The Challenge of Detecting Prodromal Alzheimer’s Disease for Clinical Trials


5 October 2016

The Challenge of Detecting Prodromal Alzheimer’s Disease for Clinical Trials

In this post, Director of Clinical Affairs, Dr Kenton Zavitz and Principal Statistical Analyst, Dr Rosemary Abbott look at the challenge of recruiting the correct patients into Alzheimer's disease trials.

By Kenton Zavitz, PhD, Director of Clinical Affairs & Rosemary Abbott, PhD, Principal Statistical Analyst



Key Points                                           

  • Alzheimer’s disease (AD) is rapidly becoming a global healthcare and economic crisis
  • Despite hundreds of clinical trials of new AD treatments, no new therapies have been approved since 2003
  • The field has now moved towards testing new therapies that can delay onset or prevent progression to Alzheimer’s dementia
  • Finding patients for clinical trials in this ‘preclinical’ or ‘prodromal’ stage of Alzheimer’s disease (prior to the onset of cognitive and functional decline) is proving to be challenging, time-consuming and expensive

The Challenge

Most of us are now familiar with the alarming statistics. The number of people living with Alzheimer’s disease (AD) has been rising rapidly with the aging of the global population. Worldwide, this number has exceeded 46 million and is expected to double every 20 years (Prince et al. World Alzheimer’s report 2015). In addition to the immense medical and social impact on those individuals suffering with the disease, their caregivers and their extended family members, the global economic impact of Alzheimer’s is estimated to exceed $1 trillion US dollars by 2018 and will balloon to $2 trillion by 2030 (Prince 2015, Wimo 2016).

These disturbing trends are expected to continue unless we find effective new therapies to alleviate the symptoms or disease modifying treatments to slow the progression or to delay or prevent the onset of AD. Indeed, even a relatively modest benefit of a disease modifier, the delay of AD onset and progression by just 1 year, is estimated to result in 9.2 million fewer AD patients by 2050 (Brookmeyer 2007).


The focus

Despite remarkable advances in our understanding of the neuropathological processes leading to AD, global research and development efforts of the past 25 years have led to only 2 classes of drugs having been approved for the treatment of AD, four cholinesterase inhibitors (approved between 1993 and 2001) and an NMDA receptor antagonist approved in 2003.  Since 2003, over 400 clinical trials (Phases 1-3) of potential new AD treatments have been performed (Cummings 2014) but none of these programs have led to the approval of a new AD therapy.  About half of these clinical trials have been focused on so-called disease modifying targets such as amyloid beta (Aβ) and tau or on other targets expected to be neuroprotective. The emerging consensus to explain this extraordinary rate of clinical failure is that once the two characteristic neuropathological processes of Aβ deposition and tau neurofibrillary tangles have progressed to the point where considerable neurodegeneration has occurred leading to the cognitive and functional deficits that define a diagnosis of Alzheimer’s disease, the damage to the brain cannot be undone by removal of various the forms of amyloid or tau.  We now know from a multitude of studies following various biomarkers and brain imaging endpoints that these proteins begin to accumulate as plaques and tangles and initiate a cascade of neuropathological changes up to 20 years before a clinical AD diagnosis is made (Jack 2013, Fagan 2014).  This raises the perplexing question for each proposed therapeutic intervention: at what stage in this process might be the optimal therapeutic window to observe effective treatment? Currently, a number of clinical trials are ongoing and are being planned in order to start to address this question and hopefully lead to new approved treatments to delay AD progression and onset.


Diagnostic frameworks

In order to identify patients with preclinical Alzheimer’s disease, new diagnostic frameworks have been proposed (Dubois 2014, Sperling 2011). These provisional frameworks utilize a combination of biomarker and imaging criteria together with clinical assessments of cognitive function and functional ability to establish standardized methods to define preclinical AD populations suitable for clinical trials.

First, in order to establish in vivo evidence of Alzheimer’s pathology, the investigator must establish one or more of the following:

  • Decreased levels of Aβ1–42 together with increased levels of Total -tau or phosphorylated-tau in cerebrospinal fluid (CSF)
  • Increased brain retention on amyloid tracer positron emission tomography (PET)

Second, subjects satisfying these AD pathology criteria must be confirmed by the investigator to have an absence of the specific clinical phenotype of AD, that is, an absence of amnestic syndrome (memory dysfunction of the hippocampal type) based on a variety of cognitive tests administered by the investigator as well as absence of functional or behavioral changes associated with dementia.  Individuals satisfying both of these pathological and clinical criteria are considered to be ‘asymptomatic at risk for AD’, and are thus an ideal population for the study of treatments to delay the onset on AD. 

The specific biomarker cutoff criteria for each of these assessments and the methodologies for operationalizing them in clinical trials vary widely depending on the specific patient population, inclusion and exclusion criteria, goals of the of the study and preferences and budget of the trial sponsor.  In addition to those listed above, other genetic factors (eg. APOE 4 genotype), plasma biomarker panels, additional imaging modalities (volumetric MRI, functional MRI, FDG-PET, Tau tracer PET) and other measures may be used as entry criteria and/or as trial endpoints for efficacy and safety assessment (Blennow 2010, Brier 2016, Westwood 2016)


The time and resource burden

Perhaps, it goes without saying that to conduct clinical research in preclinical AD is extremely expensive, time-consuming, resource intensive and can be a heavy and invasive burden for patients, caregivers and study site personnel. The cost of screening a single patient prior to determining suitability for trial enrollment may be many of thousands of dollars and the screen fail rate can easily exceed 70% of subjects screened, further increasing costs and timelines. Failure to recruit the planned number of participants in a timely manner can put a clinical development program at risk for clinical and commercial failure (Hughes 2012, Grill 2014). Thus, innovative tools and solutions are necessary to help bring suitable subjects into the clinic for further screening and to reduce site burden, costs, timelines and resource utilization.  

Next week we will be looking at a solution for detecting prodromal Alzheimer’s subjects for clinical trials, stay tuned!

You can also find out more about our tools to help recruitment rates for your study in advance of next week’s post or speak to one of our scientists about using data to enrich study populations.


Blennow K, Hampel H, Weiner M, Zetterberg H. Cerebrospinal fluid and plasma biomarkers in Alzheimer disease. Nat Rev Neurol 2010; 6: 131–44.

Brier MR, Gordon B, Friedrichsen K, McCarthy J et al. Tau and Aβ imaging, CSF measures, and cognition in Alzheimer's disease. Sci Transl Med. 2016 May 11;8(338)

Brookmeyer R1, Johnson E, Ziegler-Graham K, Arrighi HM.  Forecasting the global burden of Alzheimer's disease. Alzheimers Dement. 2007 Jul;3(3):186-91.

Cummings JL, Morstorf T, Zhong K. Alzheimer's disease drug-development pipeline: few candidates, frequent failures.  Alzheimers Res Ther. 2014 Jul 3;6(4):37.

Dubois B, Feldman HH, Jacova C et al. Advancing research diagnostic criteria for Alzheimer's disease: the IWG-2 criteria. Lancet Neurol. 2014 Jun;13(6):614-29.

Fagan AM, Xiong C, Jasielec MS, et al; Dominantly Inherited Alzheimer Network. Longitudinal change in CSF biomarkers in autosomal-dominant Alzheimer’s disease. Sci Transl Med. 2014;6(226):226ra30.

Grill JD, Galvin JE. Facilitating Alzheimer disease research recruitment. Alzheimer Dis Assoc Disord. 2014 Jan-Mar;28(1):1-8.

Hughes L, Kalali A, Vanbelle C, Cascade E. Innovative Digital Patient Recruitment Strategies in Prodromal AD trials. Poster at CTAD Annual Meeting, October 29-31, 2012.

Jack CR Jr, Holtzman DM. Biomarker modeling of Alzheimer’s disease. Neuron. 2013; 80(6):1347-1358.

Prince M, Wimo A, Guerchet M, Ali GC, Wu Y-T, Prina M. World Alzheimer Report 2015. The Global Impact of Dementia. An analysis of prevalence, incidence, costs and trends. London: Alzheimer’s Disease International; 2015. World Alzheimer’s Report.

Sperling RA, Aisen PS, Beckett LA e al. Toward defining the preclinical stages of Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease.  Alzheimers Dement. 2011 May;7(3):280-92.

Westwood S, Leoni E, Hye A et al. Blood-Based Biomarker Candidates of Cerebral Amyloid Using PiB PET in Non-Demented Elderly. J Alzheimers Dis. 2016 Mar 29;52(2):561-72.

Wimo A, Guerchet M, Ali GC, Wu YT, Prina AM, Winblad B, Jönsson L, Liu Z, Prince M. The worldwide costs of dementia 2015 and comparisons with 2010. Alzheimers Dement. 2016 Aug 29. pii: S1552-5260(16)30043-7. doi: 10.1016/j.jalz.2016.07.150. [Epub ahead of print].

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