A qualitative exploration of barriers to efficient and effective structured medication reviews in primary care: Findings from the DynAIRx study.

Introduction: Structured medication reviews (SMRs), introduced in the United Kingdom (UK) in 2020, aim to enhance shared decision-making in medication optimisation, particularly for patients with multimorbidity and polypharmacy. Despite its potential, there is limited empirical evidence on the implementation of SMRs, and the challenges faced in the process. This study is part of a larger DynAIRx (Artificial Intelligence for dynamic prescribing optimisation and care integration in multimorbidity) project which aims to introduce Artificial Intelligence (AI) to SMRs and develop machine learning models and visualisation tools for patients with multimorbidity.

Targeting myeloid chemotaxis to reverse prostate cancer therapy resistance.

Inflammation is a hallmark of cancer. In patients with cancer, peripheral blood myeloid expansion, indicated by a high neutrophil-to-lymphocyte ratio, associates with shorter survival and treatment resistance across malignancies and therapeutic modalities. Whether myeloid inflammation drives progression of prostate cancer in humans remain unclear.

Tasks and Visualizations Used for Data Profiling: A Survey and Interview Study.

The use of good-quality data to inform decision making is entirely dependent on robust processes to ensure it is fit for purpose. Such processes vary between organisations, and between those tasked with designing and following them. In this article we report on a survey of 53 data analysts from many industry sectors, 24 of whom also participated in in-depth interviews, about computational and visual methods for characterizing data and investigating data quality.

The DynAIRx Project Protocol: Artificial Intelligence for dynamic prescribing optimisation and care integration in multimorbidity.

Background: Structured Medication Reviews (SMRs) are intended to help deliver the NHS Long Term Plan for medicines optimisation in people living with multiple long-term conditions and polypharmacy. It is challenging to gather the information needed for these reviews due to poor integration of health records across providers and there is little guidance on how to identify those patients most urgently requiring review.

Objective: To extract information from scattered clinical records on how health and medications change over time, apply interpretable artificial intelligence (AI) approaches to predict risks of poor outcomes and overlay this information on care records to inform SMRs.

Using set visualisation to find and explain patterns of missing values: a case study with NHS hospital episode statistics data.

Objectives: Missing data is the most common data quality issue in electronic health records (EHRs). Missing data checks implemented in common analytical software are typically limited to counting the number of missing values in individual fields, but researchers and organisations also need to understand multifield missing data patterns to better inform advanced missing data strategies for which counts or numerical summaries are poorly suited. This study shows how set-based visualisation enables multifield missing data patterns to be discovered and investigated.

Faster than light (microscopy): superiority of digital pathology over microscopy for assessment of immunohistochemistry.

Aims: Digital pathology offers the potential for significant benefits in diagnostic pathology, but currently the efficiency of slide viewing is a barrier to adoption. We hypothesised that presenting digital slides for simultaneous viewing of multiple sections of tissue for comparison, as in those with immunohistochemical panels, would allow pathologists to review cases more quickly.

Methods: Novel software was developed to view synchronised parallel tissue sections on a digital pathology workstation.

Analysis of a Web-Based Dashboard to Support the Use of National Audit Data in Quality Improvement: Realist Evaluation.

Background: Dashboards can support data-driven quality improvements in health care. They visualize data in ways intended to ease cognitive load and support data comprehension, but how they are best integrated into working practices needs further investigation.

Objective: This paper reports the findings of a realist evaluation of a web-based quality dashboard (QualDash) developed to support the use of national audit data in quality improvement.

Repurposing Vandetanib plus Everolimus for the Treatment of -Mutant Diffuse Intrinsic Pontine Glioma.

Somatic mutations in are found in a quarter of children with diffuse intrinsic pontine glioma (DIPG), but there are no ACVR1 inhibitors licensed for the disease. Using an artificial intelligence-based platform to search for approved compounds for -mutant DIPG, the combination of vandetanib and everolimus was identified as a possible therapeutic approach. Vandetanib, an inhibitor of VEGFR/RET/EGFR, was found to target ACVR1 ( = 150 nmol/L) and reduce DIPG cell viability but has limited ability to cross the blood-brain barrier.

Hidden labour: the skilful work of clinical audit data collection and its implications for secondary use of data via integrated health IT.

Background: Secondary use of data via integrated health information technology is fundamental to many healthcare policies and processes worldwide. However, repurposing data can be problematic and little research has been undertaken into the everyday practicalities of inter-system data sharing that helps explain why this is so, especially within (as opposed to between) organisations. In response, this article reports one of the most detailed empirical examinations undertaken to date of the work involved in repurposing healthcare data for National Clinical Audits.

The Effect of Alignment on People's Ability to Judge Event Sequence Similarity.

Event sequences are central to the analysis of data in domains that range from biology and health, to logfile analysis and people's everyday behavior. Many visualization tools have been created for such data, but people are error-prone when asked to judge the similarity of event sequences with basic presentation methods. This article describes an experiment that investigates whether local and global alignment techniques improve people's performance when judging sequence similarity.

QualDash: Adaptable Generation of Visualisation Dashboards for Healthcare Quality Improvement.

Adapting dashboard design to different contexts of use is an open question in visualisation research. Dashboard designers often seek to strike a balance between dashboard adaptability and ease-of-use, and in hospitals challenges arise from the vast diversity of key metrics, data models and users involved at different organizational levels. In this design study, we present QualDash, a dashboard generation engine that allows for the dynamic configuration and deployment of visualisation dashboards for healthcare quality improvement (QI).

First-in-Human Study of AT13148, a Dual ROCK-AKT Inhibitor in Patients with Solid Tumors.

Purpose: AT13148 is an oral AGC kinase inhibitor, which potently inhibits ROCK and AKT kinases. In preclinical models, AT13148 has been shown to have antimetastatic and antiproliferative activity.

Patients And Methods: The trial followed a rolling six design during dose escalation.

Requirements for a quality dashboard: Lessons from National Clinical Audits.

Healthcare organizations worldwide use quality dashboards to provide feedback to clinical teams and managers, in order to monitor care quality and stimulate quality improvement. However, there is limited evidence regarding the impact of quality dashboards and audit and feedback research focuses on feedback to individual clinicians, rather than to clinical and managerial teams. Consequently, we know little about what features a quality dashboard needs in order to provide benefit.

Metabolomic changes of the multi (-AGC-) kinase inhibitor AT13148 in cells, mice and patients are associated with NOS regulation.

Introduction: To generate biomarkers of target engagement or predictive response for multi-target drugs is challenging. One such compound is the multi-AGC kinase inhibitor AT13148. Metabolic signatures of selective signal transduction inhibitors identified in preclinical models have previously been confirmed in early clinical studies.

How, in what contexts, and why do quality dashboards lead to improvements in care quality in acute hospitals? Protocol for a realist feasibility evaluation.

Introduction: National audits are used to monitor care quality and safety and are anticipated to reduce unexplained variations in quality by stimulating quality improvement (QI). However, variation within and between providers in the extent of engagement with national audits means that the potential for national audit data to inform QI is not being realised. This study will undertake a feasibility evaluation of QualDash, a quality dashboard designed to support clinical teams and managers to explore data from two national audits, the Myocardial Ischaemia National Audit Project (MINAP) and the Paediatric Intensive Care Audit Network (PICANet).

ALK2 inhibitors display beneficial effects in preclinical models of mutant diffuse intrinsic pontine glioma.

Diffuse intrinsic pontine glioma (DIPG) is a lethal childhood brainstem tumour, with a quarter of patients harbouring somatic mutations in , encoding the serine/threonine kinase ALK2. Despite being an amenable drug target, little has been done to-date to systematically evaluate the role of in DIPG, nor to screen currently available inhibitors in patient-derived tumour models. Here we show the dependence of DIPG cells on the mutant receptor, and the preclinical efficacy of two distinct chemotypes of ALK2 inhibitor in vitro and in vivo.

Correction to: An in vitro and in vivo study of the combination of the heat shock protein inhibitor 17-allylamino-17-demethoxygeldanamycin and carboplatin in human ovarian cancer models.

The corresponding author of this article has informed us of concerns about the immunoblots in Fig. 2 which were carried out in the collaborating laboratory of Professor Ann Jackman.

Vistusertib (dual m-TORC1/2 inhibitor) in combination with paclitaxel in patients with high-grade serous ovarian and squamous non-small-cell lung cancer.

Background: We have previously shown that raised p-S6K levels correlate with resistance to chemotherapy in ovarian cancer. We hypothesised that inhibiting p-S6K signalling with the dual m-TORC1/2 inhibitor in patients receiving weekly paclitaxel could improve outcomes in such patients.

Patients And Methods: In dose escalation, weekly paclitaxel (80 mg/m2) was given 6/7 weeks in combination with two intermittent schedules of vistusertib (dosing starting on the day of paclitaxel): schedule A, vistusertib dosed bd for 3 consecutive days per week (3/7 days) and schedule B, vistusertib dosed bd for 2 consecutive days per week (2/7 days).