NECESSITY Project’s Post

A recent article in Clinical Leader discusses the obstacles in the area of rare disease research and the challenges of global #datasharing in that domain, including the limited number of affected individuals and the diverse nature of these conditions. The solutions, the article notes, must involve initiatives focusing on standardizing data formats, enhancing #interoperability between systems, implementing robust data governance frameworks, and fostering transparent data-sharing agreements, facilitated by frameworks such as #SNOMEDCT and Human Phenotype Ontology (HPO). Read the article to learn more: https://lnkd.in/gF-d3rsM

🔍 New Publication Alert! Understanding the Real Prevalence of Interstitial Lung Disease in Rheumatoid Arthritis Patients In the realm of rare diseases, accurately estimating prevalence is a significant challenge. Literature suggests a wide prevalence range for interstitial lung disease associated with Rheumatoid Arthritis (RA) - from 1% to 60%. This vast variability poses real-world difficulties in diagnosis, treatment planning, and resource allocation, impacting patient care and research focus. 📊 Our recent study, published in RMD Open, leverages machine learning and big data to shed light on this issue. By analyzing a cohort of 14,000 RA patients, we've derived reliable real-world data, estimating that this condition affects 1 in every 20 patients. This finding narrows the prevalence gap and provides a clearer target for healthcare providers and researchers. This work was made possible through collaboration with esteemed institutions and colleagues, including various Spanish hospitals, the innovative team at SAVANA Med, and the support of Bristol Myers Squibb (BMS) and Sandra Orta. I extend my heartfelt gratitude to @Jose Andres Roman Ivorra, Ignacio H. Medrano and Diego Benavent Nuñez for their significant contributions and unwavering commitment to this project. 📝 Our findings underscore the power of technology in transforming medical research and patient care. Dive into our publication to explore how big data and machine learning are unveiling the real face of rare disease prevalence: https://lnkd.in/dZ-Gdd8n #RheumatoidArthritis #InterstitialLungDisease #MachineLearning #BigData #MedicalResearch #BMSiberia #HealthcareInnovation #SAVANAMed

📣 Publication alert!!! Just published: Defining disease severity in #atopicdermatitis and #psoriasis for the application to #biomarker research- an interdisciplinary perspective. To expedite discovery and validation, the #BIOMAP_IMI consortium (Biomarkers in #AD and Psoriasis, a large-scale European, interdisciplinary research initiative) has curated #clinical and #molecular #data across diverse study designs and sources including cross-sectional and cohort studies (small scale through to large multi-centre registries), clinical trials, electronic health records and large-scale population-based biobanks. We map all dataset disease severity instruments and measures to three key domains (symptoms, inflammatory activity and disease course), and describe important co-dependencies and relationships across variables and domains. 👉 https://lnkd.in/eCe4brZZ

"Early diagnosis of multiple diseases to enable timely treatment” may promote investment on medicine for early stages of diseases that are more effective. It is an inspiring R&D promotion method.

What does the future hold for rare disease treatment? 🔬    Access to information online will help expedite disease diagnosis further.     Online Mendelian Inheritance in Man (OMIM)17 and Orphanet18 are two highly reliable databases that collect information on newly reported diseases and disease genes.     Access to more information about patients, their symptoms and progress will likely be found from the new sources like surveys of specialty physicians, clinical labs, and patient organizations, or from rare disease networks.      People like you are the focal point of clinical research and drug development. Companies and researchers have come to rely on feedback from patients to better understand what it’s like to live with a disease, and that information can help them in the development of clinical studies.     That means that your contributions and participation are critical to the development of new treatments for others like you with a rare disease. 💙    -    #raredisease #medicalresearch #clinicaltrials #clinicaltrial #clinicalstudy #rarediseaseawareness #rarediseases #KnowRare

"We also committed to prove clear patient cohort selection performance above current best, manual practice. Deriving diagnostic models for rare diseases manually, based on input from experts, is problematic for several reasons, including the evolving nature of experts’ understanding, complexity of disease processes, and cognitive biases associated with human decision-making [Elstein, Schwarz 2002]. By September 2017, Volv had built a disease learning model, applicable not only to this disease but any disease. We called the methodology to build this model inTrigue. This prediction model is built on a research and evidence-based understanding of the disease derived from extracting clinical evidence from publicly available sources. This represented a true breakthrough in data science." - https://lnkd.in/efYNRxJM - 💭 Christopher Rudolf - Volv Global SA - #raredisease - Rennie Jasmine Musa

The risk of coronary artery disease (CAD) can change over a person’s lifetime, and current methods of estimating CAD risk don’t incorporate new information over time. Sarah Urbut, Pradeep Natarajan, and colleagues have developed MSGene, a model that accounts for longitudinal data, clinical covariates, and CAD polygenic risk scores to estimate transitions between 10 cardiometabolic states. The team used MSGene to analyze longitudinal data from more than 480,000 UK Biobank participants and found that it improved risk predictions compared to other risk scores. The findings, in Nature Communications, highlight the potential public health value of more accurate lifetime CAD risk estimation. #BroadInstitute #Science #ScienceNews #Research #ScientificResearch

Indo US Organization for Rare Diseases (IndoUSrare)'s Harsha K Rajasimha, Ph.D. and Deepti Dubey, Ph.D. explore the global issues in #raredisease research and examine how #AI is poised to revolutionize the diagnosis and treatment of these conditions. #genetherapy #raredisease #researchanddevelopment https://lnkd.in/ethFngP2