TGen Drug Development and IPC collaborate to speed up research discoveries for cancer patients

NewsGuard 100/100 Score

TGen Drug Development (TD2) and the Institut Paoli-Calmettes (IPC) have forged a strategic alliance that will enable both to maximize their worldwide contributions in the treatment of cancer patients.

The partnership between TD2, a Scottsdale subsidiary of the Phoenix-based Translational Genomics Research Institute (TGen), and Marseille, France-based IPC's comprehensive cancer center will enable both non-profit institutes to speed research discoveries to patients with cancer.

Both organizations will expand their clinical research network to evaluate new therapies in the U.S. and Europe in an effort to more quickly introduce new drugs into clinical trials.

Teams from both TD2 and IPC will focus their efforts on discovering molecular alterations within cancers and finding biomarkers that will help identify new therapeutic targets that can be used to tailor treatments for individual patients.

IPC and TD2 will collaborate on a number of primary tumor and metastasis in selected cancers, as well as initiate an exchange program for medical oncologists between the two institutions.

"Aligning with IPC represents a significant opportunity for TD2 and TGen to further expand our research affiliations into Europe," said Dr. Daniel Von Hoff, TGen's Physician-In-Chief. "In addition to our ongoing collaborations with Luxembourg, this new alliance with IPC will further our goals across both Europe and the United States of providing better treatments in a more timely fashion to our many patients who suffer from a variety of cancer types."

Professor Patrice Viens, a medical oncologist and General Director of IPC, said the alliance with TD2 will enable IPC to bridge new international relationships: "This alliance with TD2 translates to our continuing efforts to expand our collaborations in basic research and medical activities beyond Europe.''

IPC is one of the largest university-affiliated comprehensive cancer centers in France, involved in the management of nearly 6,000 new cases of cancer each year. IPC established a Biological Resource Center (BRC) in oncology that has 70,000 tumor and biological fluid samples, mostly of breast, pancreatic and blood cancers. ICP had more than 600 patients in clinical trials during 2008.

IPC is affiliated with the Ovarian Cancer Diagnosis Initiative (OVCAD), which is dedicated to ovarian cancer research, and with the European Consortium for Anticancer Antibody Development (EUCAAD), a European consortium dedicated to anti-angiogenic treatments. It also is involved in collaborations with biotech and pharmaceutical companies.

IPC will join TGen's Pancreatic Cancer Research Team (PCRT), which includes other U.S. and international researchers.

"Our meetings at TGen have confirmed our decision to team up with this premier organization on the cutting edge of research and pharmacogenomics in oncology," Professor Viens said. "In addition we are thrilled to work again with Dr. Von Hoff." Professor Viens and Dr. Von Hoff once worked together at the University of Texas Health Science Center in San Antonio, Texas.

Source: The Translational Genomics Research Institute

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...
MONET: New AI tool enhances medical imaging with deep learning and text analysis