Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2022 Jul;18(7):389-399.
doi: 10.1038/s41582-022-00645-6. Epub 2022 Apr 4.

Early-stage Alzheimer disease: getting trial-ready

Affiliations
Review

Early-stage Alzheimer disease: getting trial-ready

Paul S Aisen et al. Nat Rev Neurol. 2022 Jul.

Abstract

Slowing the progression of Alzheimer disease (AD) might be the greatest unmet medical need of our time. Although one AD therapeutic has received a controversial accelerated approval from the FDA, more effective and accessible therapies are urgently needed. Consensus is growing that for meaningful disease modification in AD, therapeutic intervention must be initiated at very early (preclinical or prodromal) stages of the disease. Although the methods for such early-stage clinical trials have been developed, identification and recruitment of the required asymptomatic or minimally symptomatic study participants takes many years and requires substantial funds. As an example, in the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease Trial (the first phase III trial to be performed in preclinical AD), 3.5 years and more than 5,900 screens were required to recruit and randomize 1,169 participants. A new clinical trials infrastructure is required to increase the efficiency of recruitment and accelerate therapeutic progress. Collaborations in North America, Europe and Asia are now addressing this need by establishing trial-ready cohorts of individuals with preclinical and prodromal AD. These collaborations are employing innovative methods to engage the target population, assess risk of brain amyloid accumulation, select participants for biomarker studies and determine eligibility for trials. In the future, these programmes could provide effective tools for pursuing the primary prevention of AD. Here, we review the lessons learned from the AD trial-ready cohorts that have been established to date, with the aim of informing ongoing and future efforts towards efficient, cost-effective trial recruitment.

PubMed Disclaimer

Conflict of interest statement

The authors have received grants from the National Institute on Aging and research support from Eisai, Janssen and Lilly. P.S.A. has consulted for Abbvie, Biogen, ImmunoBrain Checkpoint, Merck, Rainbow Medical, Roche and Shionogi.

Figures

Fig. 1
Fig. 1. The continuum of Alzheimer disease.
The figure illustrates the changes in Alzheimer disease pathologies in the brain and clinical symptoms that occur over time, highlighting the window of time during which changes in biomarkers are measurably different from those in healthy ageing but cognitive symptoms have not yet emerged. This window provides an important opportunity for the testing of clinical interventions. Aβ, amyloid-β; FDG, fluorodeoxyglucose; MCI, mild cognitive impairment. Reprinted from ref..
Fig. 2
Fig. 2. The Trial-Ready Cohort for Preclinical and Prodromal Alzheimer’s Disease.
Participants for Trial-Ready Cohort for Preclinical and Prodromal Alzheimer’s Disease are recruited primarily from existing registries and remotely consent to be followed in the Alzheimer Prevention Trials Webstudy (APT Webstudy) for quarterly unsupervised assessments (1, 2). Algorithms are run to select participants for referral for in-person assessment, managed through the Site Referral System (3). Screening for the in-person cohort includes cognitive and clinical assessments and amyloid testing (4). Eligible participants are enrolled for semi-annual clinic visits (5), until an appropriate clinical trial becomes available at their site. APOE, apolipoprotein E; CFI, Cognitive Function Index; PACC, Preclinical Alzheimer’s Cognitive Composite. Adapted from ref..
Fig. 3
Fig. 3. Intended flow of participants to European Prevention of Alzheimer’s Dementia Longitudinal Cohort Study and Proof-of-Concept trial.
Participants were identified from multiple cohorts, some community-based and prescreened for age, familial history and other risk factors. Participants were then referred for in-person screening and assessment for enrolment in the European Prevention of Alzheimer’s Dementia (EPAD) Longitudinal Cohort Study. The intention was that participants from the cohort would be screened for enrolment into the EPAD proof-of-concept trial; however, EPAD Registry funding was discontinued in 2019 and the trial was not initiated. Participants were instead referred to appropriate clinical trials that were available at their local research centre. Adapted from ref..
Fig. 4
Fig. 4. Trial-ready cohort for Down syndrome schema.
Participants can co-enrol in the Alzheimer’s Biomarker Consortium – Down Syndrome (ABC-DS) and the Trial Ready Cohort for Down Syndrome (TRC-DS). Within the TRC-DS, participants are followed up longitudinally until an appropriate clinical trial becomes available. The longitudinal data will then be used as run-in data for the trial, minimizing the burden of repeat testing for participants and increasing the efficiency of study design. Reprinted from ref..
Fig. 5
Fig. 5. The Trial-Ready Cohort for Preclinical and Prodromal Alzheimer’s Disease informatics platform: an example of a modular approach.
The Trial-Ready Cohort for Preclinical and Prodromal Alzheimer’s Disease informatics platform takes a modular approach to system and database design to support the evolution of the platform and the heterogeneity of the data. Key features include cloud IT infrastructure and a semi-structured ‘data lake’ storage model. At each of the three stages — the Alzheimer Prevention Trials (APT) Webstudy, the Site Referral System and the Trial-Ready Cohort — de-identified participant data is ingested into a data lake and is used to support a risk-based selection algorithm. Adapted from ref..

References

    1. Cummings J, Lee G, Zhong K, Fonseca J, Taghva K. Alzheimer’s disease drug development pipeline: 2021. Alzheimers Dement. 2021;7:e12179. - PMC - PubMed
    1. Cummings J, et al. Aducanumab: appropriate use recommendations. J. Prev. Alzheimers Dis. 2021;8:398–410. - PMC - PubMed
    1. Sperling RA, Jack CR, Jr, Aisen PS. Testing the right target and right drug at the right stage. Sci. Transl. Med. 2011;3:111cm133. doi: 10.1126/scitranslmed.3002609. - DOI - PMC - PubMed
    1. Rowe CC, et al. Amyloid imaging results from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging. Neurobiol. Aging. 2010;31:1275–1283. doi: 10.1016/j.neurobiolaging.2010.04.007. - DOI - PubMed
    1. Donohue MC, et al. Association between elevated brain amyloid and subsequent cognitive decline among cognitively normal persons. JAMA. 2017;317:2305–2316. doi: 10.1001/jama.2017.6669. - DOI - PMC - PubMed