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ey0020.3-1 | Novel Treatments for Rare Skeletal Disorders | ESPEYB20

3.1. Safety and efficacy of denosumab for fibrous dysplasia of bone

LF de Castro , Z Michel , K Pan , J Taylor , V Szymczuk , S Paravastu , B Saboury , GZ Papadakis , X Li , K Milligan , B Boyce , SM Paul , MT Collins , AM Boyce

In Brief: This phase 2 study investigated the effect of the RANKL inhibitor denosumab on fibrous dysplasia lesion activity, as well as the rebound in bone turnover after treatment discontinuation.Commentary: Denosumab is a humanized monoclonal antibody that inhibits RANKL with potent but transient antiosteoclastic effects, and discontinuation of denosumab treatment is associated with a rebound in bone turnover. In this study, eight women received high do...

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ey0021.15-12 | Artificial Intelligence | ESPEYB21

15.12. Accurate proteome-wide missense variant effect prediction with AlphaMissense

J Cheng , G Novati , J Pan , C Bycroft , A Zemgulyte , T Applebaum , A Pritzel , LH Wong , M Zielinski , T Sargeant , RG Schneider , AW Senior , J Jumper , D Hassabis , P Kohli , Z. Avsec

In Brief: The authors describe AlphaMissense, a machine-learning tool that predicts the pathogenicity of 71 million human coding variants. 22.8 million variants (32%) are classified as likely pathogenic and 40.9 million (57%) as likely benign. They provide these databases freely as resources to the international research community.These authors from Google DeepMind previously developed and released AlphaFold, a revolutionary machine-learning approach to ...

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ESPE Yearbook of Paediatric Endocrinology

3.1. Safety and efficacy of denosumab for fibrous dysplasia of bone

15.12. Accurate proteome-wide missense variant effect prediction with AlphaMissense

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