Lessons Learned from Alzheimer Disease: Clinical Trials with Negative Outcomes

Alzheimer disease (AD) drug development has a high failure rate. Drug development decision making can be improved based on lessons learned from past trials. Improved interpretation of animal models, better pharmacologic characterization in phase I and phase II trials, appropriate sample size, diagnosis of AD with biomarker support, optimization of global recruitment, and avoiding inappropriate subgroup analyses can improve drug development success rates. Alzheimer disease (AD) doubles in frequency every 5 years after the age of 65 years and is becoming increasingly common as the world’s population ages. It is estimated that in the United States alone, the number of patients with AD will burgeon from 5.3 million now to nearly 14 million by 2050.1 To address this impending public health disaster, there is an urgent need to discover and develop new drugs to prevent, delay the onset, slow the progression, or treat the cognitive and behavioral symptoms of AD. AD drug development has proven to be unusually difficult with a 99.6% failure rate in the decade of 2002 to 20122; currently, the success rate continues at the same low level. Each clinical trial provides evidence on a narrow range of questions. For example, does this dose of the test agent, given for a specific period of time (e.g., 18–24 months for disease-modifying therapies [DMTs]), to a defined population (e.g., preclinical AD; prodromal AD; mild, moderate, or severe AD dementia) produce a statistically significant difference compared with placebo in change from baseline on the prespecified primary outcomes, such as those measuring cognition (e.g., the Alzheimer’s Disease Assessment Scale – Cognitive Portion)3 and function (e.g., the Alzheimer’s Disease Cooperative Study Activities of Daily Living scale).4 Questions regarding effects in other populations, other doses, other exposure durations, and effects on other instruments must all be addressed in separate trials. These complex constraints on clinical trials have evolved to allow them to define efficacy in a way that is acceptable to regulatory agencies, such as the US Food and Drug Administration (FDA) and the European Medicines Agency. Regulatory acceptance of the data is the only way to gain marketing approval and make the agent widely available to patients. Each trial is a critical test of a narrow hypothesis and each incorporatesmethodologic decisions that offer valuable