Providing earlier access to medicines is a challenge for the life sciences industry. Clinical trials have a history of difficulty with recruitment. Could big data be a game changer and save the day? A new report indicates that companies conducting clinical trials for new medications can take insights from big data to recruit suitable candidates into the studies. This big data will consist of information compiled through individuals on the Internet including social media posts, search engine key word mining, Web site browsing, geographical tracking, and more. This type of data is slated to help decide factors like where and when to run the trials. The projected outcome is better, more efficient, timely studies that avoid the pitfalls of delays and failed trials and an increase in reliability. Efficiencies could include faster facilitation and reduction in costs for bringing new therapies or drugs into the marketplace.

A survey conducted in the US by the Center for Information & Study on Clinical Research Participation (CISCRP) indicates that almost half of the clinical trial respondents (46%) found information about the trials on the Internet. Only 1/5 of trial respondents were notified about trials by their physicians, and only about 20% received information from any type of health care practitioner.

The whole point of clinical trials is to develop new drugs, devices, and therapies and improve survival rates. There continues to be a challenge for the industry to find physicians willing to dedicate the time to facilitating clinical trials in their practices. Most of the barriers for physicians to undertake such a challenge include limited time, insufficient research training, lack of recognition, and taxing of staff and resources. However, there are many perks such as gaining insight and medical knowledge regarding the diagnosis and treatment of the condition in the study, having the opportunity to evaluate new drugs, and learning how to improve the quality of patient care.

Continue Reading

Many physicians are reluctant to enroll their patients or endorse clinical trials that are recruiting study participants. Patients typically continue to see their own physicians while participating in a study since the study is limited to a particular issue or disease. According to survey results published by the National Cancer Institute in 2011, based on a study of over 1500 physicians treating patients with lung or colorectal cancer, oncologists were the most likely and surgeons the least likely to refer patients to clinical trials. Physicians who teach medicine were more likely to refer patients to trials.

Doctors will always be a critical factor in recruiting to clinical trials. Patients can be unaware as to the availability and benefits of trials and rely solely, or tremendously, on their health care practitioner’s advice. Many patients who are aware of clinical trials independently choose not to participate. Primary concerns include the fear of being a “guinea pig,” the fear of receiving placebos instead of medication for treatment, and concerns that insurance carriers would not pay for the costs. Physicians can help educate and inform, which would help eliminate these fears.

With the extension of big data in the recruitment mix, it will be interesting to see if there is any significant upward trending of Internet-informed patients approaching their physicians with clinical trial opportunities instead of vice-versa. Will the use of big data consumer compilation be welcomed by potential patient participants or viewed as yet another form of invasion of privacy? It will be compelling to watch this 21st Century information adaptation process and its effects.


  1. Big data can be used to recruit people best suited for clinical drugs trials, new report says.
  2. Certain Physicians Are More Likely to Refer Patients to Clinical Trials
  3. Doctors, Patients Face Different Barriers to Clinical Trials
  5. Physician participation in clinical research and trials: issues and approaches By Sayeeda Rahman, Md Anwarul Azim Majumder, Sami F Shaban, et al Published March 2011.