Pharmaceutical Executive Editorial Staff Darzalex Faspro has previously been approved by the FDA for eight indications in multiple myeloma. The FDA will evaluate Johnson & Johnson’s supplemental Biologics License Application (sBLA) for Darzalex Faspro (daratumumab and hyaluronidase-fihj) with bortezomib, lenalidomide, and dexamethasone (D-VRd) for induction and consolidation therapy and in combination with lenalidomide (D-R) for the maintenance treatment of adults newly diagnosed with multiple myeloma who are eligible for autologous stem cell transplant (ASCT).1 Darzalex Faspro, a CD38-directed antibody, has previously been approved by the FDA for eight indications in multiple myeloma, with three in the frontline treatment of newly diagnosed patients who are transplant eligible or ineligible. “We are committed to changing the course of multiple myeloma through building combination regimens such as D-VRd with complementary mechanisms of action. The Darzalex Faspro-based quadruplet therapy demonstrated a clinically significant reduction in the risk of progression or death for transplant-eligible, newly ...
In the UK, there are about 17,000 individuals living with sickle cell disorder, and each year there are around 250 new cases. This condition, predominantly affecting people of black African and Caribbean descent, can lead to significant organ damage and intense pain. In contrast, the UK has around 800 patients with thalassaemia and less than 50 new cases annually. Thalassaemia patients struggle to produce sufficient hemoglobin, which, if untreated, can result in life-threatening anemia. This condition is most prevalent among people of Asian, Middle Eastern, and southern Mediterranean backgrounds. While life-saving blood transfusions are a common treatment for these inherited blood disorders, about 20% of patients develop antibodies against certain blood groups, causing delays in their treatment. Now, a groundbreaking ‘blood matching’ genetic test, the first of its kind in the world, is being made available to thousands of these patients in the UK to better pair people for blood ...
When cells die, they disintegrate, releasing part of their DNA material into the bloodstream. This cell-free DNA (cfDNA) contains cancer signals. The cfDNA from healthy cells breaks down into standard-sized fragments, whereas cancerous cfDNA fragments disintegrate at different locations, often in the genome’s repetitive regions. Instead of searching for specific DNA mutations, which is like finding a single misarranged letter in billions of letters, researchers have developed a novel machine-learning method. This method detects variations in fragmentation patterns between cancerous and normal cfDNA in these repetitive regions of cancer. This groundbreaking technique could potentially allow for earlier cancer detection in patients through smaller blood samples, as it requires approximately eight times less blood than what is needed for whole genome sequencing. The algorithm called Alu Profile Learning Using Sequencing (A-Plus) was developed by researchers at City of Hope (Duarte, CA, USA) and Translational Genomics Research Institute (TGen, Phoenix, AZ, USA). ...
Approximately only half of cancer patients see a positive response to treatments, with the remaining experiencing inadequate outcomes. The high costs and potential adverse reactions of treatments make it crucial for clinicians to quickly determine their effectiveness, or if an alternative therapy is more suitable. Presently, it can take weeks or months to fully gauge the success of cancer treatment, typically using CT scans to measure significant size changes in tumors. While tumor biopsies offer more precise data, their infrequency limits the ability to provide ongoing updates. As a solution, many clinicians are now resorting to liquid biopsies, which involve testing for cancer indicators in a patient’s blood, like tumor-shed cancer cells. However, these tests require sufficiently high cell levels for detection. This is particularly challenging in lung cancer, where some FDA-approved methods for detecting blood-borne cancer cells are ineffective, often due to targeting a single, less common protein in ...
Ovarian cancer, often termed the silent killer, typically presents no symptoms in its initial stages, leading to late detection when treatment becomes challenging. The stark contrast in survival rates highlights the urgent need for early diagnosis: while late-stage ovarian cancer patients have a five-year survival rate of around 31% post-treatment, early detection and treatment can raise this rate to over 90%. Despite over three decades of research, developing an accurate early diagnostic test for ovarian cancer has proved challenging. This difficulty stems from the disease’s molecular origins, where multiple pathways can lead to the same cancer type. Scientists at the Georgia Tech Integrated Cancer Research Center (ICRC, Atlanta, GA, USA) have now made a breakthrough by integrating machine learning with blood metabolite information, developing a test that can detect ovarian cancer with 93% accuracy in their study group. This test outperforms existing detection methods, especially in identifying early-stage ovarian disease ...
Diagnosing rare genetic diseases presents a significant challenge due to their complex and often hidden nature. These conditions can arise from a diverse array of genetic variations, many of which are uncommon or specific to each individual, complicating the identification of the exact cause of symptoms. Until recently, unraveling these mysteries involved extensive genetic testing and comparing an individual’s genetic profile against established disease patterns. Complicating matters further, many relevant genes are inactive in commonly tested tissues like blood and skin, which makes it difficult to get a clear picture of the genetic basis of these diseases. This complexity not only prolongs the diagnostic process but also extends patient and family uncertainty and delays the initiation of suitable treatments. Now, a new study could mark a significant step forward in the rapid and efficient diagnosis of these complex diseases, which can affect any part of the body. At Aarhus University ...
Ulcerative colitis, a type of inflammatory bowel disease, progressively damages the gut lining. It leads to inflammation and ulcers in the colon and rectum. Currently, the initial treatment for mild-to-moderate cases typically involves 5-Aminosalicylates (5-ASA), while more advanced stages are managed with steroids, immunosuppressants, and biological drugs. There is an urgent need for accurate biomarker-based methods to quickly identify the most effective treatment plans post-diagnosis. Now, a new collaboration aims to personalize treatments for ulcerative colitis, ultimately enhancing the quality of life for those affected by the condition. RCSI University of Medicine and Health Sciences (Dublin, Ireland) and diagnostics company Serosep Ltd. (Limerick, Ireland) have joined forces to expedite the development of innovative tests to predict disease progression in individuals with ulcerative colitis. This initiative will focus on developing technology to identify patients whose condition is likely to worsen. The goal is to ensure individuals receive the most beneficial care ...
Currently, no artificial intelligence (AI) or machine-learning tools are available for investigating and interpreting the complete human genome, particularly for non-experts. Now, a first-of-its-kind software combines AI and machine-learning approaches to understand the importance of specific genomic biomarkers to predict diseases in individuals. The IntelliGenes software created by researchers at Rutgers Health (New Brunswick, NJ, USA) combines conventional statistical methods with cutting-edge machine learning algorithms to generate personalized patient predictions and provide a visual representation of the biomarkers significant to disease prediction. IntelliGenes has been designed in such as way that the platform can be used by anyone, including students or those lacking strong knowledge of bioinformatics techniques or access to high-performing computers. In a study, the researchers demonstrated how IntelliGenes can be deployed by a wide range of users to analyze multigenomic and clinical data. In another study, the researchers applied IntelliGenes to discover novel biomarkers and predict cardiovascular ...
Tumors continuously release DNA from dying cells into the bloodstream, which is rapidly broken down. This makes it difficult for existing blood tests to detect the minute amounts of tumor DNA present at any given time. Now, a team of researchers has developed an innovative method to amplify the detection of tumor DNA in blood, a breakthrough that could enhance cancer diagnosis and treatment monitoring. Researchers at Massachusetts Institute of Technology (MIT, Cambridge, MA, USA) have created “priming agents,” injectable molecules that temporarily slow the clearance of circulating tumor DNA from the bloodstream. These priming agents target the body’s two main mechanisms for removing circulating DNA: DNases, enzymes that break down DNA in the blood, and macrophages, immune cells that absorb cell-free DNA during blood filtration through the liver. The researchers developed two types of priming agents. The first is a monoclonal antibody that attaches to circulating DNA, shielding ...
Today’s FDA approval amends a previously granted accelerated approval for Balversa (erdafitinib) to treat patients with metastatic urothelial carcinoma whose tumors harbor FGFR3 or FGFR2 alterations following prior platinum-based chemotherapy. The FDA has approved Balversa (erdafitinib) for adults with locally advanced or metastatic urothelial carcinoma with susceptible FGFR3 genetic mutations whose disease progressed on or following one line of systemic therapy.1 The regulatory action amends the accelerated approval granted by the FDA in April 2019 for patients with metastatic urothelial carcinoma with susceptible FGFR2 or FGFR3 alterations following prior treatment with platinum-containing chemotherapy. Balversa, a fibroblast growth factor (FGFR) inhibitor, is not recommended for patients who are eligible for, and were not previously administered, prior treatment with a PD-1 or PD-L1 inhibitor, according to the FDA.The FDA based the approval on data from Study BLC3001 cohort 1, which evaluated data from 266 patients with metastatic urothelial carcinoma harboring selected FGFR3 alterations and who previously received ...
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