Designing a SAD/MAD Study with EEG Endpoints
Defining the Transition from Single to Multiple Dosing in Phase I Trials
Single Ascending Dose (SAD) and Multiple Ascending Dose (MAD) studies form the backbone of First-in-Human (FIH) programmes. The decisions made here determine how quickly and how successfully a new asset can progress.
At this stage, the priority is clear: identify a dose range that is both safe and biologically active. But the real challenge is reducing uncertainty early, before time, cost, and patient exposure escalate.
This is where integrating a smart early-phase strategy into First-in-Human (FIH) programmes accelerates development. If not, your asset risks encountering downstream barriers and missing approval endpoints.
You may be asking, “what can I integrate that is cost effective and operationally turnkey, providing high-resolution insight without adding to our internal management burden?”
This article will explain how the non-invasive imaging technique electroencephalography (EEG), can provide the validity and integrity needed to overcome such barriers.
EEG as a Strategic Tool in Early-Phase CNS Development
EEG provides a direct, real-time measure of brain activity. But its value in early phase development is not just technical, it is strategic. EEG helps bridge the clinical decision gap by showing whether a drug is engaging its CNS target before conventional clinical endpoints register any effect.
We provide a plug-and-play service that integrates directly with your existing CRO’s operations. By providing the specialised equipment and neuroscientific expertise in-house, we remove the need for sponsors to manage additional vendors or for CROs to develop internal EEG capabilities.
EEG delivers:
- Objective evidence of CNS target engagement
- Early identification of pharmacological activity
- Clear, interpretable dose–response relationships in the brain
- High-resolution insight into rapid functional changes
Where EEG Moves from Useful to Essential
EEG provides essential insights into participant brain function, offering critical data to show effects faster than clinical symptoms can be measured.
This is particularly powerful when:
- Functional changes occur rapidly (milliseconds to seconds)
- Clinical endpoints are slow, subjective, or variable
- There is a disconnect between pharmacokinetics (PK) and observable outcomes
- Disease biology is driven by abnormal neural activity
High-impact indications include:
- Epilepsy
- Sleep Disorders
- Encephalopathy
- Alzheimer’s disease and other dementia's
- Major Depressive Disorder and anxiety
- Psychiatric disorders; Schizophrenia, PTSD, Bipolar disorder
- Many more
In these areas, EEG provides early, more objective insight than traditional endpoint methods. Supporting faster and more confident decisions.
EEG in SAD: Early Signal Detection That Drives Decisions
SAD studies answer a fundamental question: what happens after a single dose?
EEG provides immediate visibility into pharmacodynamic effects from first exposure, well before clinical symptoms emerge. Allowing exact dose measurements to be correlated to an optimal clinical outcome before any other trial programme is initiated.
More specifically, using EEG in your SAD study unlocks:
- Early identification of CNS activity and proof of pharmacology
- Clear dose–response relationships to guide escalation
- Detection of possible central side effects (e.g. sedation or stimulation)
- An integrated assessment of safety, tolerability, and pharmacokinetics (PK)
The integration of EEG into your SAD trial ensures an instant confirmation of whether a compound is behaving as expected.
By building EEG collection directly around your planned PK workflow, we ensure that high-quality pharmacodynamic data is captured in parallel with blood draws. This minimises disruption to the clinical site and ensures that target engagement is correlated with actual drug exposure in real-time.
Directly providing the robust data needed to validate a SAD phase I trial and move it into its next phase with integrity.
EEG in MAD: Deep Insights into Exposure
MAD studies move closer to real-world use testing of your compound, shifting the focus of your trial outcomes from safety measures at a single dose, to monitoring the effects of sustained exposure and the consistency of drug effects and benefits.
The fundamental question then becomes: Does the drug maintain its CNS activity over time?
EEG provides:
- Tracking of neurophysiological changes across repeated dosing
- Identification of sustained engagement or emerging tolerance
- Confirmation of steady state pharmacodynamic effects
- Insight into drug accumulation and longer-term tolerability
This is where early signals are validated confidently when using EEG, and where a dose strategy becomes validated moving forward.
Adaptive Trial Design: Faster Decisions, Lower Risk
What about Adaptive trial designs? Does EEG only work in traditional SAD or MAD trials? What if we’re using an adaptive trial design to reduce time and cost? Will EEG add to that?
If you are familiar with some of the commonly relied upon adaptive trial methods, such as the Continual Reassessment Method (CRM), Bayesian Logistic Regression Models (BLRM), or the Escalation with Overdose Control (EWOC) - you’ll be aware of how these enable more accurate and efficient dose selection compared to traditional rule-based designs (Marchenko et al. 2014). However, decision makers will also know how these models are only as powerful as the data informing them.
EEG clearly strengthens traditional trial design models - however, it also provides the bandwidth for high-quality data to fit into your adaptive trial design models. Providing the data validity and integrity needed to act on emerging signals.
Here, the advantage of incorporating EEG into your clinical trial is clear. Whether in a SAD, MAD, or SAD/MAD transition study - within a traditional or adaptive trial programme - EEG provides robust, high-quality data outputs that support confident decision-making early in development.
When integrated into SAD trials:
- Maximum tolerated dose (MTD)
- Early pharmacological activity
- Dose-limiting toxicity (DLT)
When integrated into MAD trials:
- Sustained target engagement
- Safety over repeated exposure
- A clear rationale for Phase II dose selection
When integrated into any trial programme:
- Real-time optimisation of dose escalation
- Early identification for capital preservation: pivot or persevere with confidence before high-cost Phase II investments
- Data-driven refinement of hypotheses
- Evidence-based adjustments between SAD and MAD phases
- Robust data to support adaptive and complex trial designs
- Reduced risk of patient exposure to ineffective or unsafe doses
- Clean and valid identification of the therapeutic window
- More efficient trial execution and resource utilisation
EEG is not just an additional endpoint measure, but a diverse decision-enabling tool within any trial programme.
Strengthening Your Regulatory Narrative
Regulators increasingly expect early-phase trials to provide clear, mechanistic evidence, not just safety data. EEG plays a critical role here. It provides regulators with objective evidence of CNS target engagement, supporting decision makers in key decision-making stages such as:
- Justification of dose selection
- Confidence in escalation decisions
- Reduced uncertainty before repeated dosing
- A stronger overall evidentiary package of your drug or compound
Sponsors can proactively address regulatory expectations while de-risking development. The outcome is a more efficient development pathway, reduced risk, and greater confidence in what comes next.
Final Thoughts
Integrating EEG into your early phase trials, regardless of design provides faster, clearer insight into CNS activity and drug performance. Supporting your regulatory narrative with objective evidence and expert interpretation, turning early signals into actionable decisions that drive your asset’s value.
Connect with us to explore how integrating objective neurophysiological evidence into your SAD/MAD trial can provide a clear rationale for Phase II dose selection.
References
Bowalekar, S. (2011) ‘Adaptive designs in clinical trials’, Perspectives in Clinical Research, 2(1), pp. 23–27. Available at: https://doi.org/10.4103/2229-3485.76286
Gad, S.C. (2013) ‘Safety and regulatory requirements and challenge for CNS drug development’. Neurobiology of Disease, Science Direct, pp. 39-46. Available at -https://doi.org/10.1016/j.nbd.2013.09.017
Marchenko, O.et al. (2014) ‘Adaptive clinical trials: Overview of early-phase designs and challenges’, Therapeutic Innovation & Regulatory Science, 48(1), pp. 20–30. Available at: https://doi.org/10.1177/2168479013513889
Monllor, P. et al. (2021) ‘Electroencephalography as a non-invasive biomarker of Alzheimer’s disease: A forgotten candidate to substitute CSF molecules?’, International Journal of Molecular Sciences, 22(19), p. 10889. Available at - https://doi.org/10.3390/ijms221910889
Pankevich, D. et al. (2014) ‘Improving and accelerating drug development for nervous system disorders’, Neuron, 84, pp. 546–553. Available at: DOI:10.1016/j.neuron.2014.10.007
Preller, K.H. et al. (2024) ‘Neuroimaging biomarkers for drug discovery and development in schizophrenia’, Biological Psychiatry, 96(8), pp. 666–673. Available at - https://doi.org/10.1016/j.biopsych.2024.01.009
Shen, J. et al. (2019) ‘Design and conduct considerations for first-in-human trials’, Clinical and Translational Science, 12(1), pp. 6–19. Available at: https://doi.org/10.1111/cts.12582
Suhara, T. et al. (2017) ‘Strategies for utilizing neuroimaging biomarkers in CNS drug discovery and development: CINP/JSNP working group report’, International Journal of Neuropsychopharmacology, 20(4), pp. 285–294. Available at - https://doi.org/10.1093/ijnp/pyw111

