The robustness index (RI) is determined by multiplying dental mesiodistal and buccolingual diameters, and is used to estimate occlusal area. However, because teeth are not rectangular its calculation consistently causes overestimations. Moreover, teeth, in particular molars, are not identically shaped so overestimations vary. The current study seeks to determine the extent to which overestimations are affected by tooth shape and to improve RI's efficacy. Initially, 120 molars were sorted into six shape groups, which were determined by hypocone/hypoconulid expression. Three maxillary and three mandibular shape groups were set using the Arizona State University Dental Anthropology System. ANOVA results determined that RI overestimations, which averaged around 20%, were not the same for each shape category. Maxillary molars with large hypocones and mandibular molars with no hypoconulids were overestimated significantly less than the other molar groups. Regression-based correction formulae were generated and applied to the original sample. These formulae far more precisely estimated tooth area than RI and there were no differences in estimation based upon tooth shape. A subsequent validation study of 24 additional molars was undertaken to test the formulae on teeth not from the original sample. Overestimation/underestimation averaged 0.5% and was about the same for each of the tooth shape groups. Finally, six new correction formulae were generated using all 144 molars. The correction formulae provide, what is termed here, an adjusted robustness index (ARI), and it is recommended that ARI is used in future studies of molar occlusal area.