Dopamine Transporter Neuroimaging as an Enrichment Biomarker in Early Parkinson's Disease Clinical Trials: A Disease Progression Modeling Analysis

Developing disease-modifying interventions in idiopathic REM sleep behavior disorder and early synucleinopathy

Alpha-synucleinopathies are prevalent neurological disorders that cause significant disability, leading to progressive clinical deterioration that is currently managed solely through symptomatic treatment. Efforts to evaluate disease-modifying therapies during the established stage of the disease have not yielded positive outcomes in terms of clinical or imaging efficacy endpoints. However, alpha-synucleinopathies have a long prodromal phase that presents a promising opportunity for intervention with disease-modifying therapies. The presence of polysomnography-confirmed REM sleep behavior disorder (RBD) is the most reliable risk factor for identifying individuals in the prodromal stage of alpha-synucleinopathy. This paper discusses the rationale behind targeting idiopathic/isolated RBD in disease-modifying trials and outlines possible study designs, including strategies for patient stratification, selection of biomarkers to assess disease progression and patient eligibility, as well as the identification of suitable endpoints. Additionally, the potential targets for disease-modifying treatment in alpha-synucleinopathies are summarized.

Prognostic biomarkers in prodromal α-synucleinopathies: DAT binding and REM sleep without atonia

BACKGROUND

Isolated rapid eye movement (REM) sleep behaviour disorder (iRBD) is a prodromal state of clinical α-synucleinopathies such as Parkinson's disease and Lewy body dementia. The lead-time until conversion is unknown. The most reliable marker of progression is reduced striatal dopamine transporter (DAT) binding, but low availability of imaging facilities limits general use. Our prospective observational study aimed to relate metrics of REM sleep without atonia (RWA)-a hallmark of RBD-to DAT-binding ratios in a large, homogeneous sample of patients with RBD to explore the utility of RWA as a marker of progression in prodromal α-synucleinopathies.

METHODS

DAT single-photon emission CT (SPECT) and video polysomnography (vPSG) were performed in 221 consecutive patients with clinically suspected RBD.

RESULTS

vPSG confirmed RBD in 176 patients (162 iRBD, 14 phenoconverted, 45 non-synucleinopathies). Specific DAT-binding ratios differed significantly between groups, but showed considerable overlap. Most RWA metrics correlated significantly with DAT-SPECT ratios (eg, Montreal tonic vs most-affected-region: r=-0.525; p<0.001). In patients taking serotonergic/noradrenergic antidepressants or dopaminergic substances or with recent alcohol abuse, correlations were weaker, suggesting a confounding influence, unlike other possible confounders such as beta-blocker use or comorbid sleep apnoea.

CONCLUSIONS

In this large single-centre prospective observational study, we found evidence that DAT-binding ratios in patients with iRBD can be used to describe a continuum in the neurodegenerative process. Overlap with non-synucleinopathies and clinical α-synucleinopathies, however, precludes the use of DAT-binding ratios as a precise diagnostic marker. The parallel course of RWA metrics and DAT-binding ratios suggests in addition to existing data that RWA, part of the routine diagnostic workup in these patients, may represent a marker of progression. Based on our findings, we suggest ranges of RWA values to estimate whether patients are in an early, medium or advanced state within the prodromal phase of α-synucleinopathies, providing them with important information about time until possible conversion.

Empowering drug development: Leveraging insights from imaging technologies to enable the advancement of digital health technologies

The US Food and Drug Administration (FDA) has publicly recognized the importance of improving drug development efficiency, deeming translational biomarkers a top priority. The use of imaging biomarkers has been associated with increased rates of drug approvals. An appropriate level of validation provides a pragmatic way to choose and implement these biomarkers. Standardizing imaging modality selection, data acquisition protocols, and image analysis (in ways that are agnostic to equipment and algorithms) have been key to imaging biomarker deployment. The best known examples come from studies done via precompetitive collaboration efforts, which enable input from multiple stakeholders and data sharing. Digital health technologies (DHTs) provide an opportunity to measure meaningful aspects of patient health, including patient function, for extended periods of time outside of the hospital walls, with objective, sensor-based measures. We identified the areas where learnings from the imaging biomarker field can accelerate the adoption and widespread use of DHTs to develop novel treatments. As with imaging, technical validation parameters and performance acceptance thresholds need to be established. Approaches amenable to multiple hardware options and data processing algorithms can be enabled by sharing DHT data and by cross-validating algorithms. Data standardization and creation of shared databases will be vital. Pre-competitive consortia (public-private partnerships and professional societies that bring together all stakeholders, including patient organizations, industry, academic experts, and regulators) will advance the regulatory maturity of DHTs in clinical trials.

Leveraging the regulatory framework to facilitate drug development in Parkinson's disease

There is an exigent need for disease-modifying and symptomatic treatment approaches for Parkinson's disease. A better understanding of Parkinson's disease pathophysiology and new insights in genetics has opened exciting new venues for pharmacological treatment targets. There are, however, many challenges on the path from discovery to drug approval. These challenges revolve around appropriate endpoint selection, the lack of accurate biomarkers, challenges with diagnostic accuracy, and other challenges commonly encountered by drug developers. The regulatory health authorities, however, have provided tools to provide guidance for drug development and to assist with these challenges. The main goal of the Critical Path for Parkinson's Consortium, a nonprofit public-private partnership part of the Critical Path Institute, is to advance these so-called drug development tools for Parkinson's disease trials. The focus of this chapter will be on how the health regulators' tools were successfully leveraged to facilitate drug development in Parkinson's disease and other neurodegenerative diseases.

The dilemma between milestones of progression versus clinical scales in Parkinson's disease

There are significant challenges in accurately documenting the progression of Parkinson's disease (PD). The disease course is highly heterogeneous, there are no validated biomarkers, and we are reliant on repeated clinical measures to assess disease state over time. Yet, the ability to chart disease progression accurately is vital in both observational and interventional study designs, where reliable measures are critical to determine whether an outcome has been met. In this chapter, we first discuss the natural history of PD, including the spectrum of clinical presentation and expected developments through the course of the disease. We then explore in detail the current strategies for measuring disease progression, which can be broadly divided into: (i) the use of quantitative clinical scales; and (ii) determination of the onset time of key milestones. We discuss the strengths and limitations of these approaches for use in clinical trials, with a particular focus on disease modification trials. The selection of outcome measures for a particular study will depend on multiple factors, but trial duration is an important determinant. Milestones are reached over a course of years rather than months, and hence clinical scales with sensitivity to change are needed for short-term studies. However, milestones represent important markers of disease stage which are not confounded by symptomatic therapies and are of critical relevance to the patient. Prolonged but low intensity follow-up beyond a limited period of treatment with a putative disease-modifying agent may allow milestones to be incorporated into evaluation of efficacy in a practical and cost-effective way.

Pharmacometrics: The Already-Present Future of Precision Pharmacology

The use of mathematical modeling to represent, analyze, make predictions or providing information on data obtained in drug research and development has made pharmacometrics an area of great prominence and importance. The main purpose of pharmacometrics is to provide information relevant to the search for efficacy and safety improvements in pharmacotherapy. Regulatory agencies have adopted pharmacometrics analysis to justify their regulatory decisions, making those decisions more efficient. Demand for specialists trained in the field is therefore growing. In this review, we describe the meaning, history, and development of pharmacometrics, analyzing the challenges faced in the training of professionals. Examples of applications in current use, perspectives for the future, and the importance of pharmacometrics for the development and growth of precision pharmacology are also presented.

Study in Parkinson's disease of exercise phase 3 (SPARX3): study protocol for a randomized controlled trial

BACKGROUND

To date, no medication has slowed the progression of Parkinson's disease (PD). Preclinical, epidemiological, and experimental data on humans all support many benefits of endurance exercise among persons with PD. The key question is whether there is a definitive additional benefit of exercising at high intensity, in terms of slowing disease progression, beyond the well-documented benefit of endurance training on a treadmill for fitness, gait, and functional mobility. This study will determine the efficacy of high-intensity endurance exercise as first-line therapy for persons diagnosed with PD within 3 years, and untreated with symptomatic therapy at baseline.

METHODS

This is a multicenter, randomized, evaluator-blinded study of endurance exercise training. The exercise intervention will be delivered by treadmill at 2 doses over 18 months: moderate intensity (4 days/week for 30 min per session at 60-65% maximum heart rate) and high intensity (4 days/week for 30 min per session at 80-85% maximum heart rate). We will randomize 370 participants and follow them at multiple time points for 24 months. The primary outcome is the Movement Disorders Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) motor score (Part III) with the primary analysis assessing the change in MDS-UPDRS motor score (Part III) over 12 months, or until initiation of symptomatic antiparkinsonian treatment if before 12 months. Secondary outcomes are striatal dopamine transporter binding, 6-min walk distance, number of daily steps, cognitive function, physical fitness, quality of life, time to initiate dopaminergic medication, circulating levels of C-reactive protein (CRP), and brain-derived neurotrophic factor (BDNF). Tertiary outcomes are walking stride length and turning velocity.

DISCUSSION

SPARX3 is a Phase 3 clinical trial designed to determine the efficacy of high-intensity, endurance treadmill exercise to slow the progression of PD as measured by the MDS-UPDRS motor score. Establishing whether high-intensity endurance treadmill exercise can slow the progression of PD would mark a significant breakthrough in treating PD. It would have a meaningful impact on the quality of life of people with PD, their caregivers and public health.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04284436 . Registered on February 25, 2020.

Role of Disease Progression Models in Drug Development

The use of Disease progression models (DPMs) in Drug Development has been widely adopted across therapeutic areas as a method for integrating previously obtained disease knowledge to elucidate the impact of novel therapeutics or vaccines on disease course, thus quantifying the potential clinical benefit at different stages of drug development programs. This paper provides a brief overview of DPMs and the evolution in data types, analytic methods, and applications that have occurred in their use by Quantitive Clinical Pharmacologists. It also provides examples of how these models have informed decisions and clinical trial design across several therapeutic areas and at various stages of development. It briefly describes potential new applications of DPMs utilizing emerging data sources, and utilizing new analytic techniques, and discuss new challenges faced such as requiring description of multiple endpoints, rapid model development, application of machine learning-based analytics, and use of high dimensional and real-world data. Considerations for the continued evolution future of DPMs to serve as community-maintained expert systems are also provided.

Path analysis of biomarkers for cognitive decline in early Parkinson’s disease

Clinical and biochemical diversity of Parkinson’s disease (PD) and numerous demographic, clinical, and pathological measures influencing cognitive function and its decline in PD create problems with the determination of effects of individual measures on cognition in PD. This is particularly the case where these measures significantly interrelate with each other producing intricate networks of direct and indirect effects on cognition. Here, we use generalized structural equation modelling (GSEM) to identify and characterize significant paths for direct and indirect effects of 14 baseline measures on global cognition in PD at baseline and at 4 years later. We consider 269 drug-naïve participants from the Parkinson’s Progression Marker Initiative database, diagnosed with idiopathic PD and observed for at least 4 years after baseline. Two GSEM networks are derived, highlighting the possibility of at least two different molecular pathways or two different PD sub-types, with either CSF p-tau181 or amyloid beta (1–42) being the primary protein variables potentially driving progression of cognitive decline. The models provide insights into the interrelations between the 14 baseline variables, and determined their total effects on cognition in early PD. High CSF amyloid concentrations (> 500 pg/ml) are associated with nearly full protection against cognitive decline in early PD in the whole range of baseline age between 40 and 80 years, and irrespectively of whether p-tau181 or amyloid beta (1–42) are considered as the primary protein variables. The total effect of depression on cognition is shown to be strongly amplified by PD, but not at the time of diagnosis or at prodromal stages. CSF p-tau181 protein could not be a reliable indicator of cognitive decline because of its significantly heterogeneous effects on cognition. The outcomes will enable better understanding of the roles of the clinical and pathological measures and their mutual effects on cognition in early PD.

Therapeutics in the Pipeline Targeting α-Synuclein for Parkinson's Disease

Parkinson's disease (PD) is the second most common neurodegenerative disorder and the fastest growing neurologic disease in the world, yet no disease-modifying therapy is available for this disabling condition. Multiple lines of evidence implicate the protein α-synuclein (α-Syn) in the pathogenesis of PD, and as such, there is intense interest in targeting α-Syn for potential disease modification. α-Syn is also a key pathogenic protein in other synucleionpathies, most commonly dementia with Lewy bodies. Thus, therapeutics targeting this protein will have utility in these disorders as well. Here we discuss the various approaches that are being investigated to prevent and mitigate α-Syn toxicity in PD, including clearing its pathologic aggregates from the brain using immunization strategies, inhibiting its misfolding and aggregation, reducing its expression level, enhancing cellular clearance mechanisms, preventing its cell-to-cell transmission within the brain and perhaps from the periphery, and targeting other proteins associated with or implicated in PD that contribute to α-Syn toxicity. We also discuss the therapeutics in the pipeline that harness these strategies. Finally, we discuss the challenges and opportunities for the field in the discovery and development of therapeutics for disease modification in PD. SIGNIFICANCE STATEMENT: PD is the second most common neurodegenerative disorder, for which disease-modifying therapies remain a major unmet need. A large body of evidence points to α-synuclein as a key pathogenic protein in this disease as well as in dementia with Lewy bodies, making it of leading therapeutic interest. This review discusses the various approaches being investigated and progress made to date toward discovering and developing therapeutics that would slow and stop progression of these disabling diseases.

Evaluating dopamine transporter imaging as an enrichment biomarker in a phase 2 Parkinson's disease trial

BACKGROUND

Dopamine transporter single-photon emission computed tomography (DaT-SPECT) can quantify the functional integrity of the dopaminergic nerve terminals and has been suggested as an imaging modality to verify the clinical diagnosis of Parkinson's disease (PD). Depending on the stage of progression, approximately 5-15% of participants clinically diagnosed with idiopathic PD have been observed in previous studies to have normal DaT-SPECT patterns. However, the utility of DaT-SPECT in enhancing early PD participant selection in a global, multicenter clinical trial of a potentially disease-modifying therapy is not well understood.

METHODS

The SPARK clinical trial was a phase 2 trial of cinpanemab, a monoclonal antibody against alpha-synuclein, in participants with early PD. DaT-SPECT was performed at screening to select participants with DaT-SPECT patterns consistent with degenerative parkinsonism. Acquisition was harmonised across 82 sites. Images were reconstructed and qualitatively read at a central laboratory by blinded neuroradiologists for inclusion prior to automated quantitative analysis.

RESULTS

In total, 482 unique participants were screened between January 2018 and May 2019; 3.8% (15/398) of imaged participants were excluded owing to negative DaT-SPECT findings (i.e., scans without evidence of dopaminergic deficit [SWEDD]).

CONCLUSION

A smaller proportion of SPARK participants were excluded owing to SWEDD status upon DaT-SPECT screening than has been reported in prior studies. Further research is needed to understand the reasons for the low SWEDD rate in this study and whether these results are generalisable to future studies. If supported, the radiation risks, imaging costs, and operational burden of DaT-SPECT for enrichment may be mitigated by clinical assessment and other study design aspects.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT03318523 . Date submitted: October 19, 2017. First Posted: October 24, 2017.

Dopamine Transporter Imaging, Current Status of a Potential Biomarker: A Comprehensive Review

A major goal of current clinical research in Parkinson's disease (PD) is the validation and standardization of biomarkers enabling early diagnosis, predicting outcomes, understanding PD pathophysiology, and demonstrating target engagement in clinical trials. Molecular imaging with specific dopamine-related tracers offers a practical indirect imaging biomarker of PD, serving as a powerful tool to assess the status of presynaptic nigrostriatal terminals. In this review we provide an update on the dopamine transporter (DAT) imaging in PD and translate recent findings to potentially valuable clinical practice applications. The role of DAT imaging as diagnostic, preclinical and predictive biomarker is discussed, especially in view of recent evidence questioning the incontrovertible correlation between striatal DAT binding and nigral cell or axon counts.

Stratification Tools for Disease-Modifying Trials in Prodromal Synucleinopathy

Background

Dopamine transporter single photon‐emission computed tomography (DAT‐SPECT) is the strongest risk factor for phenoconversion in patients with idiopathic rapid eye movement (REM)‐sleep behavior disorder (iRBD). However, it might be used as a second‐line stratification tool in clinical trials, because it is expensive and mini‐invasive.

Objective

Aim of the study is to investigate whether other cost‐effective and non‐invasive biomarkers may be proposed as first‐line stratification tools.

Methods

Forty‐seven consecutive iRBD patients (68.53 ± 7.16 years, 40 males) underwent baseline clinical and neuropsychological assessment, olfaction test, resting electroencephalogram (EEG), and DAT‐SPECT. All patients underwent 6 month‐based clinical follow‐up to investigate the emergence of parkinsonism and/or dementia. Survival analysis and Cox regression were used to estimate conversion risk.

Results

Seventeen patients developed an overt synucleinopathy (eight Parkinsonism and nine dementia) 32.8 ± 22 months after diagnosis. The strongest risk factors were putamen specific to non‐displaceable binding ratio (SBR) (hazard ratio [HR], 7.3), attention/working memory cognitive function (NPS‐AT/WM) (HR, 5.9), EEG occipital mean frequency (HR, 2.7) and clinical motor assessment (HR, 2.3). On multivariate Cox‐regression analysis, only putamen SBR and NPS‐AT/WM significantly contributed to the model (HR, 6.2, 95% confidence interval [CI], 1.9–19.8). At post‐hoc analysis, the trail‐making test B (TMT‐B) was the single most efficient first‐line stratification tool that allowed to reduce the number of eligible subjects to 76.6% (sensitivity 1, specificity 0.37). Combining TMT‐B and DAT‐SPECT further reduced the sample to 66% (sensitivity 0.88, specificity 0.47).

Conclusion

The TMT‐B seems to be a cost‐effective and efficient first‐line screening tool, to be used to select patients that deserve DAT‐SPECT as second‐line screening tool for disease‐modifying clinical trials. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

The Use, Standardization, and Interpretation of Brain Imaging Data in Clinical Trials of Neurodegenerative Disorders

Imaging biomarkers play a wide-ranging role in clinical trials for neurological disorders. This includes selecting the appropriate trial participants, establishing target engagement and mechanism-related pharmacodynamic effect, monitoring safety, and providing evidence of disease modification. In the early stages of clinical drug development, evidence of target engagement and/or downstream pharmacodynamic effect-especially with a clear relationship to dose-can provide confidence that the therapeutic candidate should be advanced to larger and more expensive trials, and can inform the selection of the dose(s) to be further tested, i.e., to "de-risk" the drug development program. In these later-phase trials, evidence that the therapeutic candidate is altering disease-related biomarkers can provide important evidence that the clinical benefit of the compound (if observed) is grounded in meaningful biological changes. The interpretation of disease-related imaging markers, and comparability across different trials and imaging tools, is greatly improved when standardized outcome measures are defined. This standardization should not impinge on scientific advances in the imaging tools per se but provides a common language in which the results generated by these tools are expressed. PET markers of pathological protein aggregates and structural imaging of brain atrophy are common disease-related elements across many neurological disorders. However, PET tracers for pathologies beyond amyloid β and tau are needed, and the interpretability of structural imaging can be enhanced by some simple considerations to guard against the possible confound of pseudo-atrophy. Learnings from much-studied conditions such as Alzheimer's disease and multiple sclerosis will be beneficial as the field embraces rarer diseases.

Dopaminergic imaging and clinical predictors for phenoconversion of REM sleep behaviour disorder

This is an international multicentre study aimed at evaluating the combined value of dopaminergic neuroimaging and clinical features in predicting future phenoconversion of idiopathic REM sleep behaviour (iRBD) subjects to overt synucleinopathy. Nine centres sent 123I-FP-CIT-SPECT data of 344 iRBD patients and 256 controls for centralized analysis. 123I-FP-CIT-SPECT images were semiquantified using DaTQUANTTM, obtaining putamen and caudate specific to non-displaceable binding ratios (SBRs). The following clinical variables were also analysed: (i) Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale, motor section score; (ii) Mini-Mental State Examination score; (iii) constipation; and (iv) hyposmia. Kaplan-Meier survival analysis was performed to estimate conversion risk. Hazard ratios for each variable were calculated with Cox regression. A generalized logistic regression model was applied to identify the best combination of risk factors. Bayesian classifier was used to identify the baseline features predicting phenoconversion to parkinsonism or dementia. After quality check of the data, 263 iRBD patients (67.6 ± 7.3 years, 229 males) and 243 control subjects (67.2 ± 10.1 years, 110 males) were analysed. Fifty-two (20%) patients developed a synucleinopathy after average follow-up of 2 years. The best combination of risk factors was putamen dopaminergic dysfunction of the most affected hemisphere on imaging, defined as the lower value between either putamina (P < 0.000001), constipation, (P < 0.000001) and age over 70 years (P = 0.0002). Combined features obtained from the generalized logistic regression achieved a hazard ratio of 5.71 (95% confidence interval 2.85-11.43). Bayesian classifier suggested that patients with higher Mini-Mental State Examination score and lower caudate SBR asymmetry were more likely to develop parkinsonism, while patients with the opposite pattern were more likely to develop dementia. This study shows that iRBD patients older than 70 with constipation and reduced nigro-putaminal dopaminergic function are at high risk of short-term phenoconversion to an overt synucleinopathy, providing an effective stratification approach for future neuroprotective trials. Moreover, we provide cut-off values for the significant predictors of phenoconversion to be used in single subjects.

Effective Data Sharing as a Conduit for Advancing Medical Product Development

INTRODUCTION

Patient-level data sharing has the potential to significantly impact the lives of patients by optimizing and improving the medical product development process. In the product development setting, successful data sharing is defined as data sharing that is actionable and facilitates decision making during the development and review of medical products. This often occurs through the creation of new product development tools or methodologies, such as novel clinical trial design and enrichment strategies, predictive pre-clinical and clinical models, clinical trial simulation tools, biomarkers, and clinical outcomes assessments, and more.

METHODS

To be successful, extensive partnerships must be established between all relevant stakeholders, including industry, academia, research institutes and societies, patient-advocacy groups, and governmental agencies, and a neutral third-party convening organization that can provide a pre-competitive space for data sharing to occur.

CONCLUSIONS

Data sharing focused on identified regulatory deliverables that improve the medical product development process encounters significant challenges that are not seen with data sharing aimed at advancing clinical decision making and requires the commitment of all stakeholders. Regulatory data sharing challenges and solutions, as well as multiple examples of previous successful data sharing initiatives are presented and discussed in the context of medical product development.

Rapid eye movement sleep behavior disorder: A proof-of-concept neuroprotection study for prodromal synucleinopathies

BACKGROUND AND PURPOSE

To explore the feasibility of a neuroprotection trial in prodromal synucleinopathy, using idiopathic rapid eye movement sleep behavior disorder (iRBD) as the target population and ¹²³ I-FP-CIT-SPECT as a biomarker of disease progression.

METHODS

Consecutive iRBD patients were randomly assigned to a treatment arm receiving selegiline and symptomatic rapid eye movement sleep behavior disorder treatment, or to a control arm receiving symptomatic treatment only. Selegiline was chosen because of a demonstrated neuroprotection effect in animal models. Patients underwent ¹²³ I-FP-CIT-SPECT at baseline and after 30 months on average. The clinical outcome was the emergence of parkinsonism and/or dementia. A repeated-measures general linear model (GLM) was applied using group (control and treatment) as "between" factor, and both time (baseline and follow-up) and regions (¹²³ I-FP-CIT-SPECT putamen and caudate uptake) as the "within" factors, adjusting for age.

RESULTS

Thirty iRBD patients completed the study (68.2 ± 6.9 years; 29 males; 21% dropout rate), 13 in the treatment arm, and 17 in the control arm. At follow-up (29.8 ± 9.0 months), three patients in the control arm developed dementia and one parkinsonism, whereas two patients in the treatment arm developed parkinsonism. Both putamen and caudate uptake decreased over time in the control arm. In the treatment arm, only the putamen uptake decreased over time, whereas caudate uptake remained stable. GLM analysis demonstrated an effect of treatment on the ¹²³ I-FP-CIT-SPECT uptake change, with a significant interaction between the effect of group, time, and regions (p = 0.004).

CONCLUSIONS

A 30-months neuroprotection study for prodromal synucleinopathy is feasible, using iRBD as the target population and ¹²³ I-FP-CIT-SPECT as a biomarker of disease progression.

Approaches to Disease Modification for Parkinson's Disease: Clinical Trials and Lessons Learned

Despite many clinical trials over the last three decades, the goal of demonstrating that a treatment slows the progression of Parkinson's disease (PD) remains elusive. Research advances have shed new insight into cellular pathways contributing to PD pathogenesis and offer increasingly compelling therapeutic targets. Here we review recent and ongoing clinical trials employing novel strategies toward disease modification, including those targeting alpha-synuclein and those repurposing drugs approved for other indications. Active and passive immunotherapy approaches are being studied with the goal to modify the spread of alpha-synuclein pathology in the brain. Classes of currently available drugs that have been proposed to have potential disease-modifying effects for PD include calcium channel blockers, antioxidants, anti-inflammatory agents, iron-chelating agents, glucagon-like peptide 1 agonists, and cAbl tyrosine kinase inhibitors. The mechanistic diversity of these treatments offers hope, but to date, results from these trials have been disappointing. Nevertheless, they provide useful lessons in guiding future therapeutic development.

Serum neurofilament light as a biomarker in progressive multiple sclerosis

There is an unmet need in multiple sclerosis (MS) therapy for treatments to stop progressive disability. The development of treatments may be accelerated if novel biomarkers are developed to overcome the limitations of traditional imaging outcomes revealed in early phase trials. In January 2019, the International Progressive MS Alliance convened a standing expert panel to consider potential tissue fluid biomarkers in MS in general and in progressive MS specifically. The panel focused their attention on neurofilament light chain (NfL) in serum or plasma, examining data from both relapsing and progressive MS. Here, we report the initial conclusions of the panel and its recommendations for further research. Serum NfL (sNfL) is a plausible marker of neurodegeneration that can be measured accurately, sensitively, and reproducibly, but standard procedures for sample processing and analysis should be established. Findings from relapsing and progressive cohorts concur and indicate that sNfL concentrations correlate with imaging and disability measures, predict the future course of the disease, and can predict response to treatment. Importantly, disease activity from active inflammation (i.e., new T2 and gadolinium-enhancing lesions) is a large contributor to sNfL, so teasing apart disease activity from the disease progression that drives insidious disability progression in progressive MS will be challenging. More data are required on the effects of age and comorbidities, as well as the relative contributions of inflammatory activity and other disease processes. The International Progressive MS Alliance is well positioned to advance these initiatives by connecting and supporting relevant stakeholders in progressive MS.

Predicting Progression in Parkinson's Disease Using Baseline and 1-Year Change Measures

BACKGROUND

Improved prediction of Parkinson's disease (PD) progression is needed to support clinical decision-making and to accelerate research trials.

OBJECTIVES

To examine whether baseline measures and their 1-year change predict longer-term progression in early PD.

METHODS

Parkinson's Progression Markers Initiative study data were used. Participants had disease duration ≤2 years, abnormal dopamine transporter (DAT) imaging, and were untreated with PD medications. Baseline and 1-year change in clinical, cerebrospinal fluid (CSF), and imaging measures were evaluated as candidate predictors of longer-term (up to 5 years) change in Movement Disorders Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) score and DAT specific binding ratios (SBR) using linear mixed-effects models.

RESULTS

Among 413 PD participants, median follow-up was 5 years. Change in MDS-UPDRS from year-2 to last follow-up was associated with disease duration (β= 0.351; 95% CI = 0.146, 0.555), male gender (β= 3.090; 95% CI = 0.310, 5.869), and baseline (β= -0.199; 95% CI = -0.315, -0.082) and 1-year change (β= 0.540; 95% CI = 0.423, 0.658) in MDS-UPDRS; predictors in the model accounted for 17.6% of the variance in outcome. Predictors of percent change in mean SBR from year-2 to last follow-up included baseline rapid eye movement sleep behavior disorder score (β= -0.6229; 95% CI = -1.2910, 0.0452), baseline (β= 7.232; 95% CI = 2.268, 12.195) and 1-year change (β= 45.918; 95% CI = 35.994,55.843) in mean striatum SBR, and 1-year change in autonomic symptom score (β= -0.325;95% CI = -0.695, 0.045); predictors in the model accounted for 44.1% of the variance.

CONCLUSIONS

Baseline clinical, CSF, and imaging measures in early PD predicted change in MDS-UPDRS and dopamine-transporter binding, but the predictive value of the models was low. Adding the short-term change of possible predictors improved the predictive value, especially for modeling change in dopamine-transporter binding.

Clinical and Imaging Progression in the PARS Cohort: Long-Term Follow-up

BACKGROUND AND OBJECTIVES

The PARS (Parkinson Associated Risk Syndrome) study was designed to test whether screening for hyposmia followed by dopamine transporter imaging can identify risk for conversion to clinical PD, and to evaluate progression markers during the prodromal period.

METHODS

Subjects with hyposmia completed annual clinical evaluations and biennial [¹²³ I]ß-CIT single-photon emission computed tomography scans. Subjects were categorized as normal (>80% age-expected tracer uptake; n = 134), indeterminate (>65-80%; n = 30), and dopamine transporter deficit (≤65%; n = 21) by their baseline scan, and survival analysis was used to compare risk of conversion to motor PD. Progressing to a scan with a dopamine transporter deficit was assessed for those subjects with either normal or indeterminate baseline imaging.

RESULTS

Over a mean of 6.3 [standard deviation: 2.2] years of follow-up, 67% (n = 14) of dopamine transporter deficit subjects, 20% (n = 6) of dopamine transporter indeterminate subjects, and 4% (n = 6) of dopamine transporter normal subjects converted to a PD diagnosis (P < 0.0001). Among subjects without dopamine transporter deficit at baseline, a reduction to ≤65% age-expected uptake occurred in 12 of 30 (40%) with indeterminate dopamine transporter and 7 of 134 (5%) with no dopamine transporter DAT deficit (P < 0.0001). Imaging conversion during follow-up was associated with subsequent clinical conversion (hazard ratio: 9.6; P = 0.0157).

DISCUSSION AND CONCLUSIONS

Long-term follow-up of the PARS cohort demonstrated a high rate of conversion to clinical PD in subjects who either had abnormal dopamine transporter imaging at baseline or developed abnormal imaging during follow-up. These data extend the earlier PARS findings and present new results showing the sequence of incident imaging deficit, imaging progression, and clinical changes that occur in prodromal PD. © 2020 International Parkinson and Movement Disorder Society.

Realistic simulation of virtual multi-scale, multi-modal patient trajectories using Bayesian networks and sparse auto-encoders

Translational research of many disease areas requires a longitudinal understanding of disease development and progression across all biologically relevant scales. Several corresponding studies are now available. However, to compile a comprehensive picture of a specific disease, multiple studies need to be analyzed and compared. A large number of clinical studies is nowadays conducted in the context of drug development in pharmaceutical research. However, legal and ethical constraints typically do not allow for sharing sensitive patient data. In consequence there exist data "silos", which slow down the overall scientific progress in translational research. In this paper, we suggest the idea of a virtual cohort (VC) to address this limitation. Our key idea is to describe a longitudinal patient cohort with the help of a generative statistical model, namely a modular Bayesian Network, in which individual modules are represented as sparse autoencoder networks. We show that with the help of such a model we can simulate subjects that are highly similar to real ones. Our approach allows for incorporating arbitrary multi-scale, multi-modal data without making specific distribution assumptions. Moreover, we demonstrate the possibility to simulate interventions (e.g. via a treatment) in the VC. Overall, our proposed approach opens the possibility to build sufficiently realistic VCs for multiple disease areas in the future.

A Proposed Roadmap for Parkinson's Disease Proof of Concept Clinical Trials Investigating Compounds Targeting Alpha-Synuclein

The convergence of human molecular genetics and Lewy pathology of Parkinson's disease (PD) have led to a robust, clinical-stage pipeline of alpha-synuclein (α-syn)-targeted therapies that have the potential to slow or stop the progression of PD and other synucleinopathies. To facilitate the development of these and earlier stage investigational molecules, the Michael J. Fox Foundation for Parkinson's Research convened a group of leaders in the field of PD research from academia and industry, the Alpha-Synuclein Clinical Path Working Group. This group set out to develop recommendations on preclinical and clinical research that can de-risk the development of α-syn targeting therapies. This consensus white paper provides a translational framework, from the selection of animal models and associated end-points to decision-driving biomarkers as well as considerations for the design of clinical proof-of-concept studies. It also identifies current gaps in our biomarker toolkit and the status of the discovery and validation of α-syn-associated biomarkers that could help fill these gaps. Further, it highlights the importance of the emerging digital technology to supplement the capture and monitoring of clinical outcomes. Although the development of disease-modifying therapies targeting α-syn face profound challenges, we remain optimistic that meaningful strides will be made soon toward the identification and approval of disease-modifying therapeutics targeting α-syn.

Revision of Diagnosis in Early Parkinsonism with Abnormal Dopamine Transporter Imaging

BACKGROUND

In patients with early parkinsonism, misdiagnosis may occur in >30% of cases. This can have detrimental consequences clinically and in clinical trials. Dopamine transporter (DAT) SPECT imaging can help improve diagnostic accuracy.

OBJECTIVE

To describe characteristics of individuals initially diagnosed with idiopathic Parkinson's disease (iPD) and with abnormal DAT SPECT imaging who had a change in diagnosis on follow-up.

METHODS

Data were obtained from the biomarker study Parkinson's Progression Markers Initiative (PPMI). PPMI is a multicenter, observational study that enrolled 423 individuals with a diagnosis of iPD of ≤2 years duration and with abnormal DAT SPECT imaging. Participants were assessed at least annually, and diagnosis was documented by the site neurologist. Characteristics of those that had a change in diagnosis were compared to those with stable diagnosis.

RESULTS

390 subjects were included. Eight (2%) had a change in diagnosis. The diagnosis was changed to multiple system atrophy in 5 cases, dementia with Lewy bodies in 2, and corticobasal degeneration in 1. Revision of diagnosis occurred 2-5.2 years from enrollment. Mean motor score was higher (26.9 vs 20.6; p = 0.01), DAT binding lower (1.056 vs 1.406; p = 0.01), genetic risk score lower (-0.016 vs -0.022; p = 0.0470), and olfaction score higher (28.75 vs 22.05; p = 0.03) in those whose diagnosis changed compared to those who did not.

CONCLUSION

Diagnosis remained stable in most individuals with early parkinsonism diagnosed with iPD and with abnormal DAT imaging. A small number had a revision in diagnosis. Clinical and biomarker abnormalities were greater at baseline in those whose diagnosis changed.

Next-Generation DILI Biomarkers: Prioritization of Biomarkers for Qualification and Best Practices for Biospecimen Collection in Drug Development

The diagnosis and management of drug-induced liver injury (DILI) remains a challenge in clinical trials in drug development. The qualification of emerging biomarkers capable of predicting DILI soon after the initiation of treatment, differentiating DILI from underlying liver disease, identifying the causal entity, and assigning appropriate treatment options after DILI is diagnosed are needed. Qualification efforts have been hindered by lack of properly stored and consented biospecimens that are linked to clinical data relevant to a specific context of use. Recommendations are made for biospecimen collection procedures, with the focus on clinical trials, and for specific emerging biomarkers to focus qualification efforts.

Open Data Revolution in Clinical Research: Opportunities and Challenges

Efforts for sharing individual clinical data are gaining momentum due to a heightened recognition that integrated data sets can catalyze biomedical discoveries and drug development. Among the benefits are the fact that data sharing can help generate and investigate new research hypothesis beyond those explored in the original study. Despite several accomplishments establishing public systems and guidance for data sharing in clinical trials, this practice is not the norm. Among the reasons are ethical challenges, such as privacy of individuals, data ownership, and control. This paper creates awareness of the potential benefits and challenges of sharing individual clinical data, how to overcome these challenges, and how as a clinical pharmacology community we can shape future directions in this field.

Hippocampal Neuroimaging-Informed Clinical Trial Enrichment Tool for Amnestic Mild Cognitive Impairment Using Open Data

Our goal was to assess the enrichment utility of hippocampal volume (HV) as an enrichment biomarker in amnestic mild cognitive impairment (aMCI) clinical trials, and, hence, develop an HV neuroimaging-informed clinical trial enrichment tool. Modeling of integrated longitudinal patient-level data came from open-access natural history studies in patients diagnosed with aMCI-the Alzheimer's Disease Neuroimaging Initiative (ADNI)-1 and ADNI-2-and indicated that a decrease of 1 cm³ with respect to the analysis dataset median baseline intracranial volume-adjusted HV (ICV-HV; ~ 5 cm³ ) is associated with > 50% increase in disease progression rate as measured by the Clinical Dementia Rating Scale-Sum of Boxes. Clinical trial simulations showed that the inclusion of aMCI subjects with baseline ICV-HV below the 84th or 50th percentile allowed an approximate reduction in trial size of at least 26% and 55%, respectively. This clinical trial enrichment tool can help design more efficient and informative clinical trials.

Parkinson's disease prognostic scores for progression of cognitive decline

Clinical and biochemical diversity of Parkinson’s disease (PD) presents a major challenge for accurate diagnosis and prediction of its progression. We propose, develop and optimize PD clinical scores as efficient integrated progression biomarkers for prediction of the likely rate of cognitive decline in PD patients. We considered 269 drug-naïve participants from the Parkinson’s Progression Marker Initiative database, diagnosed with idiopathic PD and observed between 4 and 6 years. Nineteen baseline clinical and pathological measures were systematically considered. Relative variable importance and logistic regressions were used to optimize combinations of significant baseline measures as integrated biomarkers. Parkinson’s disease cognitive decline scores were designed as new clinical biomarkers using optimally categorized baseline measures. Specificities and sensitivities of the biomarkers reached ~93% for prediction of severe rate of cognitive decline (with more than 5 points decline in 4 years on the Montreal Cognitive Assessment scale), and up to ~73% for mild-to-moderate decline (between 1 and 5 points decline). The developed biomarkers and clinical scores could resolve the long-standing clinical problem about reliable prediction of PD progression into cognitive deterioration. The outcomes also provide insights into the contributions of individual clinical and pathological measures to PD progression, and will assist with better-targeted treatment regiments, stratification of clinical trial and their evaluation.

Molecular Neuroimaging of the Dopamine Transporter as a Patient Enrichment Biomarker for Clinical Trials for Early Parkinson's Disease

The Critical Path for Parkinson's (CPP) Imaging Biomarker and Modeling and Simulation working groups aimed to achieve qualification opinion by the European Medicines Agency (EMA) Committee for Medical Products for Human Use (CHMP) for the use of baseline dopamine transporter neuroimaging for patient selection in early Parkinson's disease clinical trials. This paper describes the regulatory science strategy to achieve this goal. CPP is an international consortium of three Parkinson's charities and nine pharmaceutical partners, coordinated by the Critical Path Institute.

The Qualification of an Enrichment Biomarker for Clinical Trials Targeting Early Stages of Parkinson's Disease

As therapeutic trials target early stages of Parkinson's disease (PD), appropriate patient selection based purely on clinical criteria poses significant challenges. Members of the Critical Path for Parkinson's Consortium formally submitted documentation to the European Medicines Agency (EMA) supporting the use of Dopamine Transporter (DAT) neuroimaging in early PD. Regulatory documents included a comprehensive literature review, a proposed analysis plan of both observational and clinical trial data, and an assessment of biomarker reproducibility and reliability. The research plan included longitudinal analysis of the Parkinson Research Examination of CEP-1347 Trial (PRECEPT) and the Parkinson's Progression Markers Initiative (PPMI) study to estimate the degree of enrichment achieved and impact on future trials in subjects with early motor PD. The presence of reduced striatal DAT binding based on visual reads of single photon emission tomography (SPECT) scans in early motor PD subjects was an independent predictor of faster decline in UPDRS Parts II and III as compared to subjects with scans without evidence of dopaminergic deficit (SWEDD) over 24 months. The EMA issued in 2018 a full Qualification Opinion for the use of DAT as an enrichment biomarker in PD trials targeting subjects with early motor symptoms. Exclusion of SWEDD subjects in future clinical trials targeting early motor PD subjects aims to enrich clinical trial populations with idiopathic PD patients, improve statistical power, and exclude subjects who are unlikely to progress clinically from being exposed to novel test therapeutics.

Dopamine-related dissociation of cortical and subcortical brain activations in cognitively unimpaired Parkinson's disease patients OFF and ON medications

Background:

Despite dopaminergic depletion that is severe enough to cause the motor symptoms of Parkinson’s disease (PD), m any patients remain cognitively unimpaired. Little is known about brain mechanism s underlying such preserved cognitive abilities and their alteration by dopaminergic medications.

Objectives:

We investigated brain activations underlying dopamine-related differences in cognitive function using a unique experimental design with PD patients off and on dopaminergic medications. We tested the dopamine overdose hypothesis, which posits that the excess of exogenous dopamine in the frontal cortical regions can impair cognition.

Methods:

We used a two-choice forced response Choice Reaction Time (CRT) task to probe cognitive processes underlying response selection and execution. Functional magnetic resonance imaging data Were acquired from 16 cognitively unimpaired (Level-II) PD participants and 15 Well-matched healthy controls (HC). We compared task performance (i.e. reaction time and accuracy) and brain activation of PD participants off dopaminergic medications (PD_OFF) in comparison with HC, and PD_OFF participants with those on dopaminergic medications (PD_ON).

Results:

PD_OFF and PD_ON groups did not differ from each other, or from the HC group, in reaction time or accuracy. Compared to HC, PD_OFF activated the bilateral putamen less, and this w as compensated by higher activation of the anterior insula. No such differences Were observed in the PD_ON group, Compared to HC. Compared to both HC and PD_OFF, PD_ON participants showed dopamine-related hyperactivation in the frontal cortical regions and hypoactivation in the amygdala.

Conclusion:

Our data provide further evidence that PD_OFF and PD_ON participants engage different cortical and subcortical systems to achieve similar levels of cognitive performance as HC. Crucially, our findings demonstrate dopamine-related dissociation in brain activation between cortical and subcortical regions, and provide novel support for the dopamine overdose hypothesis.

Targeted Therapies for Parkinson's Disease: From Genetics to the Clinic

The greatest unmet medical need in Parkinson's disease (PD) is treatments that slow the relentless progression of symptoms. The discovery of genetic variants causing and/or increasing the risk for PD has provided the field with a new arsenal of potential therapies ready to be tested in clinical trials. We highlight 3 of the genetic discoveries (α-synuclein, glucocerebrosidase, and leucine-rich repeat kinase) that have prompted new therapeutic approaches now entering the clinical stages. We are at an exciting juncture in the journey to developing disease-modifying treatments based on knowledge of PD genetics and pathology. This review focuses on therapeutic paradigms that are under clinical development and highlights a wide range of key outstanding questions in PD. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.