Alzheimer’s Clinical Trials: Obstacles and Opportunities


Applied Clinical Trials

For sponsors who are pursuing the goal of treating Alzheimer’s disease, understanding the obstacles inherent in Alzheimer’s clinical trials can help in planning for, and overcoming, these challenges.

Dementia is a global epidemic, affecting nearly 50 million people worldwide.[1] By 2050, it’s estimated that 115 million people will suffer from some form of dementia. Alzheimer’s disease (AD) is the most common type of dementia occurring late in life. AD is also the only condition among the leading causes of death that cannot currently be prevented, cured or even significantly slowed.

Despite intensive research, we have seen no new Alzheimer’s medications since 2003, when memantine (marketed as Namenda®) was approved by the FDA. For those living with Alzheimer’s disease and their loved ones, there is a significant unmet need for progress in understanding and treating this most prevalent form of dementia. In 2010, Congress passed the National Alzheimer’s Project Act to create a national plan to address AD, and in 2012, that plan articulated the goal of preventing and effectively treating AD by 2025.

For sponsors who are pursuing this ambitious goal, understanding the obstacles inherent in Alzheimer’s clinical trials can help in planning for, and overcoming, these challenges. 

Treatment Landscape

Treatments for Alzheimer’s disease can be classified according to two broad categories:

Symptomatic Therapies[2]

Approved symptomatic therapies include the cholinesterase inhibitors (donepezil, rivastigmine, and galantamine) and memantime, a glutamate-NMDA receptor modulator. Other cholinesterase inhibitors, nicotine receptor agonists, serotonin receptor modulators, h3 histamine receptor antagonists, and numerous other neurotransmitter system-targeting agents have been investigated without success. Currently, sigma1 and muscarinic receptor modulators, intranasal insulin, peroxisome proliferator-activated receptor gamma agonists, and glucagon-like peptide 1 agonists are under development and investigation.

1. Disease-Modifying Therapies and Therapies for Behavioral Disturbances3

To date, there are no approved disease-modifying treatments for AD. Potential disease-modifying compounds fall under two dominant approaches: anti-amyloid agents and tau-targeted therapies. The amyloid therapy hypothesis (searching for agents that decrease production, prevent aggregation, or increase removal of beta-amyloid and simultaneously improve cognitive functions) has been the primary target for disease modification therapies for more than 20 years. Unfortunately, the search for agents that decrease production, prevent aggregation, or increase removal of beta-amyloid has failed to yield an effective treatment that improves cognition. More recently, the focus of research has shifted to tau-targeted therapies: phosphorylated tau protein.

Beyond the shift from anti-amyloid treatments to tau-targeted therapies, we are also seeing a shift in the stage of AD being studied in clinical trials. With advances in our understanding of the underlying anatomical and pathophysiologic changes that precede the onset of clinical symptoms, research and development has begun to focus on mild cognitive impairment (MCI) or prodromal AD. Of the 143 Alzheimer’s trials active as of July 2017, 51 are targeting healthy, healthy at-risk, or MCI to mild AD patients, including 21 studies focused on completely asymptomatic patients.[3]

Maximizing the Likelihood of Clinical Trial Success

Approximately 70% of compounds currently in Phase II or III trials aim to alter the underlying pathophysiology of AD, while the remaining 30 percent aim to treat the behavioral symptoms associated with the disease. In July 2018, a pipeline analysis presented at the Alzheimer’s Association International Conference showed 68 compounds in Phase II trials. According to this analysis, 31 drugs in Phase III clinical trials may launch in the next five years.3

The robust research activity in AD is promising, but to mitigate clinical trial risk, sponsors must learn from the failures of the past.

Adding International Sites

In the U.S., approximately 85 to 90 percent of AD trials experience delayed recruitment. As a result, sponsors may want to consider adding countries outside the United States to accelerate enrollment. If the decision is made to include international sites, understanding the startup timelines and the competitive clinical trial landscape and local regulatory environment in each country under consideration is critical for successful enrollment. There are also special considerations and nuances that must be considered when planning a global AD trial, including:[4]

· Education levels. Level of education can vary significantly from country to country, and it is known that AD tends to progress more slowly in individuals with lower levels of education. 

· Exercise levels. Level of exercise is also country-dependent, and individuals with higher levels of exercise have lower levels of amyloid deposition in the brain. 

· Factors influencing drug pharmacokinetics. For example, differences in body size may contribute to differences in brain exposure levels at the same dose of drug and may also affect drug metabolism and distribution.

· Genetic diversity. Polymorphism may influence drug metabolism, central nervous system drug exposure, and drug response across ethnic groups. Genetic diversity also creates differences in the biology of AD. 

· Use of clinical trial instruments and equipment. Nearly all widely used clinical instruments for AD were developed in North America and may need to be adjusted for cultural or ethnic differences. In addition, capabilities, access, and willingness to adopt new technology may vary widely among regions, requiring additional training. 

· Experience in conducting AD trials. Raters with little or no experience may contribute to greater score variability and more difficulty demonstrating a drug-placebo difference. Providing standardized training for raters and implementing in-study rater surveillance programs can help in optimizing data quality.


Optimizing Protocol Design

Most of the common protocol designs for AD clinical trials were created in the development programs for cholinesterase inhibitors and memantine. These programs consisted of double-blind, placebo-controlled, parallel group studies with a dual outcome including a cognitive measure, and a global impression or activities of daily living outcome. Participants were randomized to drug or placebo, and changes from baseline between groups were compared after a specified time. In most cases, the investigational agent was an add-on treatment to the standard of care.

A typical challenge of clinical trials in AD is finding ways to differentiate between symptomatic effects and disease-modifying effects. A number of newer clinical trial designs that seek to adjust for symptomatic effects and allow clinical rating scales to be used as endpoints include:[5]

· Long-term follow-up. In this type of study, disease modification is inferred from sustained divergence in outcome measures between groups over time. While this may be the best current trial design, these studies are time-consuming and expensive, and optimal study duration is still unclear. 

· Wash-in analysis. Often used in combination with other design strategies, a wash-in analysis compares the change in clinical outcome measures between groups over the initial weeks or months of a study. If a greater improvement is seen with the investigational agent, this might indicate an early symptomatic effect because it would be too early to see a true disease-modifying effect. 

· Wash-out analysis/staggered withdrawal. In this analysis, treatment is withdrawn from both the active agent- and placebo-treated groups at the end of the study. The active agent is assumed to have disease-modifying effects if patients treated with the agent show slower disease progression throughout the double-blind treatment period and less severe deterioration after treatment withdrawal.

· Randomized staggered start/delayed-start. In this design, one group of patients is randomized to receive the investigational agent from the start, while the second group is randomized to receive placebo for an initial period before being given the investigational agent. If the agent has a purely symptomatic effect, the progression curves for the two groups should meet when the second group receives the drug. If the compound has a purely disease-modifying effect, the progression curves of the second group will never catch up with those of the first group.

· Futility. In this design, the outcome of a single treated group is compared against a predetermined threshold value that reflects clinically meaningful change. The advantage of a futility design is that fewer patients are observed for a shorter period of time in Phase II to facilitate go/no-go decisions.

· Adaptive design. These designs can help minimize the overall sample size and duration of a study by stopping recruitment in response to strong signals of success or futility based on interim analysis. 

The sponsor should keep in mind that none of these study designs is perfect, and each has limitations that may confound definitive conclusions about an agent’s disease-modifying properties. 

Improving Data Quality

Approximately 25 percent of AD trial participants fail to complete the double-blind treatment period. Consequently, study results may be confounded by missing data, which can unbalance treatment arms over time, introduce bias, and reduce the overall efficacy of the study. Methods for dealing with missing data include complete-case analysis, last observation carried forward, mixed modeling, and data imputation. 

In addition, there are numerous instruments used to measure clinical endpoints in AD trials. Clinicians and may vary widely in their experience administering these instruments, leading to data variability. To overcome this challenge, many sponsors and CROs implement standardized training for raters, as well as robust and ongoing rater monitoring and quality assurance programs. 

Selecting Biomarkers

Increasingly, biomarkers are being used as surrogate outcome measures for disease modification. The most commonly assessed biomarkers in AD trials include:

· CSF biomarkers, such as total tau (t-tau), phosphorylated tau (p-tau) 181 or 231, and the isoforms of amyloid beta. 

· Brain PET biomarkers, using a variety of radioactive tracers including flouro-deoxyglucose (FDG), Pittsburgh compound B (PiB), florbetapir, and flortaucipir, which may not be available in every country. 

· Blood, plasma, and serum biomarkers, ranging from amyloid beta precursors to C-reactive protein and insulin-like growth factor 1. 

· Brain MRI biomarkers. To date, volumetric MRI measurement of different regions of the brain seems to be the most linked to cognitive decline.

· Ultrasound and brain CT biomarkers. These have not yet been validated.

Unfortunately, to date, there is no single accepted surrogate outcome biomarker for AD.

Future Trends

AD and other dementias may be among the biggest global health crises of the 21st century. As sponsors answer the call to action for developing new therapies, we expect to see a re-engineering of the overall approach to AD clinical trials that further optimizes study design to maximize the likelihood of success.

[1]World Health Organization. Dementia – Fact Sheet, Updated December 2017. Available at

[2]Yaari R, Hake A. Alzheimer’s disease clinical trials: past failures and future opportunities. Clin Invest 2015;5(3):297-309.

[3]Us Against Alzheimer’s. Alzheimer’s Drugs in Development Pipeline, presented during AAIC 22-27July 2018. 

[4]Cummings J, Reynders R, Zhong K. Globalization of Alzheimer’s disease clinical trials. Alzheimers Res Ther 2011;3(4):24.

[5]McGhee DJM, et al. A review of clinical trial designs used to detect a disease-modifying effect of drug therapy in Alzheimer’s disease and Parkinson’s disease. BMC Neurol 2016;16:92.


Dr. Krista Armstrong, VP & Head of Neuroscience, and Dr. Sebastian Turek, Project Director, Premier Research

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