By Michael Quigley, Research Analyst, LSN
It is no secret that more and more hospitals in the US and across the globe are beginning to store their patient records electronically: One of the biggest drivers of this trend in the US is the HITECH Act of 2009, which allocated nearly $30 billion to increase the use of electronic health record systems (EHR), primarily though incentive programs. Currently, under this act, hospitals that have not implemented the most basic form of EHR by July 1st, 2014, will face monetary fines that will increase over time. Furthermore, some institutions – such as the Patient-Centered Outcomes Research Institute (PCORI) – are working to develop a national, patient-centered network for clinical research that will work on improving both the quantity and quality of patient provided data.
This increase of electronic patient data is great news for companies in the health industry for a variety of reasons, but especially when applied to clinical trials: Currently, screening for clinical trials (as well as the trials themselves) often omit numerous significant factors of a participant’s health profile. With this data becoming readily available and standardized, companies will be able to dilate their inclusion criteria for candidates in their trials based on a myriad of different variables, including age, weight, race, gender, lifestyle, and perhaps most importantly, genomic data. By understanding these variables, research organizations will be able to more effectively understand how their products effects different patient types, while avoiding screening patients for trials that they do not want.
Take cancer, for example, most patients are over the age of 65 and have some sort of chronic health condition. However, in clinical testing conditions, most candidates around the age of 50 are pre-selected to only have cancer. What ends up happening is that you develop a product that will be used on a market that it has not been sufficiently tested on. Having more easily available patient data could greatly reduce this dilemma and enhance the potential benefit of personalized medicine. Also once clinical trials are completed, as it currently stands, the connection between the research organization and the patient comes to an end. But with the continued uploading of patient data, whenever they visit a doctor, more long-term effects could be evaluated as well. (1)
As more data is continually made available, the resulting increase in the efficiency of clinical trials is great news for established and emerging companies, as it may chop away at the daunting $1b number that is often associated with getting a drug on the market. This data doesn’t just have the potential to lower the cost of trials; it also gives companies greater visibility as to potential reasons for why their product did or didn’t work, and what they could alter to make it more effective, thus increasing the effectiveness of drug production process on an even larger scale. So what does it mean for the industry at large? CRO’s in the trial space should adapt and find an edge in this arena to compete for the myriad of trials due to come from emerging biotech firms. Investors should re-evalute their investment timelines due to potential shortening of time to market, and emerging biotechs should focus on more niche opportunities for treating specific subpopulations within indications.
1. Mearian, Lucas. “How Big Data Will save Your Life.” Computerworld. Computerworld, 25 Apr. 2013. Web. 11 July 2013.
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