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

The James Webb Space Telescope Mission

Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least $4m$. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the $6.5m$ James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figure

Development and Translation of Human-AI Interaction Models into Working Prototypes for Clinical Decision-making

In the standard interaction model of clinical decision support systems, the system makes a recommendation, and the clinician decides whether to act on it. However, this model can compromise the patient-centeredness of care and the level of clinician involvement. There is scope to develop alternative interaction models, but we need methods for exploring and comparing these to assess how they may impact clinical decision-making. Through collaborating with clinical, AI safety, and HCI experts, and patient representatives, we co-designed a number of alternative human-AI interaction models for clinical decision-making. We then translated these models into ‘Wizard of Oz’ prototypes, where we created clinical scenarios and designed user interfaces with different types of AI output. In this paper, we present alternative models of human-AI interaction and illustrate how we used a co-design approach to translate them into functional prototypes that can be tested with users to explore potential impacts on clinical decision-making

Protocol for a mixed-method study to inform development of an inclusive intervention that uses real-time monitoring and feedback of surgical patients’ experience of shared decision making (The Alpaca Study).

Introduction High-quality shared decision-making (SDM) is a priority of health services, but only achieved in a minority of surgical consultations. Improving SDM for surgical patients may lead to more effective care and moderate the impact of treatment consequences. There is a need to establish effective ways to achieve sustained and large-scale improvements in SDM for all patients whatever their background. The ALPACA Study aims to develop, pilot and evaluate a decision support intervention that uses real-time feedback of patients’ experience of SDM to change patients’ and healthcare professionals’ decision-making processes before adult elective surgery and to improve patient and health service outcomes. Methods and analysis This protocol outlines a mixed-methods study, involving diverse stakeholders (adult patients, healthcare professionals, members of the community) and three National Health Service (NHS) trusts in England. Detailed methods for the assessment of the feasibility, usability and stakeholder views of implementing a novel system to monitor the SDM process for surgery automatically and in real time are described. The study will measure the SDM process using validated instruments (CollaboRATE, SDM-Q-9, SHARED-Q10) and will conduct semi-structured interviews and focus groups to examine (1) the feasibility of automated data collection, (2) the usability of the novel system and (3) the views of diverse stakeholders to inform the use of the system to improve SDM. Future phases of this work will complete the development and evaluation of the intervention. Ethics and dissemination Ethical approval was granted by the NHS Health Research Authority North West-Liverpool Central Research Ethics Committee (reference: 21/PR/0345). Approval was also granted by North Bristol NHS Trust to undertake quality improvement work (reference: Q80008) overseen by the Consent and SDM Programme Board and reporting to an Executive Assurance Committee. Trial registration number ISRCTN17951423; Pre-results

Usability of an Automated System for Real-time Monitoring of Shared Decision Making for Surgery:A Mixed Methods Evaluation

This aim of this study was to examine the usability of a novel, automated, real-time measurement system to monitor surgical patients’ experience of SDM. Specific objectives were to evaluate the measurement system’s i) effectiveness, ii) efficiency, and iii) user satisfaction amongst a large sample of surgical patients from a wide range of surgical specialties

Real-time monitoring and feedback to improve shared decision-making for surgery (the ALPACA Study): protocol for a mixed-methods study to inform co-development of an inclusive intervention

Introduction High-quality shared decision-making (SDM) is a priority of health services, but only achieved in a minority of surgical consultations. Improving SDM for surgical patients may lead to more effective care and moderate the impact of treatment consequences. There is a need to establish effective ways to achieve sustained and large-scale improvements in SDM for all patients whatever their background. The ALPACA Study aims to develop, pilot and evaluate a decision support intervention that uses real-time feedback of patients’ experience of SDM to change patients’ and healthcare professionals’ decision-making processes before adult elective surgery and to improve patient and health service outcomes.Methods and analysis This protocol outlines a mixed-methods study, involving diverse stakeholders (adult patients, healthcare professionals, members of the community) and three National Health Service (NHS) trusts in England. Detailed methods for the assessment of the feasibility, usability and stakeholder views of implementing a novel system to monitor the SDM process for surgery automatically and in real time are described. The study will measure the SDM process using validated instruments (CollaboRATE, SDM-Q-9, SHARED-Q10) and will conduct semi-structured interviews and focus groups to examine (1) the feasibility of automated data collection, (2) the usability of the novel system and (3) the views of diverse stakeholders to inform the use of the system to improve SDM. Future phases of this work will complete the development and evaluation of the intervention.Ethics and dissemination Ethical approval was granted by the NHS Health Research Authority North West-Liverpool Central Research Ethics Committee (reference: 21/PR/0345). Approval was also granted by North Bristol NHS Trust to undertake quality improvement work (reference: Q80008) overseen by the Consent and SDM Programme Board and reporting to an Executive Assurance Committee.Trial registration number ISRCTN17951423; Pre-results

The James Webb Space Telescope Mission

Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least 4 m. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the 6.5 m James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 yr, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit