Innovation is revolutionizing a number of industries, but its impact has not yet been fully realized by the life science field. The mounting pressure to bring more drugs to market is exarcebated not only by rising drug R&D costs, which doubled between 2003 and 2016, but also by an increasingly crowded marketplace. The average time to market for a new drug has hovered around 12 years for the past three decades, limiting patient access to needed medicines. Even with all this time and money, the failure rate for new drugs in development is still as high as 90%.

To overcome these obstacles and meet the growing health needs of the world’s patients, life science companies must leverage new innovations to enhance drug development and market access. Recently, a research report commissioned by PAREXEL and prepared by the Economist Intelligence Unit (EIU) looked at four key drug development innovations—adaptive trials, patient-centric trials, precision medicine trials, and real-world data trials—and their impact on key industry success metrics. While the positive impact of these innovations was measurably significant, their adoption has been surprisingly low. There is room for concerted action.

The Findings: The Innovation Imperative

In the report, titled The Innovation Imperative: The Future of Drug Development, researchers found that these four specific innovations positively impact clinical trial timelines, market launch likelihood, and patient access. In fact, drugs in three major therapeutic areas developed with these innovations were 16% more likely to reach the market (33% more likely in the case of oncology drugs). In addition, the report evaluated eight major payer formularies in the U.S., Europe, and Japan and found that drugs that were approved in 2015-17 and developed using one or more of these four innovations were as much as 41% more likely to have achieved formulary inclusion by 2018.

Breaking it down by type of innovation, the report highlights the impact of each of the following innovative trials:

Adaptive Trials: Drugs developed using adaptive trials had an 81% likelihood of being launched; this is 13 percentage points higher than the likelihood of launch of drugs not using this innovation. Additionally, the average adaptive trial took three months to recruit 100 trial participants, significantly less than the seven months it took to recruit the same number of patients into a non-adaptive trial.

Patient-centric Trials: Drugs developed using patient-centric designs were more likely to be launched (87%), compared to those without patient-centric designs (68%). This 19-percentage point difference remained consistent across patient-centric trials in different therapeutic areas (neurology, oncology, and rare diseases). Similar to adaptive trials, patient-centric trials took four months to recruit 100 participants, compared to the all-trials average of seven months.

Precision Medicine Trials: Across all therapeutic areas, precision medicine trials also increased the chances of launch. The difference in likelihood of launch between precision and non-precision medicine trials was most noticeable in oncology trials (26%).

Precision-designed trials have an inherently longer recruitment period (11 months vs. 7 months), as more in-depth screening is required to determine eligibility compared to non-precision trials. For example, not only does genetic testing for eligibility take a substantial amount of time, but the strict genetic requirements limit the patient pool, causing the need to test more patients. This cycle may not be quick, but such diligence and consideration are required for precision trials.

Though researchers may sacrifice some initial speed, overall trial efficiencies and outcomes are not solely dependent on time. And, as oncology precision trials demonstrate, the best outcomes can result from slowing down the patient recruitment process to ensure that participants are a proper fit.

Real-World Data (RWD) Trials: Trials that collected RWD improved by 21 percentage points the likelihood that the drugs being tested would be launched (89% vs. 68% for all trials). It is important to note, however, that there have only been 57 RWD trials to date, therefore making it difficult to reach a conclusion for each specific therapeutic area. As the field develops, we will be able to better understand the value of RWD trials, including speed to market, site-less trials, as well as both increased and personalized data collection.

With RWD, the reduction in patient recruitment time was minimal (one month), mostly due to the procedural efficiencies required for RWD trials. For example, RWD trials may use registry data to form part of their study cohort or use electronic health records (EHRs) to identify participants. Once again, time is not the only factor impacting outcomes and for many trials the insights gained through RWD strongly outweigh any delays in the patient recruitment process.

Implementation of Innovative Trials

Surprisingly, despite the demonstrated positive impact of these innovations, the report shows that they are underutilized, likely due to cultural and systemic constraints. The use of these four innovations in Phase II and III trials turned out to be low, ranging from less than 1% for adaptive designs and real-world data trials, to 5% for patient-centric, and 14% for precision medicine trials. Because they offer great potential to increase drug success, these (and other) new trial approaches should be implemented on a wider scale by life science companies in order to reap the full benefits of innovation.

Experts engaged by the EIU in the context of the research identified four enablers that could enhance the use of innovation in drug development: The use of advanced data and analytics, preparing and educating the workforce of the future, establishing collaborative partnerships among diverse stakeholders, and driving early regulator, payer, and patient engagement. These each require strong commitments and shifts by the industry and other stakeholders. An example: The existence of separate, disparate, and unconnected repositories of vast amounts of patient data is a significant roadblock to progress.

What’s clear is that there is an opportunity for the drug development ecosystem  to address in significant ways the drug development challenges. This research presents a call to action for the industry and other stakeholders to collaborate and find creative ways to adapt our organizations, behaviors, and systems to foster a more fertile environment for innovation.

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