ADC First-in-Human (FIH) Dose Selection: Designing FIH Studies for Success

Unlike traditional chemotherapy or monoclonal antibodies, ADCs are built from three interconnected components:

• An antibody that targets tumor cells
• A potent cytotoxic payload
• A linker that connects the payload to the antibody

Each element both separately and through their interactions can affect both safety and efficacy.

Common development challenges include variable target expression across tumors, limited tumor penetration, variability in drug–antibody ratio (DAR), premature payload release, off-target toxicities, and unintended cellular uptake. Because these variables operate simultaneously and ADCs have narrow safety margins, dose optimization becomes particularly complex.

For many ADCs, increasing dose does not proportionally increase tolerability. More drug does not necessarily mean more benefit without additional risk. That’s why FIH dose selection must focus on exposure, how much drug reaches the systemic circulation, rather than simply scaling doses from animals.

Understanding what exposure level drives efficacy and what exposure level drives toxicity is central to ADC development strategy. As was highlighted in the webinar, “Dose alone doesn’t tell the full story. It’s the exposure–response relationship that ultimately informs safe and effective dose selection.”

Sponsors seeking a more detailed understanding of ADC pharmacokinetics from noncompartmental analysis through population PK approaches can explore our discussion on applying NCA and PopPK to ADCs.

Before entering the clinic, nonclinical ADC programs should evaluate the conjugated ADC (toxicity testing, toxicokinetics and safety pharmacology) and any novel components (e.g. cytotoxic payload) in safety pharmacology, ADME and/or toxicity testing.

A relevant preclinical species is typically required. If cross-reactive species are unavailable, additional laboratory and computational approaches may be necessary.

The cytotoxic payload often drives safety findings. Novel payloads may require additional safety assessment beyond what is required for the conjugated ADC.

Because ADCs combine biologics and small molecules, development strategies often bridge multiple regulatory guidelines. Programs must be tailored to the construct and indication.

Traditional rules of thumb still apply such as fractions of highest non-severely toxic doses observed in animals, but they should be complemented with translational modeling to refine predicted human exposure.

And this is where modeling shifts from helpful to essential.

Industry analyses show that programs incorporating robust preclinical modeling achieve significantly higher probabilities of reaching clinical proof of mechanism, reinforcing the value of structured, data-driven FIH strategy.

Regulatory agencies increasingly expect quantitative justification of FIH dose selection decisions, especially for complex modalities like ADCs. Empirical escalation alone is no longer enough. As Piet emphasized, “Regulators want to understand not just what dose you chose, but why, and modeling provides that scientific rationale.”

For a deeper look at how mechanistic modeling addresses translational uncertainty in ADC programs, explore our insights on mechanistic modeling to meet challenges in ADC development.

Modeling provides a structured way to:

• Anticipate human exposure
• Evaluate safety margins
• Simulate likely toxicities
• Refine escalation strategy

For ADCs, this is particularly important because safety margins are tight, and translational uncertainty is high.

Advanced modeling platforms can integrate tumor biology, pharmacokinetics, DAR, and toxicity drivers. This allows sponsors to narrow starting dose ranges, reduce unnecessary patient risk, avoid subtherapeutic dosing, and design smarter escalation plans.

In short, it shifts FIH planning from reactive to predictive.

The ADC field is expanding into bispecific constructs, antibody fragments, dual payload approaches, immune-activating payloads, and protein degraders. As molecular architecture becomes more sophisticated, translational uncertainty grows.

The underlying principles remain consistent:

• Understand the components
• Understand how they interact
• Quantify safety margins
• Align with regulators early

But the need for structured, model-informed strategies becomes even more critical.

Designing a successful ADC first-in-human study requires:

1. Early evaluation of therapeutic window
2. Scientifically justified starting dose
3. Integrated safety assessment
4. Predictive modeling
5. Early regulatory alignment

As ADC pipelines expand and competition intensifies, thoughtful, data-driven FIH strategy is no longer optional; it is a competitive advantage.

To learn more about ADC FIH dose selection and translational strategy, watch our latest webinar.