Translational PK/PD framework for antibody-drug conjugates to inform drug discovery and development.

(171/200)ADCs represent a transformative class of medicine that combines the specificity of monoclonal antibodies with the potency of highly cytotoxic agents through linkers, aiming to enhance the therapeutic index of cytotoxic drugs. Given the complex molecular structures of ADCs, combining the molecular characteristics of small-molecule drugs and those of large-molecule biotherapeutics, there are several unique considerations when designing nonclinical-to-clinical PK/PD translation strategies.This complexity also demands a thorough understanding of the ADC's components-antibody, linker, and payload-to the overall toxicological, PK/PD, and efficacy profile. ADC development is a multidisciplinary endeavor requiring a strategic integration of nonclinical safety, pharmacology, and PK/PD modeling to translate from bench to bedside successfully.The ADC development underscores the necessity for a robust scientific foundation, leveraging advanced analytical and modeling tools to predict human responses and optimize therapeutic outcomes.This review aims to provide an ADC translational PK/PD framework by discussing unique aspects of ADC nonclinical to clinical PK translation, starting dose determination, and leveraging PK/PD modeling for human efficacious dose prediction and potential safety mitigation.

Population pharmacokinetics and CD20 binding dynamics for mosunetuzumab in relapsed/refractory B-cell non-Hodgkin lymphoma.

Mosunetuzumab (Mosun) is a CD20xCD3 T-cell engaging bispecific antibody that redirects T cells to eliminate malignant B cells. The approved step-up dose regimen of 1/2/60/30 mg IV is designed to mitigate cytokine release syndrome (CRS) and maximize efficacy in early cycles. A population pharmacokinetic (popPK) model was developed from 439 patients with relapsed/refractory B-Cell Non-Hodgkin lymphoma receiving Mosun IV monotherapy, including fixed dosing (0.05-2.8 mg IV every 3 weeks (q3w)) and Cycle 1 step-up dosing groups (0.4/1/2.8-1/2/60/30 mg IV q3w). Prior to Mosun treatment, ~50% of patients had residual levels of anti-CD20 drugs (e.g., rituximab or obinutuzumab) from prior treatment. CD20 receptor binding dynamics and rituximab/obinutuzumab PK were incorporated into the model to calculate the Mosun CD20 receptor occupancy percentage (RO%) over time. A two-compartment model with time-dependent clearance (CL) best described the data. The typical patient had an initial CL of 1.08 L/day, transitioning to a steady-state CL of 0.584 L/day. Statistically relevant covariates on PK parameters included body weight, albumin, sex, tumor burden, and baseline anti-CD20 drug concentration; no covariate was found to have a clinically relevant impact on exposure at the approved dose. Mosun CD20 RO% was highly variable, attributed to the large variability in residual baseline anti-CD20 drug concentration (median = 10 µg/mL). The 60 mg loading doses increased Mosun CD20 RO% in Cycle 1, providing efficacious exposures in the presence of the competing anti-CD20 drugs. PopPK model simulations, investigating Mosun dose delays, informed treatment resumption protocols to ensure CRS mitigation.

Monomethyl Auristatin E (MMAE), a Payload for Multiple Antibody Drug Conjugates (ADCs), Demonstrates Differential Red Blood Cell Partitioning Across Human and Animal Species.

Background: Monomethyl auristatin E (MMAE) has been used as a payload for several Food and Drug Administration (FDA) approved antibody-drug conjugates (ADCs). It is known that MMAE is released from the ADC following binding, internalization and proteolytic degradation in target tissues. A striking discrepancy in systemic MMAE levels has been observed across species with 50-fold higher MMAE levels in human than that in rodents when normalized by ADC dose with unknown mechanism.Hypothesis and purpose: Multiple factors could affect systemic MMAE levels such as production and elimination of unconjugated MMAE following ADC dosing. In this study, we have explored whether MMAE displays differential red blood cell (RBC) partitioning across species that may contribute to the different MMAE levels seen between human and animals.Experiments: To determine MMAE RBC partitioning, tritium labeled MMAE ([3H]-MMAE) was incubated in whole blood from mice, rats, monkeys and humans in vitro, then RBC partitioning was determined and compared across species. To test whether MMAE released from the ADC would show any difference in RBC partitioning, pinatuzumab vedotin or polatuzumab vedotin was administered to mice, rats, and monkeys. MMAE levels were measured in both blood and plasma, and the ratios of MMAE levels were calculated as blood-to-plasma ratio (in vivo RBC partitioning).Results: Our in vitro data showed that unconjugated MMAE has a species-dependent RBC partitioning with strong RBC partitioning in mouse, rat, followed by monkey blood, whereas minimal RBC partitioning was seen in human blood. Incubation of 2 nM of MMAE in mouse blood resulted in a blood-to-plasma ratio of 11.8 ± 0.291, followed by rat, monkey, and human at 2.36 ± 0.0825, 1.57 ± 0.0250, and 0.976 ± 0.0620, respectively. MMAE RBC partitioning is also concentration-dependent, with an inverse relationship between RBC partitioning and MMAE concentration (higher RBC partitioning at lower concentration). In vivo dosing of pinatuzumab vedotin in mouse displayed systemic MMAE at about a 5-fold higher blood concentration compared to plasma concentration once MMAE reached a pseudo-equilibrium, while systemic MMAE from blood and plasma concentration showed a 1.65-fold difference in rat.Implication and conclusion: These data demonstrated that MMAE has a distinct RBC partitioning across different species, which may contribute to, at least in part, to the differential in the systemic MMAE levels observed in vivo between preclinical and clinical studies. These findings highlight the importance of fully characterizing the ADME properties of both the ADC and its payload, to enable better translation from animals to human for ADC development.

Population pharmacokinetics and exposure-response analyses of polatuzumab vedotin in patients with previously untreated DLBCL from the POLARIX study.

Polatuzumab vedotin is a CD79b-directed antibody-drug conjugate that targets B cells and delivers the cytotoxic payload monomethyl auristatin E (MMAE). The phase III POLARIX study (NCT03274492) evaluated polatuzumab vedotin in combination with rituximab, cyclophosphamide, doxorubicin, and prednisone (R-CHP) as first-line treatment of diffuse large B-cell lymphoma (DLBCL). To examine dosing decisions for this regimen, population pharmacokinetic (popPK) analysis, using a previously developed popPK model, and exposure-response (ER) analysis, were performed. The popPK analysis showed no clinically meaningful relationship between cycle 6 (C6) antibody-conjugated (acMMAE)/unconjugated MMAE area under the concentration-time curve (AUC) or maximum concentration, and weight, sex, ethnicity, region, mild or moderate renal impairment, mild hepatic impairment, or other patient and disease characteristics. In the ER analysis, C6 acMMAE AUC was significantly associated with longer progression-free and event-free survival (both p = 0.01). An increase of <50% in acMMAE/unconjugated MMAE exposure did not lead to a clinically meaningful increase in adverse events of special interest. ER data and the benefit-risk profile support the use of polatuzumab vedotin 1.8 mg/kg once every 3 weeks with R-CHP for six cycles in patients with previously untreated DLBCL.

Clinical pharmacology strategies to accelerate the development of polatuzumab vedotin and summary of key findings.

The favorable benefit-risk profile of polatuzumab vedotin, as demonstrated in a pivotal Phase Ib/II randomized study (GO29365; NCT02257567), coupled with the need for effective therapies in relapsed/refractory (R/R) diffuse large B-cell lymphoma (DLBCL), prompted the need to accelerate polatuzumab vedotin development. An integrated, fit-for-purpose clinical pharmacology package was designed to support regulatory approval. To address key clinical pharmacology questions without dedicated clinical pharmacology studies, we leveraged non-clinical and clinical data for polatuzumab vedotin, published clinical data for brentuximab vedotin, a similar antibody-drug conjugate, and physiologically based pharmacokinetic and population pharmacokinetic modeling approaches. We review strategies and model-informed outcomes that contributed to regulatory approval of polatuzumab vedotin plus bendamustine and rituximab in R/R DLBCL. These strategies made polatuzumab vedotin available to patients earlier than previously possible; depending on the strength of available data and the regulatory/competitive environment, they may also prove useful in accelerating the development of other agents.

Assessment of CYP3A-mediated drug interaction via cytokine (IL-6) elevation for mosunetuzumab using physiologically-based pharmacokinetic modeling.

Mosunetuzumab is a CD3/CD20 bispecific antibody. As an on-target effect, transient elevation of interleukin-6 (IL-6) occurs in early treatment cycles. A physiologically-based pharmacokinetic (PBPK) model was developed to assess potential drug interaction caused by IL-6 enzyme suppression on cytochrome P450 3A (CYP3A) during mosunetuzumab treatment. The model's performance in predicting IL-6 CYP3A suppression and subsequent drug-drug interactions (DDIs) was verified using existing clinical data of DDIs caused by chronic and transient IL-6 elevation. Sensitivity analyses were performed for a complete DDI risk assessment. The IL-6 concentration- and time-dependent CYP3A suppression during mosunetuzumab treatment was simulated using PBPK model with incorporation of in vitro IL-6 inhibition data. At clinically approved doses/regimens, the DDI at maximum CYP3A suppression was predicted to be a midazolam maximum drug concentration in plasma (Cmax ) and area under the plasma drug concentration-time curve (AUC) ratio of 1.17 and 1.37, respectively. At the 95th percentile of IL-6 concentration level or when gut CYP3A suppression was considered, the predicted DDI risk for mosunetuzumab remained low (<2-fold). The PBPK-based DDI predictions informed the mosunetuzumab product label to monitor, in early cycles, the concentrations and toxicities for sensitive CYP3A substrates with narrow therapeutic windows.

Ethnic sensitivity assessment: Polatuzumab vedotin pharmacokinetics in Asian and non-Asian patients with previously untreated diffuse large B-cell lymphoma in POLARIX.

This ethnic sensitivity analysis used data from the phase III POLARIX study (NCT03274492) to assess polatuzumab vedotin pharmacokinetics (PKs) in Asian versus non-Asian patients with previously untreated diffuse large B-cell lymphoma and examined the appropriateness of extrapolating global study findings to Asian patients. PK and population PK (PopPK) analyses assessed polatuzumab vedotin analyte exposures by ethnicity (Asian [n = 84] vs. non-Asian [n = 345] patients) and region (patients enrolled from Asia [n = 80] vs. outside Asia [n = 349]). In patients from Asia versus outside Asia, observed mean antibody-conjugated monomethyl auristatin E (acMMAE) concentrations were comparable (1.2% lower at cycle [C]1 postdose, 4.4% higher at C4 predose; and 6.8% lower at C4 postdose in patients from Asia). Observed mean unconjugated MMAE was lower in patients from Asia by 6.5% (C1 postdose), 20.0% (C4 predose), and 15.3% (C4 postdose). In the PopPK analysis, C6 area under the curve and peak plasma concentrations were also comparable for acMMAE (6.3% and 3.0% lower in Asian vs. non-Asian patients, respectively) and lower for unconjugated MMAE by 19.1% and 16.7%, respectively. By region, C6 mean acMMAE concentrations were similar, and C6 mean unconjugated MMAE concentrations were lower, in patients enrolled from Asia versus outside Asia, by 3.9%-7.0% and 17.3%-19.7%, respectively. In conclusion, polatuzumab vedotin PKs were similar between Asian and non-Asian patients by ethnicity and region, suggesting PKs are not sensitive to Asian ethnicity and dose adjustments are not required in Asian patients to maintain efficacy and safety.

Early Decision Making in a Randomized Phase II Trial of Atezolizumab in Biliary Tract Cancer Using a Tumor Growth Inhibition-Survival Modeling Framework.

We assess the longitudinal tumor growth inhibition (TGI) metrics and overall survival (OS) predictions applied to patients with advanced biliary tract cancer (BTC) enrolled in IMbrave151 a multicenter randomized phase II, double-blind, placebo-controlled trial evaluating the efficacy and safety of atezolizumab with or without bevacizumab in combination with cisplatin plus gemcitabine. Tumor growth rate (KG) was estimated for patients in IMbrave151. A pre-existing TGI-OS model for patients with hepatocellular carcinoma in IMbrave150 was modified to include available IMbrave151 study covariates and KG estimates and used to simulate IMbrave151 study outcomes. At the interim progression-free survival (PFS) analysis (98 patients, 27 weeks follow-up), clear separation in tumor dynamic profiles with a faster shrinkage rate and slower KG (0.0103 vs. 0.0117 week-1 ; tumor doubling time 67 vs. 59 weeks; KG geometric mean ratio of 0.84) favoring the bevacizumab containing arm was observed. At the first interim analysis for PFS, the simulated OS hazard ratio (HR) 95% prediction interval (PI) of 0.74 (95% PI: 0.58-0.94) offered an early prediction of treatment benefit later confirmed at the final analysis, observed HR of 0.76 based on 159 treated patients and 34 weeks of follow-up. This is the first prospective application of a TGI-OS modeling framework supporting gating of a phase III trial. The findings demonstrate the utility for longitudinal TGI and KG geometric mean ratio as relevant end points in oncology studies to support go/no-go decision making and facilitate interpretation of the IMbrave151 results to support future development efforts for novel therapeutics for patients with advanced BTC.

Support to early clinical decisions in drug development and personalised medicine with checkpoint inhibitors using dynamic biomarker-overall survival models.

Longitudinal models of biomarkers such as tumour size dynamics capture treatment efficacy and predict treatment outcome (overall survival) of a variety of anticancer therapies, including chemotherapies, targeted therapies, immunotherapies and their combinations. These pharmacological endpoints like tumour dynamic (tumour growth inhibition) metrics have been proposed as alternative endpoints to complement the classical RECIST endpoints (objective response rate, progression-free survival) to support early decisions both at the study level in drug development as well as at the patients level in personalised therapy with checkpoint inhibitors. This perspective paper presents recent developments and future directions to enable wider and robust use of model-based decision frameworks based on pharmacological endpoints.

Concentration QTc analysis of giredestrant: Overcoming QT/heart rate confounding in the presence of drug-induced heart rate changes.

Concentration-QTc (C-QTc) analysis has become a common approach for evaluating proarrhythmic risk and delayed cardiac repolarization of oncology drug candidates. Significant heart rate (HR) change has been associated with certain classes of oncology drugs and can result in over- or underestimation of the true QT prolongation risk. Because oncology early clinical trials typically lack a placebo control arm or time-matched, treatment-free baseline electrocardiogram collection, significant HR change brings additional challenges to C-QTc analysis in the oncology setting. In this work, a spline-based correction method (QTcSPL) was explored to mitigate the impact of HR changes in giredestrant C-QTc analysis. Giredestrant is a selective estrogen receptor degrader being developed for the treatment of patients with estrogen receptor-positive (ER+) breast cancer. A dose-related HR decrease has been observed in patients under giredestrant treatment, with significant reductions (>10 bpm) observed at supratherapeutic doses. The QTcSPL method demonstrated superior functionality to reduce the correlation between QTc and HR as compared with the Fridericia correction (QTcF). The effect of giredestrant exposure on QTc was evaluated at the clinical dose of 30 mg and supratherapeutic dose of 100 mg based on a prespecified linear mixed effect model. The upper 90% confidence interval of ΔQTcSPL and ΔQTcF were below the 10 ms at both clinical and supratherapeutic exposures, suggesting giredestrant has a low risk of QT prolongation at clinically relevant concentrations. This work demonstrated the use case of QTcSPL to address HR confounding challenges in the context of oncology drug development for the first time.

Pharmacokinetics of biologics in gastric cancer.

Gastric cancer (GC) remains one of the leading causes of cancer death worldwide despite improvements in therapeutic options. Several biologics have been investigated in patients with GC, including those approved in other solid tumors; however, the success rate of the pivotal trials that investigated these biologic molecules in GC remains low. Elevation in total clearance and a decrease in systemic pharmacokinetic (PK) exposure in GC compared with other indications have been observed in these biologics across different pathways. Achieving optimal exposure for patients with GC is an important factor in balancing risk and optimizing therapeutic benefit and thus maximizing chance of positive outcomes for pivotal trials. Therefore, in this review, we summarize the PK disposition of several molecules (e.g., anti-HER2, anti-VEGF, and anti-PD1) evaluated in GC and showed a consistent trend of lower drug exposure as compared to other solid tumors. We hypothesize that two possible mechanisms: (1) hyper-catabolism of endogenous and exogenous proteins due to cancer cachexia; and (2) gastric protein leakage due to local inflammation at the gastrointestinal tract may explain or partially explain the increase of clearance in patients with GC. Last, the potential implications of such findings on dose selection to optimize the benefit: risk profile for biologics in GC are also discussed.

Tumor Dynamic Model-Based Decision Support for Phase Ib/II Combination Studies: A Retrospective Assessment Based on Resampling of the Phase III Study IMpower150.

PURPOSE: Model-based tumor growth inhibition (TGI) metrics are increasingly incorporated into go/no-go decisions in early clinical studies. To apply this methodology to new investigational combinations requires independent evaluation of TGI metrics in recently completed Phase III trials of effective immunotherapy. PATIENTS AND METHODS: Data were extracted from IMpower150, a positive, randomized, Phase III study of first-line therapy in 1,202 patients with non-small cell lung cancer. We resampled baseline characteristics and longitudinal sum of longest diameters of tumor lesions of patients from both arms, atezolizumab+ bevacizumab+chemotherapy (ABCP) versus BCP, to mimic Phase Ib/II studies of 15 to 40 patients/arm with 6 to 24 weeks follow-up. TGI metrics were estimated using a bi-exponential TGI model. Effect sizes were calculated as TGI metrics geometric mean ratio (GMR), objective response rate (ORR) difference (d), and progression-free survival (PFS), hazard ratio (HR) between arms. Correct and incorrect go decisions were evaluated as the probability to achieve desired effect sizes in ABCP versus BCP and BCP versus BCP, respectively, across 500 replicated subsamples for each design. RESULTS: For 40 patients/24 weeks follow-up, correct go decisions based on probability tumor growth rate (KG) GMR <0.90, dORR >0.10, and PFS HR <0.70 were 83%, 69%, and 58% with incorrect go decision rates of 4%, 12%, and 11%, respectively. For other designs, the ranking did not change with TGI metrics consistently overperforming RECIST endpoints. The predicted overall survival (OS) HR was around 0.80 in most of the scenarios investigated. CONCLUSIONS: Model-based estimate of KG GMR is an exploratory endpoint that informs early clinical decisions for combination studies.

Oxidative Stress Responses and Gene Transcription of Mice under Chronic-Exposure to 2,6-Dichlorobenzoquinone.

2,6-Dichlorobenzoquinone (2,6-DCBQ), as an emerging disinfection by-production, was frequently detected and identified in the drinking water; however, limited information is available for the toxic effect of 2,6-DCBQ on mice. In the present study, adult mice were used to assess the impact of 2,6-DCBQ via measuring the responses of antioxidant enzymes (superoxide dismutase (SOD) and catalase (CAT)), the key genes (Heme oxygenase-1 (HO-1), NADPH quinone oxidoreductase 1 (NQO1) and glutamate-L-cysteine ligase catalytic subunit (GCLC)) in the Nrf2-keap1 pathway, and lipid peroxidation (malonaldehyde, MDA). Our results clearly indicated that 2,6-DCBQ decreased the activities of SOD and CAT, repressed the transcriptional levels of key genes in Nrf2-keap1 pathway, further caused oxidative damage on mice. These results provided evidence for assessing the threat of 2,6-DCBQ on human.

Pharmacokinetics and Exposure-Response Analysis of Venetoclax + Obinutuzumab in Chronic Lymphocytic Leukemia: Phase 1b Study and Phase 3 CLL14 Trial.

INTRODUCTION: This study aims to investigate pharmacokinetics (PK) and exposure-response parameters of the 400 mg once-daily venetoclax dose regimen in combination with obinutuzumab, which was approved for the first-line (1L) treatment of chronic lymphocytic leukemia (CLL) based on data from the phase 3 CLL14 study and the phase 1b dose-finding GP28331 study. METHODS: Parameter estimates and uncertainty, which were estimated by a previously developed population PK (popPK) model, were used as informative priors for this analysis. They were re-estimated, and then used to evaluate additional covariate effects, describe venetoclax PK when administered with obinutuzumab, and provide empirical Bayes estimates of PK parameters and exposure. Exposure-progression-free survival (PFS) and exposure-safety relationships were assessed using data from CLL14, with steady-state nominal venetoclax exposure (CmeanSS,nominal) as the predictor variable. Exposure-safety analyses were conducted using logistic regression for selected treatment-emergent grade ≥ 3 adverse events (AEs) and serious AEs (SAEs). Dose intensities were summarized by tertiles of CmeanSS,nominal. RESULTS: PK data from 274 patients (CLL14, n = 194; GP28331, n = 80) were included. The final model provided good fit of the observed data. Obinutuzumab co-administration, history of prior treatments, and disease severity at baseline had no appreciable influence on venetoclax steady-state exposure. No significant correlations were observed between venetoclax exposure and PFS, or between venetoclax exposure and the probability of treatment-emergent grade ≥ 3 neutropenia, grade ≥ 3 thrombocytopenia, grade ≥ 3 infections, and SAEs. Median dose intensities for venetoclax and obinutuzumab remained similar across venetoclax exposure tertiles. CONCLUSION: PopPK and exposure-efficacy, exposure-safety, and exposure-tolerability analyses support the 400 mg once-daily venetoclax dose plus obinutuzumab for 1L treatment in patients with CLL. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov Identifiers NCT02242942 and NCT02339181.

A phase 1b study of atezolizumab in combination with guadecitabine for the treatment of acute myeloid leukemia.

This phase 1 b study evaluated the safety, efficacy, and pharmacokinetics of atezolizumab in combination with guadecitabine in patients with relapsed/refractory (R/R) or first-line acute myeloid leukemia (AML). Patients received atezolizumab 840 mg (days [D] 8 and 22) and guadecitabine 60 mg/m2 (D1 and D5) over 28-day cycles. Sixteen patients (median age 73.0 years) enrolled (R/R cohort, n = 11; first-line cohort, n = 5). All patients reported at least 1 AE; 15 patients (93.8%) reported grade ≥ 3 AEs, and 15 patients (93.8%) reported SAEs. Fourteen of the 16 patients (87.5%) died during the trial period due to disease progression (8/14) or AEs (6/14), hence the study was terminated early. One patient (from the R/R AML cohort) achieved a response (CR with incomplete platelet recovery) with a DOR of 27.8 months at study termination. Atezolizumab plus guadecitabine had limited clinical activity in AML and an overall unfavorable benefit-risk profile at the investigated dose levels.

Anti-CD79B Antibody-Drug Conjugate DCDS0780A in Patients with B-Cell Non-Hodgkin Lymphoma: Phase 1 Dose-Escalation Study.

PURPOSE: Targeting CD79B using antibody-drug conjugates (ADC) is an effective therapeutic strategy in B-cell non-Hodgkin lymphoma (B-NHL). We investigated DCDS0780A, an anti-CD79B ADC with THIOMAB technology (TDC) that consistently conjugates two anti-neoplastic molecules per antibody, in contrast with ADCs with heterogeneous loads. PATIENTS AND METHODS: This phase 1 study enrolled 60 patients with histologically confirmed B-NHL that had relapsed/failed to respond following ≥1 prior treatment regimens; 41 (68%) had diffuse large B-cell lymphoma (DLBCL). Fifty-one patients received DCDS0780A monotherapy once every 3 weeks (0.3-4.8 mg/kg); 9 received combination therapy (3.6-4.8 mg/kg) with rituximab. RESULTS: Fifty-four (90%) patients experienced adverse events related to study drug, the most common of which were blurred vision, fatigue, corneal deposits, neutropenia, nausea, and peripheral neuropathy. 4.8 mg/kg was the highest dose tested and the recommended phase II dose. The pharmacokinetic profile was linear at doses ≥1.2 mg/kg. Response rate in all-treated patients (N = 60) was 47% (n = 28), including 17 complete responses (28%) and 11 partial responses (18%). The median duration of response (15.2 months) was the same for all responders (n = 28) and patients with DLBCL (n = 20). CONCLUSIONS: DCDS0780A as the TDC format for CD79B was tested at higher doses than its ADC counterpart investigated earlier, leading to deep responses. However, dose intensity was limited by ocular toxicities seen at the higher doses indicating that the TDC format was unable, in the current study, to expand the therapeutic index for the CD79B target. The encouraging antitumor activity advocates continuation of investigations into novel ADC technologies.

Risk-Based Pharmacokinetic and Drug-Drug Interaction Characterization of Antibody-Drug Conjugates in Oncology Clinical Development: An International Consortium for Innovation and Quality in Pharmaceutical Development Perspective.

Antibody-drug conjugates (ADCs) represent a rapidly evolving area of drug development and hold significant promise. To date, nine ADCs have been approved by the US Food and Drug Administration (FDA). These conjugates combine the target specificity of monoclonal antibodies with the anticancer activity of small-molecule therapeutics (also referred to as payload). Due to the complex structure, three analytes, namely ADC conjugate, total antibody, and unconjugated payload, are typically quantified during drug development; however, the benefits of measuring all three analytes at later stages of clinical development are not clear. The cytotoxic payloads, upon release from the ADC, are considered to behave like small molecules. Given the relatively high potency and low systemic exposure of cytotoxic payloads, drug-drug interaction (DDI) considerations for ADCs might be different from traditional small molecule therapeutics. The International Consortium for Innovation and Quality in Pharmaceutical Development (IQ Consortium) convened an ADC working group to create an IQ ADC database that includes 26 ADCs with six unique payloads. The analysis of the ADC data in the IQ database, as well as nine approved ADCs, supports the strategy of pharmacokinetic characterization of all three analytes in early-phase development and progressively minimizing the number of analytes to be measured in the late-phase studies. The systemic concentrations of unconjugated payload are usually too low to serve as a DDI perpetrator; however, the potential for unconjugated payloads as a victim still exists. A data-driven and risk-based decision tree was developed to guide the assessment of a circulating payload as a victim of DDI.