All articles tagged with #precision medicine
Researchers created a 3D heart-on-a-chip with dual high-resolution sensors that monitor tissue-level and cell-level activity in real time, enabling more accurate drug screening and paving the way for patient-specific cardiac therapies using a person’s own cells.
A new NHS National Inherited Cancer Predisposition Register will compile data from about 120 cancer-related genes to identify individuals and families at higher cancer risk, enabling earlier screening, tailored prevention and treatment options, and faster detection as part of a 10-year plan—with strict confidentiality and integration of existing genetic tests into a single, centralized resource.
A London study shows a simple liquid biopsy measuring circulating tumour DNA (ctDNA) in advanced breast cancer can predict treatment response before starting therapy and after one cycle. In 167 patients, lower ctDNA levels were associated with better outcomes, suggesting this test could guide personalized treatment and spare ineffective drugs, with trials exploring adaptive strategies and newer therapies.
Researchers introduce GluFormer, a self-supervised, autoregressive foundation model trained on over 10 million CGM measurements to learn transferable glucose representations across 19 external cohorts spanning 5 countries and multiple devices. The learned representations improve forecasting of glycemic metrics, stratify prediabetes progression better than baseline HbA1c, and identify higher long-term diabetes and cardiovascular mortality risk than HbA1c in follow-up data. A multimodal extension incorporating dietary data can simulate plausible glucose trajectories and predict individual glycemic responses to food, suggesting GluFormer as a generalizable tool to advance precision metabolic health.
Ghanaian scientist Moses Mayonu is pioneering metabolomics research at Florida Tech, integrating advanced techniques and AI to improve disease diagnosis and personalized medicine, while also contributing to Africa's scientific development and capacity building.
By 2026, advances in AI and aging science will enable precision medical forecasting, allowing for early prediction and prevention of major age-related diseases like cancer, cardiovascular, and neurodegenerative conditions through comprehensive data analysis and personalized interventions.
A Swedish-led clinical trial found that low-dose aspirin significantly reduces the risk of colon and rectal cancer recurrence in patients with a specific genetic mutation, highlighting its potential as an affordable, personalized treatment option for colorectal cancer.
Researchers at MIT and McMaster University used AI, specifically DiffDock, to develop and understand a targeted antibiotic, enterololin, that treats gut bacteria linked to Crohn's disease with minimal impact on the microbiome, potentially revolutionizing treatment and reducing antimicrobial resistance.
The article discusses the potential of precision medicine and immunotherapies to revolutionize cancer treatment, highlighting upcoming discussions and innovations such as antibody-drug conjugates, featuring experts from Pfizer and Yale Cancer Center.
A major study by Princeton and the Simons Foundation identified four distinct biological and clinical subtypes of autism using data from over 5,000 children, revealing different genetic profiles and developmental timelines for each, which could lead to more targeted diagnosis and treatment approaches.
Researchers used CRISPR to study the gene SDR42E1, crucial for vitamin D metabolism, finding that inhibiting it can selectively kill cancer cells and potentially lead to new cancer treatments, while also suggesting broader applications in diseases influenced by vitamin D. However, long-term effects need further investigation.
A large U.S. study shows that people's self-identified racial and ethnic categories do not accurately reflect their genetic ancestries, highlighting the complexity of genetic diversity and the limitations of using race and ethnicity as proxies in genetic research and personalized medicine.
A new study has identified six subtypes of major depression using brain imaging and machine learning, potentially paving the way for more precise and effective treatments. The research, published in Nature Medicine, tested how three of these biotypes responded to different antidepressants and therapies. This approach could significantly improve treatment outcomes by matching patients with the most suitable therapies from the start, reducing the trial-and-error process currently prevalent in depression treatment. However, further studies with more diverse samples and additional treatments are needed to validate these findings.
NIH researchers have developed a five-drug combination therapy, ViPOR, that achieves lasting remissions in patients with aggressive B-cell lymphoma resistant to standard treatments. In a clinical trial, ViPOR led to complete tumor disappearance in 38% of patients and showed significant survival benefits, particularly in specific subtypes of diffuse large B-cell lymphoma (DLBCL). The treatment's side effects were generally mild to moderate, and further studies are planned to confirm its efficacy and explore its use in other lymphoma types.
Devlin Donaldson, a CEO diagnosed with type 2 diabetes, reversed his condition and lost significant weight using a digital twin technology from Twin Health. The digital twin provided personalized health insights and real-time feedback on diet, exercise, and medication, leading to his diabetes remission and improved overall health. This precision medicine approach, which includes continuous glucose monitoring and other health tracking tools, is gaining traction for its effectiveness in managing chronic conditions.