Transdiagnostic, dimensional frameworks such as the Research Domain Criteria (RDoC) are increasingly regarded as promising vehicles for precision neuropsychiatric drug development, yet no treatment has been approved that was explicitly developed according to such principles. This work, conducted under the aegis of the European College of Neuropsychopharmacology Thematic Working Group on Clinical Outcomes in Early-Phase Clinical Trials, synthesises seven structured multidisciplinary expert meetings supported by a narrative literature review to delineate opportunities and barriers for implementing RDoC in early-phase clinical development. We identify four key operational domains that condition the success of RDoC-aligned programmes: (1) terminology clarity and working definitions for RDoC-aligned trials and target constructs; (2) construct-enriched population selection methodologies; (3) selection, development or modification of construct-aligned clinical outcome assessments that are fit-for-purpose in transdiagnostic research settings; and (4) navigation of regulatory frameworks that remain anchored in categorical diagnoses. Through selected illustrative cases-most notably the aticaprant development program targeting anhedonia in mood and anxiety disorders-we demonstrate how early phase RDoC-aligned trial designs can be compromised at the pivotal stage by the absence of validated endpoints and regulatory constraints on labelling. On this basis, we propose pragmatic recommendations, including consensus-based definitions, registry tagging of RDoC-aligned trials, data-driven biomarker-based transdiagnostic enrichment strategies (i.e., biotyping), and early, iterative engagement with regulators and health technology assessment agencies. Systematic attention to these domains is required for enabling the development of neurobiologically RDoC informed treatments to be delivered to the right patients at the right time.

Remote and unsupervised administration of neuropsychological tests may increase opportunities to understand cognition in everyday life compared to in-clinic assessments. The technological sophistication and widespread use of smartphones now allows this platform to be used for remote neuropsychological testing. However, it is important to ensure that the validity of neuropsychological tests extends to remote and unsupervised administration. As the Cogstate Brief Battery (CBB) has been validated for remote use on computers, the aim of this study was to now examine whether the acceptability and validity holds when administered via smartphone to cognitively unimpaired (CU) middle-aged and older adults. CU adults (n = 173) aged 41-75 years (M(SD) = 62.72 (7.18)) enrolled in the Healthy Brain Project completed the smartphone CBB remotely. The mean speed and accuracy of performance on the Detection (DET, psychomotor function), Identification (IDN, attention), One Back (OBK, working memory) and One Card Learning (OCL, visual learning) tests were used to define performance. Acceptability was determined by the percentage of participants completing the full CBB. Relationships between CBB performance with age and test difficulty were described to inform validity. Relationships between objective CBB performance and subjective ratings of how participants felt about their overall performance, obtained via survey, were also explored. 100% of participants completed the smartphone CBB. Increasing age was associated with slower performance on all tests (Figure 1a-1d), and reduced accuracy on the OBK (Figure 1h). Older adults (66+ years) performed slower than middle-aged adults (40-65 years) on all CBB tests, and with less accuracy on OBK (Table 1). Performance speed across all tests slowed with increasing test difficulty (Figure 2). Whilst a ceiling effect was observed for accuracy of simpler tests (DET, IDN, OBK), accuracy was lowest for the most difficult test (OCL) (Figure 2). Subjective ratings of overall CBB performance was significantly, albeit weakly, correlated with OCL accuracy ( r = 0.23, p = .003). The results support the acceptability and validity of the remote, unsupervised administration of the smartphone CBB in CU middle-aged and older adults. These results provide a foundation for gaining further understanding of the performance of the smartphone CBB in diverse and impaired populations.

Mitochondrial disease is a group of rare conditions, with no approved treatment to date, except for Leber hereditary optic neuropathy. Therapeutic options to alleviate the symptoms of mitochondrial disease are urgently needed. Sonlicromanol is a promising candidate, as it positively alters the key metabolic and inflammatory pathways associated with mitochondrial disease. Sonlicromanol is a reductive and oxidative distress modulator, selectively inhibiting microsomal prostaglandin E1 synthase activity. This Phase 2b program, aiming at evaluating sonlicromanol in adults with m.3243A>G mutation and primary mitochondrial disease, consisted of a randomized controlled (RCT) study (dose-selection) followed by a 52-week open-label extension study (EXT, long-term tolerability, safety, and efficacy of sonlicromanol). Patients were randomized (1:1:1) to receive 100- or 50-mg sonlicromanol, or placebo twice daily (bid) for 28 days with >= 2-week wash-out period between treatments. Patients who completed the RCT study entered the EXT study wherein they received 100-mg sonlicromanol bid. Overall, 27 patients were randomized (24 RCT patients completed all periods). 15 patients entered the EXT, and 12 patients were included in the EXT analysis set. All patients reported good tolerability and favourable safety, with pharmacokinetic results comparable to the earlier Phase 2a study. The RCT primary endpoint (change from placebo in the attentional domain of cognition score [IDN: visual identification, Cogstate]) did not reach statistical significance. Using a categorisation of the subject's period baseline a treatment effect over placebo was observed if their baseline was more affected (p=0.0338). Using this approach, there were signals of improvements over placebo in at least one dose in the Beck Depression Inventory (BDI, p=0.0143), Cognitive Failure Questionnaire (CFQ, p=0.0113), and the Depression subscale of the Hospital Anxiety and Depression Scale (p=0.0256). Statistically and/or clinically meaningful improvements were observed in the patient- and clinician-reported outcome measures at the end of the EXT study (Test of attentional performance [TAP] with alarm, p=0.0102; TAP without alarm, p=0.0047; BDI somatic, p=0.0261; BDI Total, p=0.0563; SF12 physical component score, p=0.0008). Seven of nine domains of RAND-Short form-36 like SF-36 pain improved (p=0.0105). Other promising results were observed in Neuro QoL-Fatigue-SF (p=0.0036), MiniBESTest (p=0.0009), McGill Pain Questionnaire (p=0.0105), EQ-5D-5L-VAS (p=0.0213) and EQ-5D-5L-index (p=0.0173). Most patients showed improvement in the 5x sit-to-stand test. S onlicromanol was well-tolerated and demonstrated a favourable benefit/risk ratio for up to one year. Sonlicromanol was efficacious in patients when affected at baseline, as seen across a variety of clinically relevant domains. Long-term treatment showed more pronounced changes from baseline.

The International Shopping List Test (ISLT) is a rater-administered verbal list learning test, sensitive to memory dysfunction in early Alzheimer’s disease (AD). This study examined the acceptability of a self-administered ISLT (called LILA) in cognitively unimpaired (CU) middle-aged and older adults. The validity of LILA was determined by the nature of ISLT learning curves and from examination of the effects of age. CU adults (n = 113) completed LILA on their own smartphone device in a remote, unsupervised setting (n = 113). The LILA app administered a novel ISLT, where a list of 12 shopping list items was read aurally through the speaker to the participant. Participants were required to recall, into the smartphone, as many words as they could remember. This immediate recall trial was repeated three times (T1-3). After a 10-minute delay, participants recalled as many of the 12 words as they could. LILA performance measures included, number of words recalled on each trial, and on the delayed recall trial. 10% of participants (n = 11) failed to provide a response on at least one learning trial (T1 = 3, T2 = 2, T3 = 4, DR = 2), with this data excluded from subsequent analyses. All participants reported feeling highly (74%) or moderately (26%) confident about using a smartphone, and reported using their phone daily. Improvement in immediate recall, known to occur for the ISLT was observed for LILA (Fig 1). Lower LILA immediate recall scores were associated with older age and higher depressive symptomatology (Table 1), but not sex, education or anxiety symptoms. Lower scores on delayed recall was associated with male sex and lower years of education (Table 1), but not age or mood symptoms. The very low rate of data loss indicates high acceptability of LILA in CU middle- and older-aged adults. Validity of performance was indicated by the learning curves, which were qualitatively similar to those of the rater-administered ISLT, and the effect of age on the immediate recall outcome. These data provide a strong foundation for future studies of the sensitivity of LILA to memory impairment in AD.

Neurosciences clinical trials continue to have notoriously high failure rates. Appropriate outcomes selection in early clinical trials is key to maximizing the likelihood of identifying new treatments in psychiatry and neurology. The field lacks good standards for designing outcome strategies, therefore The Outcomes Research Group was formed to develop and promote good practices in outcome selection. This article describes the first published guidance on the standardization of the process for clinical outcomes in neuroscience. A minimal step process is defined starting as early as possible, covering key activities for evidence generation in support of content validity, patient-centricity, validity requirements and considerations for regulatory acceptance. Feedback from expert members is provided, regarding the risks of shortening the process and examples supporting the recommended process are summarized. This methodology is now available to researchers in industry, academia or clinics aiming to implement consensus-based standard practices for clinical outcome selection, contributing to maximizing the efficiency of clinical research.

BACKGROUND:The Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog) and Mini-Mental State Examination (MMSE) are used as clinical outcome assessments (COAs) to investigate Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD). The Cogstate Brief Battery (CBB) is a digital assessment of psychomotor function, attention, visual learning, and working memory. Digital assessments may overcome limitations of traditional assessments but score conversions haven't been undertaken. METHOD:Data were aggregated for baseline visits from the A4, ADNI, and AXON studies. Participants included healthy/cognitively normal (HC), MCI, pre-clinical AD, and mild AD. An equipercentile linking routine for single-group designs, using bootstrap-resampled standard error (SE; variability of estimated CBB scores for each COA score) and bias (mean differences of resampled results from full model) metrics, was employed to fit score distributions. Reaction time (RT; log10 ms) and accuracy (proportion correct) for each of the CBB tests and two composite accuracy (LWM) and reaction time (ATT) scores were fit to ADAS-Cog and MMSE totals. RESULT:Data for 8,878 participants were analyzed (HC = 4,021; PC = 773; MCI = 420; AD = 414; Unclassified/Mixed = 3,250). Scores ranged from 0-39 (ADAS-Cog13), 0-27 (ADAS-Cog11), and 9-30 (MMSE). Estimates of CBB scores by COA scores showed expected associations between assessments. CBB composites for Accuracy and RT at MMSE > = 26 were estimated at approximately 0.7-0.9 and 2.8-2.6 respectively. SE in ADAS-Cog and MMSE totals from CBB scores were larger for scores which reflect worse performance and were from smaller samples (accuracy: > 0.10; RT > 1.0). MMSE RT SE estimates were significantly smaller (all < 0.2) than ADAS-Cog estimates. Results of both ADAS-Cog versions were virtually identical. CONCLUSION:Tables for converting ADAS-Cog and MMSE totals to CBB scores will be provided. Results can be reliably converted when performance is clinically better. Lack of samples in lower performance ranges presents an issue for reliable conversion. Demonstrating how traditional COAs compare to digital assessments can aid clinical interpretation and the understanding of limitations in each assessment. Using score equating tables may help establish a robust method for exploring associations and differences between assessments and scores.

In evaluating the clinical benefit of new therapeutic interventions, it is critical that the treatment outcomes assessed reflect aspects of health that are clinically important and meaningful to patients. Performance outcome (PerfO) assessments are measurements based on standardized tasks actively undertaken by a patient that reflect physical, cognitive, sensory, and other functional skills that bring meaning to people's lives. PerfO assessments can have substantial value as drug development tools when the concepts of interest being measured best suit task performance and in cases where patients may be limited in their capacity for self-report. In their development, selection, and modification, including the evaluation and documentation of validity, reliability, usability, and interpretability, the good practice recommendations established for other clinical outcome assessment types should continue to be followed, with concept elicitation as a critical foundation. In addition, the importance of standardization, and the need to ensure feasibility and safety, as well as their utility in patient groups, such as pediatric populations, or those with cognitive and psychiatric challenges, may enhance the need for structured pilot evaluations, additional cognitive interviewing, and evaluation of quantitative data, such as that which would support concept confirmation or provide ecological evidence and other forms of construct evidence within a unitary approach to validity. The opportunity for PerfO assessments to inform key areas of clinical benefit is substantial and establishing good practices in their selection or development, validation, and implementation, as well as how they reflect meaningful aspects of health is critical to ensuring high standards and in furthering patient-focused drug development.

The International Shopping List test (ISLT) is a verbal word list learning test set within a realistic shopping list context, supporting ease of cultural adaptation, and addressing content validity and patient relevance. Improvements to and the wide adoption of natural language processing (NLP) software has enabled the possibility for self-administered tests of verbal learning. LilaTM a self-administered, smartphone-application (app) was developed, using the virtual assistant and NLP. We have previously reported acceptability and usability data from qualitative analysis of concept elicitation interviews. We now seek to provide preliminary validation data around its use. A convenience sample of healthy young adults (n = 40), M(SD)age = 35 (16), were invited to install and complete one assessment of the LilaTM app. A usability survey was also administered to explore participants’ experiences. The sample was predominantly female (70%) and of Asian ethnicity (62.5%). Data were collected in Australia, using an English word pool developed for the USA. Acceptability was generally high with N = 38 completing immediate recall rounds and N = 32 completing the delayed recall round. Eight-two percent found it extremely or somewhat easy to hear and understand what items were on the shopping list and 95% indicated that it was extremely or somewhat easy to understand what they had to do to complete the assessment. Scoring accuracy was 88% at the word item level, with reprocessing to address accent, context setting, and other NLP approaches to improve accuracy underway e.g., homophones biased to the grocery item. Whilst acceptability was high, the importance of localization of test stimuli was confirmed as well as the need for additional data processing options to account for accent. Continued optimization of data processing to score participant responses and word item pools to reduce ambiguity is expected to further improve accuracy e.g., accounting for regional accents and consideration of homophones and compound words. However, specific characteristics of speech including in those for whom English may be a second/foreign language will be an area of focus for future development.

Remote and decentralized approaches to clinical outcome assessments in clinical trials can reduce patient and trial burden, improve recruitment and retention, and lower barriers to trial participation. Remote assessment may be facilitated through smartphone-based cognitive assessment, especially in Bring-Your-Own-Device (BYOD) trials, and can also enable novel designs, for example, the use of high frequency ‘burst’ assessments. Application of such digital assessments in remote or unsupervised settings requires understanding of potential error from test administration and delivery platform (e.g., smartphones vs. computer). A series of studies explored the modification of the well-validated Cogstate Brief Battery (CBB) to include practice trials with dynamic feedback to support unsupervised cognitive assessment, and adaptations for smartphone delivery. Data were drawn from healthy populations in (1) the Healthy Brain Project, where middle-aged adults (n = 1,594) completed unsupervised cognitive assessments on a computer, (2) a pilot study of young adults (n = 60) who completed both smartphone and computer administration, and (3) a large (n = 35,000) study of adults who completed unsupervised smartphone-based cognitive assessments in a BYOD context. Data from middle-aged adults enrolled in the Healthy Brain Project indicated that adaptation of the CBB for unsupervised computer-based assessment had high levels of acceptability (98% complete data) and usability (95%), with data meeting criteria for low error rates and ease of understanding). In young adults, rates of test completion were high and comparable (>98%), and performance accuracy (d’s <0.2) was equivalent between smartphone and computer administration. Performance was systematically slower (d’s >0.4) on smartphone than computer. Smartphone usability was high (e.g., >85% found text and button size to be ‘just right’), but there was not a strong preference for smartphone versus computer (56% preferred smartphone) and different issues of fatigue, distraction, and use of keyboard input were raised for the platforms. Similar findings of outcome consistency across platform were observed in the large BYOD sample (N>35,000). These results indicate that smartphone assessment has high acceptability, good reliability, and that accuracy of performance is equivalent between smartphone and computer versions. The data also raise important issues for the successful adaptation and modification of cognitive tasks for smartphone administration.

The Alzheimer’s Disease Assessment Scale-Cognitive subscale (ADAS-Cog) and Mini-Mental State Examination (MMSE) are used as clinical outcome assessments (COAs) to investigate Mild Cognitive Impairment (MCI) and Alzheimer’s disease (AD). The Cogstate Brief Battery (CBB) is a digital assessment of psychomotor function, attention, visual learning, and working memory. Digital assessments may overcome limitations of traditional assessments but score conversions haven’t been undertaken. Data were aggregated for baseline visits from the A4, ADNI, and AXON studies. Participants included healthy/cognitively normal (HC), MCI, pre-clinical AD, and mild AD. An equipercentile linking routine for single-group designs, using bootstrap-resampled standard error (SE; variability of estimated CBB scores for each COA score) and bias (mean differences of resampled results from full model) metrics, was employed to fit score distributions. Reaction time (RT; log10 ms) and accuracy (proportion correct) for each of the CBB tests and two composite accuracy (LWM) and reaction time (ATT) scores were fit to ADAS-Cog and MMSE totals. Data for 8,878 participants were analyzed (HC = 4,021; PC = 773; MCI = 420; AD = 414; Unclassified/Mixed = 3,250). Scores ranged from 0-39 (ADAS-Cog13), 0-27 (ADAS-Cog11), and 9-30 (MMSE). Estimates of CBB scores by COA scores showed expected associations between assessments. CBB composites for Accuracy and RT at MMSE > = 26 were estimated at approximately 0.7-0.9 and 2.8-2.6 respectively. SE in ADAS-Cog and MMSE totals from CBB scores were larger for scores which reflect worse performance and were from smaller samples (accuracy: > 0.10; RT > 1.0). MMSE RT SE estimates were significantly smaller (all < 0.2) than ADAS-Cog estimates. Results of both ADAS-Cog versions were virtually identical. Tables for converting ADAS-Cog and MMSE totals to CBB scores will be provided. Results can be reliably converted when performance is clinically better. Lack of samples in lower performance ranges presents an issue for reliable conversion. Demonstrating how traditional COAs compare to digital assessments can aid clinical interpretation and the understanding of limitations in each assessment. Using score equating tables may help establish a robust method for exploring associations and differences between assessments and scores.

The Cogstate Brief Battery (CBB) is a computerized cognitive test battery found to detect and confirm cognitive deficits related to Alzheimer’s Disease (AD). As the clinical AD and normative samples used to understand the sensitivity of the CBB to AD have been relatively small and varied in terms of selection criteria, it is important to examine the ability of all CBB measures, and potential composites, to discriminate adults with mild cognitive impairment (MCI) and dementia due to AD from carefully selected cognitively unimpaired (CU) adults. All speed and accuracy measures from the CBB were examined and both theoretically and statistically derived composites were created, from a sample of 4969 CU adults and 185 adults who met clinical criteria for MCI (clinical dementia rating, CDR = 0.5) or dementia (CDR > 0.5) due to AD. Individual CBB measures of learning and working memory showed high discriminability for AD-related cognitive impairment for CDR 0.5 (AUCs ∼ 82-.85), and CDR > 0.5 (AUCs ∼ .90-.95). There was also high discrimination ability for theoretically derived CBB composite measures, particularly for the Learning and Working Memory (LWM) composite measure (CDR 0.5 AUC = .83, CDR > 0.5 AUC = .97). Various statistically derived linear composite measures showed discrimination abilities similar to the LWM composite. In older adults, the CBB is an effective instrument for objectively discriminating cognitive impairment due to MCI or AD-dementia from unimpaired cognition, with the LWM composite being a near-optimal linear CBB composite for that purpose.

Background: The Cogstate Brief Battery (CBB) is a computerized cognitive test battery used commonly to identify cognitive deficits related to Alzheimer’s disease (AD). However, AD and normative samples used to understand the sensitivity of the CBB to AD in the clinic have been limited, as have the outcome measures studied. Objective: This study investigated the sensitivity of CBB outcomes, including potential composite scores, to cognitive impairment in mild cognitive impairment (MCI) and dementia due to AD, in carefully selected samples. Methods: Samples consisted of 4,871 cognitively unimpaired adults and 184 adults who met clinical criteria for MCI (Clinical Dementia Rating (CDR) = 0.5) or dementia (CDR > 0.5) due to AD and CBB naive. Speed and accuracy measures from each test were examined, and theoretically- and statistically-derived composites were created. Sensitivity and specificity of classification of cognitive impairment were compared between outcomes. Results: Individual CBB measures of learning and working memory showed high discriminability for AD-related cognitive impairment for CDR 0.5 (AUCs ∼ 0.79–0.88), and CDR > 0.5 (AUCs ∼ 0.89–0.96) groups. Discrimination ability for theoretically derived CBB composite measures was high, particularly for the Learning and Working Memory (LWM) composite (CDR 0.5 AUC = 0.90, CDR > 0.5 AUC = 0.97). As expected, statistically optimized linear composite measures showed strong discrimination abilities albeit similar to the LWM composite. Conclusions: In older adults, the CBB is effective for discriminating cognitive impairment due to MCI or AD-dementia from unimpaired cognition with the LWM composite providing the strongest sensitivity.

The Cogstate Brief Battery (CBB) is a computerized cognitive assessment validated for Alzheimer’s disease (AD) and unsupervised use. The CBB assesses processing speed, attention, visual learning, and working memory and is offered to cognitively normal (CN) and mild cognitive impairment (MCI) participants in ADNI-3. In-clinic visits are completed annually for MCI and every other year for CN, with both groups also able to complete unsupervised assessments at-home within 14 days of the first in-clinic visit and at up to 3 monthly intervals. Participants were 146 CN older adults ( M age  = 72.1, SD = 6.43, age range 57–90 years, 58.2% females) and 37 older adults with MCI ( M age  = 74.4, SD = 7.50, age range 61–89 years, 51.4% females). All participants underwent PET scans and confirmation of diagnosis at Baseline. Only participants with confirmed amyloid status were included in these analyses (i.e., all MCI participants were Aβ+ and all CU participants were Aβ-). Participants completed the CBB in a supervised in-clinic setting at Baseline, and again in an unsupervised remote setting within 90 days. Receiver Operating Characteristic analyses were conducted to ascertain whether the classification performance of the CBB in detecting MCI was similar in both settings. All CBB measures showed a significant ability to discriminate between CU Aβ- and MCI Aβ+ participants at both the supervised in clinic baseline (AUCs 0.63-0.75) and initial remote visit (AUCs 0.63-0.78). There was no significant difference for any CBB measure in classification performance (measured by AUC) between remote and supervised assessment ( p s > 0.146). The CBB showed good ability to classify MCI-related cognitive impairment, both supervised in clinic, and/or remotely without supervision.

Background and Objectives Identifying a clinically meaningful change in cognitive test score is essential when using cognition as an outcome in clinical trials. This is especially relevant because clinical trials increasingly feature novel composites of cognitive tests. Our primary objective was to establish minimal clinically important differences (MCIDs) for commonly used cognitive tests, using anchor-based and distribution-based methods, and our secondary objective was to investigate a composite cognitive measure that best predicts a minimal change in the Clinical Dementia Rating—Sum of Boxes (CDR-SB). Methods From the Swedish BioFINDER cohort study, we consecutively included cognitively unimpaired (CU) individuals with and without subjective or mild cognitive impairment (MCI). We calculated MCIDs associated with a change of ≥0.5 or ≥1.0 on CDR-SB for Mini-Mental State Examination (MMSE), ADAS-Cog delayed recall 10-word list, Stroop, Letter S Fluency, Animal Fluency, Symbol Digit Modalities Test (SDMT) and Trailmaking Test (TMT) A and B, and triangulated MCIDs for clinical use for CU, MCI, and amyloid-positive CU participants. For investigating cognitive measures that best predict a change in CDR-SB of ≥0.5 or ≥1.0 point, we conducted receiver operating characteristic analyses. Results Our study included 451 cognitively unimpaired individuals, 90 with subjective cognitive decline and 361 without symptoms of cognitive decline (pooled mean follow-up time 32.4 months, SD 26.8, range 12–96 months), and 292 people with MCI (pooled mean follow-up time 19.2 months, SD 19.0, range 12–72 months). We identified potential triangulated MCIDs (cognitively unimpaired; MCI) on a range of cognitive test outcomes: MMSE −1.5, −1.7; ADAS delayed recall 1.4, 1.1; Stroop 5.5, 9.3; Animal Fluency: −2.8, −2.9; Letter S Fluency −2.9, −1.8; SDMT: -3.5, −3.8; TMT A 11.7, 13.0; and TMT B 24.4, 20.1. For amyloid-positive CU, we found the best predicting composite cognitive measure included gender and changes in ADAS delayed recall, MMSE, SDMT, and TMT B. This produced an AUC of 0.87 (95% CI 0.79–0.94, sensitivity 75%, specificity 88%). Discussion Our MCIDs may be applied in clinical practice or clinical trials for identifying whether a clinically relevant change has occurred. The composite measure can be useful as a clinically relevant cognitive test outcome in preclinical AD trials.

Clinical trials for Alzheimer's disease (AD) are slower to enroll study participants, take longer to complete, and are more expensive than trials in most other therapeutic areas. The recruitment and retention of a large number of qualified, diverse volunteers to participate in clinical research studies remain among the key barriers to the successful completion of AD clinical trials. An advisory panel of experts from academia, patient-advocacy organizations, philanthropy, non-profit, government, and industry convened in 2020 to assess the critical challenges facing recruitment in Alzheimer's clinical trials and develop a set of recommendations to overcome them. This paper briefly reviews existing challenges in AD clinical research and discusses the feasibility and implications of the panel's recommendations for actionable and inclusive solutions to accelerate the development of novel therapies for AD.

Alzheimer’s disease is a large and growing unmet medical need. Clinical trial designs need to assess disease-related outcomes earlier to accelerate the development of better treatments for Alzheimer’s disease. ACU193 is a monoclonal antibody that selectively targets amyloid β oligomers, thought to be the most toxic species of Aβ that accumulates early in AD and contributes to downstream pathological effects. Nonclinical data indicate that ACU193 can reduce the toxic effects of amyloid β oligomers. ACU193 is currently being investigated in a phase 1 clinical trial designed with the properties described in this report. This phase 1 trial is designed to provide data to enable a go/no-go decision regarding the initiation of a subsequent phase 2/3 study. To design a phase 1 study that assesses target engagement and incorporates novel measures to support more rapid development of a potential disease-modifying treatment for Alzheimer’s disease. The INTERCEPT-AD trial for ACU193 is an ongoing randomized, placebo-controlled phase 1a/b study that assesses safety, tolerability, pharmacokinetics, target engagement, clinical measures, and several Alzheimer’s disease biomarkers, including novel digital and imaging biomarkers. For INTERCEPT-AD, brief inpatient stays for patients in the single ascending dose portion of the study, with the remainder of the evaluations being performed as outpatients at multiple clinical trial sites in the U.S. Patients with early Alzheimer’s disease (mild cognitive impairment or mild dementia with a positive florbetapir positron emission tomography scan). ACU193 administered intravenously at doses of 2–60 mg/kg. Safety assessments including magnetic resonance imaging for the presence of amyloid-related imaging abnormalities, clinical assessments for Alzheimer’s disease including the Alzheimer’s Disease Rating Scale-cognition and Clinical Dementia Rating scale, pharmacokinetics, a measure of target engagement, and digital and imaging biomarkers, including a computerized cognitive test battery and a measure of cerebral blood flow using arterial spin labelling magnetic resonance imaging. A phase 1 study design was developed for ACU193 that allows collection of data that will enable a go/no-go decision for initiation of a subsequent adaptive phase 2/3 study. A phase 1a/b trial and an overall clinical development plan for an Alzheimer’s disease treatment can be designed that maintains patient safety, allows informed decision-making, and achieves an accelerated timeline by using novel biomarkers and adaptive study designs.

The International Shopping List test (ISLT) is a verbal word list learning assessment set within a realistic shopping list context, supporting ease of cultural adaptation, and addressing content validity and patient relevance. Improvements to and the wide adoption of natural language processing (NLP) software has enabled the possibility for self-administered tests of verbal learning. A beta version of a self-administered, smartphone-application (app) was developed, using the virtual assistant and NLP: the “List Learning and Memory Assessment (Lila TM )”. To ensure usability of the app, a user led design process was followed. A beta version was created via several rounds of focus group development in older adults. 12 older adults were then recruited for interviews (8 healthy and 4 with Mild Cognitive Impairment). Participants were pseudo-randomly assigned to participate in interviews during test performance, using either iPhone or Nokia devices. Each participant completed the test and provided concept elicitation feedback. Qualitative analysis of the interview results was performed using thematic coding. Key positive themes included the ease with which the app could be navigated, and the clarity of visual display and instructions, whilst an important negative theme was the length of time between different components of the test. Qualitative analysis of concept elicitation interviews has suggested several areas of improvement to the beta-app, including improvements to performance that shorten processing and wait times between test components. The clarity of the visual display and test instructions were well supported.

The One Card Learning Test (OCL80) from the Cogstate Brief Battery has shown high sensitivity to changes in memory in early Alzheimer’s disease (AD), although recent studies suggest that OCL sensitivity to memory impairment in symptomatic AD is not as strong as that for other standardized assessments of memory. This study aimed to improve the sensitivity of the OCL80 to AD-related memory impairment by reducing the test difficultly (i.e., OCL48). Experiment 1 showed performance in healthy adults improved on the OCL48 while the pattern separation operations that constrain performance on the OCL80 were retained. Experiment 2 showed repeated administration of the OCL48 at short retest intervals did not induce ceiling or practice effects. Experiment 3 showed that the sensitivity of the OCL48 to AD-related memory impairment (Glass’s ∆ = 3.11) was much greater than the sensitivity of the OCL80 (Glass’s ∆ = 1.94). Experiment 4 used data from a large group of cognitively normal older adults to calibrate performance scores between the OCL80 and OCL48 using equipercentile equating. Together these results showed the OCL48 to be a valid and reliable test of learning with greater sensitivity to memory impairment in AD than the OCL80.