Neuroplasticity in Action: Reducing Risk in Early-Phase CNS Trials 

Is Your Drug Actually Working in the Brain? 

Early-phase central nervous system (CNS) trials are full of high-stakes decisions: dose selection, escalation, and whether to move forward at all. Yet many of these decisions are made without direct evidence that a drug is doing anything meaningful in the brain. 

That’s a major, and avoidable, risk. This is where synaptic plasticity changes the game. 

What is Synaptic Plasticity?  

Synaptic plasticity is the brain’s ability to adapt by strengthening or weakening connections between neurons. It underpins learning, memory, and behaviour, and critically, it is disrupted in most CNS disorders. 

Synaptic plasticity is not just a biological concept. It is: 

If your therapy is designed to act on the CNS, the key question becomes: can you prove early that it is modifying brain function? 

The Hidden Risk in Early-Phase CNS Trials 

Many trials still rely on indirect or delayed clinical endpoints, subjective symptom scores, long timelines, or unclear dose-response relationships. 

The result? 

You may be advancing compounds without knowing if they ever engaged the brain. 

Measuring Synaptic Plasticity: From Theory to Actionable Data 

Today, synaptic plasticity can be measured safely and non-invasively in early-phase trials using easily deployable technologies.  

Technologies such as Transcranial Magnetic Stimulation (TMS), Electroencephalography (EEG), Cognitive and physiological testing, and Quantitative Sensory Testing (QST) allow you to observe how the brain responds before and after intervention. 

This isn’t about adding complexity, it’s about adding clarity through modern technologies that improve your interpretation of variable outcomes and support data-driven decision-making.   

What Decisions Does This Enable? 

Measuring synaptic plasticity provides something early-phase CNS trials often lack objective, functional biomarkers of brain activity. 

This translates directly into better decisions for: 

When is this Approach Most Valuable? 

Not every trial requires these tools, but the need is high when: 

In these scenarios, not measuring brain response is a strategic blind spot. Using these technologies to measure synaptic plasticity can significantly strengthen the interpretability and impact of early-phase trial data. 

What Does “Measuring Plasticity” Actually Look Like? 

Different methods provide different insights into how the brain is responding. Synaptic plasticity is disrupted in many CNS disorders, and the nature of this disruption varies by condition. These differences inform which technologies, and which metrics, are best suited to monitor how a therapeutic intervention is affecting specific dysregulated plasticity pathways. 

These tools can be used independently or in combination across a broad range of CNS related disorders, including: 

TMS: Probing Brain Circuits Directly

TMS can measure changes in cortical excitability and inhibition: the key components of synaptic plasticity. 

Key signals include: 

EEG: Capturing Brain-Wide Activity 

EEG provides a system-level view of neural communication and timing. It helps to understand how synaptic plasticity affects whole-system function and broader patient outcomes. 

Relevant signals include: 

These metrics can help validate changes in synaptic plasticity. 

Cognitive and Physiological Testing: Translating Biology into Function 

These tests connect neural changes to functional outcomes. By comparing participant performance before and after drug administration, you can assess real-world effects of your intervention. 

This provides early insight into whether synaptic plasticity changes translate into meaningful outcomes. 

Key measures include: 

QST: Linking Plasticity to Sensory Processing

Particularly valuable in pain and neuroinflammatory conditions, QST reflects how the nervous system adapts to stimuli. These adaptive responses reflect underlying synaptic plasticity, making QST particularly valuable for assessing treatment effects in pain and neuroinflammatory conditions during early-phase development. 

Real-World Impact: From Signals to Decisions

This approach is already shaping smarter early-phase strategies.  

Example 1: Anti-Epileptic Drug Development (Ruijs et al., 2022) 

In a controlled Phase I crossover biomarker study, researchers used TMS and EEG to measure synaptic plasticity following drug administration. 

Key measures included Cortical excitability (MEP amplitude) and Inhibitory control through short intracortical inhibition (SICI) and long intracortical inhibition (LICI). 

Outcome: 
These measures acted as pharmacodynamic biomarkers, confirming that the drugs were modulating brain function and influencing synaptic plasticity, a sign of successful target engagement.  

Decision Impact: 
Enabled confident progression based on proof of mechanism, not just safety data. 

Example 2: Targeting NMDA Receptors (Wrightson et al., 2023) 

A compound designed to enhance synaptic plasticity was tested in healthy volunteers using a placebo-controlled crossover design with intermittent theta-burst stimulation (iTBS). 

Outcome: 
Clear increases in plasticity-related signals were observed with the drug versus placebo. 

Decision Impact: 

Regulatory Expectations are Shifting 

Regulators increasingly expect more than safety in early-phase CNS trials. They want: 

Synaptic plasticity measures provide exactly that. 

They help build: 

The Bottom Line: Better Signals, Better Outcomes 

Integrating synaptic plasticity into early-phase trials delivers three critical advantages: 

1. Risk Reduction: Identify ineffective compounds earlier 

2. Speed: Make faster, data-driven decisions