MPI's Lung Prognostic Chip study expanded with new gene test - publication of data consequently postponed to H1 2015

2014-07-11

Hoersholm; July 11 2014 - Medical Prognosis Institute A/S (MPI) announced today that tissue biopsies from patients enrolled in the prospective study of stage 1a Non Small Cell Lung Cancer will undergo a new gene test on mRNA (messengerRNA) in addition to microRNA to further enhance the strength of the data predicting which patients might progress following surgery. MPI has strengthened its technology in both the Lung Prognostic Chip program (LPC) and for the lead product Drug Response Predictor (DRP) to include information on how genes are expressed in tumor tissue. This can be done on all tumor tissue exposed to standard procedures for storage and cutting (biopsies fixed in formalin and embedded in paraffin). This information is now to be included to the potential benefit of the lung cancer patients in the here mentioned study. Publication of data in the LPC study has consequently been postponed from late 2014 to H1 of 2015.

"I'm very excited that the MPI technology has been significantly strengthened by the addition of the analysis of mRNA to the toolbox. I believe that this can strengthen the value of the LPC why we have chosen to take the time to implement the work in the Lung Chip study. As a consequence the publication of the data will be postponed from 2014 to H1 2015," Said CEO, Peter Buhl Jensen


About Lung Prognostic Chip - LPC

MPI's LPC will be used for test of cancer specimens in order to gain information about potential disease progression after surgery. A subgroup of patients (approximately 70%) diagnosed with stage 1a lung cancer is expected to be cured  after radical surgery whereas the other subgroup of patients are expected to have disease progression. LPC has with success been tested in two smaller clinical studies and a large prospective multi-center clinical trial with an observation period of five (5) years is planned to be unblinded at the end of 2014 whereas the analytical validation is expected to be finalized in the first half of 2015. Clinical trial protocol has been forwarded to the FDA for review to ensure that this study comply with regulatory guidelines and can form the basis for notification of the health authorities before launch on the US marked. MPI will further ensure that the LPC can obtain appropriate labeling for launch in Europe.

About Drug Response Predictor - DRP

MPI's lead product DRP is a tool to develop tumor-derived gene signatures that may predict which cancer patients are high likely responders to a given anticancer product. The DRP has been tested in 24 trials where 20 trials were positive.  The DRP has also been externally validated and published in collaboration with leading statisticians at the MD Anderson Cancer Center. The DRP method can be used to design the Clinical Development Plan i.e. to select which indications are relevant for a given anticancer drug. Further to and in addition to this, individual patient's gene patterns can be analyzed as part of a screening procedure for a clinical trial to ensure inclusion of patients who have a high likelihood of response to the drug. The DRP method can be used in all cancer types and has been patented for more than 60 anticancer drugs in the US in 2013.

 

For further information please contact
CEO Peter Buhl Jensen, Professor, MD, PhD
E-mail: pbj@medical-prognosis.com
Cell Phone: (+45) 21 60 89 22

Certified Advisor: Carsten Yde Hemme, PricewaterhouseCoopers, Strandvejen 44, 2900 Hellerup, Denmark

 

About MPI

MPI's proprietary method can predict patients sensitivity towards a given anticancer drug by its Drug Response Prediction a gene-tests on tumours. MPI's customers are Pharma and biotech engaged in developing anticancer drugs. MPI's technology has derived from data from more than 3.000 patient's tumours and are validated in 24 clinical studies. The test is broadly applicable in all cancer types and for almost all anticancer therapies. The test is believed to be of high value especially for the very large group of cancer patients for whom there are no other bio-markers available.