Introduction

There is an urgent need to advance new and innovative therapeutic approaches and drug development tools for neurological disorders. The massive health and economic impacts of neurological diseases have raised the issue to an international health policy level, capturing the attention of the World Health Organization in the most rapidly growing nervous system diseases [1]. Common challenges that are shared across individual neurological diseases include the variable course of disease trajectories, the lack of biomarkers that track the onset and progression of disease, and the need for patient focused endpoints. Such factors contribute to the necessity for long duration and costly clinical trials. Few opportunities exist to share learnings across individual diseases and to encourage collaborations among diverse disease-focused stakeholders around the world. Regulatory agencies across the globe have recommended public–private partnerships as key to accelerating drug development [2,3,4,5].

The Critical Path Institute (C-Path) is a unique nonprofit organization with the mission of leading collaborations that accelerate drug development, advancing better treatments for people worldwide. C-Path serves as a neutral third party to lead public–private partnerships (PPPs) for several chronic diseases of high unmet medical need. The range of diseases that impact the nervous system, covered by C-Path PPPs, includes Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), Duchenne muscular dystrophy (DMD), and inherited ataxias. C-Path leads collaborative teams to advance regulatory science needs in many specific disease areas, and neurological disorders are a key focus. To date, C-Path has successfully advanced data-driven approaches to advance drug development tools with regulatory milestones achieved in several disorders of the nervous system. Table 1 lists specific drug development tools that have received FDA and/or EMA regulatory endorsement by C-Path consortia for AD, PD, and DMD. Table 2 illustrates modeling drug development tools under regulatory review for HD, PD, and DMD. The drug development tools listed in Tables 1 and 2 include biomarkers and clinical trial simulation tools all developed by integrating diverse clinical data from around the world. Endorsement of such tools then serves to streamline drug development review for future sponsors that utilize these tools in their programs.

Table 1 Regulatory milestones achieved in public private partnerships for nervous system disorders
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Table 2 Drug development tool neuroscience initiatives under regulatory review
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C-Path organized a Neuroscience Annual Workshop convening representatives from academia, industry, regulatory agencies (FDA and EMA), and the patient community to address a range of unmet needs and challenges in drug development (a list of workshop participants is included in the acknowledgments). This diverse set of voices across the ecosystem was critical to generating a holistic output of perspectives including the patient voice to be shared with the wider community and distilled into recommendations for the future.

Patient-Focused Drug Development: the Patient Voice Drives Change

The 21st Century Cures Act statute (85 FR 25642 [34]) specified that the FDA develops guidance documents over a period of five years regarding the collection of patient experience data and the recommendations for the proper use of such data and related information in the process of drug development. This initiative is referred to as patient-focused drug development (PFDD) and is grounded in four FDA guidance documents (https://www.ema.europa.eu/en/events/multi-stakeholder-workshop-patient-experience-data-medicines-development-regulatory-decision-making). Individuals living with a disease are true experts with lived experience and are uniquely positioned to inform the therapeutic context for evaluation of safety and efficacy of new drugs under development. A systematic approach led by regulatory agencies has been transformative to ensure that patients’ experiences, perspectives, needs, and priorities are captured and meaningfully incorporated into the drug development and evaluation processes [6, 7]. Perspectives from five annual meeting in-person participants who represented the patient voice were shared throughout the three days of the workshop. The lived experience of individuals affected by AD (patient perspective Box 2) and PD (patient perspectives Box 1 and Box 3) provided a unique sense of urgency and inspiring viewpoints for all to learn from.

Clinical Outcome Measures as Clinical Trial Endpoints

Traditional endpoints to study progression of neurological disorders primarily rely on measures assessed by clinicians evaluating signs and symptoms based on impact and individuals’ inability to perform functional tasks in their daily lives. Yet there are unique differences between endpoints used in clinical settings as compared to what is required for evaluation of safety and efficacy of new drugs. The implementation of PFDD has catalyzed the recognition of improved measures that are reflective of the patient and caregiver voice. This has led to the emergence of new or refined clinical outcome assessments (COAs) for use in clinical trials. Patient organizations and patient representatives play an integral role in developing COAs. It is recognized that neurological diseases represent a continuum rather than a defined list of discrete milestones and that a time-to-event endpoint might not be adequate for chronic progressive disorders where the pathophysiology of disease occurs over decades. Multiple regulatory pathways are in place to advance COAs for use in clinical trials. It is important to distinguish between evaluation of signs and symptoms in clinical care vs. a well-defined COA needed for evaluation of clinical trials. FDA’s PFDD guidance has been transformative in defining the requirements for fit-for-purpose COAs of clinical trials. The EMA recently held a “Multi-stakeholder workshop: Patient experience data in medicines development and regulatory decision-making” (European Medicines Agency, 2022; https://www.ema.europa.eu/en/events/multi-stakeholder-workshop-patient-experience-data-medicines-development-regulatory-decision-making) with the goal of highlighting the importance of including the patient voice in regulatory review of medical products in the European Union. Both the FDA and the EMA are open to novel approaches and endpoints, particularly for diseases where there is no precedent.

Understanding Disease Progression for Optimizing Endpoints

Global health authorities have identified natural history studies and data from registries as suitable supporting data for drug approvals, particularly in orphan diseases [8, 9]. Strategies include the use of natural history to generate historical control data for a range of applications such as in silico simulations, use of external controls, nontraditional study designs, and identifying inclusion/exclusion criteria and appropriate endpoints from untraditional data sources. These examples have been captured in recent regulatory guidance documents publicly posted on behalf of both FDA and EMA.

C-Path is a leader in data aggregation, standardization, and generation of hypotheses and solutions based on patient-level and item level data [10] across diverse sources of clinical data. Most of the neurology data sets in the C-Path repository are from industry clinical trials, constituting high-quality controlled data of the highest standards and rigor and are well curated making them suitable for modeling and analyses that can accelerate and increase efficiency in drug development (Fig. 1).

Fig. 1
figure 1

Graphic histogram of the data acquired and integrated into unified databases at C-Path across distinct diseases that impact the nervous system. Patient-level item level data is fully anonymized and integrated using CDISC therapeutic area standards. The number of participants denotes the status as of January 2023

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Digital Health Technologies as Drug Development Tools

The integration of digital health technologies (DHTs) into drug development is advancing at a rapid pace [11]. A broad spectrum of applications for DHTs has emerged including early diagnosis, longitudinal characterization, and monitoring of disease progression. The ability to derive continuous measures of daily life function in real-world settings holds significant promise for decentralized trials in neurological diseases. Confidence in the reliability and reproducibility of the measures derived from DHTs is essential to assure that the platform is fit-for-purpose and to effectively advance the successful integration of DHTs in drug development. Cutting edge advances in technology platforms, algorithm development, and robust analytic platforms pose both advantages and challenges given the rapid pace of innovation. Independent validation of study results is still lacking in the majority of case examples. Several regulatory frameworks have been proposed, and it is recommended that early and close communication with regulatory health authorities is followed to ensure that the validation plan will address evidentiary requirements, which allow for integration of DHTs in drug development. The use of such tools as exploratory endpoints in clinical trials and sharing of the generated data promises to accelerate the rate of progress in the field. This requires multidisciplinary stakeholders across a diverse array of disciplines to collaborate within a pre-competitive framework to achieve success. Integrating patient perspectives is especially critical at all stages of DHT development, study design, and execution. The Critical Path for Parkinson’s (CPP) digital drug development tool (3DT) initiative was highlighted as a case example that is unique in sharing of data, costs, and knowledge under the iterative advisement of regulators. A dedicated team comprised of industry, academic experts, patient research organizations, clinicians, regulators, and people living with PD have agreed to collaborate on prospective data collection and share data to advance the regulatory endorsement of DHTs for use in PD clinical trials [12, 13].

Biomarkers

Throughout the three days of the annual meeting, regulators emphasized the importance of understanding the biology of a given disease to better understand its various stages and advised implementation of tools to measure its progression. A central message was that a disease should not be exclusively defined by its clinical manifestations but also should be defined by the biology. The syndromic landscape of neurodegenerative diseases is shifting to one that includes more precisely grouped subtypes with diverse molecular pathologies. AD represents a flagship example that has shifted from postmortem confirmation of diagnosis as gold standard to premortem classification that incorporates molecular neuropathological hallmarks of disease such as in vivo measurement of β-amyloid, hyperphosphorylated tau, and TDP-43. Biomarker classification has catalyzed biological staging of disease and incentivized early intervention in AD. Similarly, a new HD Integrated Staging System (HD-ISS) based on biomarkers and genetics was developed by C-Path’s HD Regulatory Science Consortium (HD-RSC) [14]. To consider biomarkers as primary data supportive of drug approval is a relatively new concept in neuroscience. The work at C-Path provides tremendous opportunities to advance overall science towards using biomarkers to capture the underlying disease biology in patients and to implement these evolving insights into drug development in dynamic and iterative ways.

Recent regulatory approvals for disorders that impact the nervous system represent true paradigm shifts in many ways from historical approaches. The acceptance of a greater degree of uncertainty with robust scientific protocols and rigorous assessment of the data is a prerequisite. One example is accelerated approval paths which provide a regulatory pathway to make therapies available to patients with serious life-threatening diseases for which there are no therapies earlier than the more traditional regulatory pathways might allow. In neuroscience, there are, however, significant barriers to applying accelerated approval in regulatory decision-making. A major challenge is the need for biomarkers that reliably reflect the disease biology or intermediate endpoints that reasonably predict clinical benefit. The case of amyloid as a likely surrogate of efficacy for drugs to slow disease progression in early stages of AD was highlighted as an example of the ability to rely on biomarkers to make regulatory decisions [15]. This decision was grounded in an understanding of the disease stages as defined by biomarkers [16]. Additional examples include the role of neuroimaging biomarkers in defining the longitudinal progression of HD [17, 18] and neurofilament light chain (NfL) as a reasonably likely surrogate biomarker in ALS [19].

Fluid Biomarkers

Recent advances in the measurement of biomarker analytes in cerebrospinal fluid and blood are having significant impact on drug development and leading to a better-informed decision-making. The ability to measure pathologic proteins such as mutant Huntingtin, amyloid, tau, and alpha-synuclein with ultrasensitive assays in biologic fluids is advancing rapidly. Proteinopathies are now being pursued for therapeutic intervention across a range of disorders previously assumed to be distinct disease states due to diverse clinical manifestations (e.g., frontotemporal dementia and amyotrophic lateral sclerosis). Multistakeholder attention to assay standardization, harmonization, prospective integration, and rigorous longitudinal assessment of these promising biomarkers in natural history studies is critical.

The FDA has issued multiple letters of support for biofluid biomarkers as a regulatory path to identifying promising tools for drug development. Examples include the blood biomarkers GFAP and UCHL1 for traumatic brain Injury(https://www.fda.gov/media/112687/download) [20] and NfL in progressive multiple sclerosis (MS) (https://www.fda.gov/media/149608/download) [21]. The letter of support mechanism exists with both FDA (https://www.fda.gov/drugs/biomarker-qualification-program/letter-support-los-initiative) and EMA (https://www.ema.europa.eu/en/human-regulatory/research-development/scientific-advice-protocol-assistance/novel-methodologies-biomarkers/opinions-letters-support-qualification-novel-methodologies-medicine-development) and has led to an increase in use of such biomarkers in clinical trials and facilitates more data collection and data sharing. The letters of support serve as catalysts to further drug development and enable alignment for a more unified consensus on which promising biomarkers should be measured and evaluated in ongoing and future trials. A list of biomarkers that were highlighted during the workshop is illustrated in Table 3.

Table 3 Examples of biomarkers and data sharing reviewed at the C-Path neuroscience meeting
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Imaging Biomarkers

The ability to identify and quantify in vivo the hallmark pathological markers amyloid and tau has transformed drug development for AD [22, 23]. The potential for imaging biomarker modalities such as positron emission tomography (PET) as drug development tools is unique, as it allows for defining and quantifying brain region-specific changes that may correlate with functional outcomes. While a powerful tool, the neuroanatomic spatial specificity of neuroimaging biomarkers, cannot be achieved by biofluid measurement of specific analytes in blood or cerebral spinal fluid (CSF). Neuroimaging biomarkers have the potential to predict earlier symptom onset for individual patients and to assess longitudinal progression with region-specific neuroanatomic precision (e.g., [24]). Imaging of biomarker modalities outside the brain may be informative, in particular early in disease, when autonomic dysfunction may occur or, for example, where the enteric nervous system has been hypothesized to play a role in the etiology of neurological disease, as in PD. Quantitative magnetic resonance imaging (MRI) and spectroscopy (MRS) play important roles as well in imaging of neurological disorders (e.g. [18, 25,26,27]). In DMD, peripheral imaging using MR has been informative to measure muscle damage, inflammation, and fat fraction infiltration [28, 29].

Advanced Modeling and Analytics

Development of models that are refined based on emerging data is key, and the FDA recommends defining best practices for prospective modeling technologies to integrate contemporary data as new measurement platforms evolve (e.g., [9]). Disease progression models are key to designing and optimizing clinical trials. The last two decades have catalyzed a rapid growth and expansion of model informed drug development (MIDD). Models are evolving for optimizing clinical trial designs in addition to their role in characterizing safety and supporting evaluation of effectiveness of novel therapies. Methodologies include empirical, semi-mechanistic, and mechanistic modeling.

It is important to recognize that one study, whether it be a clinical trial or a natural history study, is not likely to be sufficient to support the true predictive accuracy of a disease progression model for future trials. From a regulatory perspective, merging multiple data sources is key when trying to increase the analytical power of each dataset and to improve descriptions of disease trajectories. Additional methodologies such as quantitative systems pharmacology and item response theory (IRT) modeling can facilitate increased precision in linking novel biomarkers and genes to clinically meaningful domains, particularly in heterogeneous disease conditions.

Both FDA and EMA have elucidated formal regulatory paths for drug developers, sponsors, and regulatory scientists to engage in specific MIDD-based quantitative opportunities in drug development in a real-time manner. The FDA fit-for-purpose (FFP) path was formed in 2013 with the regulatory endorsement of the first clinical trial simulation tool in Alzheimer’s disease as a precedent for other disease areas to follow [30]. The EMA has adopted the qualification of novel methodologies path for quantitative disease progression models. C-Path neurological disease-focused consortia have received two letters of support for the use of clinical trial simulation platforms to optimize the design of clinical trials in PD and DMD (Table 1a).

Innovative Clinical Trial Designs

Regulatory agencies have served as catalysts to drive innovative clinical trial designs, particularly following the global COVID-19 pandemic. The first adaptive trial was initiated for breast cancer, and the ISPY2 trial is viewed as transformative in enabling collaboration across traditional boundaries between regulators, researchers, and industry partners [31]. Multi-arm adaptive platform trials represent a novel way to evaluate multiple targets with a shared placebo group to enable iterative investigation of novel mechanisms in parallel. Such an approach is particularly attractive for rare diseases. A number of examples are now emerging across neurological disorders including ALS (HEALEY ALS), AD (DIAN-TU), DMD master protocol [32], and PD (path to prevention P2P platform trial in prodromal PD) [33]. In all examples, multistakeholder collaborations are in place to advance the platform trial. Shared learnings across these disease areas are key to improving efficiencies based on key lessons learned from these innovative trials.

Nonprofit research organizations are key in enabling much needed resources as well as providing patient perspectives and facilitating recruitment and other essential clinical resources. Regulators observe that platform trials represent a unique learning opportunity and recommend that such studies are best suited for an initial assessment that is as informative as possible, perhaps testing out new strategies and techniques followed up by confirmation elsewhere.

Paving the Path for the Future: Outlook and Critical Success Factors

A rich pipeline of disease modifying therapies is advancing rapidly across a broad range of nervous system disorders. The rapid pace of scientific advances in the neurosciences is transforming traditional drug development approaches to enable new pioneering precision medicine strategies grounded in genetics, biomarkers, and innovative technologies. The regulatory landscape globally is innovating by expanding focus on patient focused drug development and clearly pointing the way to hope for drug approvals for disorders that historically had no effective treatments.

Recommendations for the future that emerged from this unique workshop centered around the importance of fostering collaborations among experts across distinct diseases. Forums such as this multistakeholder workshop serve as enablers for achieving consensus on cross-cutting data-driven approaches to solving problems that drug developers face. Progress in drug development tools including biomarkers, innovative clinical trial design, disease progression models, and clinically meaningful endpoints will be hastened by adopting efficient data sharing and by expanding the precompetitive space. It behooves all stakeholders to support data sharing as an ethical imperative as study participants are putting themselves at risk to contribute to science. Attention to adopting unified data standards and inclusion of exploratory tools in early clinical development will streamline the path for drug approvals. Drug development speed is crucial for patients, physicians, and drug development stakeholders alike. Regulators serve as catalysts for driving change for the future with urgency in meeting the needs of all those impacted by such devastating diseases.

Voice of the Patient Perspectives