When a clinical trial is conducted, it often has specific goals. It may be to test the safety and efficacy of a drug or other treatment on a small or large population, or it might look at other previously unstudied beneficial effects of a treatment already in use. Any study tends to generate tons of information that begins with thorough interviews of study participants and ends with reactions to the testing. This information is called clinical trial data.
Even though a study can have particular objectives, clinical trial data may exceed these objectives and reveal patterns for which researchers weren’t looking. For instance, many years ago, minoxidil, or Rogaine®, was being studied as a drug for high blood pressure. During testing it was discovered that the medicine could retard hair loss or stimulate new hair growth. Today, Rogaine® is mostly marketed as a medicine to prevent hair loss, and clinical trial data is largely responsible for this change in marketing strategy. Many other medicines or treatments have revealed through collected clinical data or later data review that they perform some function for which they were not originally designed.
Some of the things included in clinical trial data are ages, disease statistics, family history, gender, and other personal information about each participant. As a study progresses, researchers continue the collection of data including self-reports or physical findings of those being tested. Depending on length of the clinical trial, information could be collected numerous times as a study progresses, adding to the sum total of knowledge about effects of treatments.
A few factors that get analyzed in particular are the degree to which a medicine appears to work and the amount of side effects that might occur. Even if clinical trial data shows a treatment to be effective, other data suggesting a heavy side effect profile usually means the treatment won’t be popular. It may not become an approved treatment or might only be considered if no other medical management strategies can work.
A topic that is frequently undertaken in discussing clinical trial data is the issue of how data is collected. Many times, despite proliferation of electronic means of data collection, research findings are all collected on paper. For large studies, this can produce a huge amount of extra work when it comes to organizing and analyzing data. There are a few computer systems that could be used instead, and which would streamline the process of collating information found. Yet these are employed not as often as many researchers would like; there is a general demand for better and more efficient data collection methods or use of those already available.
Computer analysis of clinical trial data is certainly easier, but no data collection method should begin to determine what information is not of interest. Due to the fact that information can be studied at time of trial or later by other researchers, all information gleaned from a trial should be kept intact. Occasionally, a review of data reveals new information about a treatment or drug that can suggest its use or implementation in other areas.
