Oxford-based cell therapy company Adaptimmune Therapeutics has received accelerated approval from the US Food and Drug Administration (FDA) for Tecelra (afamitresgene autoleucel) for treatment of synovial sarcoma. Tecelra is the first engineered cell therapy for solid tumours approved in the US, and represents the first therapy option against synovial sarcoma in more than a decade. It is indicated to treat adults with unresectable or metastatic synovial sarcoma who have received prior chemotherapy, and whose tumours express the MAGE-A4 antigen. Additionally, the tumours need to have a certain HLA type— HLA-A*02:01P, -A*02:02P, -A*02:03P, or -A*02:06P positive. The approval was granted based on results from the Phase II SPEARHEAD-1 trial (NCT04044768). Amongst 44 patients with synovial sarcoma, the overall response rate (ORR) to treatment was 43% with a median duration of response of six months (95% CI: 4.6, not reached). Continued approval remains subject to verification of clinical benefit in further trials. ...
The rapidly progressive neurological condition affects around 5,000 people in the UK Health Data Research UK (HDR UK) and Dementias Platforms UK (DPUK) have received £2m in funding to launch a new initiative to accelerate motor neurone disease research. Supported by the UK Dementia Research Institute, the MND Research Data Catalyst is funded by the Department of Health and Social Care and delivered through the National Institute of Health and Care Research (NIHR). Currently affecting around 5,000 people in the UK, MND is a fatal, rapidly progressing neurological condition caused by the accumulation of proteins in the brain that clump together to gradually stop cells from working. Supported by the UK government in partnership with charities and organisations including the NIHR, UK Research and Innovation, MND Association, My Name’5 Doddie Foundation, MND Scotland and LifeArc, along with the MND research community, the new initiative aims to accelerate the discovery of ...
Early detection is critical for successful cancer treatment. Yet, many patients with cancer visit their primary care providers with vague symptoms that could result from various benign conditions, complicating the determination of who needs further diagnostic testing or a referral. Most existing guidelines highlight specific “alarm” symptoms for different cancers to guide referrals, but advice on nonspecific symptoms that span multiple cancer types is scarce. Now, a new study has found that incorporating data from routine blood tests could improve cancer risk assessment for patients presenting with abdominal symptoms. Conducted by researchers at University College London (London, UK), the study utilized data from the UK Clinical Practice Research Datalink, examining over 470,000 patients aged 30 and older who consulted their general practitioner for abdominal pain or bloating. Within one year of these consultations, about 9,000 patients with abdominal pain and 1,000 with bloating were diagnosed with cancer. The study assessed ...
Scientists have developed an advanced artificial intelligence (AI) approach that can predict the likelihood of developing age-related conditions such as Alzheimer’s and heart disease up to a decade before symptoms manifest. By analyzing blood samples from over 45,000 individuals using machine learning, researchers identified specific protein patterns associated with an increased risk of disease. This capability to predict the probability of developing a health condition before any symptoms are observed could potentially enhance personalized medicine by providing early warnings, thereby opening doors for preventative interventions. Researchers from the University of Edinburgh (Edinburgh, UK) participated in a study that used data from the UK Biobank, which contains genetic and health information from half a million UK participants. They applied AI and machine learning to detect protein patterns in blood that correlate with the onset of common ailments including Alzheimer’s, heart disease, and type 2 diabetes. The analysis was based on medical ...
Alzheimer’s disease impacts one in five women and one in ten men over their lifetimes, yet diagnostic tools are still often cumbersome and not widely accessible in primary care settings. Although specialized memory clinics frequently use advanced diagnostic methods like PET scans and cerebrospinal fluid tests, there is a significant need for simpler, quicker diagnostic tools that can be used in primary care. Now, a commercially available blood test for Alzheimer’s has demonstrated approximately 90% reliability in primary care settings, representing a major development for individuals seeking assistance for memory loss and suspected of having this neurological disease. Research on this innovative blood testing method, which evaluates levels of Plasma Phospho-Tau217, commenced in 2019 with studies showing that the blood test can detect Alzheimer ‘s-related changes even before symptoms appear and monitor the disease’s progression. Earlier this year, results indicated that this blood test is as reliable as, and ...
A revolutionary microarray immunoassay enables patients to receive results for multiple allergens using just a single blood sample, thereby minimizing the necessity for multiple tests and appointments. AliveDx’s (Eysins, Switzerland) groundbreaking microarray immunoassay is specifically designed to detect specific IgE antibodies directed against protein allergens in human serum and runs on the company’s proprietary MosaiQ platform. This multiplex immunoassay microarray is capable of detecting over 30 allergens, including those from both inhalants and foods and represents a significant leap in diagnostic capabilities by allowing simultaneous testing for various conditions. This method streamlines the diagnostic process, simplifies laboratory workflows, and reduces the manual labor typically associated with singleplex testing methods. Consequently, it saves significant time for both laboratories and clinicians, enhancing the ability to efficiently diagnose and exclude multiple conditions. For patients who are sensitized to multiple allergens, this technology offers a rapid, comprehensive diagnostic process and supports more targeted ...
Annually, sepsis claims the lives of 11 million people globally, with 1.3 million of these deaths linked to antibiotic-resistant bacteria. For clinicians, the ability to quickly and accurately interpret antimicrobial susceptibility testing (AST) results is essential to save lives and tailor treatment strategies effectively. Rapid AST not only improves patient outcomes but also reduces the global antimicrobial resistance (AMR) burden by supporting the execution of effective Antimicrobial Stewardship (AMS) programs. Predicting AMR in patients with gram-negative infections is often a more complex and time-consuming process. Early diagnosis and timely treatment are crucial in enhancing outcomes for sepsis patients. Studies have shown that each hour’s delay in administering antibiotics significantly increases the likelihood of hospital mortality, even if antibiotics are given within the first six hours. Now, a novel AST system delivers actionable results for gram-negative bacteria directly from positive blood cultures in an average of 5.5-6 hours, enabling same-day treatment ...
Drugdu.com expert’s response: The establishment of a quality management system (QMS) for sterile in vitro diagnostic (IVD) medical devices is a complex and systematic process aimed at ensuring product safety, effectiveness, and compliance with regulatory requirements. Below is a detailed, professional step-by-step approach, referencing the Medical Device Manufacturing Practice and relevant regulatory mandates: I. Define Quality Policy and Objectives 1.Establish Quality Policy: The enterprise shall articulate a quality policy that embodies its commitment to medical device quality and patient safety. 2.Set Quality Objectives: Based on the quality policy, set specific, measurable quality objectives, such as product conformity rates and customer satisfaction levels. II. Establish Organizational Structure and Responsibilities 1.Setup Management Organization: Create a management structure tailored to medical device production, clearly defining the responsibilities and authorities of each department. 2.Appoint Management Representative: The corporate leader should designate a management representative responsible for establishing, implementing, and maintaining the QMS. 3.Clarify Responsibilities and Authorities: ...
Hypothyroidism impacts about 10% of the U.S. population, making the Thyroid Stimulating Hormone (TSH) test the most frequently conducted immunoassay in the United States. Traditional testing often involves significant time commitments for patients, including visits to labs and waiting 2 to 5 days for results. Now, a new TSH immunoassay performed on a silicon chip delivers results in approximately 30 minutes. Genalyte (San Diego, CA, USA) has received U.S. Food and Drug Administration (FDA) approval for its groundbreaking immunoassay, the first of its kind to be cleared for use on a silicon chip-based device. The Maverick Diagnostic System (MDS) incorporates silicon chip-based photonic ring resonator technology, enabling the execution of multiple rapid tests simultaneously from a small sample of whole blood or serum. This system is also connected to the cloud, facilitating the retrieval of assay protocols and enabling clinical oversight. Genalyte’s innovation effectively minimizes the traditional bulky lab machinery ...
Ductal carcinoma in situ (DCIS) is a non-invasive type of tumor that can sometimes progress to a more lethal form of breast cancer and represents about 25% of all breast cancer cases. Between 30% and 50% of DCIS patients may develop an invasive stage of cancer, yet identifying which tumors will progress is still a challenge due to unknown biomarkers. Current diagnostic practices include multiplexed staining or single-cell RNA sequencing to determine DCIS stages in tissue samples, but these methods are costly and not widely used. This has led to potential overtreatment of patients with DCIS. Now, a new artificial intelligence (AI) model can distinguish different stages of DCIS from inexpensive and readily available breast tissue images. The model developed by an interdisciplinary team of researchers from MIT (Cambridge, MA, USA) and ETH Zurich (Zurich, Switzerland) was trained and tested using one of the largest datasets of its kind ...
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