The Impact of the Top 3 Strategic Imperatives on the Precision Neurodegenerative Disease (NDD) Industry

Industry Convergence

• Globally, the number of people living with an NDD has grown substantially during the past 30 years because of the increasingly aging population and more exposure to environmental, metabolic, and lifestyle risk factors. 
• The growing number of people with an NDD makes strategic integration between pharmaceutical, diagnostics, imaging, and medical devices vital to create complementary capabilities that enable novel drug discovery, development, and commercialization. 
• Integrating technological synergies between industry participants, researchers, and pharmaceutical companies will help launch digital and medical technology (MedTech) solutions to monitor disease progression and design tailored treatment strategies that meet the needs of individual patients, bridging treatment gaps.
• Pharmaceutical and diagnostic companies will increasingly collaborate with academic institutions in the next 5 years to validate and commercialize novel biomarkers (fluid, genetic, and digital) because of the ongoing revisions by the US Food and Drug Administration (FDA) that facilitate the adoption of novel endpoints for clinical trial outcome measures. 
• Partnerships between digital health and data science companies will grow to build real-world evidence (RWE) for reimbursements, predictive modeling, and data-driven insights and improve clinical decision support.
• Pharma’s convergence with MedTech will advance neuromodulation and augmented reality (AR) as alternative therapies, increasing investor interest in the neurotechnology sector in the short term. In the next 2 years, the expansion of collaborative biotech platforms, consortia, and open innovation strategies will drive innovations at scale.

Disruptive Technologies

• To optimize therapy and facilitate accurate patient stratification for NDD therapeutics trials, it is imperative to address the shortcomings of standard diagnostics and neuroimaging technologies by developing novel biomarkers and companion and molecular diagnostics. 
• AI technologies are finding growing applications in pharmacogenomics, target identification, high-throughput screening, and predictive analysis for determining the success of targets, which decreases clinical trial failures—a significant obstacle in NDD drug research.
• The need to identify targeted drug delivery (DD) systems that help drugs cross the blood–brain barrier (BBB) requires exploring novel DD technologies.
• In the next 5 years, companies will leverage AI, multi-omics, digital twins (DTs), and digital health tools to identify novel targets and develop drug, diagnostics, disease screening solutions, and patient monitoring technologies.
• Companies will explore using AI-based neuroimaging and molecular imaging to guide personalized treatment and nanotechnology-based systems to effectively and safely deliver drugs to the brain.
• Partnership-based growth strategies will propel tech-driven neuroscience research for product innovation across geographies. 
• For instance, the Indian Institute of Technology Madras’s brain center has a computing platform that it combined with NVIDIA's DGX to map and analyze more than 100 whole human brains at the cell level to advance neuroscience research on a national/global scale at a breakthrough speed.

Transformative Mega Trends

• Because existing treatments focus on symptom modification, the NDD Industry’s R&D is shifting to focus on disease-modifying therapeutics. The shift includes targeting underlying pathological mechanisms, such as protein misfolding, neuroinflammation, and synapse dysfunction, targeting specific biomarkers, patient profiles, disease subtypes, and distinct biomarkers.
• Precision medicine (PM) companies are increasingly collaborating with technology firms, academia, and pharmaceutical companies to develop mechanistic-specific therapy approaches while developing precision medicine or genomic association studies (GWAS) and precision research tools.
• In the next 2–3 years, advances in genomics and the understanding of NDD pathophysiology will drive the identification of disease-specific biomarkers, leading to the development of novel diagnostics, prognostics, and disease progression and response-to-treatment monitoring solutions. 
• Companies and institutions will adopt novel therapeutic approaches, such as epigenetic therapies, active immunotherapies, protein degradation therapies, and diagnostics (e.g., sequencing companion diagnostics [CDx]) for drug development. The NDD industry will evaluate drugs and interventions for a broader NDD spectrum rather than just for single diseases. For example, CuraSen Therapeutics Inc. is testing its CST-103 and CST-107 drugs for the entire NDD spectrum.
• In the next 5 years, regulatory bodies will adapt their policies to drive PM in the NDD industry by expediting regulatory pathways, enabling adaptive clinical trial designs and payor coverage models.

Scope of Analysis

• This research service provides an overview of the global precision neurodegenerative disease (NDD) industry, including analysis of industry participants and trends shaping the uptake of innovative therapeutics and platforms in the NDD landscape.
• The study covers the ongoing dynamics of precision health (PH) applications in pharma, including discovery and development solutions and services, targeted therapeutics, and monitoring and patient support solutions.
• The research service identifies the most prevalent and emerging business models helping industry stakeholders enhance their competitiveness, service offerings, and geographic patient outreach and address challenges that lead to inadequate patient access.
• The study highlights the primary market drivers and restraints, partnerships, and present and future market trends affecting the NDD market’s growth.
• The study provides industry use cases for different diseases and brief insights into some game-changing companies that are developing disruptive technologies and drugs for NDDs.
• The report provides emerging growth opportunities for the NDD market based on clinical needs, use cases, business models, predictive care, market access strategies, and technology trends.

Industry Definition and Segmentation

NDDs involve the progressive deterioration of the peripheral or central nervous system’s (CNS) structure and function because of nerve cells’ gradual loss of function and eventual death.

Primary NDDs include AD, PD, Huntington’s disease (HD), and amyotrophic lateral sclerosis (ALS). Among these, AD and PD are the most prominent.

The NDD industry encompasses all aspects of PH applications in pharma, including R&D, treatment, and personalized management of AD and PD.

Alzheimer's Disease (AD)

• Incurable and progressive
• Type of dementia
• Affects language, thinking, and memory
• Severely impairs the ability to carry out daily activities
• Risk factors: Psychotic disorders at an early age (a strong risk factor for dementia/AD), age, and genetics/heredity

Parkinson’s Disease (PD)

• Incurable and progressive movement disorder
• Involves tremors and stiffness in the limbs or the trunk of the body, bradykinesia (slowing down of spontaneous and automatic movements), and postural imbalance
• Risk factors: Age, being male (higher predisposition), heredity, exposure to pesticides, and psychotic disorders

Growth Drivers:

• Increased Prevalence of NDDs

  The increased prevalence of NDDs propels the demand for more effective medicines. The aging global population and longer life expectancy contribute to the growing incidence rate. The increase in NDDs promotes more drug innovations by pharmaceutical companies, as the field still lacks disease-modifying drugs, and current therapies focus only on limiting symptom progression without impacting the underlying disease mechanism, driving the search for more targeted and disease-modifying drugs.

• Advancements in Omics and Biomarker Research

  Advancements in omics (genomics and proteomics), gene editing, and biomarker-based research have uncovered unique mutations associated with NDDs, improving understanding of NDDs' genetic predisposition. Identifying disease-specific biomarkers has become a crucial step toward PM, as it allows the industry to develop more precise diagnostics, prognostics, and disease-progression monitoring solutions and evaluate patients' responses to treatments.

• Advancements in Neuroimaging and Data Analytics

  Advancements in neuroimaging techniques and data analytics using AI and Big Data allow the industry to understand unknown disease pathways in the human brain. AI, ML, and wearables are laying a strong foundation for PM to grow and enable more personalized solutions, improved data analytics, and better patient engagement with support from digital health platforms.

• Support from Global Regulatory Bodies

  Global regulatory bodies are offering support by acknowledging the pressing need for novel therapies for NDDs. For promising treatments, regulatory bodies frequently offer priority review designations, quicker approval processes, and accelerated review paths. Governments and regulatory agencies are providing financial opportunities, grants, and incentives that promote R&D in the NDD field.

• Public–Private Partnerships and Collaborations

  Public–private partnerships (PPPs) and the NDD industry’s collaborations with academia and advocacy organizations are building awareness through advocacy, knowledge sharing, and driving GWASs, which requires harmonized and appropriately diverse data sources. Public and private organizations are increasing data availability and supporting research collaboration.

Growth Restraints:

• Current therapeutic research uses a 1-size-fits-all approach, which is insufficient and faces challenges because of NDDs’ heterogeneous disease progression. The industry has a significant shortage of genomic data sets and tools that include the growing body of research on ancestral diversity in genetics. Access to well-powered genetic research and functional assays in varied ancestries is essential to quantify and remove biases, even in sophisticated models that rely on ancestry databases, which is crucial for precise target identification. For example, NDDs such as frontotemporal and vascular dementia lack sufficiently powered and accessible genetic data, which limits drug discovery
• Reimbursement policies for treating NDDs have limitations and deter people from obtaining treatment. Insurance coverage and reimbursement vary widely and may only cover a small patient group. The high costs associated with precision therapies can hinder market expansion and treatment compliance. Establishing reimbursement guidelines for precision treatments is difficult, and policies might not cover the entire cost of personalized treatment.
• The failure rate in NDD drug development remains very high. Drug development requires substantial preclinical research and can have many trial dropouts because of adverse effects, complex and difficult-to-measure endpoints, lack of precise biomarkers, and variability in disease presentation. Slow NDD progression often leads to long trial durations and high development costs, which can deter pharmaceutical companies from investing in drug R&D because of the uncertainty and risk involved. Additionally, the need to demonstrate NDD therapies’ safety and efficacy during an extended period to satisfy regulatory agencies has resulted in more stringent criteria and additional data point requirements. Navigating these complex regulatory pathways and approvals is time consuming.
• Establishing centralized data repositories for NDD research is difficult because of regulatory constraints, such as the General Data Protection Regulation (GDPR) and prohibitions on omics data sharing. These difficulties impede international collaborative research networks and increase the complexity of data access, standardization, and compliance (e.g., the rules around sharing neuroimaging data). Because NDD data are sensitive, entities must be careful when handling consent and data subject rights because they present ethical and privacy issues. Compliance requirements could make it more difficult for smaller groups to contribute to centralized data repositories.