The role of biomarkers in clinical development of drugs for neuropsychiatric disorders - A pragmatic guide.

The failure rate of drugs being developed for neuropsychiatric indications remains high. Optimizing drug discovery and development requires not only a better neurobiological understanding of disease aetiology and development, but also the means by which we can measure relevant biological and clinical processes related to disease progression, drug target engagement, and sensitivity to treatment. Here we address the role and key considerations for the selection of biomarkers in clinical drug development for neuropsychiatric disorders. We do not provide an exhaustive list of biomarkers; rather we lay out a pragmatic, well-defined biomarker selection strategy that addresses the main goals for each of the phases in the drug development cycle. We discuss the key questions and issues that concern biomarker selection and implementation in each phase of development. For the better development of biomarkers, we emphasize the need to focus on discrete biological dysfunction and/or symptom domains rather than diagnoses. We also advocate the use of biomarker-based patient stratification in phase 2 and 3 to increase sensitivity and power and reduce costs. Our aim is to enhance precision and chances of success for these complex and heterogeneous brain disorders with a high unmet medical need.

Social dysfunction relates to shifts within socioaffective brain systems among Schizophrenia and Alzheimer's disease patients.

Social dysfunction represents one of the most common signs of neuropsychiatric disorders, such as Schizophrenia (SZ) and Alzheimer's disease (AD). Perturbed socioaffective neural processing is crucially implicated in SZ/AD and generally linked to social dysfunction. Yet, transdiagnostic properties of social dysfunction and its neurobiological underpinnings remain unknown. As part of the European PRISM project, we examined whether social dysfunction maps onto shifts within socioaffective brain systems across SZ and AD patients. We probed coupling of social dysfunction with socioaffective neural processing, as indexed by an implicit facial emotional processing fMRI task, across SZ (N = 46), AD (N = 40) and two age-matched healthy control (HC) groups (N = 26 HC-younger and N = 27 HC-older). Behavioural (i.e., social withdrawal, interpersonal dysfunction, diminished prosocial or recreational activity) and subjective (i.e., feelings of loneliness) aspects of social dysfunction were assessed using the Social Functioning Scale and De Jong-Gierveld loneliness questionnaire, respectively. Across SZ/AD/HC participants, more severe behavioural social dysfunction related to hyperactivity within fronto-parieto-limbic brain systems in response to sad emotions (P = 0.0078), along with hypoactivity of these brain systems in response to happy emotions (P = 0.0418). Such relationships were not found for subjective experiences of social dysfunction. These effects were independent of diagnosis, and not confounded by clinical and sociodemographic factors. In conclusion, behavioural aspects of social dysfunction across SZ/AD/HC participants are associated with shifts within fronto-parieto-limbic brain systems. These findings pinpoint altered socioaffective neural processing as a putative marker for social dysfunction, and could aid personalized care initiatives grounded in social behaviour.

When a test is more than just a test: Findings from patient interviews and survey in the trial of a technology to measure antidepressant medication response (the PReDicT Trial).

BACKGROUND: A RCT of a novel intervention to detect antidepressant medication response (the PReDicT Test) took place in five European countries, accompanied by a nested study of its acceptability and implementation presented here. The RCT results indicated no effect of the intervention on depression at 8 weeks (primary outcome), although effects on anxiety at 8 weeks and functioning at 24 weeks were found. METHODS: The nested study used mixed methods. The aim was to explore patient experiences of the Test including acceptability and implementation, to inform its use within care. A bespoke survey was completed by trial participants in five countries (n = 778) at week 8. Semi-structured interviews were carried out in two countries soon after week 8 (UK n = 22, Germany n = 20). Quantitative data was analysed descriptively; for qualitative data, thematic analysis was carried out using a framework approach. Results of the two datasets were interrogated together. OUTCOMES: Survey results showed the intervention was well received, with a majority of participants indicating they would use it again, and it gave them helpful extra information; a small minority indicated the Test made them feel worse. Qualitative data showed the Test had unexpected properties, including: instigating a process of reflection, giving participants feedback on progress and new understanding about their illness, and making participants feel supported and more engaged in treatment. INTERPRETATION: The qualitative and quantitative results are generally consistent. The Test's unexpected properties may explain why the RCT showed little effect, as properties were experienced across both trial arms. Beyond the RCT, the qualitative data sheds light on measurement reactivity, i.e., how measurements of depression can impact patients.

Exploring the incidence of inadequate response to antidepressants in the primary care of depression.

Data from the UK suggests 13-55 % of depression patients experience some level of treatment resistance. However, little is known about how physicians manage inadequate response to antidepressants in primary care. This study aimed to explore the incidence of inadequate response to antidepressants in UK primary care. One-hundred-eighty-four medication-free patients with low mood initiated antidepressant treatment and monitored severity of depression symptoms, using the QIDS-SR16, for 48 weeks. Medication changes, visits to healthcare providers, and health-related quality of life were also recorded. Patients were classified into one of four response types based on their QIDS scores at three study timepoints: persistent inadequate responders (<50 % reduction in baseline QIDS at all timepoints), successful responders (≥50 % reduction in baseline QIDS at all timepoints), slow responders (≥50 % reduction in QIDS at week 48, despite earlier inadequate responses), and relapse (initial ≥50 % reduction in baseline QIDS, but inadequate response by week 48). Forty-eight weeks after initiating treatment 47 % of patients continued to experience symptoms of depression (QIDS >5), and 20 % of patients had a persistent inadequate response. Regardless of treatment response, 96 % (n = 176) of patients did not visit their primary care physician over the 40-week follow-up period. These results suggest that despite receiving treatment, a considerable proportion of patients with low mood remain unwell and fail to recover. Monitoring depression symptoms remotely can enable physicians to identify inadequate responders, allowing patients to be reassessed or referred to secondary services, likely improving patients' quality of life and reducing the socioeconomic impacts of chronic mental illness.

Digital behavioural signatures reveal trans-diagnostic clusters of Schizophrenia and Alzheimer's disease patients.

The current neuropsychiatric nosological categories underlie pragmatic treatment choice, regulation and clinical research but does not encompass biological rationale. However, subgroups of patients suffering from schizophrenia or Alzheimer's disease have more in common than the neuropsychiatric nature of their condition, such as the expression of social dysfunction. The PRISM project presents here initial quantitative biological insights allowing the first steps toward a novel trans-diagnostic classification of psychiatric and neurological symptomatology intended to reinvigorate drug discovery in this area. In this study, we applied spectral clustering on digital behavioural endpoints derived from passive smartphone monitoring data in a subgroup of Schizophrenia and Alzheimer's disease patients, as well as age matched healthy controls, as part of the PRISM clinical study. This analysis provided an objective social functioning characterization with three differential clusters that transcended initial diagnostic classification and was shown to be linked to quantitative neurobiological parameters assessed. This emerging quantitative framework will both offer new ways to classify individuals in biologically homogenous clusters irrespective of their initial diagnosis, and also offer insights into the pathophysiological mechanisms underlying these clusters.

Effects of ulotaront on brain circuits of reward, working memory, and emotion processing in healthy volunteers with high or low schizotypy.

Ulotaront, a trace amine-associated receptor 1 (TAAR1) and serotonin 5-HT1A receptor agonist without antagonist activity at dopamine D2 or the serotonin 5-HT2A receptors, has demonstrated efficacy in the treatment of schizophrenia. Here we report the phase 1 translational studies that profiled the effect of ulotaront on brain responses to reward, working memory, and resting state connectivity (RSC) in individuals with low or high schizotypy (LS or HS). Participants were randomized to placebo (n = 32), ulotaront (50 mg; n = 30), or the D2 receptor antagonist amisulpride (400 mg; n = 34) 2 h prior to functional magnetic resonance imaging (fMRI) of blood oxygen level-dependent (BOLD) responses to task performance. Ulotaront increased subjective drowsiness, but reaction times were impaired by less than 10% and did not correlate with BOLD responses. In the Monetary Incentive Delay task (reward processing), ulotaront significantly modulated striatal responses to incentive cues, induced medial orbitofrontal responses, and prevented insula activation seen in HS subjects. In the N-Back working memory task, ulotaront modulated BOLD signals in brain regions associated with cognitive impairment in schizophrenia. Ulotaront did not show antidepressant-like biases in an emotion processing task. HS had significantly reduced connectivity in default, salience, and executive networks compared to LS participants and both drugs reduced this difference. Although performance impairment may have weakened or contributed to the fMRI findings, the profile of ulotaront on BOLD activations elicited by reward, memory, and resting state is compatible with an indirect modulation of dopaminergic function as indicated by preclinical studies. This phase 1 study supported the subsequent clinical proof of concept trial in people with schizophrenia.Clinical trial registration: Registry# and URL: ClinicalTrials.gov NCT01972711, https://clinicaltrials.gov/ct2/show/NCT01972711.

Use of experimental medicine approaches for the development of novel psychiatric treatments based on orexin receptor modulation.

Despite progress in understanding the pathological mechanisms underlying psychiatric disorders, translation from animal models into clinical use remains a significant bottleneck. Preclinical studies have implicated the orexin neuropeptide system as a potential target for psychiatric disorders through its role in regulating emotional, cognitive, and behavioral processes. Clinical studies are investigating orexin modulation in addiction and mood disorders. Here we review performance-outcome measures (POMs) arising from experimental medicine research methods which may show promise as markers of efficacy of orexin receptor modulators in humans. POMs provide objective measures of brain function, complementing patient-reported or clinician-observed symptom evaluation, and aid the translation from preclinical to clinical research. Significant challenges include the development, validation, and operationalization of these measures. We suggest that collaborative networks comprising clinical practitioners, academics, individuals working in the pharmaceutical industry, drug regulators, patients, patient advocacy groups, and other relevant stakeholders may provide infrastructure to facilitate validation of experimental medicine approaches in translational research and in the implementation of these approaches in real-world clinical practice.

Predictive validity in drug discovery: what it is, why it matters and how to improve it.

Successful drug discovery is like finding oases of safety and efficacy in chemical and biological deserts. Screens in disease models, and other decision tools used in drug research and development (R&D), point towards oases when they score therapeutic candidates in a way that correlates with clinical utility in humans. Otherwise, they probably lead in the wrong direction. This line of thought can be quantified by using decision theory, in which 'predictive validity' is the correlation coefficient between the output of a decision tool and clinical utility across therapeutic candidates. Analyses based on this approach reveal that the detectability of good candidates is extremely sensitive to predictive validity, because the deserts are big and oases small. Both history and decision theory suggest that predictive validity is under-managed in drug R&D, not least because it is so hard to measure before projects succeed or fail later in the process. This article explains the influence of predictive validity on R&D productivity and discusses methods to evaluate and improve it, with the aim of supporting the application of more effective decision tools and catalysing investment in their creation.

Feasibility, acceptability and costs of nurse-led Alpha-Stim cranial electrostimulation to treat anxiety and depression in university students.

BACKGROUND: Only a relatively low proportion of university students seek help for anxiety and depression disorders, partly because they dislike current drug and psychological treatment options and would prefer home-based care. The aim of this study is to determine the feasibility, acceptability and cost utility of Alpha-Stim cranial electrostimulation (CES) delivered through a nurse led primary care clinic as a daily treatment for anxiety and depression symptoms by the student at home in contrast to usual primary care. METHOD: Feasibility and acceptability of a nurse led clinic offering Alpha-Stim CES in terms of the take up and completion of the six-week course of Alpha-Stim CES. Change in score on the GAD-7 and PHQ-9 as measures of anxiety and depression symptoms at baseline and at 8 weeks following a course of Alpha-Stim CES. Similar evaluation in a non-randomised control group attending a family doctor over the same period. Cost-utility analysis of the nurse led Alpha-Stim CES and family doctor pathways with participants failing to improve following further NICE Guideline clinical care (facilitated self-help and cognitive behaviour therapy). RESULTS: Of 47 students (mean age 22.1, years, 79% female opting for Alpha-Stim CES at the nurse-led clinic 46 (97.9%) completed a 6-week daily course. Forty-seven (47) students comprised a comparison group receiving usual family doctor care. Both Alpha-Stim CES and usual family doctor care were associated with large effect size reductions in GAD-7 and PHQ-9 scores from baseline to 8 weeks. There were no adverse effects and only one participant showed a clinically important deterioration in the Alpha-Stim group. In the cost utility analysis, Alpha-Stim CES was a cheaper option than usual family doctor care under all deterministic or probabilistic assumptions. CONCLUSION: Nurse delivered Alpha-Stim CES may be a feasible, acceptable and cheaper way of providing greater choice and home-based care for some university students seeking help from primary care with new presentations of anxiety and depression.

Cross-disorder and disorder-specific deficits in social functioning among schizophrenia and alzheimer's disease patients.

BACKGROUND: Social functioning is often impaired in schizophrenia (SZ) and Alzheimer's disease (AD). However, commonalities and differences in social dysfunction among these patient groups remain elusive. MATERIALS AND METHODS: Using data from the PRISM study, behavioral (all subscales and total score of the Social Functioning Scale) and affective (perceived social disability and loneliness) indicators of social functioning were measured in patients with SZ (N = 56), probable AD (N = 50) and age-matched healthy controls groups (HC, N = 29 and N = 28). We examined to what extent social functioning differed between disease and age-matched HC groups, as well as between patient groups. Furthermore, we examined how severity of disease and mood were correlated with social functioning, irrespective of diagnosis. RESULTS: As compared to HC, both behavioral and affective social functioning seemed impaired in SZ patients (Cohen's d's 0.81-1.69), whereas AD patients mainly showed impaired behavioral social function (Cohen's d's 0.65-1.14). While behavioral indices of social functioning were similar across patient groups, SZ patients reported more perceived social disability than AD patients (Cohen's d's 0.65). Across patient groups, positive mood, lower depression and anxiety levels were strong determinants of better social functioning (p's <0.001), even more so than severity of disease. CONCLUSIONS: AD and SZ patients both exhibit poor social functioning in comparison to age- and sex matched HC participants. Social dysfunction in SZ patients may be more severe than in AD patients, though this may be due to underreporting by AD patients. Across patients, social functioning appeared as more influenced by mood states than by severity of disease.

Validation of the P1vital® Faces Set for Use as Stimuli in Tests of Facial Emotion Recognition.

BACKGROUND: Negative bias in facial emotion recognition is a well-established concept in mental disorders such as depression. However, existing face sets of emotion recognition tests may be of limited use in international research, which could benefit from more contemporary and diverse alternatives. Here, we developed and provide initial validation for the P1vital® Affective Faces set (PAFs) as a contemporary alternative to the widely-used Pictures of Facial Affect (PoFA). METHODS: The PAFs was constructed of 133 color photographs of facial expressions of ethnically-diverse trained actors and compared with the PoFA, comprised of 110 black and white photographs of facial expressions of generally Caucasian actors. Sixty-one recruits were asked to classify faces from both sets over six emotions (happy, sad, fear, anger, disgust, surprise) varying in intensity in 10% increments from 0 to 100%. RESULTS: Participants were significantly more accurate in identifying correct emotions viewing faces from the PAFs. In both sets, participants identified happy faces more accurately than fearful faces, were least likely to misclassify facial expressions as happy and most likely to misclassify all emotions at low intensity as neutral. Accuracy in identifying facial expressions improved with increasing emotion intensity for both sets, reaching peaks at 60 and 80% intensity for the PAFs and PoFA, respectively. The study was limited by small sizes and age-range of participants and ethnic diversity of actors. CONCLUSIONS: The PAFs successfully depicted a range of emotional expressions with improved performance over the PoFA and may be used as a contemporary set in facial expression recognition tests.

Relationships between social withdrawal and facial emotion recognition in neuropsychiatric disorders.

BACKGROUND: Emotion recognition constitutes a pivotal process of social cognition. It involves decoding social cues (e.g., facial expressions) to maximise social adjustment. Current theoretical models posit the relationship between social withdrawal factors (social disengagement, lack of social interactions and loneliness) and emotion decoding. OBJECTIVE: To investigate the role of social withdrawal in patients with schizophrenia (SZ) or probable Alzheimer's disease (AD), neuropsychiatric conditions associated with social dysfunction. METHODS: A sample of 156 participants was recruited: schizophrenia patients (SZ; n = 53), Alzheimer's disease patients (AD; n = 46), and two age-matched control groups (SZc, n = 29; ADc, n = 28). All participants provided self-report measures of loneliness and social functioning, and completed a facial emotion detection task. RESULTS: Neuropsychiatric patients (both groups) showed poorer performance in detecting both positive and negative emotions compared with their healthy counterparts (p < .01). Social withdrawal was associated with higher accuracy in negative emotion detection, across all groups. Additionally, neuropsychiatric patients with higher social withdrawal showed lower positive emotion misclassification. CONCLUSIONS: Our findings help to detail the similarities and differences in social function and facial emotion recognition in two disorders rarely studied in parallel, AD and SZ. Transdiagnostic patterns in these results suggest that social withdrawal is associated with heightened sensitivity to negative emotion expressions, potentially reflecting hypervigilance to social threat. Across the neuropsychiatric groups specifically, this hypervigilance associated with social withdrawal extended to positive emotion expressions, an emotional-cognitive bias that may impact social functioning in people with severe mental illness.

Effect of disease related biases on the subjective assessment of social functioning in Alzheimer's disease and schizophrenia patients.

BACKGROUND: Questionnaires are the current hallmark for quantifying social functioning in human clinical research. In this study, we compared self- and proxy-rated (caregiver and researcher) assessments of social functioning in Schizophrenia (SZ) and Alzheimer's disease (AD) patients and evaluated if the discrepancy between the two assessments is mediated by disease-related factors such as symptom severity. METHODS: We selected five items from the WHO Disability Assessment Schedule 2.0 (WHODAS) to assess social functioning in 53 AD and 61 SZ patients. Caregiver- and researcher-rated assessments of social functioning were used to calculate the discrepancies between self-rated and proxy-rated assessments. Furthermore, we used the number of communication events via smartphones to compare the questionnaire outcomes with an objective measure of social behaviour. RESULTS: WHODAS results revealed that both AD (p < 0.001) and SZ (p < 0.004) patients significantly overestimate their social functioning relative to the assessment of their caregivers and/or researchers. This overestimation is mediated by the severity of cognitive impairments (MMSE; p = 0.019) in AD, and negative symptoms (PANSS; p = 0.028) in SZ. Subsequently, we showed that the proxy scores correlated more strongly with the smartphone communication events of the patient when compared to the patient-rated questionnaire scores (self; p = 0.076, caregiver; p < 0.001, researcher-rated; p = 0.046). CONCLUSION: Here we show that the observed overestimation of WHODAS social functioning scores in AD and SZ patients is partly driven by disease-related biases such as cognitive impairments and negative symptoms, respectively. Therefore, we postulate the development and implementation of objective measures of social functioning that may be less susceptible to such biases.

Social dysfunction is transdiagnostically associated with default mode network dysconnectivity in schizophrenia and Alzheimer's disease.

OBJECTIVES: Social dysfunction is one of the most common signs of major neuropsychiatric disorders. The Default Mode Network (DMN) is crucially implicated in both psychopathology and social dysfunction, although the transdiagnostic properties of social dysfunction remains unknown. As part of the pan-European PRISM (Psychiatric Ratings using Intermediate Stratified Markers) project, we explored cross-disorder impact of social dysfunction on DMN connectivity. METHODS: We studied DMN intrinsic functional connectivity in relation to social dysfunction by applying Independent Component Analysis and Dual Regression on resting-state fMRI data, among schizophrenia (SZ; N = 48), Alzheimer disease (AD; N = 47) patients and healthy controls (HC; N = 55). Social dysfunction was operationalised via the Social Functioning Scale (SFS) and De Jong-Gierveld Loneliness Scale (LON). RESULTS: Both SFS and LON were independently associated with diminished DMN connectional integrity within rostromedial prefrontal DMN subterritories (pcorrected range = 0.02-0.04). The combined effect of these indicators (Mean.SFS + LON) on diminished DMN connectivity was even more pronounced (both spatially and statistically), independent of diagnostic status, and not confounded by key clinical or sociodemographic effects, comprising large sections of rostromedial and dorsomedial prefrontal cortex (pcorrected=0.01). CONCLUSIONS: These findings pinpoint DMN connectional alterations as putative transdiagnostic endophenotypes for social dysfunction and could aid personalised care initiatives grounded in social behaviour.

From structure to clinic: Design of a muscarinic M1 receptor agonist with potential to treatment of Alzheimer's disease.

Current therapies for Alzheimer's disease seek to correct for defective cholinergic transmission by preventing the breakdown of acetylcholine through inhibition of acetylcholinesterase, these however have limited clinical efficacy. An alternative approach is to directly activate cholinergic receptors responsible for learning and memory. The M1-muscarinic acetylcholine (M1) receptor is the target of choice but has been hampered by adverse effects. Here we aimed to design the drug properties needed for a well-tolerated M1-agonist with the potential to alleviate cognitive loss by taking a stepwise translational approach from atomic structure, cell/tissue-based assays, evaluation in preclinical species, clinical safety testing, and finally establishing activity in memory centers in humans. Through this approach, we rationally designed the optimal properties, including selectivity and partial agonism, into HTL9936-a potential candidate for the treatment of memory loss in Alzheimer's disease. More broadly, this demonstrates a strategy for targeting difficult GPCR targets from structure to clinic.

Accuracy in recognising happy facial expressions is associated with antidepressant response to a NOP receptor antagonist but not placebo treatment.

BACKGROUND: Clinical trials with putative antidepressants can be difficult to execute as it can take up to 8 weeks before differences emerge between drug and placebo, and long expensive trials often fail. Implementation of early response biomarkers could aid this process significantly with potential to identify new treatments. AIMS: In a secondary analysis, we examined the association of early effects on emotional processing with later clinical outcome following treatment with the novel NOP antagonist LY2940094 versus placebo. We hypothesised that early induction of positive bias would be associated with reduced severity of depression after 8 weeks of treatment. METHODS: This was a multicentre, randomised, double-blind, parallel-group, fixed-dose, placebo-controlled, 8 week study to assess sensitivity of the facial emotional recognition task (FERT) to early changes in emotional bias induced by LY2940094. Patients who met diagnostic criteria for major depression were randomised to receive LY2940094 (N = 70) or placebo (N = 66). At week 1 and 6, the FERT was completed by 33 patients in the LY2940094 group and 34 in the placebo group. RESULTS: Patients identified happy faces with higher accuracy (Wald χ2(1,33) = 14.25, p < 0.001) after 1 week treatment with LY290094 compared to placebo (Wald χ2(1,32) = 0.83, p = 0.36) and this correlated with eventual treatment response measured by the Hamilton Depression Rating Scale 7 weeks later. CONCLUSION: These data suggest that emotional processing biomarkers may be sensitive to early effects of antidepressant treatment indicative of later clinical response. Further studies in this area may be useful in developing new treatments and clinical trial designs for predicting antidepressant response.

The clinical effectiveness of using a predictive algorithm to guide antidepressant treatment in primary care (PReDicT): an open-label, randomised controlled trial.

Depressed patients often do not respond to the first antidepressant prescribed, resulting in sequential trials of different medications. Personalised medicine offers a means of reducing this delay; however, the clinical effectiveness of personalised approaches to antidepressant treatment has not previously been tested. We assessed the clinical effectiveness of using a predictive algorithm, based on behavioural tests of affective cognition and subjective symptoms, to guide antidepressant treatment. We conducted a multicentre, open-label, randomised controlled trial in 913 medication-free depressed patients. Patients were randomly assigned to have their antidepressant treatment guided by a predictive algorithm or treatment as usual (TaU). The primary outcome was the response of depression symptoms, defined as a 50% or greater reduction in baseline score of the QIDS-SR-16 scale, at week 8. Additional prespecified outcomes included symptoms of anxiety at week 8, and symptoms of depression and functional outcome at weeks 8, 24 and 48. The response rate of depressive symptoms at week 8 in the PReDicT (55.9%) and TaU (51.8%) arms did not differ significantly (odds ratio: 1.18 (95% CI: 0.89-1.56), P = 0.25). However, there was a significantly greater reduction of anxiety in week 8 and a greater improvement in functional outcome at week 24 in the PReDicT arm. Use of the PReDicT test did not increase the rate of response to antidepressant treatment estimated by depressive symptoms but did improve symptoms of anxiety at week 8 and functional outcome at week 24. Our findings indicate that personalisation of antidepressant treatment may improve outcomes in depressed patients.

Optimizing Behavioral Paradigms to Facilitate Development of New Treatments for Anhedonia and Reward Processing Deficits in Schizophrenia and Major Depressive Disorder: Study Protocol.

Background: Behavioral tasks focusing on different subdomains of reward processing may provide more objective and quantifiable measures of anhedonia and impaired motivation compared with clinical scales. Typically, single tasks are used in relatively small studies to compare cases and controls in one indication, but they are rarely included in larger multisite trials. This is due to limited systematic standardization as well as the challenges of deployment in international studies and stringent adherence to the high regulatory requirements for data integrity. The Reward Task Optimization Consortium (RTOC) was formed to facilitate operational implementation of reward processing tasks, making them suitable for use in future large-scale, international, multisite drug development studies across multiple indications. The RTOC clinical study aims to conduct initial optimization of a set of tasks in patients with major depressive disorder (MDD) or schizophrenia (SZ). Methods: We will conduct a multicenter study across four EU countries. Participants (MDD = 37, SZ = 37, with ≤80 age- and gender-matched healthy volunteers) will attend a study visit comprising screening, self-report and clinically rated assessments of anhedonia and symptom severity, and three reward processing tasks; specifically, the Grip Strength Effort task, the Doors task, and the Reinforcement Learning Working Memory task. The Grip Strength Effort and Doors tasks include simultaneous electroencephalography/event-related potential recordings. Outcomes will be compared using a two-way group design of MDD and SZ with matched controls, respectively. Further analyses will include anhedonia assessment scores as covariates. Planned analyses will assess whether our findings replicate previously published data, and multisite deployment will be evaluated through assessments of quality and conduct. A subset of participants will complete a second visit, to assess test-retest reliability of the task battery. Discussion: This study will evaluate the operational deployment of three reward processing tasks to the regulatory standards required for use in drug development trials. We will explore the potential of these tasks to differentiate patients from controls and to provide a quantitative marker of anhedonia and/or impaired motivation, establishing their usefulness as endpoints in multisite clinical trials. This study should demonstrate where multifaceted reward deficits are similar or divergent across patient populations. Registration: ClinicalTrials.gov (NCT04024371).

Value of monitoring negative emotional bias in primary care in England for personalised antidepressant treatment: a modelling study.

BACKGROUND: Depressed patients often focus on negative life events. Effective antidepressant therapy reverses this negative emotional bias (NEB) within 1 week. Clinical therapeutic effect usually requires 4-6 weeks. The value of implementing NEB monitoring for the personalisation of antidepressant therapy is unknown. OBJECTIVE: To estimate the likely outcome and cost consequences of adopting the P1vital Oxford Emotional Test Battery (ETB) for this purpose in routine primary care in England. METHODS: A hybrid decision analytic model (decision tree plus Markov model) was developed to estimate the cost-effectiveness of ETB monitoring versus no ETB over 52 weeks using quality-adjusted life years (QALYs). Differences in depression severity, episode type and analytical perspectives were considered. Input data were derived from relevant guidelines, literature, national databases, expert opinion and the developers for the year 2013. Multiple sensitivity analyses addressed uncertainty. FINDINGS: The mean number of ETB tests is 2.162 per newly diagnosed patient and 2.166 per patient with recurrent depression. The incremental cost-effectiveness of ETB versus 'no ETB' is £4355/QALY from the healthcare perspective. From the broader societal perspective, ETB is more effective and cost saving. CONCLUSIONS: Monitoring negative emotional bias in primary care in England for personalised antidepressant treatment using ETB seems as an effective and cost-effective option under all considered scenarios (including worst case). Its main economic value seems to lie in reduced productivity loss as opposed to healthcare savings. CLINICAL IMPLICATIONS: The test supports accelerated application of evidence-based depression care. Further optimisation and implementation in the ongoing European PReDicT trial is ongoing.

Overview of the clinical implementation of a study exploring social withdrawal in patients with schizophrenia and Alzheimer's disease.

Trans-diagnostic, domain- or symptom-focused approaches have been heralded as advancing psychiatric research, but relatively few clinical research programmes have been undertaken to leverage their potential. In this manuscript we describe the approach and protocol for an exploratory study, PRISM (Psychiatric Ratings using Intermediate Stratified Markers), that will be conducted to explore the biomarkers in schizophrenia (SZ) and Alzheimer's Disease (AD) that may be related to a common symptom, social withdrawal. Patient participants (N = 72 SZ and N = 72 AD study completers), will complete a series of fMRI, EEG, and behavioural paradigms, as well as contributing blood-derived (e.g. epigenetic) and smartphone data related to social behaviour. Self- as well as caregiver- and researcher-reported assessments will be provided to characterise social withdrawal. Normative data will also be collected from a group of healthy controls (N = 48 study completers), half of whom will be matched in terms of age and gender distribution to the SZ and AD group, respectively. Thus we will explore both differentiation and cross-diagnostic overlap in the biomarkers associated with different levels of social withdrawal in SZ and AD. In this way we aim to provide a deeper understanding of the biological underpinnings of symptomatology common to both disorders, and provide insights into novel treatment targets and future drug development approaches.