Guest Column | June 11, 2019

How Amgen Is Taking An Adaptive Approach To Clinical Trials

By Elliott Levy, SVP, Global Development, Amgen


Clinical research is sometimes viewed as a box-checking exercise, where we run fairly cut-and-dried randomized, placebo-controlled studies based on long-established protocols. But things are actually changing very rapidly in the world of clinical development, which is by far the largest part of pharma R&D spending. We are on the threshold of a transformation that will allow us to dramatically accelerate the acquisition of useful knowledge, get new medicines to patients sooner, and expand their usage to new indications more quickly.

Truly innovative methods for study design are maturing or already mature, including the approach known as adaptive clinical trials. While the concept of adaptive trials has been around for a while, adoption of the new paradigm has been slow, at least until recently. However, in 2016 the 21st Century Cures Act was passed, which requires the FDA to provide updated guidance on how companies can use adaptive trial designs in a way that satisfies the agency’s evidence standards. That guidance was published in September 2018.

The FDA’s support for this innovation may help to change the view in the industry that adaptive trial designs are novel and risky. At Amgen, we’ve recognized that there’s a much larger risk in not deploying methods that can get medicines to patients faster and more reliably. Approximately 80 percent of Amgen’s clinical trial designs today are adaptive.

Benefits Of Adaptive Clinical Trials

In conventional clinical trials, the study protocol is set in stone before the first patient is enrolled. The inclusion and exclusion criteria for patients, doses tested, outcomes to be measured, and study duration are established up front, and the trial is executed without change.

Adaptive clinical trial designs allow us to monitor the incoming data and modify the protocol based on what we’re learning as the study unfolds. Any and all potential changes need to be spelled out before the trial begins. If the pre-established criteria for making a change are met, you can implement a range of adaptations, such as:

  • Dropping or adding doses. Eliminating doses that aren’t effective, differentiated, or safe can increase the value and efficiency of the study by allocating more patients to the more informative doses.
  • Increasing the size or duration of a trial gives the test drug a better opportunity to demonstrate its true impact.
  • Enriching the study population by adding more of the types of patients who respond to the treatment being investigated.

In addition to generating greater clarity around a test drug’s potential, adaptive designs can also benefit patients. This means that we can find out faster whether a drug works or doesn’t work and make quicker decisions to advance a program or terminate it. 

In conventional clinical development programs, trade-offs are required if you want to prioritize for speed, cost, or likelihood of success. For example, optimizing for cost by staging your investment can slow you down, while optimizing for speed tends to drive up the cost. With adaptive designs, we can simultaneously increase our odds of success, reduce our spend, and get to an answer more quickly, which makes this methodology highly attractive.

Adaptive design can enhance the odds of success by correcting assumptions that may otherwise obscure a drug’s true potential. In designing any clinical study, assumptions need to be made — about the patient population, disease progression, dose performance, and treatment efficacy. Some assumptions will always be wrong, of course. That’s why we’re running the trial — because we want to learn. However, an incorrect assumption can increase the risk of failure in a program that might otherwise have succeeded.

In fact, a few years ago, the FDA published an analysis of the agency’s reasons for delaying or denying approval of 150 new drug submissions received from 2000 to 2012. That analysis pointed to “several potentially preventable deficiencies, including failure to select optimal drug doses and suitable study end points” as major factors in failures and delays. By allowing for course corrections that address flawed assumptions, adaptive designs may lead to improved results.

Implementing Adaptive Clinical Trials At Amgen

Amgen’s R&D strategy highlights the role these approaches can play in accelerating drug development and increasing the probability of success. To implement this new aspect of the strategy, we created a group called the Center for Design and Analysis. It includes new departments focused on data science, design and innovation, and the biostatistical sciences used to evaluate sophisticated trial designs and perform the modeling and simulations needed to support this work.

Simulations based on real-world data allow us to model variables such as the rate of patient recruitment, the time it will take for the drug to have an impact, the size of the impact, and more. The goal is not to predict the study’s results, but rather to show how different study designs are likely to perform under different scenarios. With simulations, we have found that the design option that looks the worst — a smaller trial with fewer patients — may actually be the best at providing faster answers at less cost and with equal or higher odds for the trial’s success. While simulating a clinical trial won’t make a drug work if it’s not going to work, it can help inform an optimized trial design with the highest likelihood of providing meaningful, actionable answers.

For companies accustomed to conventional study designs, adaptive trials require new skillsets and a change in the organization’s mind-set and culture. At Amgen, one of our top development priorities now is ensuring that all staff involved in planning, overseeing, and evaluating trials get the training and support they need to apply the methods effectively. We also want our physicians and statisticians to know that they will be respected for their efforts to apply this new paradigm even in cases where the outcome isn’t successful.

Adaptive clinical trials are part of Amgen’s broader effort to bend the R&D cost curve by making clinical development more productive and successful. The cost for new drug approvals has risen to roughly $2.6 billion – $2.9 billion if you count the expense of required post-approval studies. The cost of success is so high because of all the money invested in drugs that fail: 90 percent of test drugs that enter clinical trials never get approved. As an industry, we need to increase the amount we spend on medicines that reach the market and decrease the amount we spend on those that don’t. By reducing the time and money spent on programs that fail, we can pursue more promising programs than would be possible under a more traditional approach to clinical research. So, ultimately, adaptive trials are a better way to serve the patient.

In the past, a lot of failures in clinical development were due to picking the wrong drug targets. Human genetics is helping us to solve this problem by identifying genes and proteins proven to have a real impact on disease risk.  As we get better at selecting relevant targets, clinical trial design will become a key variable that we need to optimize to improve success rates further. Adaptive trial designs have shown they can meet this critical need, and at Amgen we intend to use them every chance we get.

About The Author:

Elliott Levy, M.D., is SVP, Global Development, responsible for the clinical development of Amgen’s pipeline. Before joining Amgen, he served as SVP and head of Specialty Development at Bristol-Myers Squibb (BMS). During his 17 years at BMS, Levy held a range of senior positions in cardiovascular clinical development, immunoscience clinical research, and global clinical research operations. Prior to BMS, he was a member of the Renal Division at Brigham and Women's Hospital in Boston, where he was an investigator in federally sponsored outcomes research as well as industry-sponsored clinical trials. Levy is a graduate of the Yale School of Medicine.