Release date: 2015-04-22
Life sciences companies continue to explore ways to strengthen clinical research while increasing their understanding of the drugs they develop. One of the biggest problems faced by current researchers is the high failure rate of new drugs in the clinical development process. This is a very serious problem. It is estimated that the global pharmaceutical market will exceed $1.2 trillion in 2018.
According to data from the Tufts Drug Development Research Center, a new drug is approved from the R&D to the FDA (US Food and Drug Administration), with an average cost of $2.5 billion. Among them, the higher drug failure rate has greatly promoted the increase in research and development.
But now, a new opportunity emerges: If life sciences companies get enough data early in development, they can create a more effective drug development process that prioritizes resources for the most effective treatments. Big data analytics and new clinical technologies (such as mobile health solutions and wearables) can dramatically change the way clinical experiments are performed, increase the value of data, and get more results from clinical trials.
The increase in computing power and the emergence of predictive analysis tools allow us to process massive amounts of data in seconds and obtain analytical results. Among them, the role of technology is to integrate decentralized data resources, allowing industry sharing and analysis to help make more informed decisions. This will allow us to develop more effective drugs faster.
For example, 23andMe, a Silicon Valley genetic data company, recently named Richard Scheller, a senior researcher at genetic engineering technology company Genentech, as chief scientific officer (CSO) and head of therapeutics, responsible for mining genetic database information for nearly 900,000 people in 23andMe. I hope to find new clues to treat common and rare diseases.
There are also companies that are working together to better map wearable devices for patients, combining data from these devices with traditional clinical data to measure patient behavioral changes and use that information to make more informed decisions. Last month, Medidata, a provider of cloud solutions for life sciences clinical research, announced a strategic partnership with Garmin to enhance patient engagement, data quality and operational efficiency in clinical trials through the combination of Garmin's health bracelet and Medidata Clinical Cloud. In addition, companies such as Vital Connect have received FDA approval to use their biosensors to monitor patient biomarkers.
Previously, the patient's health status could only be assessed in the clinic. But these life science companies are pushing us into a new era, connecting to a new set of behavioral data that was previously unavailable. The cases described above allow us to enhance patient interaction in clinical trials, and ultimately allow us to obtain more and more useful data, which is critical for breakthroughs in drug discovery.
When you ask the patient how they feel, you get a subjective answer. Subjective data is also important in scientific research, but far from objective data. Life sciences companies can now collect a range of new objective data from mobile devices and various activity tracking devices, allowing us to evaluate patient physiological indicators in real time to understand the extent to which a drug affects a patient's quality of life. This is an increasingly important measure for pharmaceutical companies, regulators and insurance companies.
Take the 6-minute walk test as an example. This test has been used to measure the severity of illness in patients with cardiovascular, respiratory, and central nervous system disorders for many years. There are no mathematical or scientific errors in the test plan, but with the new technology, we can make a more comprehensive assessment of the patient's condition. More than just showing the doctor a 6-minute walk, the patient can now wear wearables and keep track of the activity, providing comprehensive information on the activity to the doctor without going into the doctor's office. In this way, the patient's daily life will not be disrupted, and doctors and researchers will get more abundant data.
Apple recently released the ResearchKit platform to promote medical research with iOS applications. It also shows that all industries are interested in the value of data directly from patients.
Mobile devices and big data analytics can also significantly reduce the burden on patients. Wearable devices can reduce the number of visits to patients, provide more comprehensive, higher quality patient physiology data to assess efficacy, and minimize unnecessary patient examinations.
GlaxoSmithKline (GSK) said last month that it plans to introduce biosensors into clinical trials to improve data quality. These biosensors not only provide more data, but also reduce the interference to the patient's daily life through remote monitoring. Therefore, technology will greatly enhance the patient experience in clinical trials.
Ultimately, if life sciences companies can not only demonstrate the effectiveness of their drugs in treating specific diseases, but also greatly improve the quality of life of patients, they can help regulators make better decisions and get drugs to market as soon as possible. .
Of course, to see this change requires the joint efforts of the main players in the market. When regulators recognize this new approach to clinical development, pharmaceutical companies are willing to use new technologies and big data analytics in their clinical research. Vice versa, regulators are willing to accept this new approach if pharmaceutical companies are able to develop standardized clinical development methods based on strong scientific evidence.
Source: Singularity Network
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