Drug development innovations that work: real-world data studies (Part 2 in a series)
Many pharmaceutical industry leaders recognize that new drug development is increasingly slower, more difficult and more expensive than ever before. Failure rates are high, and costs are expected to only increase.
Are there any solutions? Are there any innovations that can turn this ship around? Yes. A recent study by the Economist Intelligence Unit (EIU) analyzed data from thousands of clinical trials and found that four types of clinical trial innovations significantly increase drugs’ chances of success: adaptive trials, patient-centric trials, precision medicine trials and real-world data trials.
Overall, drugs developed using these innovations showed 10-21% increases in their likelihood to launch successfully, compared to drugs that did not employ any of those innovative designs. In addition, drugs developed using innovative methods reached the market more quickly—as much as a 41% increase in achieving formulary or national market authorization in the U.S., Europe and Japan.
Despite the positive results, these innovative clinical trial designs are underutilized, the study found, due to a combination of systemic and cultural barriers. Part one of this series examined the issues surrounding adaptive trials. Today’s installment focuses on real-world data trials.
The impact of real-world data
The term “real-world data,” as defined in the EIU report, refers to data collected during drug development and following market approval that helps to assess the impact that a therapy has in a real-world setting, rather than in the trial environment. It typically includes data from electronic health records, claims and billing data, product and disease registries, and data gathered from health apps and wearable devices. In a practical sense, this might mean recruiting study participants from registries, gathering data from participants via wearable devices or creating a virtual control group from existing data.
Studies that incorporate real-world data, the EIU study found, show significant benefits over other trials:
- Real-world data improves the likelihood of a successful product launch across all therapeutic areas. Drugs developed using real-world data had an 89% likelihood of launch, 21 percentage points higher than the comparison group (68%). That 21-point surge, moreover, was the biggest increase seen in likelihood to launch among the four innovations studied.
- Real-world data results in faster study-recruitment time. Studies using real-world data needed six months on average to recruit 100 people, versus seven months in all trials.
More successful launches mean real-world data studies help to get drugs into the hands of patients more successfully. “That’s because real-world data helps to inform a study design,” says Michelle Hoiseth, Chief Data Officer, PAREXEL. “It helps ensure that the study will work better within the standard of care, within the available patient populations. Real-world data can tell you what the patient characteristics should be and what the eligibility criteria should look like. The study is better designed.”
Faster recruitment times also result in considerable benefits, she noted. “Startup and enrollment are the most time-consuming and costly parts of any study,” says Hoiseth. “Decreasing enrollment time not only increases the probability of success of the study itself but has the potential to dramatically reduce time and costs.”
Given such benefits, why are clinical trials that incorporate real-world data so uncommon? They made up less than 1% of the thousands of studies that were examined in the EIU investigation.
The barriers to adoption of real-world data trials are common to all four areas of innovation, the EIU study found. New and large sets of data that could be used in such trials are now available, but they are fragmented and often held in isolated, proprietary data silos that are not being shared. In addition, many companies don’t currently have a workforce that is ready and able to make good use of such data. Finally, many drug development companies are simply reluctant to try new things or to move in new directions.
Data-savvy companies are already taking advantage of real-world data
Some innovative, forward-looking companies are moving forward, however, and finding ways to take full advantage of the promise of real-world data.
“People are beginning to see the value in these new ways of doing things,” says Hoiseth. “They are starting to overcome their aversion to working in new ways.”
For example, she says, new public-private partnerships are helping to improve access to data that many institutions were long reluctant to share. “People are now thinking of data less as a proprietary asset and more as something that can be used to improve the care of all people,” she says.
In addition, she says, companies are starting to rethink the composition of their study teams, building data-savvy workforces that can make better use of the data they collect. Advanced data analytics packages are making it possible for end users to do their own analysis of the data, without the help of programmers and statisticians. “But you still need someone to help configure the data on the back end, figure out what technologies are needed and what analytics package is best for that particular use of the data,” says Hoiseth. “You need a data-savvy workforce that can ensure that analyses are appropriate and accurate. Those are new roles for a study team.”
Smart companies are also taking steps to ensure early stakeholder involvement in the drug-development process, again making good use of real-world data, adds Leanne Larson, Corporate Vice President and WW Head, Real-World Evidence Strategy, PAREXEL.
“Early payer engagement in the clinical trial process is central to drug development success today,” she says. “Engaging with payers early allows you to better understand the questions they are going to ask. That, in turn, helps you to better understand the evidence you’re going to need to produce to answer those questions and to ensure the product receives reimbursement. It will drive better and faster patient access to important therapies. Early engagement also allows you to better define any additional studies you might need to do, putting you in a much better position going forward.”
Real-world data studies are likely to soon grow beyond their 1% representation in drug development. Research models that can take advantage of real-world data are becoming more popular, often combined with traditional, randomized controlled studies.
“We are now seeing many more hybrid studies that are collecting both primary and secondary data,” says Larson. “The end result is a very robust, deep study that’s scientifically sound and can answer a broad range of questions.”
Hoiseth and Larson suggest four steps that companies can take today to move toward better, more-successful clinical trials:
- Foster innovation in clinical trial processes and measure impact.
- Invest in the workforce to deliver the promise of big data and innovative trial design.
- Collaborate to innovate and connect people and data silos.
- Engage in multi-stakeholder initiatives earlier and more often.
“Everyone is moving in this direction now,” adds Hoiseth.
Ready to explore innovative clinical trial designs that can boost the success of your products? PAREXEL’s experts can help your company to develop truly innovative studies that result in impactful drug development.