Inform Genomics Transplant Product Shown to Predict Oral Mucositis with a High Degree of Accuracy in Patients Undergoing Conditioning Regimens Prior to Hematopoetic Stem Cell Transplant

Oral presentation at 2012 American Society of Hematology meeting highlights final results of first phase of development and announces plans for multicenter validation study


Boston, MA, Dec. 11, 2012 (GLOBE NEWSWIRE) --  Inform Genomics, Inc., a private company focused on developing novel platforms of genomic-based personalized medicine products for cancer supportive care, presented results that demonstrate the ability of its Transplant Product to predict a patient's risk for developing oral mucositis (OM) prior to high dose chemotherapy as part of conditioning regimens for stem cell transplant in patients with hematologic malignancies.

"Using DNA collected from saliva, we can now identify patients at risk for serious and often debilitating oral mucositis before they undergo high dose conditioning chemotherapy," said Dr. Stephen T. Sonis, cofounder of Inform Genomics and principal investigator of the study.  "This allows us to consider preemptive use of approved interventions such as Kepivance® to reduce the duration and severity of oral mucositis. Furthermore, it allows us to investigate other novel interventions for mucositis since we can now identify the at-risk patients. This paradigm of using Bayesian single nucleotide polymorphism (SNP) networks to predict side effects of chemotherapy has the potential to usher in a new era of customized cancer care."

The first phase of development for the Transplant Product was conducted as a single-center study at Dana-Farber Cancer Institute in Boston, Massachusetts. The study enrolled 153 patients including 82 with multiple myeloma and 71 with Hodgkin's' Disease and lymphoma. High dose chemotherapy conditioning regimens included melphalan, etoposide and carmustine. Patients who underwent stem cell transplant from 2006-2011 were identified and after informed consent had their saliva collected with an FDA approved kit which, when analyzed, detected 1.1 million SNPs per patient. Demographic information, oral mucositis incidence, and grade using the WHO (World Health Organization) scoring system and other clinical characteristics were abstracted from the medical records.

Using algorithms based on Bayesian methodological programming, an 82 SNP predictive network was discovered for Grade >2 oral mucositis. In an independent exploratory validation set, the 82 SNP predictive network from the 153 patient study was then applied to a separate group of 16 patients treated with similar regimens during the same time interval. The SNP network was able to predict which patients were at risk of developing OM with an accuracy of 81%.

"This presentation highlights the first independent validation of our predictive Bayesian SNP networks in identifying patients at risk of oral mucositis as a consequence of high-dose chemotherapy prior to potentially curable hematopoietic stem cell transplant" said Dr. Ed Rubenstein, president & CEO of Inform Genomics. "We are particularly pleased that we did not see false positive classifications in the independent exploratory validation set."

We have completed the design of a multicenter validation study and look forward to enrolling patients in the second half of 2013. Once commercialized, the Transplant Product will be available to help healthcare professionals further customize their cancer care strategies in the management of hematologic malignancies and will complement the target market of our lead product, OnPART™ for patients with solid tumors."

About OnPART™

OnPART™, Oncology Preferences And Risk of Toxicity, is Inform Genomics' lead platform personalized medicine product for treatment decisions in patients who will receive chemotherapy for breast, colorectal, lung, or ovarian cancer. Based upon response rates and survival, more than one chemotherapy regimen may be considered appropriate care for patients with these common solid tumors, yet the regimens vary widely in their side effect profiles.  OnPART™ is being developed to assess genomic risk for 6 common and often debilitating therapy-related side effects, including oral mucositis, nausea and vomiting, diarrhea, fatigue, cognitive dysfunction and peripheral neuropathy. The product includes a differentiating factor in personalized medicine, quantifying patient concerns for side effects, using a validated, copyrighted patient questionnaire (Preference Assessment Inventory©). OnPART™ is expected to provide valuable information for patients and medical oncologists to help clarify clinical choices and is projected to be commercially available in 2014.

About Cancer Supportive Care

Most patients with cancer receive supportive care as part of their multimodal anti-cancer therapy, regardless of cancer diagnosis, stage of disease, or treatment modality. Common side effects associated with cancer or its treatments include oral mucositis, nausea and vomiting, diarrhea, fatigue, cognitive dysfunction, and peripheral neuropathy. Some of these conditions are manageable with commercially available medications, while others are the focus of current drug development programs. These side effects are costly for payers, create inefficiencies for oncology practices, may interfere with ongoing anti-cancer treatment, impair patient functioning, negatively impact a patient's quality of life, and may even increase the risk of mortality.

About Inform Genomics

Inform Genomics, Inc. is a private company focused on developing novel platforms of genomic based personalized medicine products for cancer supportive care. Our proprietary methodologies, including the utilization of Bayesian Network analysis, have discovered biologically valid, single nucleotide polymorphism (SNP) networks that are highly predictive of moderate-to-severe side effects of common chemotherapy regimens. We have completed the first phase of development for our products.  The development programs are expected to lead to commercial, single source laboratory developed tests consisting of SNP networks that determine the likelihood of individual patient clinical outcomes.  The U.S. market opportunity for these differentiated products exceeds $1B annually. We expect to begin product sales in 2014.


            

Contact Data