Real-World Outcomes of Trilaciclib Among Patients with Extensive-Stage Small Cell Lung Cancer Receiving Chemotherapy.

Introduction: Trilaciclib was recently approved in the USA for reducing chemotherapy-induced myelosuppression (CIM) among adults with extensive-stage small cell lung cancer (ES-SCLC) when administered prior to chemotherapy. There is limited understanding of real-world outcomes of trilaciclib.

Methods: A comprehensive literature review was conducted using a keyword search in the MEDLINE, Embase, and conference abstracts.

Burden of chemotherapy-induced myelosuppression among patients with extensive-stage small cell lung cancer: A retrospective study from community oncology practices.

Background: Myelosuppression is a major dose-limiting complication of chemotherapy for patients with extensive-stage small cell lung cancer (ES-SCLC). The objective was to describe the burden of myelosuppression, treatment patterns, and supportive care use among patients with ES-SCLC treated with chemotherapy in a US community oncology setting.

Methods: This retrospective cohort study used structured electronic medical record (EMR) data from the Florida Cancer Specialists & Research Institute between January 2013 and December 2020.

Evaluation of freely available data profiling tools for health data research application: a functional evaluation review.

Objectives: To objectively evaluate freely available data profiling software tools using healthcare data.

Design: Data profiling tools were evaluated for their capabilities using publicly available information and data sheets. From initial assessment, several underwent further detailed evaluation for application on healthcare data using a synthetic dataset of 1000 patients and associated data using a common health data model, and tools scored based on their functionality with this dataset.

Network graph representation of COVID-19 scientific publications to aid knowledge discovery.

Introduction: Numerous scientific journal articles related to COVID-19 have been rapidly published, making navigation and understanding of relationships difficult.

Methods: A graph network was constructed from the publicly available COVID-19 Open Research Dataset (CORD-19) of COVID-19-related publications using an engine leveraging medical knowledge bases to identify discrete medical concepts and an open-source tool (Gephi) to visualise the network.

Results: The network shows connections between diseases, medications and procedures identified from the title and abstract of 195 958 COVID-19-related publications (CORD-19 Dataset).

Unsupervised 3D ring template searching as an ideas generator for scaffold hopping: use of the LAMDA, RigFit, and field-based similarity search (FBSS) methods.

Crystal structures taken from the Cambridge Structural Database were used to build a ring scaffold database containing 19 050 3D structures, with each such scaffold then being used to generate a centroid connecting path (CCP) representation. The CCP is a novel object that connects ring centroids, ring linker atoms, and other important points on the connection path between ring centroids. Unsupervised searching in the scaffold and CCP data sets was carried out using the atom-based LAMDA and RigFit search methods and the field-based similarity search method.

OptiDock: virtual HTS of combinatorial libraries by efficient sampling of binding modes in product space.

Products from combinatorial libraries generally share a common core structure that can be exploited to improve the efficiency of virtual high-throughput screening (vHTS). In general, it is more efficient to find a method that scales with the total number of reagents (Sigma growth) rather with the number of products (Pi growth). The OptiDock methodology described herein entails selecting a diverse but representative subset of compounds that span the structural space encompassed by the full library.

Evaluation of a novel molecular vibration-based descriptor (EVA) for QSAR studies: 2. Model validation using a benchmark steroid dataset.

The EVA molecular descriptor derived from calculated molecular vibrational frequencies is validated for use in QSAR studies. EVA provides a conformationally sensitive but, unlike 3D-QSAR methods such as CoMFA, superposition-free descriptor that has been shown to perform well with a wide range of datasets and biological endpoints. A detailed study is made using a benchmark steroid dataset with a training/test set division of structures.

Evaluation of quantitative structure-activity relationship methods for large-scale prediction of chemicals binding to the estrogen receptor.

Three different QSAR methods, Comparative Molecular Field Analysis (CoMFA), classical QSAR (utilizing the CODESSA program), and Hologram QSAR (HQSAR), are compared in terms of their potential for screening large data sets of chemicals as endocrine disrupting compounds (EDCs). While CoMFA and CODESSA (Comprehensive Descriptors for Structural and Statistical Analysis) have been commercially available for some time, HQSAR is a novel QSAR technique. HQSAR attempts to correlate molecular structure with biological activity for a series of compounds using molecular holograms constructed from counts of sub-structural molecular fragments.

Evaluation of a novel infrared range vibration-based descriptor (EVA) for QSAR studies. 1. General application.

A novel molecular descriptor (EVA) based upon calculated infrared range vibrational frequencies is evaluated for use in QSAR studies. The descriptor is invariant to both translation and rotation of the structures concerned. The method was applied to 11 QSAR datasets exhibiting both a range of biological endpoints and various degrees of structural diversity.

EVA: a new theoretically based molecular descriptor for use in QSAR/QSPR analysis.

A new descriptor of molecular structure, EVA, for use in the derivation of robustly predictive QSAR relationships is described. It is based on theoretically derived normal coordinate frequencies, and has been used extensively and successfully in proprietary chemical discovery programmes within Shell Research. As a result of informal dissemination of the methodology, it is now being used successfully in related areas such as pharmaceutical drug discovery.