Kris Kaleta 
Recording of the workshop on the new X-Linked Hypophosphataemia (XLH) international guidelines. The sessions look back at the journey so far in XLH and discuss the new guidelines from adult and paediatric viewpoints.
IFMRS/ORS Webinar Series
Speakers
Grace Drury MA Oxf, MA |
Global Health Project Manager, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences at the University of Oxford
Billy Thomason Haonga, MD |
Specialist Orthopaedic Surgeon – MAMC/Muhimbili Orthopaedic Institute, Associate Professor at the Muhimbili University of Health and Allied Sciences – https://muhas.ac.tz/
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The video is part of the LearnORS Video Library.
The new XLH International Guidelines: sharing patients’ and experts’ perspectives.
Supported by an unrestricted educational grant of Kyowa Kirin.
Join IFMRS on Wednesday, 29 October, for a free virtual workshop on the new X-Linked Hypophosphataemia (XLH) international guidelines. Hear from leading experts and the XLH community on diagnosing, evaluating, managing, and monitoring XLH, with an emphasis on multidisciplinary care and current treatment options, including burosumab.
The session will look back at the journey so far in XLH and discuss the new guidelines from adult and paediatric viewpoints, with time for Q&A.
Speakers: Prof Thomas Carpenter (Yale University), Prof Leanne Ward (University of Ottawa), Prof Suzanne Jan De Beur (University of Virginia), Tenna Toft Sylvester (International XLH Alliance).
Co-chairs: Martine Cohen-Solal (ECTS President-elect) and Dr Adalbert Raimann (XLH expert).
Free, registration required (click).
What is XLH?
Symptoms: Reduced bone mineralisation and skeletal deformities.
Causes: Variants in the PHEX gene leading to increased FGF23 activity and phosphate wasting.
New guidelines focus on: diagnosing • evaluating • managing • monitoring.
Care model: Strong emphasis on multidisciplinary care (including endocrinologists and dentists).
Therapy note: Information on treatment with burosumab, where appropriate.
See references below.
1. https://pubmed.ncbi.nlm.nih.gov/39960858/
A fresh episode of the Bone Up podcast is now available, hosted by Dr. Richie Abel (PhD) and Prof. David Armstrong (MD). In this installment, recorded in Innsbruck during the 2025 ECTS Annual Meeting, the hosts discuss the latest advances in bone research:
Insights from Giovanni Adami on optimizing the combination and sequencing of bone medications, including the role of AI in osteoporosis management.
A spotlight on Claus‑Christian Glüer and his novel fracture-risk prediction tool, Hive.
Running approximately 45 minutes, the episode is a must-listen for clinicians, researchers, and anyone passionate about bone health.
LISTEN AT:
https://rss.com/podcasts/boneup/2154457/
SARCOPENIA AND OSTEOSARCOPENIA INFOGRAPHIC
~3,500 Scopus papers projected for 2025 since sarcopenia received the ICD-10-CM code M62.84 (2016).
Higher risks of falls, fractures, mortality; risk escalates further in osteosarcopenia (sarcopenia + osteoporosis).
The Global Leadership Initiative in Sarcopenia (GLIS) is finalising universal diagnostic criteria to harmonise case finding and trial endpoints.
Standardised cut-points for muscle mass, strength, function, and physical activity are central to the coming guidelines.
Recommended reading and data sources
Other definitions based on regions:
Patient-specific digital twins = thousands of variables cloned
A high-performance model integrates omics, clinical, and lifestyle data to create unlimited copies of one patient, each exposed in silico to a different drug. Comparing responses pinpoints the treatment most likely to work in real life.
Why they matter: Medication failure is often a timing problem
Late diagnosis, lack of early biomarkers, and years of silent disease progression drive poor efficacy and huge costs. Digital twins shift the focus upstream—predicting risk, preventing onset, and tailoring therapy before irreversible damage occurs.
Data resolution is everything
Bulk data are like mixed Lego bricks; single-cell and spatial omics sort them by colour and position, revealing which cell types spark disease and where they sit in tissue. That granularity enables precise biomarker discovery and cell-targeted drug search.
Arthritis as a proving ground
Chosen for its joint-plus-immune features, rich single-cell datasets, and tractable mouse models. Analysis of 45 human cell types flagged 24 strongly linked to arthritis and thousands of risk genes.
Multi-organ, multi-cell networks expose hidden crosstalk
A mouse single-cell atlas uncovered ~1,000 inter-organ interactions—joints, lung, muscle, skin, and even brain – explaining extra-articular symptoms invisible in routine exams.
Module-based strategy finds actionable targets
Disease-related protein clusters (modules) reveal convergent pathways, early biomarkers, and druggable nodes – even amid noisy data. The method extends to DNA, RNA, symptoms, and lifestyle layers for richer predictions.
Drug-ranking engine validates fast
Mapping modules onto DrugBank and scoring intra/inter-cellular centrality produced a top-five list; two candidates (dabrafenib, amurannon) suppressed B-cell activation in vitro and eased joint inflammation in mice.
Personalisation demo: TNF-α responders vs non-responders
Patient-specific network models showed TNF-α as a central hub only in responders; the drug-ranking list differed completely between the two, illustrating how twins can prioritise therapy on a person-by-person basis.
Early-warning markers without big panels
‘Upstream regulator‘ mining distils hundreds of genes to a handful that control disease trajectories, while a spatiotemporal ML method (StudioTime) pinpoints progression genes that achieved high AUC in > 2,000 clinical samples—enabling routine-test detection.
Take-home message
Network-driven digital twins can predict, prevent, and personalise treatment by linking multi-layer data to drug and biomarker discovery, and the approach is directly transferable to other complex diseases.
Data and model always go together
Digital twins rely on four layers working in concert:
sensors/measurements → middleware → computing hardware → software models.
Twins can represent cells, tissues, organs, whole systems, medical devices, bioprocesses or entire facilities, whichever is sufficient to answer the clinical or research question.
Modelling spans a spectrum, not just AI
From black-box, data-only approaches to white-box, physics-only ones, most useful twins sit in the grey zone – hybrid models that combine mechanistic knowledge with machine-learning components to curb ‘hallucinations’.
Lab examples show the breadth of scales
Clinical traction is already real (at single-organ scale)
Personalized left-atrial appendage occluder sizing, surgical planning tools, and other device-focused twins are in routine use and even reimbursed; one physics-only twin has entirely replaced a medical-device clinical trial.
Regulatory and credibility science are maturing
EMA/FDA guidance, emerging “Good Simulation Practice” and ~150 existing standards give clear (if complex) pathways for validation, documentation, and risk management.
Europe’s next step: the Virtual Human Twin initiative
The EU aims to knit dispersed efforts into a shared platform that includes:
Community-built roadmap & manifesto
800+ stakeholders co-authored a 30-recommendation roadmap (plus a short policy brief and 2-page manifesto) emphasising unmet-need-driven use cases, full clinical-workflow integration, and sustainable infrastructure and business models.
Validation remains context-dependent
High-TRL scaffold work moves quickly from mouse to large-animal to spin-off products; the inflammatory fracture-healing twin is lower-TRL and still in fundamental calibration, illustrating that digital first, then bench & animal is iterative, not linear.
Bottom line
Digital twins are already delivering niche clinical value, and hybrid, multiscale approaches are unlocking far richer questions – from single-cell fate decisions to hospital logistics. Europe’s Virtual Human Twin push seeks to make those scattered successes reproducible, interoperable, and trustworthy at continent scale.