At Stanford, our BPAN research initiative is built around three complementary, high-impact pathways. Each pathway tackles a different part of the puzzle - from understanding underlying biology to discovering and testing potential treatments - so we can move in parallel and accelerate progress.
Pathway 1: Biomarker Discovery
Goal: Find early warning signs and measurable indicators of disease progression in BPAN.
Why it matters:
We need biomarkers to predict how severe the disease may become in each child.
Biomarkers help us monitor whether treatments are working.
They can improve patient stratification in clinical trials (so children receive the right treatments at the right time).
What we’re doing:
Generating patient-derived neurons (from blood or skin cells) to model BPAN in lab settings.
Developing assays using gene expression, metabolic profiling, imaging, EEG, or other technologies to uncover signatures of dysfunction (for example, in autophagy, lysosomal, or iron homeostasis pathways).
Validating biomarkers in both cell and animal models to ensure they reliably reflect what’s happening in people.
Pathway 2: High-Throughput Drug Screening
Goal: Quickly identify drugs or compounds that can correct or slow down BPAN disease processes.
Why it matters:
There are no approved treatments to stop or reverse BPAN.
Screening large libraries (including existing drugs) speeds discovery and can find repurposing opportunities.
Effective preclinical testing allows us to prioritize the most promising candidates for further study.
What we’re doing:
Setting up automated screening platforms (cell-based and high content imaging) using BPAN models (neuron/astrocyte/other relevant cell types).
Testing compounds for their effects on key cellular deficits seen in BPAN: clearance of protein aggregates, iron accumulation, oxidative stress, autophagy, mitochondrial dysfunction.
Selecting top hits from screens to test in animal models and more complex patient-derived cell systems.
Using machine learning / computational approaches to analyze screening data more deeply and predict which compounds may translate to human benefit.
Goal: Develop organoid (3D) and other advanced human-derived models that accurately represent brain tissue, to improve preclinical testing and translational potential.
Why it matters:
Traditional cell culture models may miss complex interactions present in brain tissue. Organoids can better mimic human neurodevelopment and disease.
Organoids allow testing of therapies in human-relevant contexts, bridging the gap between cells in dishes and animal models.
These models can also help study how BPAN begins to affect brain development and how interventions might correct early pathology.
What we’re doing:
Growing BPAN patient-derived brain organoids, including midbrain and cortical regions, to study disease onset and progression.
Using organoids to test drug responses, biomarker read-outs, and more nuanced phenotypes (structural, electrophysiological, metabolic).
Combining organoid data with imaging, RNA sequencing, and other -omics to understand if therapies are having desired effects.
Refining organoid protocols to ensure reproducibility, scalability, and suitability for drug screening.
Key Milestones & What We’ve Achieved So Far
Established BPAN patient-derived iPSC neuronal models that show disease-relevant phenotypes (autophagy defects, iron accumulation, ER stress).
Conducted medium-throughput screening in vitro, identifying compounds that partially correct disease-associated features.
Initial biomarker candidates are under validation.
Some early organoid work underway to scale models and test multiple compounds in more complex systems.
Our progress across these three pathways – biomarker discovery, drug screening, and organoid modeling – represents hope and momentum for children affected by BPAN. But this is just the beginning.
