Our science

We utilize patient biology, biomarker-based screening, and advanced data analytics to de-risk clinical translation.

Illustration of a dense network of glowing blue neurons and synapses

Patient inspired, ML/AI-powered

A groundbreaking discovery engine to facilitate clinical translation and accelerate CNS drug development

Our proprietary platform combines human patient iPSC-derived models of brain disease, large-scale biology, and the computational tools of deep learning and network medicine to identify therapeutic candidates that halt, prevent, or reverse critical molecular events that lead to synaptic network dysfunction and neurodegeneration.

Fluorescence microscopy image of a patient-derived brain organoid, with neurons glowing orange and green
Patient-derived brain organoid, fluorescence microscopy. Image: María Baeza Trallero & Martin Berryer.

The platform

Patient-derived iPSC organoids

Leverage an understanding of human disease biology to identify clinically translatable disease phenotypes.

Biomarker-based screening

Identify, validate, and de-risk targets and hits across multiple biological endpoints.

Value creation

Discover and develop best-in-class novel and repurposed drugs.

AI/ML powered

Integrating deep learning and network medicine to usher in a new era in CNS drug discovery.

Platform features

  • Reproducibly capture human disease pathophysiology in a high-throughput format.
  • Amenable to both phenotypic and target-based screening.
  • Drive compound discovery with clinically translatable disease endpoints.
  • Rapid discovery of first- and/or best-in-class therapeutic candidates.
Animated fluorescence recording of a brain organoid, its activity flickering in red and yellow on a blue background
View of an organoid using Fluorescence Imaging Plate Reader, or FLIPR: a technique used to study the effect of compounds on cells during drug screening.

Our approach

Patient inspired

Patient-inspired drug discovery and development involves actively engaging and incorporating patient perspectives throughout the process, aiming to create more effective and patient-centric treatments that address real-world needs and challenges.

AI/ML-powered

AI/ML-powered drug discovery and development involves using artificial intelligence and machine learning to analyze vast amounts of data, predict drug efficacy, identify potential candidates, and optimize clinical trials, ultimately accelerating the process of finding new and effective treatments for improved patient outcomes.

Currently focused on drug discovery for Parkinson’s disease (PD)

  1. 01

    PD pathophysiology

    Human PD patient-derived midbrain organoids recapitulate key elements of PD pathophysiology, including dopamine neuron degeneration and synaptic dysfunction.

  2. 02

    Genetic entry points

    Utilize familial PD genetic entry points into dysfunctional autophagy/lysosomal and mitochondrial/oxidative stress pathways for expansion into the sporadic PD population.

  3. 03

    Underlying disease processes

    Phenotypic screening of targeted small molecule libraries with clinically translatable endpoints to identify compounds that ameliorate the underlying disease processes.

  4. 04

    Design better clinical trials

    Identify and define key molecular signatures to refine clinical trial endpoints and patient selection.

Foundation model-based organoid network browser

Explore BrainStorm’s organoid network browser, an interactive tool hosted on a separate server.

About the organoid network browser

Get in touch

Talk to us about our precision neuroscience platform, our Parkinson’s disease program, or working with the BrainStorm team.

Robert.fremeau@brainstormtherapeutics.org818-584-4788

Get in touch
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