New collaboration with Pharmacometrics Limited

RNS Number : 8683F
Physiomics PLC
04 May 2011
 



Physiomics plc

("Physiomics" or "the Company")

New collaboration with Pharmacometrics Limited

 

Physiomics (AIM: PYC), the Oxford, UK based systems biology company, is pleased to announce the execution of a new collaboration agreement with Pharmacometrics Limited ("Pharmacometrics"), pursuant to which it is agreed that both parties will work together to develop an anti-cancer drug regimen and combination database.

 

Pharmacometrics will provide its proprietary drug information dataset, which will be united with Physiomics drug and regimen dataset; creating a new comprehensive anti-cancer drug regimen database.

 

This database will ultimately be marketed to clinicians and researchers in oncology, as well as used to supplement and enhance Physiomics' Virtual Tumour service. In particular, as the database will include new clinical data, the directors believe this information can be utilised to make Physiomics Virtual Tumour predictions more relevant clinically (a key objective of the second strategic imperative announced in the Company's interim statement of 9th March 2011).

 

Physiomics will be responsible for the technical implementation and commercialisation of the database, whereas Pharmacometrics will receive a nominal royalty on net sales of the database and if information from the database is utilised in the Virtual Tumour service.

 

Dr Mark Chadwick, CEO of Physiomics, said

 

"This collaboration represents a significant step forward in our pursuit of more clinically relevant models.  The database should also improve our speed of delivery to customers by allowing us to quickly research standard of care data."

 

Dr Robert Jackson, Director of Pharmacometrics, said

 

"As the large number of new targeted anticancer drugs entering development makes the oncology field more complex, I believe health information systems will increasingly be used to guide preclinical and clinical drug development, and ultimately to make possible personalised medicine.  The drug regimen database that we have built is our way of addressing this process."

 

 

Enquiries:

 

Physiomics plc                                                  

Dr Mark Chadwick, CEO

+44 (0)1865 784980

 

WH Ireland Limited

Katy Mitchell

+44 (0) 161 832 2174

 

Information on Physiomics plc

 

Physiomics (AIM:PYC) is a computational systems biology services company applying simulations of cell behavior 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.

 

Physiomics 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 and apoptosis processes. The company's SystemCell® technology enables the simulation of populations of "virtual cells". The company has also developed a "Virtual Tumour" model to simulate the effect of anti-cancer drugs on tumour growth. The models are used to optimise compound design and to design drug schedules and combination therapies.

 

Physiomics, based in Oxford, UK, was founded in 2001, and floated on AIM in 2004. For further information, please visit www.physiomics-plc.com

 

SystemCell® is a registered trademark of Physiomics plc

1Tufts Centre Impact Report 2002

 

Information on Pharmacometrics Ltd

 

Pharmacometrics Ltd (www.pharmacometrics.co.uk) offers consulting services and proprietary software in computational pharmacology with a focus on pharmacokinetic/pharmacokinetic modelling and cytokinetics.  Its long-term objective is to develop expert systems for prediction of optimal treatment of malignant disease based upon biomarker expression patterns.

 

 


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