The next twelve months represent a stress test for Parkinson’s research. We are moving past the theoretical phase of precision medicine to start to determine whether targeting genetic pathways translates to human efficacy.
By this summer we should know the results of two pivotal studies. The LUMA (BIIB122) study serves as the primary bellwether for the LRRK2 hypothesis, and Bial is set to read out Phase 2 data for BIA 28-6156, a first-in-class allosteric activator of GCase. Success in these primary endpoints would validate the industry’s pivot toward genetic targeting.
However, a structural risk remains. Is our current trial infrastructure—still reliant on the MDS-UPDRS—sensitive enough to detect a significant enough signal, or are we once again bringing a ruler to a quantum physics fight?
The Past
“The farther backward you can look, the farther forward you are likely to see.”
— Winston Churchill
Below is a breakdown of data from a pivotal study that covered all trials in PD from 1999-2019: Parkinson’s Disease Drug Development Since 1999.
The history of Parkinson’s drug development from 1999 to 2019 reveals a stark reality: out of 152 distinct compounds tracked across 357 clinical trials, the failure rate stands at 85.1%. While repurposed drugs—those already approved for other conditions—saw a moderate success rate of 21.4%, novel therapies struggled significantly, with only 6.7% reaching approval. These figures underscore a historical “bottleneck” where promising early-stage research frequently failed to translate into effective, approved treatments for patients.
A critical lesson from these decades of research is that our traditional trial infrastructure may be fundamentally misaligned with the biological complexity of the disease. By relying on broad patient populations and subjective measurement tools like the MDS-UPDRS, the field struggled to detect meaningful disease-modifying signals amidst the clinical noise. This era of high-stakes failure has catalyzed the current strategic pivot away from generalized neuroprotection toward precision medicine and the targeting of specific genetic pathways like LRRK2 and GBA.
The Present
The following data was derived from: Parkinson’s Disease Drug Therapies in the Clinical Trial Pipeline: 2024 Update. Look for the 2025 Update coming soon.
Total Active Trials: 136
- Phase 1 (Early Stage): 30% (Approx. 41 trials) — Testing for safety and dosage.
- Phase 2 (The Bottleneck): 58% (Approx. 79 trials) — Testing for efficacy; this large volume creates a significant demand for funding as well as trial participants.
- Phase 3 (Final Stage): 12% (Approx. 16 trials) — Large-scale trials intended to confirm efficacy and safety for regulatory approval.
For more on the current pipeline see this video from NoSilverBullet4PD titled: Parkinson’s research takeaways from 2025 and research results to look for in 2026 by Dr. Simon Stott. Below are the three key takeaways from that video.
GLP-1 Agonist Setbacks: Major phase 3 clinical trials for GLP-1 receptor agonists (such as exenatide) failed to demonstrate any difference compared to placebos, contradicting earlier phase 2 data and forcing researchers to reassess drug brain penetrance and patient stratification [06:33].
Adaptive Trial Infrastructure: Parkinson’s research is transitioning to Multi-Arm Multi-Stage (MAMS) trial platforms, which accelerate development by continuously testing multiple investigational drugs against a single shared placebo group [13:41].
Limits of Broad-Immunosuppression: The field is moving away from generalized neuroprotection toward targeted therapies addressing specific biological pathways (e.g., LRRK2 inhibitors and GCase activators), driven by the recognition that Parkinson’s is a collection of distinct sub-diseases requiring genetic stratification [46:32].
For more on the present state of trials in Parkinson’s disease Kevin McFarthing’s The Hope List has been an indispensable resource.
The Future
The graph Below depicts projected phase 2 & 3 trials in PD set to read out over the next few years…
Before I get into the key takeaways from the above graph here is an overview of which companies sponsor which drugs in development…
Key Takeaways:
- Concentration of Readouts in 2026: A significant number of phase 2 and phase 3 trials are scheduled to conclude in 2026. This includes key data on LRRK2 inhibition (BIIB122), inflammation (SNT-4728), and cognitive impairment (SAGE-718).
- Regulatory Decisions for Novel Delivery Systems: 2026 is also a pivotal year for the approval of new delivery methods for existing therapies. Specifically, regulatory decisions are expected for subcutaneous levodopa infusions (ND0612) and the once-daily D1/D5 agonist Tavapadon.
- Transition to Biologics and Gene Therapy (2027–2028): While near-term data focuses on small molecules, the timeline for 2027 and 2028 shifts toward the readouts of advanced modalities. This includes phase 2 results for cell therapies like Bemdaneprocel and gene therapies such as AB-1005 and AAV-GAD.
- Follow-up on Subgroup Efficacy: Several trials are moving into open-label extensions or further phases despite mixed primary results. This indicates an industry focus on identifying specific patient subgroups—such as fast-progressors—who may derive more benefit from therapies like Prasinezumab than the general trial population.
Deep Dive: The GBA-PD Landscape…
The 2026 Clinical Horizon
The GBA sector is nearing some results that could have broad implications for the entire Parkinson’s field. The ACTIVATE trial for BIA 28-6156—a once-daily GCase activator—is in final stages, with topline data expected by mid-2026. Simultaneously, early data from modulators like GT-02287 has shown a reduction in a key substrate known as Glucosylsphingosine (GluSph), providing the first direct evidence that these molecules are successfully engaging their targets in the brain.
A Global Collaborative Front
The fight against GBA-linked Parkinson’s is a global effort unified by an “Open Science” model. This collaborative framework—linking many of the foundations and institutions involved—ensures that genetic, imaging, fluid and biomarker data are shared freely. This model allows for pre-competitive data sharing on GBA natural history, which lowers the cost of entry for new biotech firms entering the space.
However, we must be clear-eyed about the limits of this framework. “Open science” and pre-competitive collaboration routinely evaporate the moment a viable molecule enters Phase 2. Once target engagement is proven and IP protection takes priority, this collaborative spirit is immediately replaced by competitive siloing, directly contributing to the geographic trial cannibalization and data hoarding that is currently choking the mid-stage pipeline.
Thankfully, attempts are being made to break those silos such as Cure Parkinson’s phase 3 trial of Ambroxol which may be pioneering a new way forward for how to run these kinds of trials.
Expanding the GBA Lens
Furthermore, the recent discovery of a novel African GBA1 variant (found in ~40% of PD cases in the affected area and contrasts with the prevalence of GBA mutations in European populations (typically 5-15%) has expanded the research focus, opening up a promising future for precision therapies, one that is inclusive of global genetic diversity.
The Neuromodulation Parkinson’s Landscape
Key Takeaways
- Total Market Valuation: The global DBS market alone is estimated at $1.61 Billion in 2026, projected to reach ~$3.0 Billion by 2030 as adaptive technologies become standard.
- The “Adaptive” Standard: 2026 marks the year where “sensing” is no longer a premium feature but a baseline requirement. Medtronic’s aDBS (Adaptive Deep Brain Stimulation) is the current gold standard, allowing the device to auto-adjust stimulation levels based on the patient’s own brain signals (LFP).
- The Rise of FUS (Focused Ultrasound): Insightec has successfully transitioned FUS from a “last resort” for Essential Tremor to a promising PD therapy. Their 2025/2026 expansion into staged bilateral treatments (treating both sides of the brain without surgery) is a significant competitive threat to traditional DBS for tremor-dominant patients.
Pipeline Vulnerabilities
How We Measure
The most critical, underappreciated risk facing the current wave of Parkinson’s disease-modifying therapies may be methodological rather than biological. We are currently attempting to validate molecularly targeted precision medicines using a clinical observation scale designed in the 1980s. This misalignment between our therapeutic sophistication and our measurement infrastructure creates a significant structural liability for the entire field.
The current gold standard, the MDS-UPDRS (Movement Disorder Society-Unified Parkinson’s Disease Rating Scale), is inherently ill-suited for detecting disease modification. While therapies with obvious effect do pierce the noise; the danger is that we are discarding therapies with modest but meaningful benefits because our tools act as a high-pass filter that only catches treatments that have profound symptomatic benefit.
The MDS-UPDRS is a subjective clinical test designed to assess symptomatic severity at a single point in time. It was not engineered to measure the subtle preservation of neuronal health over 12 to 18 months. In PD, motor symptoms fluctuate based on fatigue, stress, and timing of medication. This inherent variability creates substantial noise in clinical trial data. For a trial to succeed, the therapeutic signal must be stronger than the measurement noise. By relying on an instrument with high variability and insensitivity to subtle progression, we are stacking the statistical deck against success. A drug that successfully slows underlying neurodegeneration by 20-30% may fail to show a statistically significant separation on the MDS-UPDRS against a noisy placebo background.
However, there may be a solution in continuous passive wearables that replace infrequent clinical snapshots with continuous, longitudinal monitoring. While legacy scales like the MDS-UPDRS are “blunt instruments” masked by stochastic noise and symptomatic variability, wearables aggregate thousands of real-world data points to filter out this background. This high-resolution approach enables tremor, dyskinesia, gait and fall detection with much greater fidelity than even the best physician could possibly capture. The infrastructure needed to bypass the MDS-UPDRS already exists at scale, it’s time trial sponsors ask regulators to use them as primary endpoints.
Who We Measure
The visual distribution of the current Phase 2 and Phase 3 pipeline below reveals another clinical vulnerability that is just as dangerous as the methodological bottlenecks of legacy endpoints.
The complete absence of mid- and late-stage clinical development across South and Central Asia, Africa, and South America represents a glaring failure of both global health equity and scientific rigor. While the industry fiercely competes for a narrow, largely homogenous demographic in the West, it ignores regions with massive, genetically diverse populations that carry a profound unmet clinical need.
The lack of advanced trial infrastructure in the Global South is often cited as the barrier, but accepting this as a permanent constraint is a short-sighted excuse. By excluding these populations, the industry is not just failing these patients; it is actively blinding itself to novel disease presentations and genetic variants—such as the highly prevalent African GBA1 mutation—that could unlock entirely new therapeutic pathways. We can no longer claim to be pursuing precision medicine while systematically excluding the majority of the human genome from our clinical trials.
What We Measure
While replacing legacy endpoints and expanding geographic trial footprints would fix the mechanics of our clinical trials, these operational upgrades cannot save us if the biological premise we are testing is fundamentally flawed. The current pipeline remains overwhelmingly anchored to the “toxic accumulation” dogma—specifically, targeted protein clearance. We must confront the existential risk that the field is simply chasing the wrong underlying hypothesis by ignoring two critical dimensions of the disease.
First, there is a glaring failure to advance protein replacement strategies. The industry treats Parkinson’s as a garbage disposal problem, aiming to clear out aggregated proteins while ignoring the profound loss of normal protein function that may be the primary driver of cellular failure. Restoring these critical proteins is rarely tried because the field has been betrothed to the idea that aggregates are toxic for decades.
Second, this narrow molecular fixation ignores the growing evidence pointing toward Parkinson’s functioning fundamentally as an oscillopathy—a disease driven by abnormal neural network oscillations and the degradation of synchronized brain rhythms. Intervening in these dynamic electrophysiological networks with pharmacology is more difficult to model and measure than static protein targets, leading the industry to bypass the circuits entirely.
The persistent dominance of the “toxic accumulation” dogma is not merely a theoretical bias; it is physically hardcoded into the infrastructure of our preclinical models and clinical assays. The vast majority of standard biological assays deployed in Parkinson’s research—such as the highly touted RT-QuIC (Real-Time Quaking-Induced Conversion) assay for cerebrospinal fluid—are engineered specifically to detect and amplify misfolded alpha-synuclein aggregates. Consequently, our foundational disease models, primarily transgenic mice engineered to overexpress human alpha-synuclein, exist almost exclusively to validate drugs that clear these aggregates. This creates a deeply entrenched, self-fulfilling feedback loop in drug development: the field defines the pathology by the presence of aggregates, builds diagnostic tools solely capable of measuring those aggregates, and then advances only the pipeline candidates that successfully reduce them in the clinic. If the primary driver of Parkinson’s is actually a prior loss-of-function, synaptic energy failure, or a network oscillopathy, the current clinical testing infrastructure is structurally blind to it. We are not necessarily measuring disease modification; we are simply measuring a drug’s ability to perform the highly specific, isolated clearance task that our assays were engineered to reward.
Continuing to deploy billions of dollars into trials that measure the wrong biology, in a narrow band of people, using obsolete rulers may prove to be a dereliction of capital. To avoid repeating the failure rate of the past two decades, drug developers may need to abandon the comfort of legacy metrics while finding a way to remove their geographic and biological blinders. The pivot to precision medicine demands a commensurate leap in precision infrastructure; until the field embraces continuous objective measurement, expands its geographic footprint, and critically re-evaluates its foundational biological dogmas, disease-modifying therapies might remain a theoretical promise rather than a clinical reality.
Note: Graphs and images above, unless otherwise indicated, were created using Gemini