Business
Extensions for Virtual Tumour Project
Extensions for Virtual Tumour Project.
About this update from Physiomics Plc
[{"type":"text","content":"\n \nRNS Number : 2596Y Physiomics PLC 16 May 2016 \n\nPhysiomics plc \n(\"Physiomics\") or (\"the Company\")\n \nUpdate: 6th and 7th extension projects to advance oncology candidate with global pharma company\n \nPhysiomics plc (AIM: PYC), the Oxford, UK based systems biology company, is pleased to announce that it has signed further extensions to a Virtual Tumour project with a major global pharmaceutical company, first announced on 1st March 2012. The 6th extension will cover predicting optimal regimens for follow-up compounds and in vitro to in vivo translation, whereas the 7th extension will predict optimal regimens for a candidate in an additional cancer indication. \n \nThe project will be performed on a fee-for-service basis. \n \nDr Jim Millen, CEO of Physiomics, commented: \n\"We are very pleased to have further extended this collaboration, showing the value of our Virtual Tumour technology in supporting the development of follow-on compounds and indications. We hope this collaboration will continue well into the future\"\nEnquiries:\n \nPhysiomics plc \nDr Jim Millen, CEO\n+44 (0)1865 784 980\n \n \nWH Ireland Limited (nomad/broker)\nKaty Mitchell\n+44 (0) 161 832 2174\n \n \n \nAbout Physiomics plc\n \nPhysiomics (AIM:PYC) is a computational systems biology services company applying simulations of cell behaviour to drug development to reduce the high attrition rates of clinical trials. 80-90 per cent of all clinical drug candidates fail to reach the market and estimates show that an overall ten per cent improvement in success rates could reduce the cost of one drug's development by as much as $242 million, from the current estimate of around $800 million1.\n \nPhysiomics develops computational systems biology models to predict and understand cancer drug efficacy from pre-clinical research to clinical development. Physiomics has created detailed mathematical models incorporating the most important molecular events taking place during the human cell cycle...