Predictive Biosciences to present its novel MADR approach during 2010 GU Symposium

Predictive Biosciences today announced that the Company will be presenting its novel Multi-Analyte Diagnostic Readout (MADR™) approach to the development of a non-invasive, urinary biomarker based assay for the detection of bladder cancer during the 2010 Genitourinary Cancers Symposium (GU Symposium), being held March 5-7 in San Francisco. The GU Symposium is co-sponsored by the American Society of Clinical Oncology (ASCO), the American Society for Radiation Oncology (ASTRO) and the Society of Urologic Oncology (SUO). The MADR research, which combines protein and DNA biomarkers to identify with high certainty a group of bladder cancer patients who are disease free and could be excluded from undergoing invasive procedures, was conducted under collaboration agreements with Lahey Clinic Medical Center and Mayo Clinic.

“Multi-Analyte Diagnostic Readout (MADR™): Combining Protein and DNA Markers to Maximize Clinical Performance”

Predictive’s abstract (#278) and poster titled “Multi-Analyte Diagnostic Readout (MADR™): Combining Protein and DNA Markers to Maximize Clinical Performance” will be displayed during poster session D on Saturday, March 6 at 5:30 p.m. PST.

Predictive found that the combination of four biomarkers (MMP-9, MMP-2, ADAM12 and FGFR3) in its bladder cancer assay resulted in 96 percent sensitivity with a 98 percent negative predictive value (NPV) among a cohort of patients known to be cancer free by standard methods. NPV is the probability that a patient who has tested negative for cancer is actually free of the disease.

“The bladder cancer assay being highlighted at the GU Symposium demonstrates the potential of Predictive’s novel MADR approach of combining DNA and protein biomarkers into a single assay. Using our multi-analyte diagnostic assay, we can identify with very high certainty a cohort of patients who do not have cancer, and who therefore could be excluded from undergoing unnecessary invasive procedures,” remarked Anthony P. Shuber, co-founder and chief technology officer for Predictive Biosciences. “Those determined to be cancer free at the time of evaluation could forgo cystoscopy, while all others would continue to receive existing standard of care procedure. This work has important implications for potentially improving the care of cancer patients while reducing overall healthcare costs.”

The MADR approach is being utilized by Predictive in the development of its CertNDx™ line of cancer assays, and is an extension of Predictive’s Clinical Intervention Determining Diagnostic (CIDD™) approach. CIDD was developed by Predictive to identify biomarker cutoffs that maximize negative predictive value in order to identify with very high certainty those who require no further intervention.

Predictive is currently conducting two clinical trials for its CertNDx bladder cancer test; one in individuals who have exhibited symptoms of bladder cancer such as hematuria (blood in the urine), and one in bladder cancer patients undergoing recurrence monitoring. The Company expects to launch its first bladder cancer assay this year through its OncoDiagnostic Laboratory division.

SOURCE Predictive Biosciences

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
AI-powered tool predicts gene activity in cancer cells from biopsy images