Cancer Chemotherapy and Pharmacology (2021) 87:743–765 https://doi.org/10.1007/s00280-021-04250-0

REVIEW ARTICLE

Clinical pharmacology strategies in supporting drug development and approval of antibody–drug conjugates in oncology

Stephanie N. Liu1 · Chunze Li1

Received: 14 September 2020 / Accepted: 18 February 2021 / Published online: 1 April 2021 © The Author(s) 2021

Abstract Antibody–drug conjugates (ADCs) are important molecular entities in the treatment of cancer. These conjugates combine the target specifcity of monoclonal antibodies with the potent anti-cancer activity of small-molecule therapeutics. The complex structure of ADCs poses unique challenges to characterize the drug’s pharmacokinetics (PKs) and pharmacodynamics (PDs) since it requires a quantitative understanding of the PK and PD properties of multiple diferent molecular species (e.g., ADC conjugate, total antibody and unconjugated cytotoxic drug). As a result, clinical pharmacology strategy of an ADC is rather unique and dependent on the linker/cytotoxic drug technology, heterogeneity of the ADC, PK and safety/efcacy profle of the specifc ADC in clinical development. In this review, we summarize the clinical pharmacology strategies in supporting development and approval of ADCs using the approved ADCs as specifc examples to illustrate the customized approach to clinical pharmacology assessments in their clinical development.

Keywords Antibody–drug conjugate · Clinical pharmacology · Population pharmacokinetics · Exposure–response analysis · Specifc population · Drug interaction · QTc prolongation

Introduction designed to enhance the antitumor efects of the molecule while minimizing the toxicity in the normal tissues. Antibody drug conjugates (ADCs) are an emerging class As of January 2020, nine ADCs have received US Food of anti-cancer therapeutic agents that combine the antigen and Drug Administration (FDA) approval [2]. The frst of targeting specifcity and favorable pharmacokinetic prop- these, (1) gemtuzumab ozogamicin (Mylotarg®; an anti- erties of monoclonal antibodies (mAbs) with the cytotoxic CD33 mAb linked to calicheamicin), for the treatment of potential of small-molecule chemotherapeutics [1]. ADCs acute myelogenous leukemia (AML) was approved in 2000 typically consist of three components, namely a mAb to under the FDA accelerated-approval process [3]. In 2010, determine which cells to be targeted, a cytotoxic drug to this agent was voluntarily withdrawn from the market due determine the mechanism of action by which cells are killed, to confrmatory trials failing to demonstrate clinical ben- and a chemical linker that attaches these two components eft and safety concerns [3]. Gemtuzumab ozogamicin was together to determine how the drug is released. The mAb re-approved in 2018 at a sub-fractionated dose of 3–6 mg/ component of an ADC enables the ADC to specifcally m2 (compared to 9 mg/m2 at first approval) [4]. Since bind to targeted cell surface antigens overexpressed on the gemtuzumab ozogamicin’s initial market approval, seven tumor cells. Upon binding, the ADCs are internalized and more ADCs were FDA approved: (2) brentuximab vedotin trafcked to lysosomes, from which the cytotoxic drug is (Adcetris®; an anti-CD30 mAb and monomethyl auristatin released within the cell, thus resulting in the cell death. The E [MMAE] conjugate) for the treatment of Hodgkin lym- use of targeted delivery of highly potent cytotoxic drugs is phoma and systemic anaplastic large-cell lymphoma, (3) trastuzumab emtansine (T-DM1, Kadcyla®; an anti-human epidermal growth factor receptor 2 (HER2) mAb and DM1 * Chunze Li [a derivative of maytansine] conjugate) for the treatment [email protected] of HER2 + metastatic breast cancer (mBC), (4) inotuzumab ozogamicin (Besponsa®, an anti-CD22 mAb and calicheam- 1 Department of Clinical Pharmacology, Genentech, Inc, 1 icin conjugate) for the treatment of adults with relapsed or DNA Way, South San Francisco, CA 94080, USA

Vol.:(0123456789)1 3 744 Cancer Chemotherapy and Pharmacology (2021) 87:743–765 refractory B-cell precursor acute lymphoblastic leukemia by catabolism mediated by target-specifc or nonspecifc (ALL), (5) polatuzumab vedotin (Polivy®, an anti-CD79b cellular uptake followed by lysosomal degradation, similar mAb and MMAE conjugate) for the treatment of relapsed to mAbs. Deconjugation clearance is usually mediated by or refractory difuse large B-cell lymphoma (DLBCL), (6) enzymatic or chemical cleavage (e.g., maleimide exchange) enfortumab vedotin (Padcev®, an anti-Nectin 4 mAb and of the linker leading to the release of the cytotoxic drug from MMAE conjugate) for the treatment of locally advanced the ADC [16]. Once released from the ADC, the cytotoxic or metastatic urothelial cancer, (7) trastuzumab deruxte- drug may be further metabolized, transported, and elimi- can (Enhertu®, an anti-HER2 mAb and exatecan deriva- nated via traditional mechanisms applicable to small mol- tive conjugate) for the treatment of HER2 + mBC, and (8) ecules (see DDI section). Alternatively, ADC catabolism sacituzumab govitegcan (Trodelvy®, an anti-Trop-2 mAb and deconjugation in vivo leads to the formation of multiple and SN-38 conjugate) for the treatment of metastatic triple- diferent molecular species (e.g., ADC species with diferent negative breast cancer [5–11]. In August 2020, the 9th ADC, drug antibody ratios [DAR]) and payload-containing catabo- namely belantamab mafodotin-blmf (Blenrep®, an anti- lites) [17]. The bioanalytical strategy for ADCs thus requires BCMA mAb and MMAF conjugate) achieved accelerated defning the specifc analytes of relevance to clinical phar- approval from FDA for the treatment relapsed and refractory macology. Although multiple analytes may be quantifed multiple myeloma [12]. following the dosing of an ADC, the clinical importance of These ADCs prove that the therapeutic window of other- the multi-analyte bioanalytical data in context of safety and wise intolerable cytotoxic drugs can be improved to a thera- efcacy remains to be established. With numerous ADCs peutically benefcial level by conjugating it to an antibody. in clinical development, streamlining the bioanalytical and Despite the great success of ADCs, it is worth noting that clinical pharmacology strategy is critical. the therapeutic window for ADCs remains relatively nar- The clinical pharmacology assessments for ADCs to row with the maximum tolerated dose (MTD) often reached address scientifc and regulatory concerns are summarized before ADCs achieve the maximal efcacious dose [13]. As in Fig. 1. The clinical pharmacology of an ADC incorporates a result, numerous innovative approaches (e.g., site-specifc elements of small molecule and mAb (large molecule) devel- conjugation or novel payloads) have been implemented to opment strategies. The scope of work is usually unique and further improve the therapeutic window, resulting in the dependent on the linker/cytotoxic drug technology, heteroge- “next-generation” ADCs, many of which are currently tested neity of the ADC, pharmacokinetics (PK) and safety/efcacy in clinical development. profle of the specifc ADC in clinical development. Given The current understanding of the mechanism at which the structural complexity, multiple analytes were measured ADCs are cleared is through two major pathways: proteo- across Phase I, Phase II and Phase III clinical studies to lytic degradation and deconjugation [14, 15]. ADC clear- characterize the PK of an ADC, including, but not limited ance through proteolytic degradation is driven primarily to, conjugate, total antibody and unconjugated payload.

Fig. 1 Clinical pharmacology considerations in the stages of ADC drug development

1 3 Cancer Chemotherapy and Pharmacology (2021) 87:743–765 745

Intrinsic (e.g., body weight, organ dysfunction) and extrin- the availability of bioanalytical techniques at the time of sic factors (e.g., concomitant medications) likely to impact development. the PK of an ADC were assessed using diverse approaches Although multiple analytes may be quantifed following (Fig. 1). Relationships between exposure to ADC conju- the dosing of an ADC, the bioanalytical strategy for ADCs gate (and other relevant analytes) and efcacy/safety were requires defning the specifc analytes of relevance to clini- assessed in support of the clinical dosing regimen selection cal pharmacology in the context of safety and efcacy. Most using quantitative approaches. This review summarized the commonly, three analytes, namely ADC conjugate, TAb and unique clinical pharmacology consideration in supporting unconjugated cytotoxic drug are measured in preclinical and development and approval of ADCs (Fig. 1). The seven clinical studies to characterize the PK properties of an ADC approved ADCs are used as specifc examples to illustrate [17, 19]. the customized approach to clinical pharmacology assess- ments in their clinical development. Sacituzumab govitecan and belantamab mafodotin-blmf were not included in the Population PK modeling summary due to limited clinical pharmacology information available at the time of the review. Population PK modeling is an important approach to char- acterize the ADC PK properties and assess the efect of intrinsic and extrinsic factors on ADC PK, and thus guide dose recommendations in specifc populations (e.g., geriatric Bioanalytical consideration patients or patients with organ dysfunction). Given multi- ple analytes were measured for an ADC during its clinical ADCs incorporate both large- and small-molecule charac- development, one of the unique features of population PK teristics and are usually present as a heterogeneous mixture for an ADC is that more than one analyte is often included in of the species difering not only in the number of cytotoxic the population PK model development. ADC conjugate, the drugs attached to the antibody, but also in the protein con- main analyte of interest per mechanism of action of ADCs, jugation sites of drug linkage [18]. Furthermore, biotrans- is the most common analyte included in the population PK formations in vivo can lead to additional changes in DARs model. Additionally, given the high potency of cytotoxic resulting in dynamically changing mixtures. As a result, drugs, the potential contribution of unconjugated drug to unlike mAbs, the heterogeneity of ADCs in vivo makes it safety could not be ruled out. Exposure-safety analysis with critical to measure multiple analytes in clinical trials [17, unconjugated cytotoxic drug has been conducted for the four 19]. These analytes may include, but are not limited to, the out of the seven approved ADCs (see exposure–response following: ADC conjugate (measured as conjugated anti- section). As a result, unconjugated drug analyte is often body or conjugated payload), total antibody (TAb, conju- included in the population PK model in addition to ADC gated and unconjugated antibody), unconjugated antibody conjugate to understand the PK characteristics of unconju- and unconjugated (free) payload. Conjugated antibody and gated drugs after ADC dosing and generate exposure metrics conjugated payload are the two alternative ways to quantify for exposure-response analysis. the ADC conjugate [20]. From the perspective of the anti- As shown in Table 1, fve out of the seven approved body, the ADC conjugate can be measured as “conjugated ADCs include the two analytes in their population PK mod- antibody”, namely the concentration of antibody molecules els. Integrated two-analyte models (i.e., ADC conjugate- with one or more cytotoxic drugs attached. This bioanalyti- unconjugated payload models) were developed for brentuxi- cal method is used to measure serum concentrations of ADC mab vedotin, polatuzumab vedotin, enfortumab vedotin and conjugate for brentuximab vedotin, inotuzumab ozogamicin, trastuzumab deruxtecan, while for gemtuzumab ozogamicin T-DM1, enfortumab vedotin, and trastuzumab deruxtecan population PK model for TAb and unconjugated payload was [21–25]. Alternatively, from the perspective of the payload, developed separately and ADC conjugate analyte was not the ADC conjugate can be measured as “conjugated drug”, measured clinically [28]. Typically, the ADC conjugate is namely as the total concentration of cytotoxic drug that dosed in the linear range based on the fndings of the phase is conjugated to the antibody. Currently, only ADCs with 1 dose escalation study. The population PK model structures cleavable linker are amenable to the conjugated drug assay. for ADC conjugate are usually characterized by a 2- or 3- This bioanalytical method is used to measure polatuzumab compartment model with a mixture of linear and non-linear vedotin given that not all the DAR species can be measured elimination pathways. Notably, three out of the seven ADCs accurately in the conjugated-antibody ELISA assay [26]. have non-linear time-dependent clearance and all of them In comparison, gemtuzumab ozogamicin does not measure target hematological malignancy (Table 1). The ADC linear ADC conjugate. Instead, gemtuzumab ozogamicin measured clearance (CL = 1.6–2.5 L/day) and central volume of distri- TAb and unconjugated calicheamicin [27, 28] likely due to bution (Vc = 6.4–6.7 L) are similar for brentuximab vedotin

1 3 746 Cancer Chemotherapy and Pharmacology (2021) 87:743–765 with a maximum of 180 mg for individuals with > 100 kg BW maximum of one 4.5 mg vial) on 1, 4, and 7 Days by followed day1 0.5 mg/m [ 2 ] on 8 and 15 Q3W days dosing regimen 1.8 mg/kg q3w, q3w, 1.8 mg/kg 3.6 mg/kg Q3W 3.6 mg/kg 3 mg/m [ 2 ] (with a 0.8 mg/m [ 2 ] on Clinical approved Clinical approved dose regimen = − = 18[11.2– * = 0.809 /F = 0.0262 des f des [0.001–0.0510] 0.261 (14%); beta = 0.0785 (12%) 25.0] [0.602–1.02] 1 day K K K cycle fm by Others : BMAR, BBC, : ALL, des des FIX) COMB BLSTPB (0.698)* SEX (0.503) FIX) FIX) ALL, RTX ECD, ALB, TMBD, TBL, AST DOSE, ALB FIX), DOSE, SEX, ALB CL/F: BW (0.75, CL/F: BW (1, FIX) V1/F: BW V1: BW (0.503), V1: BW V2, V3: BW CL: Q2, Q3, BW CL: Q2, Q3, BW V1, V2: BW (1, V1, V2: BW CL, Q: BW(0.75, CL, Q: BW(0.75, CL: BSA (1.54), CL: BSA (1.64) CL2: BSA V1: BSA; K CL: BW (0.49), CL: BW V1: BW Covariates^ CL: BW (0.75,FIX), CL: BW (0.75, V1: BW K

[90.1–104] [394–824] [6.40–7.00] [4.60–5.60] [3.08–3.174] [0.58–0.752] [5.86–6.68] [6.9–10.2] V1/F = 96.9 V2/F = 61.0 V1 = 4.29 (1.9%) V2 = 3.83 (6.3%) V3 = 9.52 (8.8%) V1 = 79.8 (11%) V2 = 28.1 (14%) V1 = 6.7 V2 = 5.10 V1 = 3.127 V2 = 0.66 V(L) V1 = 6.37 V2 = 8.58 39.1] Q/F = 68.9 [54.2–83.5] [2.54–2.88] [7.97–9.74] 1.11] 0.691] Q = 1.534 [1.286–1.83] [2.52–3.096] [39.1–92.9] 2.64] CL/F = 32.4 [25.7– CL = 1.56 (2.9%) Q2 = 2.83 (5.95) Q3 = 0.708 (8.2%) CL = 55.7 (5.2%) Q = 65 (30%) CL* = 2.71 CL2* = 8.86 Q = 0.972 [0.838– CL = 0.676 [0.661– Key populations parameters Key CL(L/day) CL* = 2.81 CL2* = 66 Q = 2.07 [1.51–

- st 1 Formation cycle LE + cycle dependent semi for mechanistic mation 3-COMP, LE 3-COMP, 2-COMP, 2-COMP, 2-COMP, 2-COMP, LE + TD 2-COMP, LE 2-COMP, 2-COMP, 2-COMP, LE + ­ Model description 2-COMP, 2-COMP, LE + TD ADC Unconjugated MMAE ADC ADC Calicheamicin Analyte TAb analyte (ADC- analyte unconjugated MMAE) model (joint model) with ADC con - jugate with ADC con - jugate unconjugated unconjugated calicheamicin) model Integrated two- One analyte model One analyte One analyte model One analyte Overall model Overall structure Two-analyte (TAb- Two-analyte Summary of population PK models of the seven approved ADCs approved Summary of population PK models the seven tin [ 29 ] gamicin [ 47 ] gamicin sine (T-DM1) [ 31 ] sine (T-DM1) gamicin [ 4 , 32 ] gamicin - vedo Brentuximab Inotuzumab ozo - Inotuzumab Trastuzumab emtan - Trastuzumab 1 Table ADC Gemtuzumab ozo -

1 3 Cancer Chemotherapy and Pharmacology (2021) 87:743–765 747 cycles 1, 8, 15 per 28 day 1, 8, 15 per 28 day with a maxi - cycle, mum of 125 mg for individuals with > 100 kg BW 1.8 mg/kg 1.8 mg/kg Q3W × 6 1.25 mg/kg on days on days 1.25 mg/kg Clinical approved Clinical approved dose regimen = 0.487 = 0.00053 ** = 0.11 max des des [0.035–0.62] ng/mL [ 31 ]; Km = 0.604 [0.175–1.03] ng/ mL; T50 = 3.53 {3.07–4] months; = 2.27 GAM [1.71–2.82] ] for additional [ 30 ] for information ­ K day1; CLINF. CLINF. day1; MAX = 0.223 [0.185–0.261]; ­ V {0.000444– 0.000737] Refer to Lu et al. et al. Lu to Refer = 3.8, DAR FIX; K Others : NAÏVE, CT : NAÏVE, des AGE, SEX, AGE, SOD; Q2, Q3: (0.65); V1: BW (0.59), SEX, BW SOD; V2: BW (0.59); V3: BW (0.59), CT FIX), ALB, Hgb, Bili; ECOG, (0.75, Q2: BW FIX); V1: BW (1, FIX), ALB; (1, FIX), V2: BW ALB, Hgb, Race, SEX FIX), SEX, OB, ALB, RTX, B-Cells, TMBD - TMBD, Thresh old, B-Cells NAÏVE (0.50, FIX); CL: BW (0.65), CL: BW CL: BW (0.75, CL: BW Covariates^ CLINF: BW (0.73, CLINF: BW NAÏVE, CLT: V1: SEX, ASIAN, Q, V1, V2: BW K

[69.1–95.4] [176–224] [3.62–3.87] [2.98–5.89] [2.70–3.08] [94.0–105] [107–130] [3.05–3.25] [1.75–4.2] V1 = 82.2 V2 = 200 V1 = 3.75 V2 = 4.54 V3 = 2.88 V1 = 99.3 V2 = 118 V(L) V1 = 3.15 V2 = 3.98 52.8] 2.57] Q2 = 0.0595 [0.0504–0.0701] Q3 = 0.895 [0.845–0.958] 69.1] Q2 = 365 [322–418] [0.77–0.88] = 0.15 CLT** [0.092–0.128] Q = 0.348 [0.33–0.367] CL = 45.4 [38.2– Q = 871 [660–1082] CL = 2.50 [2.42– CL = 65.8 [61.2– Key populations parameters Key CL(L/day) CLINF** = 0.83 formation, formation, LE + MM NLE LE + TD ELE + MM NLE 2-COMP, 2-COMP, L + NL 3-COMP, LE 3-COMP, 2-COMP, LE 2-COMP, Model description 2-COMP, TD 2-COMP, Unconjugated MMAE ADC Unconjugated MMAE Analyte acMMAE analyte (ADC- analyte unconjugated MMAE) model analyte model analyte (ADC-uncon - MMAE jugated model) Integrated two- Overall model Overall structure Integrated two- (continued) [ 21 ] tin [ 30 ] Enfortumab vedotin vedotin Enfortumab 1 Table ADC - vedo Polatuzumab

1 3 748 Cancer Chemotherapy and Pharmacology (2021) 87:743–765 - - Clinical approved Clinical approved dose regimen 5.4 mg/kg Q3W 5.4 mg/kg volume of the drug released volume a > c1 = 0.829 = 0.0159 frac rel [0.803–0.01721] [0.0146–0.172]; ­ K Others K trastuzumab emtansine, trastuzumab MMAE T-DM1 total antibody, apparent fraction of unconjugated calicheamicin that appears calicheamicin of unconjugated fraction /F apparent f SEX, JAP; V1: SEX, JAP; SEX; V2: BW, JAP ITRA, AST, BILI, AST, ITRA, FL-DP2, V: AGE; FL-DP1 every 3 weeks, 1, Q3W every after cycle itraconzaole, FL-DP1 itraconzaole, drug liquid 1, FL-DP2 frozen product fro Covariates^ CL: BW, ALB, TS, ALB, TS, CL: BW, CL: BW, RITO, RITO, CL: BW, rels K body surface area, BBC baseline peripheral area, body surface count, BMAR baseline blast BSA (FIX) BSA a 17 2.78] 5.97] fraction of ­ > c1 fraction V = ­ V(L) V1 = 2.78 [2.74– V2 = 5.17 [4.40– frac initial time-dependent clearance, after CLNS nonspecifc linear clearance dosing, repeated body weight, BSA body weight, 20.4] 0.434] Q2 = 0.200 [0.190–0.212] CL = 19.1 [17.8– Key populations parameters Key CL(L/day) CL = 0.42 [0.405–

st 1 decay coefcient associated with time-dependent CL, K decay des ritonavir, ITRA ​ ritonavir, country non-japanese), RITO (japanese vs the deconjugation rate for DXd, K DXd, for rate the deconjugation rels formation Model description 2-COMP, LE 2-COMP, 1-COMP, 1-COMP, LE + ­ tumor size, JAP Eastern Cooperative Oncology Group per Oncology Group Eastern CT cancer type, ECOG Cooperative naïve, rituximab,treatment OB obinutuzumab, B-Cells B-cell count, NAÏVE Analyte ADC DXd deruxtecan, 2-comp 2-compartment,- 3-comp 3-compartment, ELE exponen LE linear elimination, NLE non-linear TD time-dependent clearance, the deconjugation rate for acMMAE, K for rate the deconjugation dec analyte (ADC- analyte unconjugated model DXd) Overall model Overall structure Integrated two- sum of tumor diameter, RTX SOD sum of tumor diameter, AST aspartate lesions, dimension of target ami - BLSTPB in peripheral TMBD baseline sum of longest concentration, of blasts baseline percentage blood, TBL baseline trastuzumab volume of distribution in peripheralV2 or V3 volume compartment, ALB basesline albumin, BW (continued) tecan [ 25 ] CL = CL1 + CL2 * + Vmax*V1/(Km C) exp(-kdes*time). + TGAM)) + CLINF*(1 CLINFEMAX*T50GAM/(T50GAM **CL = CLT*EXP(-KDES*T)

zen liquid drugzen liquid 2, K product acute lymphocytic ALL acute lymphocytic domain concentration, ECD baseline serum 2 shed extracellular receptor human epidermal factor growth combination therapy, COMB in bone marrow, blast percentage leukemia, notransferase, hemoglobin, Bili bilirubin, Hgb hemoglobin, score, formance TS Typical value [95% CI] or typical value (%RSE); ^covariates provided for CL and V parameters only CL and V parameters for provided (%RSE); ^covariates [95% CI] or typical value value Typical TAb payload), as conjugated MMAE (measured ADC antibody–drug antibody), acMMAE conjugated as conjugated (measured conjugate monomethyl auristatin E, DXdmonomethyl compartment, central from CL linear clearance CLTtial linear elimination, MM Michaelis–Menten, Q or Q2 Q3 intercompartmental of distribution intercompartmental Q/F apparent clearance, CL/F apparent com - clearance, in central V1 volume clearance, CLINF CLNS at time of infnity, partment, in circulation following release from gemtuzumab ozogamicin, K ozogamicin, gemtuzumab from release following in circulation * 1 Table ADC Trastuzumab derux - Trastuzumab was not estimable from current data so it was fxed to 17 L/m2 (literature documented volume of distribution of exatecan mesylate DX-8951f) and multiplied by individual body surface area individual body surface and multiplied by DX-8951f) mesylate of distribution of exatecan documented volume 17 L/m2 (literature to current fxed from estimable not data so it was was

1 3 Cancer Chemotherapy and Pharmacology (2021) 87:743–765 749 and enfortumab vedotin, the MMAE-containing ADCs that been discussed previously [33, 34]. Consistent with other share the same cytotoxic drug and linker but against diferent biotherapeutics, baseline albumin and disease factors (e.g., targets [21, 29]. Polatuzumab vedotin is not included in the tumor burden) were often identifed as signifcant covariates comparison due to apparent non-linear and time-dependent for ADC clearance, however, the magnitude of the efect of PK [30]. Conversely, T-DM1 and trastuzumab deruxtecan, these signifcant covariates on ADC exposure is minimal both of which share the same mAb but with diferent cyto- compared with overall PK variability and therefore the BW- toxic drugs and linkers, exhibited linear PK with similar and BSA- based dose without further adjustment for other CL (0.4–0.7 L/day) and central volume of distribution (~ 3 factors is considered appropriate for ADCs. L) at the clinical approved dose [23, 31]. As expected for small molecules, the unconjugated payloads released from ADCs exhibit faster apparent clearances (> 19 L/day) from Organ dysfunction studies circulation with larger apparent central volume of distribu- tion (> 80 L) into extravascular tissues compared to the ADC The general concept that hepatic impairment may not afect or TAb. For MMAE-containing ADCs, the MMAE appar- therapeutic proteins PK, including mAbs and ADCs, is being ent clearance and apparent central volume of distribution is challenged with emerging evidence [34]. Recent publica- 45–66 L/day and 80–99 L, respectively. The calicheamicin tion by Sun et al. showed that of 20 mAbs and 4 ADCs with analyte was not characterized in the population PK model hepatic impairment data, a decrease in exposure of 1 mAb for inotuzumab ozogamicin so PK parameters for the pay- and 2 ADCs were observed in patients with hepatic impair- load were not available for comparison, but for gemtuzumab ment. Although the mechanism is unknown, Sun et al. pro- ozogamicin, unconjugated calicheamicin CL/F was 32 L/day poses worsening of disease associated with hepatic impair- and V1/F was 97 L [32]. For trastuzumab deruxtecan, the ment may increase the elimination of therapeutic proteins unconjugated DXd clearance (CL = 19 L/day) was the lowest through increased competition of FcRn binding with other for the payloads and the central volume was not estimable soluble proteins (i.e. albumin) and target mediated drug dis- with data collected so it was fxed to nonclinical data in the position. In addition, the liver and kidneys play an impor- population PK model [25]. tant role in elimination of the small-molecule component of The covariate efects from body weight (BW) or body an ADC, namely cytotoxic drug once it gets released from surface area (BSA) is consistently identifed as one of sig- the ADC. As a result, impairment of the functions of these nifcant covariates on key PK parameters (i.e., CL and/or organs may result in alteration of ADC and/or cytotoxic drug Vc) in the fnal popPK models for all the approved ADCs. clearance, leading to exposure changes, which may in turn The exponential of BW efect on CL ranged from 0.49 to impact the safety and efcacy. This is especially important 0.75, thus supporting the BW- and BSA- based dosing strat- given ADCs generally have a relatively narrow therapeutic egy for ADCs. It was worth noting that BW and BSA were index. Therefore, assessment of the impact of organ dysfunc- highly correlated, of these two covariates, BW is usually tion on the disposition of ADCs to inform appropriate dos- preferred to be included in the model as it is the simpler ing in these patients is an important component of clinical measure to obtain. Six out of the seven approved ADCs iden- pharmacology strategy for these molecules. tifed BW as a signifcant covariate in their population PK Table 2 summarizes the impact of liver and kidney func- model except inotuzumab ozogamicin which included BSA tion on ADCs PK and their corresponding dosing recom- (Table 1). Among the seven approved ADCs, fve of them mendation for the seven approved ADCs. It is noted that two utilized BW-based dosing regimen with the two calicheam- alternative approaches were used to characterize the impact icin-containing ADCs using BSA-based dosing. Since these of organ dysfunction on ADC PK across the seven approved agents have relatively narrow therapeutic windows, some of ADCs (1) a dedicated organ dysfunction clinical study or (2) the ADCs (i.e., brentuximab vedotin, enfortumab vedotin) model-based approach using patients with organ dysfunction adopted dose capping strategy to further reduce inter-indi- across clinical studies to determine the efects of clinical PK. vidual variability for the ADC exposure and thus potentially As shown in Table 2, three out of seven ADCs conducted improve the ADC’s safety profles, particularly for patients dedicated hepatic and/or renal impairment clinical studies: with higher BW (i.e., BW > 100 kg) that would achieve brentuximab vedotin, T-DM1, and enfortumab vedotin. higher drug exposure from a weight-based dosing regimen While for the remainder of ADCs, modeling and simulation [21, 22]. Notably, no signifcant PK diferences based on through popPK has been utilized to assess the organ dys- age was observed. Some diferences in PK parameters with function subpopulation across clinical studies. The current gender was observed, but post-hoc analyses showed it did ADC model-based approach requires that existing clinical not have any clinical meaningful efect on ADC exposures studies allow enrollment of patients with organ impairment. and thus did not warrant dosing adjustment based on gender. ADC conjugate exposure was generally comparable The impact of extrinsic and intrinsic factors on ADC PK has between patients with hepatic impairment and normal

1 3 750 Cancer Chemotherapy and Pharmacology (2021) 87:743–765 Avoid Avoid Severe Moderate Approved dose Approved Approved dose Approved Label recommendation Mild - - efect in mild ( n = 4) or moder ate ( n = 3) renal impairment; GMR 0.71 AUC (90% CI 0.54– 0.94) in severe impairmentrenal ( n = 3) efect in mild ( n = 4) or moder ate ( n = 3) renal impairment; GMR 1.90 AUC (90% CI 0.85– 4.21) in severe impairmentrenal ( n = 3) mild ( n = 149) or ( n = 47) moderate impairmentrenal ADC: No PK ADC: No MMAE: No PK MMAE: No No PK efect in No Result CrCL Clinical Study: Clinical Study: PopPK: CrCL PopPK: Renal impairmentRenal Approach Severe Avoid Moderate Not studied Not 1.8—> 1.2 mg/kg Label recommendation Mild Approved dose Approved - GMR 2.29 (90% CI 1.27–4.12) hepatic any for impairment ( n = 7) 0.67 (90% CI 0.48–0.93) for hepatic any impairment ( n = 7) ment mild ( n = 58) or ( n = 6) moderate hepatic impair MMAE: AUC MMAE: AUC ADC: AUC GMR ADC: AUC Result No PK efect in No Child–Pugh criteria Clinical study: Clinical study: Approach Hepatic impairment PopPK: NCI NCI PopPK: Efect of hepatic and renal impairment on ADC PK and dose recommendation for the seven approved ADCs approved the seven impairmentEfect of hepatic and renal for on ADC PK and dose recommendation tin [ 5 , 36 ] gamicin [ 4 , 32 ] gamicin - vedo Brentuximab 2 Table ADC Gemtuzumab Ozo -

1 3 Cancer Chemotherapy and Pharmacology (2021) 87:743–765 751 Not studied Not Not studied Not Severe Moderate Approved dose Approved Approved dose Approved Label recommendation Mild Approved dose Approved in mild ( n = 161) or moderate ( n = 109) renal impairment efect on PK in mild ( n = 237), moderate ( n = 122), or ( n = 4) severe impairmentrenal mild ( n = 254) or ( n = 53) moderate impairmentrenal No efect on PK No ADC only: No No ADC only: Result No efect on PK in No PopPK: CrCL PopPK: PopPK: CrCL PopPK: Renal impairmentRenal Approach PopPK: CrCL PopPK: Severe Not studied Not Avoid Not studied Not Moderate Approved dose Approved Approved dose Approved Label recommendation Mild Approved dose Approved - - 40% higher and Cmax 37% for in mild hepatic impairment ( n = 54); insuf - - fcient informa tion in moderate ( n = 2) and severe ( n = 0) hepatic impairment rable exposure rable not impacted by by impacted not mild ( n = 150), ( n = 3), moderate ( n = 1) or severe hepatic impair ment cycle 1 was 38% 1 was cycle in and 67% lower the mild ( n = 10) and moderate ( n = 8) hepatic impairment and 3 at cycle AUC within range was of normal hepatic function ment containing catabolites: low and comparable with or without hepatic impair MMAE: AUC was was MMAE: AUC - acMMAE: compa ADC only: CL ADC only: Result T-DM1: AUC at AUC T-DM1: DM1 and DM1- criteria criteria Child–Pugh PopPK: NCI NCI PopPK: PopPK: NCI NCI PopPK: Approach Hepatic impairment Clinical study: Clinical study: (continued) tin [ 10 , 28 ] gamicin [ 6 , 24 ] gamicin emtan - sine (T-DM1) [ 8 , 37 ] - vedo Polatuzumab Inotuzumab ozo - Inotuzumab 2 Table ADC Trastuzumab Trastuzumab

1 3 752 Cancer Chemotherapy and Pharmacology (2021) 87:743–765

hepatic function for most of the approved ADCs, except for brentuximab vedotin and T-DM1 (Table 2). For bren- tuximab vedotin, ADC conjugate exposure (i.e., AUC) Not studied Not Severe decreased by 35% in lymphoma patients with moderate hepatic impairment, and there was only one patient each with mild or severe hepatic impairment [35]. For T-DM1, Moderate AUC of T-DM1 conjugate at Cycle 1 in patients with mild and moderate hepatic impairment were approximately 38% and 67% lower than that of patients with normal hepatic function, respectively [36]. Interestingly, the exposure Approved dose Approved Approved dose Approved Label recommendation Mild diference was less apparent after repeated dosing with T-DM1 AUC at Cycle 3 in patients with mild and moderate National Cancer Institute National hepatic impairment largely comparable to the patients with normal hepatic function. There was no apparent efect of hepatic impairment on the cytotoxic drug exposure except for brentuximab vedotin (unconjugated MMAE AUC mild ( n = 206) or ( n = 58) moderate impairmentrenal mild ( n = 135), moderate ( n = 147), or ( n = 8) severe impairmentrenal No efect on PK in No No efect on PK in No Result GMR 2.29 for any hepatic impairment vs normal hepatic function) and polatuzumab vedotin (unconjugated MMAE AUC GMR 1.40 for mild hepatic impairment vs normal hepatic function) [26, 36]. The fact that the exposure of unconjugated MMAE was increased by two-to-threefold in moderate hepatic impaired patients resulted in label CrCL and PopPK:CrCL PopPK: CrCL PopPK: Clinical Study: Clinical Study: Renal impairmentRenal Approach recommendation for brentuximab vedotin to avoid use in patients with moderate to severe hepatic impairment [5]. The comparable unconjugated DM1 exposure and transient change of T-DM1 conjugate exposure in mild or moder- Not studied Not Severe ate hepatic impairment lead to label recommendation of no adjustments of the dose of T-DM1 in these patients [8, 37]. Although an increase in unconjugated MMAE expo- Moderate Avoid sure for polatuzumab vedotin was observed, based on the exposure-safety relationship established across clinical studies, the increased unconjugated MMAE exposure was not clinically relevant and no adjustment in the starting dose is required for polatuzumab vedotin in patients with mild hepatic impairment [26]. Approved dose Approved Label recommendation Mild Approved dose Approved For patients with renal impairment, ADC conjugate and - - cytotoxic drug PK are comparable for most of the approved ADCs, except for brentuximab vedotin in patients with severe renal impairment (ADC AUC GMR 0.71 and MMAE AUC GMR 1.90) (Table 2) [36]. The altered PK in brentuxi- ment in mild ( n = 215) hepatic impair ment in mild ( n = 31) hepatic impair mab vedotin results in label recommendation to avoid use in No efect on PK No Result No efect on PK No patients with severe renal impairment [5]. The approach to evaluate organ dysfunction for ADC drug development remains situation dependent, but is trend- ing toward a modeling and simulation approach. The popu- lation PK approach is routinely conducted to evaluate the criteria criteria PopPK: NCI NCI PopPK: Approach Hepatic impairment PopPK: NCI NCI PopPK: impact of organ dysfunction on the exposure of ADC and its relevant analytes. If there is an impact on the exposure, such - an impact on dose recommendation should be assessed in the context of beneft risk assessment and/or exposure–response (continued) relationship. In the future, physiologically based pharma- cokinetic (PBPK) modeling approach may be used to assess uxtecan [ 7 , 25 ] tin [ 9 , 21 ] trastuzumab emtansine, trastuzumab DM1 emtansine, MMAE T-DM1 payload), as conjugated MMAE (measured ADC antibody–drugantibody), acMMAE conjugated as conjugated (measured conjugate population pharmacokinetics,NCI auristatin MMAE, PK pharmacokinetics,PopPK clearance, E, acMMAE conjugated CrCL creatinine monomethyl Trastuzumab der Trastuzumab 2 Table ADC - vedo Enfortumab the impact of organ dysfunction on ADC PK once the ADC

1 3 Cancer Chemotherapy and Pharmacology (2021) 87:743–765 753

PBPK model and organ dysfunction patient population is in the labeling statement such as, “at clinical relevant con- fully established. centrations, the payload has no or low potential to inhibit the CYP enzymes and/or transporters”. In vitro studies showed that MMAE and DM1 exhibited time-dependent Drug–drug interactions and/or competitive inhibition of CYP3A with K­ i values in the micromolar range, however, the systemic levels of Assessing drug–drug interaction (DDI) risk associated MMAE and DM1 released after administration of brentuxi- with ADCs needs to consider both the large- and small- mab vedotin and T-DM1 at their clinically approved doses molecule components of the ADC. The cytotoxic payloads, are only in the nanomolar range [22, 23]. Consistent with upon release from ADCs, are expected to behave like small these observations, a dedicated clinical DDI study showed molecules and thus may be of concern for enzyme or trans- that co-administration of brentuximab vedotin did not afect porter-mediated DDIs. The FDA and European Medicines exposure to midazolam, a sensitive CYP3A substrate [38]. Agency (EMA) have issued comprehensive recommenda- PBPK modeling by integrating the in vitro DDI and clini- tions for in vitro and in vivo studies to evaluate DDI poten- cal data further confrms the low risk of MMAE for being tial for small molecules, but specifc guidelines on DDI a perpetrator for CYP3A substrates. The prediction results risk assessment for ADCs have not been issued. Given the were highlighted in polatuzumab vedotin prescribing infor- relatively high potency and low systemic exposure of cyto- mation [10]. toxic payloads, some unique DDI consideration might be In contrast, the potential for a released payload to be a needed for ADCs. Diferent from other molecules, human DDI victim still exists, which could possibly impact safety mass balance study is usually not conducted for most of the as these payloads are highly potent and typically have a nar- approved ADCs (6 out of 7 approved ADCs). Brentuximab row or even no therapeutic window. As shown in Table 3, vedotin is the only ADC that conducted a clinical excretion three out of the four payloads for the approved ADCs are study but without complete recovery [21]. Instead, leverag- metabolized by CYP3A with the exception of calicheam- ing preclinical ADME data is the main strategy for initial icin. In the case of calicheamicin, it has been shown that DDI assessment of ADCs. N-acetyl gamma calicheamicin dimethyl hydrazide, the main DDIs related to the payload have been extensively evalu- circulating catabolite, is extensively metabolized, primar- ated during the clinical development of an ADC. Table 3 ily via non-enzymatic reduction of the disulfde moiety, but summarizes the approaches, key fndings and its implication not CYP enzymes, thus DDI risk for N-acetyl gamma cali- on the drug label of payload-mediated DDIs for the seven cheamicin dimethyl hydrazide as a victim of metabolizing approved ADCs, which include four diferent payloads: cali- enzymes is considered low and no additional assessment cheamicin, MMAE, DM1, and DXd. Multiple approaches, was conducted. Dedicated clinical studies were conducted namely dedicated clinical DDI study, theoretical risk assess- for brentuximab vedotin and trastuzumab deruxtecan to ment, physiologically based pharmacokinetic (PBPK) assess the DDI risk for the released payload as a victim. model, concomitant medication analysis, and referencing Low magnitude of DDI interaction for MMAE and DXd existing DDI data from a previously established ADC were was observed when co-administration with strong CYP3A used for DDI risk assessment. Theoretical risk assessment inhibitors and inducers. Co-administration of trastuzumab based on the in vitro DDI and clinical data is the most com- deruxtecan with itraconazole (a strong CYP3A inhibitor) monly used approach for the 7 ADCs (Table 3). Dedicated and ritonavir (a dual inhibitor of OATP1B/CYP3A) resulted clinical DDI studies were conducted for two out of the seven in an 18% and 22%, respectively, increase in steady-state ADCs: brentuximab vedotin and trastuzumab deruxtecan. exposure of DXd [25]. The magnitude of these changes is PBPK modeling approach by leveraging available clinical not considered clinically meaningful. In the case of brentuxi- DDI data for the same payload was used to inform DDI risk mab vedotin, co-administration with ketoconazole, strong for polatuzumab vedotin, while exploratory concomitant CYP3A inhibitor, and rifampin, strong CYP3A inducer, medications analysis using NCA or population PK of clini- increased MMAE exposure by ~ 34% and decreased MMAE cal data to evaluate the efect of concomitant medications exposure by ~ 46%, respectively [38]. As increased exposure on payload PK was used for T-DM1. to MMAE may increase the risk of adverse reaction, close Given low systemic concentrations of released pay- monitoring of adverse reactions is recommended when bren- loads relative to its in vitro ­Ki/IC50 values of metabolizing tuximab vedotin is given concomitantly with strong CYP3A enzymes and/or transporters, the risk for a payload to be a inhibitors [5]. Instead of conducting a clinical DDI study, perpetrator of metabolizing enzymes and/or transporters is polatuzumab vedotin, an MMAE-containing ADC with the considered to be low. As shown in Table 3, most of these same linker and payload as brentuximab vedotin, adopted assessments are based on the theoretical risk assessments a PBPK approach to project the magnitude of DDI with using the in vitro DDI and clinical data, which often results strong CYP3A inhibitors and inducers. The PBPK model

1 3 754 Cancer Chemotherapy and Pharmacology (2021) 87:743–765 strong CYP3A4 inhibi - strong or inducers, tors has the inhibitors, P-gp afect the to potential MMAE to exposure strong CYP3A4 inhibi - strong should be avoided tors thefor due to potential in DM1 an increase and toxicity. exposure be avoided, If cannot consider delaying until TDM1 treatment cleared. are inhibitors closely delay, If cannot adverse for monitor reactions Concomitant use of No recommendation No No recommendation No Concomitant use of Label Recommendation no other CYP isoforms. no other CYP isoforms. major induce any Did not CYP450 enzymes in pri - mary of human cultures hepatocytes and UGT at physiologic at physiologic and UGT concentrations efect on CYP3A4; no inhibition on CYP1A2, CYP2B6, UGT1A4, UGT1A9, UGT1A6, UGT2B7 CYP2B6, CYP3A4/5; no inhibition on CYP1A2, CYP2B6, CYP2C8, CYP2C9, CYP2C19, be time- CYP2D6; may of dependent inhibitor CYP3A4 (CYP3A4 substrate) (CYP3A4 substrate) exposure Inhibits CYP3A4/5 but No inhibition on CYP450 No Inhibits UGT1A1; no Inhibits UGT1A1; No induction on CYP1A2, No Enzyme No efect on midazolam No inhibit P-gp, inhibit P-gp, OATP1B1, BCRP, OAT1, OATP1B3, and OCT2 OAT3, OATP1B3; no efect OATP1B3; BCRP, on P-gp, or OAT3, OAT1, OCT2 NA Low potential to to potential Low Inhibits OATP1B1- Inhibits OATP1B1- NA Perpetrator Transporter NA by by 0-INF 0-INF (CYP3A4/P-gp (CYP3A4/P-gp increased inhibitor) ​ MMAE AUC tion; expect no efect tion; expect CYP or UGT from perpetrators (inhibi - or inducers) on tors drug CL tion; expect no efect tion; expect CYP or UGT from perpetrators (inhibi - or inducers) on tors drug CL CYP3A4/5; no efect CYP1A2, from CYP2A6, CYP2B6, CYP2C19, CYP2C8, CYP2C9, CYP2D6 inhibitors 34% gp inducer) decreased ​ MMAE AUC 46% Ketoconazole Ketoconazole Substrate of CYP3A4/5 Substrate - reduc Non-enzymatic - reduc Non-enzymatic Substrate of Substrate Enzyme Rifampin (CYP3A4/P- Rifampin BCRP, OATP1B1, or OATP1B1, BCRP, OATP1B3 NA P-gp substrate P-gp P-gp substrate, but not for for but not substrate, P-gp NA NA Victim Transporter (rats) Clinical study In vitro In vitro Approach In vitro, in vivo in vivo In vitro, In vitro MMAE Calicheamicin Payload Calicheamicin DM1 Payload-mediated DDI and its impact on drug label for the seven approved ADCs approved the seven on drug DDI and its impact label for Payload-mediated vedotin [ 5 , 38 ] vedotin gamicin [ 6 , 24 ] gamicin ozogamicin [ 4 , ozogamicin 28 ] emtansine [ 8 , 40 ] (T-DM1) Brentuximab Brentuximab Inotuzumab ozo - Inotuzumab 3 Table Molecule Gemtuzumab Trastuzumab Trastuzumab

1 3 Cancer Chemotherapy and Pharmacology (2021) 87:743–765 755 - are recommended for for recommended are drug-drug- interac monitor tions. Closely signs of toxicity for in patients taking concomitant strong as CYP3A4 inhibitors, increased potentially of exposure systemic increase MMAE may the incidence or sever toxicity ity of PADCEV strong CYP3A inhibi - strong or inducers has thetors afect the to potential MMAE to exposure No dose adjustments dose adjustments No Concomitant use of Label Recommendation tor of tor CYP1A2, CYP2B6, or CYP3A4/5 tor of CYP3A4; No of CYP3A4; No tor inhibition on CYP1A2, CYP2B6, CYP2C8, CYP2C9, CYP2C19, or induction CYP2D6; No CYP enzymes on major on midazolam (CYP3A exposure substrate) Mechanism-based inhibi - Mechanism-based of CYP3A4/5; No Time dependent inhibi - Time MMAE showed no impact no impact MMAE showed Enzyme MRP2, OCT1, OAT3, OCT2, OAT1, OATP1B3 P-gp Not an inhibitor of an inhibitor Not BCRP, P-gp, BSEP, or OATP1B1, Not an inhibitor of an inhibitor Not NA Perpetrator Transporter by 18% by max by 41% by ­ C max inhibitor) increased increased inhibitor) 45% by MMAE AUC and inducer) decreased inducer) decreased 63% and by AUC ­ C Substrate of CYP3A Substrate Fluconazole (CYP3A Substrate of CYP3A Substrate Rifampin (CYP3A Rifampin Enzyme for BCRP, MRP2, BCRP, for OCT2, and OATP1B1/3, OAT1/3 P-gp substrate, but not but not substrate, P-gp NA P-gp substrate P-gp Victim Transporter In vitro Approach PBPK model In vitro MMAE Payload MMAE (continued) tin [ 9 , 20 ] vedotin [ 10 , 39 ] vedotin - vedo Enfortumab 3 Table Molecule Polatuzumab Polatuzumab

1 3 756 Cancer Chemotherapy and Pharmacology (2021) 87:743–765

was developed using in silico and in vitro data and in vivo ADME and pharmacokinetic data of MMAE and a vc- MMAE ADC and subsequently verifed by the clinical DDI data of brentuximab vedotin [39]. The model projections were used to inform polatuzumab vedotin prescribing infor- mation. A slightly diferent approach was used for enfor-

needed for patients who needed for co-administered are with OATP1B CYP3A, inhibitors or P-gp tumab vedotin, another MMAE-containing ADC, where its No dose adjustment is dose adjustment No Label Recommendation prescribing information simply refers to the clinical DDI results for brentuximab vedotin. For T-DM1, concomitant uridine glucuronosyltransferase, uridine glucuronosyltransferase, medication analysis with the Phase III pivotal clinical study showed that co-medication of CYP3A inhibitors and induc- ers does not result in any noticeable change in the phar- macokinetics of T-DM1 and DM1 [40]. However, given a dedicated clinical study was not conducted, caution language

CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6 and CYP3A; induction of No CYP1A2, CYP2B6, or CYP3A with detailed instructions was included in the T-DM1 label. No inhibition of CYP1A2, No NA Enzyme Assessing DDI risk associated with the mAb component of ADCs is often relatively rare since DDI involving mAbs are typically limited. Population PK approach is commonly used for such a DDI assessment. Population PK analysis of inotuzumab ozogamicin identifed concomitant rituximab treatment as one of the signifcant covariates on inotuzumab

OAT1, OAT3, OCT1, OAT3, OAT1, OCT2, OATP1B1, MATE1, OATP1B3, P-gp, MATE2-K, or BSEP BCRP, transporters ozogamicin clearance (CL decreased by 16%). Similarly, Low potential to inhibit to potential Low NA Perpetrator Transporter population PK analysis with polatuzumab vedotin, which is approved for the treatment of r/r DLBCL in combination with rituximab and bendamustine, showed that combina- tion with rituximab had 24% higher acMMAE exposure (ie,

by 11% for 11% for by AUC) and 37–40% lower exposure of unconjugated MMAE compared to patients receiving single-agent [26]. There was inhibitor) increased increased inhibitor) ​ AUC steady-state ADC and 18% for ADC and 18% for DXd 0-17 days no apparent impact of bendamustine on polatuzumab vedotin Substrate of CYP3A4 Substrate Itraconazole (CYP3A Itraconazole Enzyme

breast can - BCRP breast P-glycoprotein, based pharmacokinetic model, P-gp PBPK physiologically available, not and MMAE PK. It is worth noting that the magnitude of DDIs seen with concomitant medications was small and was not considered clinically relevant. Therefore, no dose adjust- ment is recommended for inotuzumab ozogamicin or polatu- - of fam-tras zumab vedotin in concomitant treatment with rituximab. In summary, given the complex structure and unique 0-17 days

​ UGT P450 enzymes, BSEP bile salt export pump, anion transporter 3, CYP cytochrome organic PK characteristics of an ADC, risk-based DDI strategy by CYP3A inhibitor) CYP3A inhibitor) steady-state increased ​ AUC but not for OATP1B3, OATP1B3, for but not MRP1 P-gp, MATE2-K, and BCRP tuzumab deruxtecan-nxki 22% by 19% and DXd by integrating both large and small-molecule components of Ritonavir (OATP1B/ Ritonavir OATP1B1 substrate, substrate, OATP1B1 Victim Transporter

clearance, NA CL clearance, exactecan, an ADC is warranted to support the clinical development and approval of an ADC. Theoretical risk assessment using in vitro DDI and clinical data should be conducted based on FDA and EMA DDI guidelines. Depending on the level of risk, diferent approaches may be implemented to fur- Approach Clinical study In vitro ther assess the DDI potential. Modeling based approaches such as population PK and PBPK modeling, have become increasingly accepted and used to support DDI assessment organic anion transporter 1, OAT3 organic and regulatory submission for ADCs. Payload DXd

- QTc assessment

(continued) According to the ICH E14 [41] guidelines, it is generally recommended to evaluate the potential of non-antiarrhyth- uxtecan [ 7 , 24 ] organic OCT2 organic anion transporting polypeptide, organic OATP1B3 1B1, anion transporting polypeptide organic MRP2 multidrug 2, OATP1B1 cer resistance protein, resistance-associated protein cation transporter 2, OAT1 Molecule auristatin E, DM1 emtansine,DXd MMAE monomethyl 3 Table 2-K extrusion multidrug protein 1, MATE2-K and toxin multidrugextrusion protein MATE1 and toxin Trastuzumab der Trastuzumab mic drugs, such as ADCs to prolong the QT/QTc intervals

1 3 Cancer Chemotherapy and Pharmacology (2021) 87:743–765 757 in clinical development. A thorough QT study for an ADC Overall, QTc risk for ADCs is expected to be low given is usually not feasible due to safety concerns on cytotox- the mAb component of the ADC and low levels of circulat- icity of released payloads in healthy subjects and ethical ing payloads. Leveraging preclinical and clinical data such concerns regarding a placebo arm in cancer patients. As an as in vitro hERG test, cardiac safety data in animals and alternative, a clinical study that incorporates many of the key the level of circulating payload, is important for developing components of the thorough QT study is usually needed for appropriate ECG strategy in clinical studies. Additionally, an ADC, especially when there is evidence suggesting that ECG monitoring may not be warranted for ADCs with the the small-molecule component of the ADC or its catabolites circulating concentrations of the released payload similar are present in human systemic circulation. or lower than those established as having no QT efect. Table 4 summarizes the approaches and results of QT Although dedicated QT studies have been conducted for the assessment for the seven approved ADCs. In general, these 4 approved ADCs, increasing trends showed that integrating seven ADCs did not show clinically meaningful impact high-quality ECG monitoring and exposure-QTc analysis to on QTc prolongation, which is somewhat expected as the the existing phase I and/or II studies could be an efective mAb component of the ADC is unlikely to interact with the way to assess overall risk and meet regulatory submission human Ether-à-go-go-Related Gene (hERG) channel and the requirements. low concentrations of circulating payload after ADC dosing is unlikely to inhibit hERG channels in vivo. A dedicated clinical QT study was conducted for four out of the seven Exposure–response (ER) modeling ADCs. The study design for brentuximab vedotin, T-DM1, and trastuzumab deruxtecan are similar, which involved a Given a relatively narrow therapeutic window of ADCs [13] dedicated QT study collecting triplicate 12-lead ECG data compared to mAbs, exposure–response (ER) analysis plays with time-matched PK samples in ~ 50 cancer patients at a critical role for supporting Phase II/III dose selection, a single dose level (i.e., clinical approved dose for bren- label dose justifcation and guidance of dose adjustment for tuximab vedotin and T-DM1; a dose higher than clinical ADCs. Gemtuzumab ozogamicin dose is one of the exam- approved dose for trastuzumab deruxtecan). Gemtuzumab ples highlighting the importance of ER analysis for selecting ozogamicin dedicated QT study is still ongoing (n = 56, appropriate dose and schedule. Gemtuzumab ozogamicin NCT03727750). In comparison, inotuzumab ozogamicin, was frst granted an accelerated approval in 2000 as a mono- polatuzumab vedotin and enfortumab vedotin adopted a therapy with dose of 9 mg/m2 for the treatment of patients slightly diferent approach, instead of conducting a dedi- with CD33 positive acute myeloid leukemia, however, the cated QT study, high-quality triplicate 12-lead ECG and sponsor withdrew gemtuzumab ozogamicin from the market time-matched PK samples were integrated in existing clini- in 2011 as the confrmative study failed to demonstrate bet- cal Phase I and/or Phase II studies. Data pooled from one ter efcacy but showed higher rates of fatal hepatotoxicity or multiple studies with ~ 17–250 cancer patients were used and veno-occlusive disease (VOD). Exploratory ER analyses for QT assessment. It was noted that the majority of the of gemtuzumab ozogamicin using data from single agent approved ADCs had QT evaluation during cycles 1 and 3 of 9 mg/m2 dose showed that the risk for VOD increases as representative of frst dose and steady-state kinetics, except Cmax after frst dose of gemtuzumab ozogamicin increases, for enfortumab vedotin. Due to enfortumab vedotin’s short while exposure-efcacy (i.e., complete remission) relation- half-life (3.4 days for ADC; 2.4 days for MMAE) and dos- ship, however, was relatively fat for any exposure meas- ing on Days 1, 8 and 15 of a 28-day cycle (see Table 4), ure including Cmax after frst dose, indicating a fractionated triplicate 12-lead ECGs were collected on days 1 and 3 and lower dose may have the potential to reduce the risk for VOD days 15 and 17 during the frst 28-days cycle to capture the but preserve the efcacy of gemtuzumab ozogamicin. Recent QTc efects at frst dose and steady-state kinetics, respec- positive study read-out with fractionated dosing of 3 mg/m2 tively. Regardless of the study approaches, analysis of ECG confrmed the above hypothesis and demonstrated improved data from clinical studies typically follows the ICH E14 [41] clinical beneft with reduced VOD risk, thus leading to the guidelines. For the seven approved ADCs, QT intervals cor- re-approval of gemtuzumab ozogamicin in 2016 [42, 43]. rected for heart rate using Frederica’s formula (QTcF) are One of unique features of ADC ER analysis which is dif- commonly used in concentration-QTc analysis. Three ana- ferent from other therapies, is that it requires comprehen- lytes (i.e., ADC conjugate, total antibody and unconjugated sive understanding which analyte(s) are the key drive for payload) were included in the concentration-QTc analysis efcacy and safety due to the complex structure of ADCs. for T-DM1, inotuzumab ozogamicin, polatuzumab vedotin Based on the mechanism of action, ADC conjugate, meas- while two analytes (i.e., ADC conjugate and unconjugated ured as conjugated antibody or conjugated payload, is gener- payload) used for brentuximab vedotin, enfortumab vedotin, ally believed to be the key analyte of interest to drive safety trastuzumab deruxtecan (Table 4). and efcacy for an ADC. However, it is worth noting that

1 3 758 Cancer Chemotherapy and Pharmacology (2021) 87:743–765 - avail not 20 ms) 20 ms) on the QTc interval in 20 ms) on the QTc > QTcF QTcF (< 10 ms) large QTc prolongation (> prolongation QTc large TD (6.4 mg/kg every 3 weeks, which which 3 weeks, every TD (6.4 mg/kg is 1.2 times the dos - recommended mean efect large show did not age) (i.e., an open label, single-arm in 51 study patients with HER2-expressing mBC QTcF QTcF (< 10 ms) QTcF (< 10 ms) observed in patients treated with in patients treated observed other drugs containing calicheamicin QTcF (< 10 ms) Label recommendation No clinically meaningful change in meaningful change clinically No At the dose, EV had no recommended At The administration of multiple doses The administration No clinically meaningful change in meaningful change clinically No in meaningful change clinically No QT interval prolongation has been QT interval prolongation in meaningful change clinically No in single and divided in single 2 IV given on days 1, 4, and 7 on days IV given 2 days 1 and 8 (cycle 1 only) of cycles of cycles 1 only) 1 and 8 (cycle days 1 and 3 15 (3 doses) per cycle QTcF evaluated evaluated QTcF 15 (3 doses) per cycle 1, 3, 15, 17 on days 1 and 3 days 2,3,4 of cycles 1 and 3 2,3,4 of cycles days 1 and 3 2, 3, 4 of cycles on days (3 doses) per cycle QTcF evaluated evaluated QTcF (3 doses) per cycle and 7 of 1 only) 1, 4 (cycle on days 1 and 2 cycles - on pre QTcF cycle doses per 28-day blood drawn before defned postdose 3 and 1, 2 [cycle (days PK analysis for of 3 and 4 only] and 7 [cycle 4 only], 1, 3, 4, and 6) Cycles Dose(s) evaluated 3 mg/m 1.2–1.8 mg/m 3.6 mg/kg IV Q3W QTcF evaluated on evaluated IV Q3W QTcF 3.6 mg/kg 1.25 mg/kg IV given on days 1, 8, and on days IV given 1.25 mg/kg 6.4 mg/kg Q3W QTcF during cycles Q3W QTcF 6.4 mg/kg 1.8 mg/kg IV Q3W QTcF evaluated on evaluated IV Q3W QTcF 1.8 mg/kg evaluated IV Q3W QTcF 1–2.4 mg/kg mBC ( n = 51) patients ( n = 46) + + r/r B-cell ALL or NHL pts r/r B-cell ALL or NHL pts + study in adult and pediatricstudy patients AML ( n = 56) with r/r CD33 ‑ positive ( n = 250) CD22 study in HER2 study in patients with locally advanced or advanced in patients with locally metastatic UC ( n = 17) study in patients with study mBC ( n = 51) study in CD30 study in patients with studies B-cell malig - nancies ( n = 209) Study Method Study Phase 4 open label, single-arm clinical Data pooled from 3 clinical studies in Data 3 clinical studies pooled from Phase 2 open label, single-arm clinical Data pooled from phase 1 clinical study Data phase 1 clinical study pooled from Phase 1 open label, single-arm clinical Phase 1 open label, single-arm clinical Data 2 open-label clinical pooled from every 3 weeks, NA PK pharmacokinetics, Q3W every formula, heart QT interval corrected using Fridericia’s rate for QTcF total antibody, Analytes NA ADC, TAb, Cal ADC, TAb, ADC, TAb, DM1 ADC, TAb, ADC, MMAE ADC, DXd MMAE, ADC MMAE, acMMAE, TAb deruxtecan, TAb DM1 emtansine, DXd QT assessment and key fndings for the seven approved ADCs approved the seven fndings for QT assessment and key urothelial can - UC urothelial NHL non-hodgkins lymphoma, leukemia, ALL acute lymphocytic cancer, mBC metastatic breast leukemia, AML acute myeloid IV intravenous, carcinoma, UC urothelial [ 4 , 45 ] 50 ] able, deruxtecan TD trastuzumab vedotin, ms milliseconds, EV enfortumab r/r relapsed/refractory, cer, 4 Table Drug trastuzumab trastuzumab auristatin E, T-DM1 MMAE monomethyl payload), as conjugated MMAE (measured ADC antibody–drugantibody), acMMAE conjugated as conjugated (measured conjugate emtansine, Gemtuzumab ozogamicin (ongoing) Gemtuzumab ozogamicin Inotuzumab ozogamicin [ 6 , 51 ] ozogamicin Inotuzumab Trastuzumab emtansine (T-DM1) [ 8 , emtansine (T-DM1) Trastuzumab [ 9 , 21 ] vedotin Enfortumab Trastuzumab deruxtecan [ 7 , 25 ] Trastuzumab Brentuximab vedotin [ 5 , 46 ] vedotin Brentuximab [ 10 , 52 ] vedotin Polatuzumab

1 3 Cancer Chemotherapy and Pharmacology (2021) 87:743–765 759 released payloads are highly potent and may possibly pose the exposure-efcacy analysis given efcacy data is indica- a safety risk, exposures of unconjugated drug are sometimes tion-specifc and only one dose level is usually studied in included in the exposure-safety analysis. Table 5 summa- the pivotal study. Similar to ER analysis of other cancer- rizes the ER results for the seven approved ADC. Among targeting biologics, caution needs to be taken to interpret the seven approved ADCs, four of the ADCs, namely bren- the ER results of an ADC when the analyses are performed tuximab vedotin, polatuzumab vedotin, enfortumab vedotin with data with only single dose levels as the efect of disease and trastuzumab deruxtecan, included both ADC conjugate severity on ADC exposure may confound ER relationship and unconjugated drug analytes in their ER analyses. A (i.e., a visual steep trend is seen when the true relationship positive exposure-efcacy relationship with ADC conju- is fat) [45, 46]. The exposure-safety, however, is less likely gate exposure was consistently observed for the four ADCs, to be confounded as the safety data are often pooled across however, no apparent or negative exposure-efcacy rela- the multiple studies, dose levels and patient populations. As tionship was observed for unconjugated drug exposure. In illustrated in Table 5, a range of clinically tested doses were comparison, exposure-safety relationships for the four ADCs included in the ER safety analysis for most of the seven vary, depending on safety endpoints and analytes used in the approved ADCs, while only three out of the seven ADCs analyses. For brentuximab vedotin and enfortumab vedo- include multiple dose levels in the ER efcacy analyses. tin, ADC conjugate exposure appeared to correlate better In summary, ER analysis provided valuable information with safety than that of unconjugated drug. In the case of beyond dose confrmation of the clinically tested dosage reg- brentuximab vedotin, a positive exposure-safety relationship imen in the phase 3 studies. We have illustrated the impact was observed with ADC conjugate exposure, but not with of ER analyses of gemtuzumab ozogamicin to enable test a that of unconjugated drug, while for enfortumab vedotin, fractionated lower dose thus leading to the re-approval of positive exposure-safety relationships were observed with gemtuzumab ozogamicin. Additionally, ER analyses could exposure of both ADC conjugate and unconjugated drug, guide dose adjustment. For brentuximab vedotin, the posi- but the strengthen of exposure-safety relationship appears tive ER relationships with peripheral neuropathy and neutro- to be much weaker for unconjugated drug. For polatuzumab penia support the dose reduction recommendation from 1.8 vedotin and trastuzumab deruxtecan, no consistent expo- to 1.2 mg/kg in the event of Grade 2 + peripheral neuropathy sure-safety trends were observed; positive exposure-safety and Grade 4 + neutropenia [22]. Furthermore, ER analysis relationships were observed sparsely between some safety could be used to identify the appropriate therapeutic dose endpoints and exposure of ADC conjugate and/or uncon- for phase 2. For trastuzumab deruxtecan, ER analysis identi- jugated payload. For T-DM1, inotuzumab ozogamicin and fed two potential phase 2 doses of 5.4 and 6.4 mg/kg from gemtuzumab ozogamicin, only one analyte was used in their phase 1 data and confrmed the fnal dose recommendation ER analyses. Specifcally, ADC conjugate was used for ER of 5.4 mg/kg in pivotal studies based on similar predicted analyses of T-DM1 and inotuzumab ozogamicin. For both ORR probability (ORR 90% CI 0.63 [0.55, 0.70] and 0.68 ADCs, increased conjugate exposure appeared to be asso- [0.58, 0.77] for 5.4 mg/kg and 6.4 mg/kg, respectively) and ciated with improved efcacy (i.e., ORR, PFS, OS). No exposure-safety relationships with greater rate of AEs in the apparent positive exposure-safety relationship was observed 6.4 mg/kg group compared to the 5.4 mg/kg group [25]. with T-DM1 treatment (i.e., hepatotoxicity and thrombo- cytopenia), while a positive exposure-efcacy relationship was founded between inotuzumab ozogamicin and some Summary and future directions of treatment-related AE (i.e., Grade 3 + thrombocytopenia and HEAB-assessed VOD). Given ADC conjugate was not ADCs represent a rapidly evolving area of oncology drug measured for gemtuzumab ozogamicin, total antibody ana- development and hold signifcant promise. The complex lyte was used for the ER analysis instead. Together, for most structure of ADCs poses unique challenges to clinical phar- of the seven approved ADCs, the efcacy endpoints appear macology strategy in supporting development and approval to correlate best with ADC conjugate compared to that of of ADCs, since it requires a quantitative understanding of unconjugated payload. For safety outcomes, while ADC the PK and PD properties of multiple diferent molecular exposures were often correlated with AEs, unconjugated species (e.g., ADC conjugate, total antibody and unconju- payload exposures may also be important for certain AEs. gated payload) in the systemic circulation and/or tissues of Total antibody analyte was usually not included in the ER interest (e.g., tumors). Integration of diverse clinical phar- analysis since there is a high correlation between conjugate macology approaches, ranging from dedicated clinical phar- and the total antibody exposures [44]. macology studies (e.g., DDI, QTc, renal/hepatic impairment It is worth noting that four out of the seven ADCs (i.e., study) to mechanistic and/or empirical models (e.g., PBPK, gemtuzumab ozogamicin, brentuximab vedotin, T-DM1 and population PK modeling for one- or two- analytes, expo- enfortumab vedotin) use the data from single dose level in sure–response analysis) can provide insights into the PK, PD

1 3 760 Cancer Chemotherapy and Pharmacology (2021) 87:743–765

- exposure min,cycle1 min, cycle1 relationship relationship exposure across metrics No apparent apparent No for relationship exposure TAb and signifcant for relationship TAb negative trend trend negative with ADC ­ C quartiles nia and dose adjustments: no apparent relationship negative trend trend negative with ADC ­ C with ADC , no relationship with MMAE trend positive for for trend MMAE No topenia: apparent for relationship both analytes Consistent Consistent Liver toxicity: toxicity: Liver positive VOD: Key Findings* Key Grade Grade 3 + AEs: - Thrombocytope reportedPN: not Hepatotoxicity: Hepatotoxicity: PN: positive trend trend PN: positive Neutropenia: ADC , negative Thrombocy (AST, ALT, ALT, (AST, total biliru - bin), VOD totoxicity, Grade 3 + throm - bocytopenia, - dose adjust ments, PN event, tropenia, 3 + thrombo - cytopenia Liver toxicity toxicity Liver Safety Endpoint Safety Grade Grade 3 + hepa - Grade 3 + AEs, Grade Grade 2 + PN Grade 3 + neu - Grade - min,ss ­ C and AUC after and AUC frst dose, and aver frst ​ AUC age min,cycle1 max Model-predicted C PK Parameter C Average Average and mBC logical refractory malignancies HER2 + mBC Study Popu- lation Popu- Study AML HER2 + refractory - CD30 + hemato on 2 IV days 1 and 15 days Q3W IV Q3W 3.6 mg/kg Q3W 3.6 mg/kg Exposure-Safety Dose 0.3–4.8 mg/kg 0.3–4.8 mg/kg 9 mg/m 0.1–3.6 mg/kg * ADC and ­ Findings min, cycle1 1 min, cycle and signifcant withtrend ADC ­ C relationship relationship TAb for exposure relationship - expo across metricssure with trend negative with MMAE tive and sig - tive nifcant trend with ADC ­ C Key Key ORR: positive ORR: positive No apparent apparent No Consistent trend Positive OS/PFS: posi - Efcacy End - point ORR, OS/PFS CR ORR min,ss ​ , AUC ­ C avg ,and min,cycle1 ​ AUC cycle1 ­ C max,cycle1 PK Parameter C Average Average Model-predicted Model-predicted Study Popu- Popu- Study lation AML r/r HL, ALCL HER2 + mBC on days on days 2 1 and 15 IV Dose 9 mg/m Exposure-Efcacy 1.8 mg/kg Q3W 1.8 mg/kg 3.6 mg/kg Q3W 3.6 mg/kg Analytes TAb ADC, MMAE ADC only Summary of exposure-efcacy and exposure-safety analyses for the seven approved ADCs approved the seven for analyses and exposure-safety Summary of exposure-efcacy ozogamicin ozogamicin [ 4 , 28 ] vedotin (AA) vedotin [ 5 , 22 ] emtansine [ 8 , (T-DM1) 23 ] Gemtuzumab 5 Table ADC Brentuximab Brentuximab Trastuzumab Trastuzumab

1 3 Cancer Chemotherapy and Pharmacology (2021) 87:743–765 761

max max , max C C ­ C cycle1 cycle1 max only in patients only who did not undergo HSCT post inotuzumab ozogamicin treatment no apparent relationship ​ and AUC no apparent relationship and signifcant relationship with ADC ​ cAUC (pola only): and Positive signifcant trend with acMMAE and ­ AUC signifcant trend with acMMAE and ­ AUC and signifcant withtrend MMAE modifcation: and Positive signifcant trend with acMMAE ­ C penia: positive penia: positive and signifcant relationship with ADC ​ cAUC All other AEs: All other AEs: Key Findings* Key VOD: positive positive VOD: Dose intensity and PN: Positive Anemia: Positive Time to dose to Time - Thrombocyto - frst dose frst modifcation AEs, due to dose intensity (pola, rtx, benda), event, mia, Grade - 3 + neutro penia, Grade 3 + infections - and infesta tions, Grade 3 + throm - - bocytope nia, Grade 3 + diar Grade rhea, 3 + liver toxicity ALT, (AST, bilirubin) 3 + thrombo - cytopenia, - 3 + neutro penia, liver (ALT, toxicity total AST, bilirubin), hepatic events Safety Endpoint Safety Time to to Time Grade 2 + PN Grade 3 + ane - Grade Grade Grade VOD, avg C ),

, max ­ C ​ , log(AUC ) and ­ , ​ cAUC max,cycle1 avg , ) max,cycle1 cycle1 cycle6 ­ C ​ , log(cAUC ) log(C cycle1 ss ss log(C (ADC and MMAE) ​ AUC ​ cAUC PK Parameter r/r DLCBL CD22 + ALL Study Popu- lation Popu- Study ing 1.8 mg/kg ing 1.8 mg/kg Q3W mg/kg on days 1,8 on days and 15 per cycle 28-day 0.1–2.4, includ - Exposure-Safety Dose 1.2–1.8 mg/m2 * and avg avg ­ C ­ C ­ Findings Phase I/II studies: and signifcant withtrend ​ ADC AUC only signifcant withtrend ADC efcacy endpoints: no signifcant relationship cAUCP1 and positive signifcant withtrend ADC positive and positive signifcant withtrend ADC Supporting ORR: positive study Pivotal and OS: positive All other Key Key PFS/OS: CR/CRi: to relapse to OS, ORR, PFS, time Efcacy End - point CR/CRi, PFS, OS and , , (ADC ss cycle1 cycle6 max,cycle1 avg only) ​ cAUC ­ C ­ C PK Parameter ​ cAUC ​ AUC Study Popu- Popu- Study lation CD22 + ALL r/r DLCBL

2 on days 1,8 on days and 15 per cycle 28-day Phase I/ II studies: 0.1–2.4 mg/kg 1.8 mg/ only: mg/kg kg Q3W Dose 1.2–1.8 mg/m Exposure-Efcacy Supporting study Pivotal (ADC), MMAE Analytes ADC only acMMAE (continued) ozogamicin ozogamicin [ 6 , 24 ] vedotin (AA) vedotin [ 10 , 26 ] Inotuzumab Inotuzumab Polatuzumab Polatuzumab 5 Table ADC

1 3 762 Cancer Chemotherapy and Pharmacology (2021) 87:743–765

deruxtecan, positive trend trend positive with both ADC and MMAE , the much trend, for weaker MMAE - all the 3 expo metricssure reported with either ADC or DXd exposure and emergent grade 3 + LVEF not reductions analyzed Key Findings* Key G3 + TEAEs: for Similar trend Other AEs: not AE correlates Treatment covariate, VOD covariate, cumulative AUC, AUC, cumulative - hematopoietic , HSCT hematopoietic + 3 + TEAEs, Grade 3 + rash, Grade 3 + hypergly cemia, Grade 2 + PN event or reduction interruption associated with AEs, INTER AEs, SAEs, grade any and Grade 3 + (AEs, anemia, neutropenia, thrombocyto - penia, ILD), grade and any Grade 2 + and 3 + LVEF reductions Safety Endpoint Safety Grade Grade DISC AEs, dose alanine aminotransferase, AML alanine aminotransferase,

, , min,ss max,cycle1, max,cycle1 adverse events of special interest, interest, special of events adverse AESIs ­ C ​ , AUC , ­ C ­ C , , avg max,ss ­ C cycle1 cycle1 ­ C minimum concentration, COV minimum concentration, min,cycle1 min,cycle1 , and ­ C ­ C ss min PK Parameter (ADC and MMAE) (ADC and DXd) Model-predicted ​ AUC ​ AUC bendamustine, polatuzumab, Benda bendamustine, rituximab, Pola adverse events, events, adverse AEs average concentration defned as the cumulative AUC divided by by divided AUC theas defned concentration cumulative average ing malignant solid tumors avg Study Popu- lation Popu- Study - Nectin-4-express HER2 + mBC C kg on days 1, on days kg 8, and 15 per cycle 28 day Q3W Exposure-Safety Dose 0.5–1.25 mg/ 0.8–8.0 mg/kg 0.8–8.0 mg/kg * 3) adverse events, HER2 +: human epidermal 2 receptor growth events, 3) adverse ; no ≥ avg ­ C ­ Findings Positive trend trend Positive with ADC and exposure trend negative with MMAE exposure - all the 3 expo metricssure trend for all for trend exposure metrics for ADC , only signifcant for relationship relationship with DXd relationship both ADC for and DXd exposure Key Key BOR only: only: BOR for Similar trend ORR: positive ORR: positive DOR, PFS: no cutaneous t-cell lymphoma, cutaneous lymphoma, t-cell CTCL PFS, OS PFS Efcacy End - point BOR, DOR, BOR, ORR, DOR, ,

, , , min,ss ­ C , , , avg cycle1 ss ­ C cycle1 conjugated MMAE (measured as conjugated payload), payload), conjugated as (measured MMAE conjugated acMMAE max,cycle1, min,cycle1 max,cycle1 min,cycle1 max,ss complete response, response, complete CR ­ C and ­ C ​ AUC MMAE) ­ C ­ C ​ AUC ­ C PK Parameter Model-predicted Model-predicted (ADC and (ADC and DXd) ​ AUC time-averaged area under the the area to curve concentration–time point of time-averaged state, AUC/time under the area at steady curve concentration–time ss Study Popu- Popu- Study lation mUC HER2 + mBC days 1, 8, and days 15 per 28 day cycle kg Q3W kg Dose 1.25 mg/kg on 1.25 mg/kg Exposure-Efcacy 5.4, 6.4, 7.4 mg/ maximum concentration in plasma, in concentration maximum max peripheral neuropathy, PFS progressionsurvival, r/r HL relapsed/refractory free hodg - PN peripheral rate, response neuropathy, NDIS number of disease site, ORR objective available, not C Analytes ADC, MMAE (monotherapy) ADC, DXd (monotherapy) accelerated approval, RTX approval, AA accelerated events, adverse TEAEs treatment-emergent Y yes, TMBD baseline sum of longest, total antibody, (continued) TAb vedotin (AA) vedotin [ 9 , 21 ] deruxtecan (AA) 7 , 25 The analyte associated with a positive trend key fnding is bolded key trend associated with a positive The analyte

Enfortumab Enfortumab anaplastic large-cell lymphoma, ALT lymphoma, large-cell ALCL anaplastic occurrence the or time of frst AE (safety), of treatment duration of each progression or censoring (efcacy) and over baseline lactic dehydrogenase, C BLDH baseline lactic dehydrogenase, in bone marrow, blast BMAR baseline percentage response, overall BOR best leukemia, acute myeloid 5 Table ADC antibody), antibody–drugADC conjugated as (measured conjugate * left ejection fraction ventricular LVEF monomethyl auristatin E, mBC metastatic INTER AEs drug lung disease, lesions, ILD interstitial MMAE monomethyl interruption dimension of target cell transplant stem events, associated with adverse N no, NA cancer, breast serious adverse serious SAEs adverse 4 months, cancer, at least mUC metastatic urothelial lasting rate response B-cell lymphoma, ORR4 objective r/r DLBCL relapsed/refractory difuse large kins lymphoma, events, trastuzumab emtansine, trastuzumab DM1 emtansine, DXd disease, T-DM1 DME measurable of response, DOR duration events, DISC AEs discontinuation associated withits duration, adverse (Grade performance Oncology Group status, G3AEs grade 3 and above EasternECOG Cooperative Trastuzumab Trastuzumab veno-occlusive disease, veno-occlusive ​ cAUC 1, cycle in treatment AUC cumulative ALBU serum cAUCP1 ALKP serum albumin concentration, leukemia, alkaline phosphataseALL acute lymphocytic concentration, ​ AUC concentration, AST aspartate aminotransferase

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Concentration-QTC Analysis of Polatuzumab Vedotin in Patients Publisher’s Note Springer Nature remains neutral with regard to with B-Cell Hematologic Malignancies (conference paper S5-S5). jurisdictional claims in published maps and institutional afliations. Conference of Clinical Pharmacology and Therapeutics Annual Meeting

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