Insights
9 April 2018
The challenge of detecting early Alzheimer’s disease for clinical trials
In this post, Director of Clinical Affairs, Dr Kenton Zavitz, looks at the challenge of recruiting the correct patients into Alzheimer's disease trials.
Key Points
- Alzheimer’s disease (AD) is 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 moved towards testing new therapies that can delay onset, or prevent progression to, Alzheimer’s dementia and the FDA has just released a new Draft Guidance to assist drug development in the earliest stages Alzheimer’s disease.
- Finding patients for clinical trials in these early ‘preclinical’ or ‘prodromal’ stages of Alzheimer’s disease (prior to the onset of significant 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).
Figure 1. AD prevalence data from Herbert et al (2010), displayed in page 23 of Alzheimer’s Association 2018 fact sheet.
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 this year (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).
Figure 2. The Alzheimer’s Association commissioned Precision Health Economics to conduct analyses on the projected savings from early diagnosis using The Health Economics Innovation Simulation (THEMIS) model. The graph is reproduced from page 65 of Alzheimer’s Association 2018 fact sheet. In this model, ‘partial early diagnosis’ refers to a scenario where people are more likely to receive an AD diagnosis during the MCI stage rather than the dementia stage. The graph illustrates the projected savings of such a scenario, compared to the current diagnosis model ‘status quo’.
The focus
Tackling Alzheimer’s disease is at the top of the agenda with congress approving a $414 million increase to the research budget in the 2018 spending plan (released 21st March 2018), bringing the total allowance to $1.8 billion (Science, 2018).
However, 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, potential 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 cut-off 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)
In a recent blog post, we have discussed the February 2018 US FDA Draft Guidance on clinical trials in Early Alzheimer’s disease and how this presents additional opportunities and challenges for drug developers.
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 enrolment 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). Furthermore, the trial-type has ramifications for recruitment time: with preventative trials taking significantly longer to recruit for (133.5 weeks), than prodromal or mild-moderate AD trials (105.4 weeks and 106.9 weeks respectively) (Cummings, Lee, Mortsdorf, Ritter, & Zhong 2017).
Figure 3. The number of weeks it takes to recruit for preclinical, prodromal and mild-moderate AD trials. Data from Cummings et al. (2017).
AD trial recruitment is typically slow, expensive and challenging (Cummings et al. 2017), and with over 54000 participants required to complete just the AD trials currently in progress (Cummings et al. 2017), it has never been more important to develop and employ, innovative tools and solutions to help bring suitable subjects into the clinic for further screening and to reduce site burden, costs, timelines and resource utilization.
What’s next?
Next, we will be discussing a potential solution for detecting prodromal Alzheimer’s subjects for clinical trials.
You can find out more about tools to help recruitment rates for your study in advance of our next post or speak to one of our specialists about using data to enrich study populations.
For a complete look at the issues, and potential solutions, for early AD trials watch our webinar.
References
Alzheimer’s Association. 2018 Alzheimer’s Disease Facts and Figures. Alzheimers Dement 2018;14(3):367-429
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, Ritter A, Zhong K. Alzheimer’s disease drug-development pipeline: 2017. Alzheimer’s & Dementia: Translational Research & Clinical Interventions, 2017, 3(3), 367–384
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.
Hebert LE, Weuve J, Scherr PA, Evans DA. Alzheimer disease in the United States (2010-2050) estimated using the 2010 Census. Neurology 2013;80(19):1778-83.
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.
Science. (2018, March 22). Congress apporove largest U.S. research spending increase in a decade.https://doi.org/10.1126/science.aat6620
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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