Erratum: Erratum.

[This corrects the article DOI: 10.1177/11795484221119316.].

Efficacy and Safety of LY3127804, an Anti-Angiopoietin-2 Antibody, in a Randomized, Double-Blind, Placebo-Controlled Clinical Trial in Patients Hospitalized with Pneumonia and Presumed or Confirmed COVID-19.

BACKGROUND: Severe cases of coronavirus disease 2019 (COVID-19) are characterized by progressive respiratory failure and the development of acute respiratory distress syndrome (ARDS), with high mortality rates for patients requiring mechanical ventilation. Levels of the vascular growth factor Angiopoietin 2 (Ang2) in plasma have been strongly correlated with increased ARDS risk in patients with pneumonia or sepsis. The intent of this study was to determine whether LY3127804, an anti-Ang2 monoclonal antibody, could reduce the need for mechanical ventilation among patients admitted to the hospital with pneumonia and presumed or confirmed COVID-19. METHODS: Patients admitted to hospital with confirmed pneumonia, presumed or confirmed COVID-19, and infiltrates on chest imaging and/or oxygen saturation of ≤ 95% on room air were stratified by age group (< 65 years and ≥ 65 years), sex, and site and randomly assigned 1:1 within each stratum to receive either LY3127804 (20 mg/kg) or placebo on Day 1 and possibly on Day 15. The primary end point for this study was number of days in which a patient did not require a ventilator over the 28-day study period. RESULTS: Interim analysis assessed study futility after 95 randomized patients had 28-day data available and showed no benefit of LY3127804 in reducing the number of ventilator days over placebo. The study was subsequently terminated. CONCLUSION: LY3127804 treatment did not decrease the need for ventilator usage in patients hospitalized with pneumonia and presumed or confirmed COVID-19. ClinicalTrialsgov identifier: NCT04342897.

A decade of innovation in pharmaceutical R&D: the Chorus model.

Chorus is a small, operationally independent clinical development organization within Eli Lilly and Company that specializes in drug development from candidate selection to clinical proof of concept. The mission of Chorus is to achieve proof of concept rapidly and at a low cost while positioning successful projects for 'pharma-quality' late-stage development. Chorus uses a small internal staff of experienced drug developers and a network of external vendors to design and implement chemistry, manufacturing and control processes, preclinical toxicology and biology, and Phase I/II clinical trials. In the decade since it was established, Chorus has demonstrated substantial productivity improvements in both time and cost compared to traditional pharmaceutical research and development. Here, we describe its development philosophy, organizational structure, operational model and results to date.

Estimation of upper-limb orientation based on accelerometer and gyroscope measurements.

A solution is proposed to the estimation of upper-limb orientation using miniature accelerometers and gyroscopes. This type of measurement device has many different possible applications, ranging from clinical use with patients presenting a number of conditions such as upper motor neuron syndrome and pathologies that give rise to loss of dexterity, to competitive sports training and virtual reality. Here we focus on a design that minimizes the number of sensors whilst delivering estimates of known accuracy over a defined frequency range. Minimizing the sensor count can make the measurement system less obtrusive, as well as minimising cost and reducing the required bandwidth if using a wireless solution. Accurate measurement of movement amplitude up to 15 Hz is required in our immediate application, namely to quantify tremor in multiple sclerosis patients. The drive for low numbers of sensors and good accuracy at higher frequencies leads to a novel design based on composite filters. The simple estimator structure also gives good insight into the fundamental accuracy limitations based on the sensors chosen. This paper defines the underlying mathematics, and quantifies performance for an estimator for shoulder, upper arm, lower arm and hand orientations. Good estimation accuracy up to 15 Hz is indicated, and this with a reduced total sensor count of 18 compared to 24 that would be required for more conventional estimator architectures.