US Food and Drug Administration has approved AstraZeneca’s Truqap (capivasertib) combination therapy as the first and only targeted treatment for adult patients suffering from PTEN-deficient mAPMN/S prostate cancer.
Pfizer’s Phase 3 TALAPRO-3 trial reveals that combining Talzenna with Xtandi significantly improves radiographic progression-free survival by more than 50% in HRR gene-mutated mCSPC patients.
Johnson & Johnson secures EC approval for AKEEGA® as the first precision-medicine combo for BRCA1/2-mutated metastatic hormone-sensitive prostate cancer, supported by landmark rPFS data from the AMPLITUDE trial.
A landmark real-world analysis revealed that patients with metastatic castration-sensitive prostate cancer (mCSPC) treated with Erleada® (apalutamide) saw a 51% lower risk of death compared to those treated with darolutamide. This data marks a significant breakthrough for patients seeking effective, “chemo-free” treatment options.
Johnson & Johnson announced today that the European Medicines Agency’s (EMA) Committee for Medicinal Products for Human Use (CHMP) has issued a positive opinion recommending [Read More…]
Pfizer and Astellas report groundbreaking Phase 3 EMBARK trial results showing XTANDI® (enzalutamide) plus leuprolide significantly improves overall survival in men with non-metastatic hormone-sensitive prostate cancer (nmHSPC) and high-risk biochemical recurrence. This marks the first time an androgen receptor inhibitor-based therapy has shown a definitive survival benefit in this specific patient population, offering new hope for extending lives through early and effective treatment.
XTANDI® (enzalutamide), co-developed by Astellas and Pfizer, has shown a significant 30% reduction in risk of death over five years in metastatic hormone-sensitive prostate cancer (mHSPC) patients, marking it as the first androgen receptor inhibitor to demonstrate this long-term survival benefit.
The test, which examines 18 genes, was created especially to identify malignancies that require rapid treatment as opposed to those that grow slowly.
Researchers made a substantial advancement in computational pathology and medical diagnostics by creating a machine-learning model to enhance prostate cancer biopsy evaluation.
