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Reflections on the New FDA Clinical Pharmacology Guidance for Antibody-Drug Conjugates

The new Clinical Pharmacology Considerations for Antibody-Drug Conjugates (ADC), Guidance for Industry, was issued by the US Food and Drug Administration (FDA) in February 2022. ADCs are targeted therapies that are designed to deliver cytotoxic payloads to cancer cells. The cytotoxic payload is attached to a monoclonal antibody (that is designed for binding to the target) through a linker.

The guidance provides a framework for ADC drug developers, particularly in the context of the cytotoxic small molecule drug or payload. The guidance covers many areas central to clinical pharmacology including bioanalytical methods, dosing strategies, dose- and exposure-response analysis, intrinsic factors, QTc assessments of proarrhythmic potential, immunogenicity, pharmacogenomics, and drug-drug interactions (DDIs).

Figure 1. Illustration of an antibody drug conjugate. From Sikorski, S.R.I.Q.R. The Clinical Landscape of Antibody-drug Conjugates. 2014

From an ADC point of view, the guidance shares insights on specific analytic moieties, including free and total antibody, free small molecule, linker, and pharmacologically active metabolite of small molecule. Whilst the guidance acknowledges the challenges related to dose adjustments based on intrinsic and extrinsic factors, many topics are consistent with how the agency has shared its feedback on individual programs and/or existing clinical pharmacology guidance.

Let’s reflect on a few key areas that may interest you.


The guidance is specific to analytes that sponsors should consider measuring depending on the phase of the drug development. For example, with first-in-human (FIH) studies, it prescribes that the ADC, its constituent parts, and its pharmacologically active metabolites, if any, should be measured. Later in development, the ADC, its constituent parts, and its pharmacologically active metabolites that are quantifiable in systemic circulation should be measured to inform exposure-response analyses. The guidance also provides provisions to support excluding measurements of ADC constituents or pharmacologically active metabolites in later development. Interestingly, the guidance provides some specificity on the systemic presence of the shed target. If that is deemed significant, that pre-supposes that the bioanalytical assays need to distinguish the target-unbound ADC from the target-bound ADC. While the agency’s guidance on this subject is meaningful, the confounding elements during ADC characterization in humans sometimes hinges on the presence of multiple molecular species, including the different drug-to-antibody (DAR) species. The dynamically changing nature of the mixture in vivo as well as various catabolites/adducts can complicate this analysis and makes developing quantitative assays very challenging because different DAR species might behave differently in the assays. When it comes to the presence of pharmacologically active metabolites (a metabolite that has pharmacological activity at the target receptor), it is unclear whether the metabolites in safety testing (MIST) guidance will apply.

Figure 2. ADCs are heterogeneous mixtures of molecules that differ in the number of small molecule drugs conjugated to a monoclonal antibody.


The guidance stipulates that the exposure-response analyses should be conducted for safety and efficacy with the ADC, its constituent parts, and pharmacologically active metabolites, if any, to support dose selection. Notably, in later development, the guidance stipulates that justification could be provided for not conducting exposure-response analyses with an ADC constituent part or pharmacologically active metabolites depending on certain situations.  It further states that if the antibody target is shed significantly into the systemic circulation, exposure-response analyses should only be conducted with the ADC and/or total antibody that is not bound to the shed target in circulation.

Developing E/R models for ADCs presents several challenges including presence of multiple analytes for ADCs with their own physiochemical characteristics that may impact disposition, the changing nature of the ADC with regard to DARs in vivo, as well as the possible immunogenicity that can lead to anti-drug antibody (ADA) formation.

Intrinsic factors

The guidance suggests that intrinsic factors (e.g., renal or liver impairment, pharmacogenomics, body weight, age, gender, race) that can influence exposure of the ADC, its constituent parts, and pharmacologically active metabolites, if any, should be evaluated in either: 1) clinical studies, through population pharmacokinetic (PK) analysis; or 2) dedicated studies. This is consistent with other FDA guidances on this subject. Notably, a population pharmacokinetic approach can be used to assess the effects of organ impairment on the unconjugated payload, pharmacologically active metabolites, if any, and/or other ADC constituent parts if patients with organ impairment are enrolled in pivotal studies, and pharmacokinetic data coupled with safety and efficacy information in those patients are available. Such an approach increases the probability of success of the development program.

QTc assessment

The guidance confirms that the unconjugated payload is the only part of the ADC with potential risk for QT prolongation (Figure 3). Any QT assessment plan for an ADC development program should consider all the factors that would be part of an QT assessment for a small-molecule drug.

Figure 3. Components of a normal ECG

The ADC is unlikely to interact with the human Ether-à-go-go-Related Gene (hERG) channel because of the low concentrations of circulating payload after ADC dosing. In general, a cQT analysis showing no meaningful effect should support a TQT study waiver. When time-matched PK and QT samples are not collected, the ICH E14 guideline allows one to use modeled concentrations.

This aspect should not be taken lightly because the agency can request clinical assessment of QT prolongation risk. Summary basis of approvals for both brentuximab-vedotin and trastuzumab-emtansine, both indicate that studies were done to evaluate the effects on QTc interval in patients with CD30 positive hematologic malignancies (for brentuximab-vedontin) and in HER2-positive metastatic breast cancer (for trastuzumab emtansine).

Drug-Drug interactions

The guidance stipulates that ADC development programs should include an in vitro DDI risk assessment for the unconjugated payload and pharmacologically active metabolites, if any, as both a perpetrator and a victim using both CYP enzyme- and transporter-related assays. The FDA could recommend that the sponsor conduct an in vivo DDI evaluation of the unconjugated payload as a victim and considers physiologically-based pharmacokinetic (PBPK) modeling to be appropriate to characterize the probability of an effect. The guidance further states that the FDA could recommend assessing the DDI potential for the antibody component.

In general, extensive in vitro DDI risk assessment is very helpful in rationalizing that no clinical DDI studies are needed. The FDA supports the use of PBPK modeling which could be used to further strengthen the evidence. While the agency has borrowed drug interaction information from other approved ADCs, such an approach by a sponsor may be limited to situations where there is a right of reference.

In summary, nothing is new in the latest ADC clinical pharmacology guidance. However, this guidance will help sponsors pay attention to several considerations including, but not limited to:

  • In vitro and in vivo ADME characterization during preclinical development, including identification of metabolites and determining their pharmacological activity
  • Bioanalytical method strategy development before clinical evaluation
  • Translational PK/PD strategy for payload and linker components
  • Dose and regimen selection during early clinical development using exposure/response
  • Concentration/QT assessment within the FIH study
  • Modeling and simulation strategy that includes developing population PK, PK/PD, and PBPK models to interrogate the effects of intrinsic and extrinsic factors

For an example of how modeling and simulation was used to support an ADC development program, please read this case study.

Case Study


Krishna, R., 2021. Key Considerations to Ensure Maximal Probability of Antibody Drug Conjugate Development Success. [Blog] Certara, Available at: <> [Accessed 18 April 2022].

Sikorski, S.R.I.Q.R. The Clinical Landscape of Antibody-drug Conjugates. 2014 [cited 2021 30 September]; Available from:

About the author

Rajesh Krishna, PhD
By: Rajesh Krishna, PhD

Rajesh Krishna, PhD, FAAPS is Senior Director, clinical pharmacology and lead of the integrated practice area on rare diseases at Certara Strategic Consulting. With ~25 years of combined pharmaceutical industry and consulting experience, he has contributed to over 40 INDs; over 200 Phase 1/1b studies; and to several NDAs/BLAs. He is an author of Raj’s clinical pharmacology blogs.

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