The Future of Clinical Trials – Part 2 Analytics

In the last blog, we briefly examined the role of ‘wearables’ in future clinical trials. Wearable are devices patients carry that remotely sends medical data back to the testing site either periodically or on a continuous basis. This capability both broadens the geographic range of patient recruitment and produces a greater amount of data that more accurately reflects the new medication’s effects in patients throughout the day. The capability dramatically increases the flexibility and range of clinical trials.

One clear result of using mobile devices to collect clinical trial data is that there is an exponential increase in the amount of data collected when compared to older manual methods of gathering information. Because of this, there is increasing demand for access to software and computing facilities capable of analyzing both a far greater volume of data and also examining that data in new and innovative ways. The development of this type of data analysis – called ‘Big Data’ – is progressing in parallel with other advances in clinical trial techniques.

Analysis of more extensive and more varied data sets is allowing research sites to look closely at aspects of drug and treatment effectiveness not possible before. For example, data can now be analyzed from more patient sub-groups within a population of trial participants. Because of increased abilities to examine more focused areas, researchers can develop a more detailed analysis of any new product’s performance. Also, subtle differences in product performance under various real-world conditions can be identified. With better data analysis, these kinds of product performance differences, if any are detected, can result in slight modifications to the trial’s protocol. Thus, examining a broader spectrum of clinical trial data gives researchers a clearer picture of the product’s performance under more patient conditions. The result: improved patient outcomes using the new drugs or treatments.

This analysis also allows for changes in the ways clinical trials are conducted. When a large amount of trial data can be analyzed both quickly and early in the trial, before the trial is ‘locked,’ changes can be made to the trial’s protocol. For example, modification of the type or amount of data being collected might be changed. Being able to make these types of changes increases the ability of researchers to understand the effects of new products within patient populations.

Including larger groups of patients and covering more variations in each patient, conditions allow clinical trial researchers to understand better how new products work in both the larger populations as well as in patient sub-groups. As the development of analytics progresses, the research community is benefiting from faster data analysis, more and better information being produced, and broader ranges of patients being tested.

DM Clinical Research, based in Tomball, Texas, is a leading provider of clinical trials examining new drugs and treatments used for many important diseases. Currently DM Clinical is conducting important clinical trials investigating new treatments in Meningitis, Rheumatoid Arthritis, Clostridium Difficile (C Diff), Type 2 Diabetes, and COPD. At DM Clinical Research we are continually recruiting new patients to participate in any of our ongoing trials. Selected patients receive the most advanced treatments available for various conditions free of charge, along with free doctor consultations, and lab work. Participants are also compensated for their time and travel.

If you believe you may be a candidate for one of our exciting research trials currently underway, please give us a call at 281-517-0550. One of our professional staff will be glad to assist you and answer any questions you may have. Get started today.

Disclaimer - Use At Your Own Risk :- The information on this website is for general information purposes only. Nothing on this site should be taken as advice for any individual case or situation. Any action you take upon the information on these blogs are strictly at your own risk. We will not be liable for any losses or damages in connection with the use of the information from these blogs.