ARPA-H has launched EVIDENT, a $100M program to build quantitative measurement systems and data infrastructure for mental health, linking rapid-acting treatments to objective, longitudinal clinical evidence.

China is assembling a vertically integrated neurotech stack, with state-backed companies advancing invasive BCIs, EEG platforms, neuromodulation, and imaging into structured clinical programs at growing scale.

Machine Medicine is building a data and AI operating system for neurotech, using tools like video, wearables, and machine learning to make neurological symptoms measurable and treatments more precise.

A UT Dallas team built a small neuromorphic prototype where learning occurs directly in hardware via magnetic synapses, showing a path toward energy-efficient, on-device learning inspired by the brain.

Rune Labs is translating passive digital data into clinically actionable insights, using neuroscience-grounded validation to make digital phenotyping work in real-world neurology.

Alto Neuroscience has raised $50 million and aligned with the FDA to accelerate its depression program, positioning biomarker-guided patient selection as a practical tool for late-stage psychiatric drug development.

Neurodegenerative diseases unfold over decades, but our data is fragmented and short-term. New computational models are beginning to reconstruct long-term disease timelines, with implications for trials, neurotech, and precision care.

From academic lab work to biotech leadership, a new generation of founders is rethinking how brain drugs are discovered. Patient-derived organoids and AI are beginning to reshape what’s possible in CNS therapeutics.

CRISPR has become more than a gene-editing tool. In neuroscience, it is now used to modulate gene expression, build human brain models, trace development, and uncover disease pathways with unprecedented precision.

As neuroscience pushes toward more naturalistic and long-term experiments, new classes of neural interfaces are expanding what can be measured, manipulated, and integrated inside the living brain.

Parkinson’s disease unfolds continuously, yet care remains episodic. By turning everyday wearables into sources of clinical signal, a new approach is emerging that reframes how neurological disease is measured, tracked, and managed.

Understanding how drugs act on the living brain has long been a bottleneck in neuroscience. Advances in neuroimaging are beginning to make drug effects observable earlier, more precisely, and with far greater confidence.

Psychiatric diagnosis remains largely behavioural, despite growing biological insight. Emerging biomarkers in autism and schizophrenia hint at more precise, individualised care, but translation into clinical practice has proven difficult.