Data has always been the fuel powering clinical trials. Data generated during clinical studies are the scientific basis for drug approval, but to run efficient trials, a lot more and different data are required.

The speed with which companies can identify physicians, patients, and sites for their trials as well as external experts who advise on various aspects of drug development can make an enormous difference in the commercialization timeline. In a competitive market, data that help companies find these critical resources can accelerate clinical trials and shorten time to market – sometimes by years.

Here are four primary data-driven approaches organizations can leverage to efficiently plan and manage clinical trials.

Finding the best physicians for the trials

The principal investigator (PIs) and their team of physicians are critical for clinical trial success and many factors go into determining who the best physicians are for each trial. In the past, PIs were identified through networking. Drug makers relied on a group of physicians they worked with before as well as referrals by this group of established PIs. This approach has both advantages and disadvantages: known physicians can be signed up more easily and an established working relationship can get trials started quickly. However, it is blind to new experts outside the network and may fail to find the best people, especially when a company enters a new therapeutic area.

Today, pharma companies subscribe to powerful databases that collect comprehensive profiles of millions of healthcare providers (HCPs) as well as medical and scientific experts. These databases contain up-to-date information like physicians’ research focus and publication list, the clinical trials they were involved with, their hospital affiliation, which conferences they presented at and which pharma partners they work with. They also reveal what diseases a physician specializes in and whether they are seeing patients or focus on research.

This information can be filtered and searched to hone in on HCPs best suited to drive a drug maker’s clinical trials. Streamlining the identification of the best physicians for clinical trials alone can shorten the process by months.

Databases can also help ensure that trials meet diversity requirements by identifying physicians who focus on diversity and inclusivity. These physicians often have deep connections into underrepresented communities and can help companies reach out.

Increasing successful patient enrollment

All clinical trials have specific criteria that patients must meet to enroll. Identifying enough qualifying patients to guarantee the trial will enable statistically meaningful conclusions can be difficult and time consuming, especially in the case of rare diseases and precision oncology trials. Failure to identify patients that meet the eligibility criteria and to recruit them is a frequent reason that clinical studies are delayed.

“Most studies do not finish in time due to low patient participation and slow recruitment.” said  Laurie M. Ryan, program director for Alzheimer’s disease clinical trials at the National Institute on Aging at the National Institutes of Health, according to Clinical Trials Arena.

Successful patient recruitment also means identifying patients from diverse racial, ethnic and socio-economic backgrounds. Comprehensive claims data can help identify where these patients live, guide enrollment efforts and ensure that the trial participants are representative of the population as a whole.

One well-known example is the underrepresentation of women in cardiovascular clinical trials. Cardiovascular disease is a leading cause of death among women worldwide, but they continue to be underrepresented in clinical trials to this day. A recent study showed that only 38% of patients in these trials were women despite the fact that they are almost 51% of the US population.

Ideal trial site: where PIs and patients meet

Efficient and successful clinical trials need qualified PIs, enough eligible patients, and a hospital where they meet: the clinical trial site.

Combining data about physicians that could serve as PIs and information about disease incidence can help companies identify trial sites that offer the best chance for successful recruitment. Again cardiovascular disease is a good example: different states in Germany have significantly different prevalence of cardiovascular disease ranging from 10% to almost 16% – a fact that can inform site selection for cardiovascular drug trials.

Other data that can inform the selection of a trial site are size and specialization of the hospital, patient referral patterns and other treatment centers in the area. If a site has a large network of referring healthcare providers and no other hospitals that offer similar medical services nearby it has a higher chance of recruiting eligible patients than one that is less specialized and competes with other facilities for the patients.

Finding experts and key opinion leaders

Pharma companies continually engage experts who can provide insights, expertise, and feedback to inform the entire drug development process. Clinical trials are no exception. For successful planning and management, companies partner with experts who have expertise in clinical trial design and can advise on the right endpoints and biomarkers. There are so many examples in medicine of good drugs with bad trial designs — having experts that can help you pick the right primary and secondary endpoints can be the difference between being first or third to market or never making it at all. As the therapeutic gets closer to approval, companies also engage experts who can present data at scientific and medical congresses to inform their peers about the new drug and support many other crucial activities.

Companies traditionally identified external experts through networking. Now, expert databases containing millions of healthcare providers, as well as scientific and medical experts are used. These databases make it easier to quickly identify highly qualified people with the right combination of expertise and experience, even if they are outside their established networks.

Developing a drug, especially the clinical trials performed to ensure its safety and efficacy, are necessarily time-consuming processes that require extremely careful planning and implementation. After all, the well-being of the study participants and later all patients is at stake. Detailed, comprehensive data can help streamline inefficient processes that lead to avoidable delays, e.g., related to underperforming clinical trial sites and slow patient recruitment. Data can also help identify the most qualified experts on a local, regional, national or global level, without introducing a network bias.

Data-driven trials do not only translate into shortened timelines and lower overall cost for drug development, but they also decrease the time it takes for a new, potentially life-saving drug to reach all patients.