Out-Law News 2 min. read
03 Dec 2013, 3:52 pm
Life sciences specialist Helen Cline of Pinsent Masons, the law firm behind Out-Law.com, said pharmaceutical companies could speed up the time it takes to develop new products and launch them to market if they can find a way to glean insights from failed projects they and others have previously invested in.
Cline was commenting after a study conducted by Deloitte and Thomson Reuters found that it costs on average $1.3 billion to develop new drugs all the way from discovery through to launch. Those costs have risen from $1.1bn in 2010, the companies said. The study, into the 12 largest life sciences companies by R&D spend, said the businesses have together lost $243bn in total from "late stage terminations" over the past four years and that the companies also expect to earn on average 43% less in "peak sales" of new products now compared with in 2010.
"For a variety of reasons, some medicinal products disappear into pharmaceutical obscurity," Cline said. "Problems with IP, toxicity, or a limited understanding about how a medicine works at the time of its discovery may all be to blame."
"Leveraging off previous investment into these products, originators and generic companies - often called supergenerics - alike, are looking at disease areas where there is significant unmet need and are investigating how existing medicines can be adapted or improved, repurposed or repositioned for new uses," she said. "While it is often still necessary to carry out clinical trials, the existing data on the medicines mechanism and safety profile may reduce the time and streamline the process of bringing the 'new' medicine to market."
"Big data is the game changer and has the potential to reduce uncertainty, facilitate more targeted drug discovery and make personalised medicine and earlier access to medicines a reality. In many circumstances, to fully understand a clinical phenomenon the snapshot of a patient's condition needs to be integrated with data on his or her past clinical history. European legislation, regulations and policies must be updated to fully leverage the potential of big data and developments in social media to assist to 'individualise' diagnosis and treatment," Cline added.
The term 'big data' refers broadly to the exponential growth in volume of data being generated and its allying to advancements in data analytics tools.
"Although personalised medicine starts with the patient, in practice, rather than having a unique treatment for each individual, pharmaceutical companies are looking at ways of identifying and targeting a treatment for only those groups of patients who respond to the drug - so called stratified medicine," Cline said. "Patients are sub-divided into groups based on their 'molecular make up', using companion diagnostics such as biomarkers.”
"Adopting this ‘stratified’ approach, within the industry, could help reduce the uncertainty drugs companies face when developing products and companies who embrace stratified medicine may even be able to gain early access to market under progressive regulatory schemes," she added.
Last week the Association of the British Pharmaceutical Industry (ABPI) hosted an event looking at the potential for big data to improve health outcomes. At the time life sciences Allistair Booth of Pinsent Masons reflected on the possible improvements that could be made to clinical trials if the potential of big data could be harnessed.
"Increasing the amount of data that is available to researchers in the life sciences industry could potentially allow clinical trials to be better targeted to involve more specific kinds of people and allow greater confidence to be derived from clinical trials data," Booth said. "Potentially the data could then be used to inform decision-making on sister trials and provide for increasing reliability on the data gathered from research. This process has the potential to cut the time it takes to run clinical trials and therefore reduce the time and costs involved in bringing new drugs to market."
