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Research ArticleMetabolism, Transport, and Pharmacogenetics
Open Access

Identification and Characterization of ACP-5862, the Major Circulating Active Metabolite of Acalabrutinib: Both Are Potent and Selective Covalent Bruton Tyrosine Kinase Inhibitors 

Terry Podoll, Paul G. Pearson, Allard Kaptein, Jerry Evarts, Gerjan de Bruin, Maaike Emmelot-van Hoek, Anouk de Jong, Bart van Lith, Hao Sun, Stephen Byard, Adrian Fretland, Niels Hoogenboom, Tjeerd Barf and J. Greg Slatter
Journal of Pharmacology and Experimental Therapeutics January 2023, 384 (1) 173-186; DOI: https://doi.org/10.1124/jpet.122.001116

Abstract

Acalabrutinib is a covalent Bruton tyrosine kinase (BTK) inhibitor approved for relapsed/refractory mantle cell lymphoma and chronic lymphocytic leukemia/small lymphocytic lymphoma. A major metabolite of acalabrutinib (M27, ACP-5862) was observed in human plasma circulation. Subsequently, the metabolite was purified from an in vitro biosynthetic reaction and shown by nuclear magnetic resonance spectroscopy to be a pyrrolidine ring–opened ketone/amide. Synthesis confirmed its structure, and covalent inhibition of wild-type BTK was observed in a biochemical kinase assay. A twofold lower potency than acalabrutinib was observed but with similar high kinase selectivity. Like acalabrutinib, ACP-5862 was the most selective toward BTK relative to ibrutinib and zanubrutinib. Because of the potency, ACP-5862 covalent binding properties, and potential contribution to clinical efficacy of acalabrutinib, factors influencing acalabrutinib clearance and ACP-5862 formation and clearance were assessed. rCYP (recombinant cytochrome P450) reaction phenotyping indicated that CYP3A4 was responsible for ACP-5862 formation and metabolism. ACP-5862 formation Km (Michaelis constant) and Vmax were 2.78 μM and 4.13 pmol/pmol CYP3A/min, respectively. ACP-5862 intrinsic clearance was 23.6 μL/min per mg. Acalabrutinib weakly inhibited CYP2C8, CYP2C9, and CYP3A4, and ACP-5862 weakly inhibited CYP2C9 and CYP2C19; other cytochrome P450s, UGTs (uridine 5′-diphospho-glucuronosyltransferases), and aldehyde oxidase were not inhibited. Neither parent nor ACP-5862 strongly induced CYP1A2, CYP2B6, or CYP3A4 mRNA. Acalabrutinib and ACP-5862 were substrates of multidrug resistance protein 1 and breast cancer resistance protein but not OATP1B1 or OATP1B3. Our work indicates that ACP-5862 may contribute to clinical efficacy in acalabrutinib-treated patients and illustrates how proactive metabolite characterization allows timely assessment of drug-drug interactions and potential contributions of metabolites to pharmacological activity.

SIGNIFICANCE STATEMENT This work characterized the major metabolite of acalabrutinib, ACP-5862. Its contribution to the pharmacological activity of acalabrutinib was assessed based on covalent Bruton tyrosine kinase binding kinetics, kinase selectivity, and potency in cellular assays. The metabolic clearance and in vitro drug-drug interaction potential were also evaluated for both acalabrutinib and ACP-5862. The current data suggest that ACP-5862 may contribute to the clinical efficacy observed in acalabrutinib-treated patients and demonstrates the value of proactive metabolite identification and pharmacological characterization.

Introduction

Acalabrutinib (Calquence; https://den8dhaj6zs0e.cloudfront.net/50fd68b9-106b-4550-b5d0-12b045f8b184/e2a005a7-65a0-4388-a671-dc887815a938/e2a005a7-65a0-4388-a671-dc887815a938_viewable_rendition__v.pdf) is a potent, highly selective, next-generation, targeted covalent inhibitor of Bruton tyrosine kinase (BTK) approved in adults with previously treated mantle cell lymphoma and in patients with chronic lymphocytic leukemia or small lymphocytic lymphoma. Covalent inhibition of BTK is a clinically validated mechanism for the treatment of B-cell malignancies (Ponader and Burger, 2014). Other approved covalent kinase inhibitors such as ibrutinib (BTK), osimertinib [epidermal growth factor receptor (EGFR)], and neratinib [EGFR, human epidermal growth factor receptor (HER)-2, and HER4], and afatinib (EGFR, HER2, and HER4) contain acrylamide-based electrophiles that generally have higher reactivity relative to the butynamide in acalabrutinib (Podoll et al., 2019; https://nerlynxhcp.com/pdf/full-prescribing-information.pdf; https://content.boehringer-ingelheim.com/DAM/07c11f94-358a-439d-b0c8-af1e011f04c4/gilotrif-us-pi.pdf; https://www.imbruvica.com/files/prescribing-information.pdf; https://den8dhaj6zs0e.cloudfront.net/50fd68b9-106b-4550-b5d0-12b045f8b184/52503580-1192-44f7-a05e-5743159ed19b/52503580-1192-44f7-a05e-5743159ed19b_viewable_rendition__v.pdf). The electrophile is the moiety that binds the selected cysteine thiol nucleophiles in the ATP binding pocket of a protein kinase to provide the covalent bond (Barf et al., 2017; Podoll et al., 2019). Covalent inhibitors with highly reactive acrylamide-based electrophiles are very effective in inhibiting their respective protein kinase target but may lack selectivity, which could result in off-target binding to kinases and nonkinase proteins (Chandrasekaran et al., 2010; Stopfer et al., 2012; Scheers et al., 2015; Dickinson et al., 2016). Compared with the other BTK inhibitors approved for clinical use (ibrutinib, zanubrutinib), acalabrutinib has demonstrated greater selectivity for BTK in vitro and reduced inhibition of signaling through EGFR, interleukin-2–inducible T-cell kinase (ITK), Tec protein tyrosine kinase (TEC), and Src family kinases (Byrd et al., 2016; Barf et al., 2017; Kaptein et al., 2018). Lower off-target binding to protein kinases and biologic nucleophiles in general may yield an improved safety profile for acalabrutinib compared with other BTK inhibitors (Singh et al., 2011; Pal Singh et al., 2018).

The 2-butynamide electrophile in acalabrutinib is positioned in proximity to the Cys481 nucleophile at the rim of the ATP binding pocket (Barf et al., 2017). Unlike drugs that interact reversibly with their targets and generally require sustained plasma levels to achieve target coverage over the dose interval, potent covalent inhibitors such as acalabrutinib can drive high target occupancy after a relatively brief systemic exposure (Baillie, 2016; Lonsdale and Ward, 2018). This can result in prolonged pharmacodynamic effects, with the duration of effect related to the time required for target resynthesis (Singh et al., 2011; Barf and Kaptein, 2012). Acalabrutinib has rapid absorption and a short plasma half-life, key pharmacokinetic (PK) characteristics of safe and effective covalent inhibitors (Byrd et al., 2016; Barf et al., 2017). Because pharmacologically active metabolites may contribute to the overall efficacy of any treatment, they must be considered when evaluating overall efficacy and/or safety, especially when formed at pharmacologically relevant concentrations.

Early studies characterized several metabolites of acalabrutinib that are related to glutathione (GSH) conjugation of the 2-butynamide electrophile and were later confirmed to be minor metabolites (Podoll et al., 2019). The major metabolite of acalabrutinib was first identified by mass-defect filter high-performance liquid chromatography (HPLC)–high resolution mass spectroscopy in clinical plasma samples as an abundant, +16 Da, oxidized metabolite (M27) that eluted after acalabrutinib; however, it was not quantified, and fragmentation did not reveal the regiochemistry of oxidation. Subsequently, results from a [14C]microtracer human absorption, distribution, metabolism, and excretion and bioavailability study demonstrated 25% absolute bioavailability of acalabrutinib, rapid radioactivity excretion mainly in feces, and near-complete radiolabel recovery (Podoll et al., 2019). One major, late-eluting oxidized metabolite was observed that matched the retention time of M27 (ACP-5862) (Fig. 1) (Podoll et al., 2019). ACP-5862 comprised 35% of total drug-related material in plasma, representing fourfold higher systemic exposure than the parent acalabrutinib, based on time-proportional pooling in six healthy volunteers.

Fig. 1.
Fig. 1.

Metabolism of acalabrutinib: primary metabolic routes.

The objective of this study was to characterize acalabrutinib’s major metabolite and assess its potential contribution to pharmacological activity during acalabrutinib therapy. Herein, we report the covalent BTK binding kinetics, kinase selectivity, and potency in cellular assays for acalabrutinib and ACP-5862. Ibrutinib and zanubrutinib were included to allow direct comparison of acrylamide versus butynamide electrophile attributes. The potential for drug-drug interactions with acalabrutinib and ACP-5862 was determined to elucidate intrinsic and extrinsic factors that may influence their exposure-response relationships (Baillie et al., 2002; Edlund et al., 2019; Zhou et al., 2019; Edlund et al., 2022a; https://www.fda.gov/regulatory-information/search-fda-guidance-documents/safety-testing-drug-metabolites). Purification and structural elucidation of the M27 in vitro metabolite by NMR spectroscopy enabled subsequent chemical synthesis of ACP-5862 (M27), and the proposed mechanism of its formation is first reported herein.

Materials and Methods

Materials

Radiolabeled acalabrutinib (1,4-[8-amino-3-[(2S)-1-but-2-ynoylpyrrolidin-2-yl]imidazo[1,5-α]pyrazin-1-yl]-N-(2-pyridyl)-benzamide), labeled at the carboxyl carbon atom of the 2-pyridylbenzamide portion of the molecule (Fig. 1), was prepared with a [14C]acalabrutinib radioactivity content of 57 mCi/mmol. The radiochemical purity of [14C]acalabrutinib was verified at the beginning and end of the metabolite preparation incubations using an HPLC method. Metabolite ref-erence standard materials were prepared by Kalexsyn (Kalamazoo, MI) or Acerta Pharma, BV (Oss, Netherlands) (https://patentimages.storage.googleapis.com/6a/e5/44/abb83f5c5dcc87/US20190345164A1.pdf). 1-Chloro-2,4-dinitrobenzene was purchased from Sigma-Aldrich Chemical Co. (St. Louis, MO). Pooled human liver microsomes (HLMs) were obtained from BioreclamationIVT (Baltimore, MD) and were stored at approximately −70°C. Cryopreserved human hepatocytes were supplied by XenoTech, LLC (Kansas City, KS) for assessment of the induction of cytochrome P450 (P450) enzymes by acalabrutinib and ACP-5862. Bactosomes containing individually expressed P450 enzymes or control expression plasmid without P450 in Escherichia coli membranes were obtained from Cypex, Ltd. (Dundee, UK). Human embryonic kidney 293 (HEK293) cells and Caco-2 cells were obtained from American Type Culture Collection (Manassas, VA). The HEK293 cells were transfected with the individual transporter genes by Sekisui Medical Co. Ltd. (Tokyo, Japan). Madin-Darby canine kidney (MDCKII) cells overexpressing human P-glycoprotein (P-gp; multidrug resistance protein 1) and breast cancer resistance protein (BCRP) were obtained from the Netherlands Cancer Institute (Amsterdam). All other reagents and chemicals were obtained from standard commercial sources. In addition, plasma samples collected from patients receiving repeated oral doses of acalabrutinib in a phase 1/2 study (#NCT02029443) were used in the analysis of the M25 and M27 metabolites; that study was conducted according to the principles of the Declaration of Helsinki and the International Conference on Harmonization Good Clinical Practice, and informed written consent was obtained from all patients.

Biochemical Kinase Assays

BTK and ITK (Millipore, Dundee, UK) enzyme activities were measured as described previously using the immobilized metal ion affinity-based fluorescence polarization (IMAP) assay(Barf et al., 2017). IC50 measurements over time were obtained using LanthaScreen (Thermo Fisher Scientific, Carlsbad, CA) for wild-type BTK (BTK-WT) and C481S (Barf et al., 2017) under conditions in which the reaction was linear with time in the absence or presence of inhibitor; from these time-dependent experiments, inactivation rate constant (kinact) and inhibitory constant (KI) values were obtained using the method of Krippendorff et al. (2009) as described previously (Barf et al., 2017).

The inhibition kinase activity for TEC was measured using the LanthaScreen assay (Thermo Fisher Scientific), and the inhibition of BMX nonreceptor tyrosine kinase (BMX), TXK tyrosine kinase/protein tyrosine kinase 4 (TXK), EGFR, erythroblastosis oncogene B2 (ERBB2), erythroblastosis oncogene B4 (ERBB4), B-lymphocyte kinase (BLK), and Janus-associated kinase 3 (JAK3) was measured using the Z′-LYTE assay (Thermo Fisher Scientific) as described previously (Barf et al., 2017).

The ATP concentrations in all IMAP, LanthaScreen, and Z′-LYTE assays were set at the Michaelis constant (Km) ATP for each kinase to enable comparative selectivity profiles between kinase inhibitors. Similarly, the overall kinase selectivity was assessed using kinome profiling at a single inhibitor dose (1 µM) using KINOMEscan (Eurofins DiscoverX) (Fabian et al., 2005; Herman et al., 2017) because it does not require ATP or phosphorylation substrate, enabling direct comparison of the relative binding affinities of the kinase inhibitors.

B-Cell Inhibition of BCR-Induced CD69 Surface Expression in Human Peripheral Blood Mononuclear Cells and Human Whole Blood

BTK inhibition in whole-cell assays was conducted as described previously (Barf et al., 2017). Briefly, cryopreserved peripheral blood mononuclear cells (PBMCs) were suspended in RPMI 1640 plus 10% FBS (2 × 105 cells per well) and incubated with acalabrutinib and ACP-5862 (0.316 to 10,000 nM) for 2 hours at 37°C, 5% CO2. Goat anti-human IgM F(ab′)2 (Southern Biotech, Birmingham, AL) was then added, and cells were incubated for an additional 18 hours. For the whole-blood (WB) assay, 45 µl blood was diluted 1:1 in RPMI 1640 plus 1% FBS and incubated with test compound (as described above). WB was stimulated with 10 µg/ml mouse antihuman anti-IgD (BD Biosciences) and incubated for 18 hours. PBMCs or WB were stained with CD69-fluorescein isothiocyanate, CD19-BV421, and CD3-BV510 antibodies (BD Biosciences, San Diego, CA), with 7-aminoactinomycin D as a viability measure. To lyse red blood cells, WB was treated with fluorescence-activated cell sorter lysing solution (BD Biosciences), washed, pelleted, and resuspended in 200 µl per well PBS plus 0.5% bovine serum albumin before flow cytometry. For both the PBMC and WB assays, the median fluorescence intensity values for CD69 were obtained from the CD19+ CD3− B-lymphocyte gate using FCS Express analysis software (De Novo Software, Glendale, CA). EC50 values were determined based on curve fitting of experimental results using Dotmatics.

Metabolism of Acalabrutinib and ACP-5862 in Vitro: P450 Enzyme Identification

The metabolism of acalabrutinib and ACP-5862 (1 µM) were investigated in the presence and absence of P450 isoform-selective chemical inhibitors under conditions in which the reaction was linear with time. HLMs (0.1 and 0.5 mg/ml protein for acalabrutinib and ACP-5862, respectively) were incubated at 37°C with 10 µM furafylline (CYP1A2), 30 µM phencyclidine (CYP2B6), 100 µM gemfibrozil glucuronide (CYP2C8), 20 µM tienilic acid (CYP2C9), 10 µM esomeprazole (CYP2C19), 10 µM quinidine (CYP2D6), 5 µM paroxetine [CYP2D6 (ACP-5862 only)], 10 µM diethyldithiocarbamate (CYP2E1), 50 µM troleandomycin (CYP3A4), or 1 µM ketoconazole [CYP3A4/5 (acalabrutinib only)]. Reactions utilizing metabolism-dependent inhibitors (furafylline, phencyclidine, gemfibrozil glucuronide, tienilic acid, esomeprazole, paroxetine, diethyldithiocarbamate, or troleandomycin) were incubated with the HLMs and an NADPH-generating system for 30 minutes at 37°C prior to initiating the reaction by the addition of acalabrutinib or ACP-5862. Reactions utilizing direct inhibitors (quinidine or ketoconazole) were initiated with the addition of an NADPH-generating system consisting of NADP (1 mM, pH 7.4), glucose-6-phosphate (5 mM, pH 7.4), and glucose-6-phosphate dehydrogenase (1 U/ml). All incubations also contained 50 mM potassium phosphate buffer (pH 7.4), MgCl2 (3 mM), and EDTA (1 mM) and were terminated after 60 and 45 minutes for acalabrutinib and ACP-5862, respectively, by the addition of an equal volume of acetonitrile (ACN) containing their respective deuterium-labeled internal standards. The samples were centrifuged (e.g., 920g for 10 minutes at 10°C). The supernatant fractions were analyzed by liquid chromatography with tandem mass spectrometry (LC-MS/MS) to quantify the amount of acalabrutinib and ACP-5862 remaining based on a calibration curve.

Membranes isolated from E. coli expressing individual cytochrome P450 enzymes rCYP1A2, rCYP2B6, rCYP2C8, rCYP2C9, rCYP2C19, rCYP2D6, and rCYP3A4 were incubated with acalabrutinib (1 and 10 µM) and ACP-5862 (0.1 and 1.0 µM) at 10 and 2.5 pmol P450 per incubation, respectively. The content and conduct of the incubations and subsequent sample preparation steps were similar to those described above. Consumption of acalabrutinib and ACP-5862 in the presence of individual P450s was compared with that observed in membranes from vector control E. coli membranes.

ACP-5862 initial-rate formation kinetics were measured in HLM (0.1 mg/ml) during a 6-minute reaction time and in rCYP3A4 (12.5 pmol/ml) during a 4-minute reaction time over an acalabrutinib concentration range of 0.7–70 µM and 1.5–150 µM, respectively. ACP-5862 (0.1 µM) in vitro intrinsic clearance (Clint) was measured in HLM (0.5 mg/ml) by monitoring its disappearance after 5, 15, 30, and 45 minutes in the presence of NADPH (1-mM generating system as described above). The Clint was determined using the following equation: Embedded Image

Metabolism of Acalabrutinib in Vitro: Glutathione S-Transferase Enzyme Identification

Metabolism of acalabrutinib (1.0, 10, and 100 µM) was investigated in human liver cytosol (up to 2.0 mg/ml protein) incubated up to 120 minutes at 37°C with and without supplementation with reduced GSH (0.6 mM). Additionally, metabolism of acalabrutinib (100 µM) was investigated across a panel of individually expressed recombinant human glutathione s-transferase (GST) enzymes (rGSTA1, A2, M1, M2, P1, and T1 at 0.1 and 0.5 mg protein per ml). Incubation at 37°C was initiated by the addition of acalabrutinib and terminated at 0 and 120 minutes by the addition of an equal volume of acetonitrile. In all experiments, acalabrutinib was analyzed by LC-MS/MS to quantify the amount of acalabrutinib remaining based on a calibration curve. Additionally, the formation of GSH, cysteine-glycine, and cysteine conjugates of acalabrutinib (M5, ACP-5530; M7, ACP-5531; and M10, ACP-5461) (Podoll et al., 2019) was monitored by LC-MS/MS using the ratio of metabolite to internal standard. Incubations of 1-chloro-2,4-dinitrobenzene with human liver cytosol and each recombinant enzyme were analyzed using colorimetric analysis to quantify glutathione conjugate formation and to ensure that the test systems were metabolically competent.

P450 Inhibition by Acalabrutinib and ACP-5862

Coincubation of acalabrutinib or ACP-5862 with P450 enzyme–selective substrates was performed to determine their potential to cause drug-drug interactions in a manner similar to that previously described (Paris et al., 2009). The formation of acetaminophen, 8-hydroxyefavirenz, N-desethylamodiaquine, 4′-hydroxydiclofenac, 4′-hydroxymephenytoin, dextrorphan, 6β-hydroxytestosterone, and 1′-hydroxymidazolam were individually quantified as markers for CYP1A2, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A4/5, and CYP3A4/5 again, respectively, following incubations with pooled, mixed-gender HLMs (≤0.1 mg protein per ml). Acalabrutinib or ACP-5862 were coincubated with the marker substrates in duplicate at concentrations up to 100 or 20 µM, respectively. Metabolism- and time-dependent inhibition of each P450 by acalabrutinib and ACP-5862 up to their respective concentrations stated above was assessed by conducting 30-minute preincubations in the presence and absence of the NADPH-generating system. Reversibility was assessed, and samples were analyzed by LC-MS/MS as described previously (Watanabe et al., 2007; Paris et al., 2009). The respective metabolite formation from each probe substrate was compared with that observed for the solvent control incubations. To determine the kinact and KI values for the inactivation of P450s, primary incubations of acalabrutinib or ACP-5862 with HLMs at approximately 0.1 mg/mL and an NADPH-generating system were conducted for 0, 3, 6, 9, 15, and 30 minutes. The mixtures were then diluted 10-fold into secondary incubation tubes containing the marker substrate [near saturable rate (Vmax) concentrations] and an NADPH-generating system to arrest any inactivation by the inhibitor and measure residual activities for 5 minutes. The rates of enzyme inactivation at each inhibitor concentration were determined to calculate the kinact and KI values as described previously (Kitz and Wilson, 1962; Jones et al., 1999).

UGT1A1 and UGT2B7 Inhibition by Acalabrutinib and ACP-5862

Coincubation of acalabrutinib or ACP-5862 with UGT enzyme–selective substrates was also performed. The formation of estradiol 3-glucuronide and zidovudine 5′-glucuronide was individually quantified as markers for UGT1A1 and UGT2B7, respectively, following incubations with pooled, mixed-gender HLMs (0.2 mg protein per ml). Acalabrutinib or ACP-5862 was coincubated with the marker substrates in duplicate over the concentration range from 0.003 to 3 μM.

P450 Induction by Acalabrutinib and ACP-5862

Acalabrutinib and ACP-5862 were tested individually for their capacity to induce the expression of P450 enzymes in primary cultures of freshly isolated human hepatocytes from three individual donors (48-year-old female Caucasian, 57-year-old female Caucasian, and 56-year-old male Caucasian for acalabrutinib; 39-year-old female Caucasian, 57-year-old female Caucasian, and 61-year-old male Caucasian for ACP-5862), similar to methods previously described (Robertson et al., 2000; Paris et al., 2009). The hepatocytes were treated once daily for 3 consecutive days with acalabrutinib and ACP-5862 (up to 50 µM). Cultures were also treated with flumazenil (25 µM, negative control) or 1 of 3 known human P450 enzyme inducers, omeprazole (50 µM), phenobarbital (750 µM), and rifampicin (20 µM). Induction was measured by changes in P450 mRNA expression assessed by quantitative reverse-transcription polymerase chain reaction assays selective for CYP1A2, CYP2B6, and CYP3A4.

In Vitro Efflux and Uptake Transporter Inhibition

Coincubation of acalabrutinib or ACP-5862 with various substrates of human efflux and uptake transporters was performed to evaluate inhibition of transporters in cell lines (Kazmi et al., 2018). The bidirectional permeability of specific probe substrates for P-gp (digoxin, 10 µM in Caco-2 cells) and BCRP (prazosin, 1 µM in MDCKII cells) was measured in the presence of acalabrutinib (up to 400 µM) or ACP-5862 (up to 20 and 50 µM for P-gp and BCRP, respectively) by adding them to both apical and basolateral sides for 120 minutes before stopping with the addition of methanol:water (50:50, v:v) and analysis by LC-MS/MS. Under the condition of the assay, the recovery of the probe substrate (digoxin) ranged from 91.2% to 112%, and valspodar and verapamil (positive controls) inhibited the transport of digoxin in an expected manner.

During uptake assays, HEK293 cells were preincubated with acalabrutinib or ACP-5862 [up to 20 µM for OATP1B and OATP1B3 (0.05 μM [3H]estradiol 17β-glucuronide as substrate), OAT1 (1 μM para-aminohippurate as substrate), OAT3 (50 nM estrone sulfate as substrate), and OCT2 (10 μM metformin as substrate); up to 3 µM for MATE1 and MATE2-K (10 μM metformin as substrate)] for 15 minutes, followed by a 1- to 5-minute incubation with both radiolabeled probe substrate and acalabrutinib or ACP-5862, and then stopped by aspiration and washed as previously described (Kazmi et al., 2018). Incubations were repeated for OATP1B1- and OAT1-expressing cells for ACP-5862 (up to 50 µM). Cells were extracted (0.1N NaOH), and scintillation counting was conducted (Microbeta2, Perkin Elmer, Waltham, MA) to quantify uptake.

In Vitro Efflux and Uptake Transporter Substrate Determination

The bidirectional permeability of acalabrutinib [1, 3 (BCRP only), 10, and 30 (P-gp only) µM] and ACP-5862 (2, 10, and 50 µM) across MDCKII–P-gp cells (acalabrutinib only), Caco-2 cells, or MDCKII-BCRP cells was measured to evaluate each as substrates of P-gp or BCRP as described previously (Brouwer et al., 2013). After the cells were confluent, transport was measured from apical to basolateral and basolateral to apical with samples being collected from the receiver compartment after 15 (acalabrutinib only), 30 (acalabrutinib only), and 120 minutes of incubation, mixed with their respective deuterium-labeled internal standards, and quantified for substrate content by LC-MS/MS.

The cellular uptake of acalabrutinib or ACP-5862 was assessed in HEK293 cells transfected with OATP1B1, OATP1B3, or vector control. Acalabrutinib was tested at 1, 3, and 10 µM and ACP-5862 at 2, 10, and 50 µM, with both at 1- to 10-minute incubation times. The maximum influx uptake ratio (the influx rate of the test compound in transfected cells over that in nontransfected cells) was measured by quantifying the accumulation of each test substrate by LC-MS/MS. The cellular uptake of acalabrutinib was similarly assessed in HEK293 cells transfected with OAT1, OAT3, and OCT2 or vector control. Acalabrutinib was tested at 1, 10, and 30 µM and at 1-, 3-, and 10-minute incubation times. ACP-5862 was not tested as a substrate for renal influx transporters.

Metabolite M27 (ACP-5862) Preparative Scale Biosynthesis

[14C]Acalabrutinib (10 µM, 4280 µCi/mmol) was incubated with pooled, mixed-sex HLMs (2 mg protein per ml) in 100 mM potassium phosphate buffer (pH 7.4) with nicotinamide adenine dinucleotide phosphate, reduced form (NADPH, 2 mM), at 37°C for 30 minutes in a shaking water bath (10 replicates at 20 ml each). Incubations were terminated by the addition of an equal volume of ACN. The organic phase was separated from the proteins by centrifugation. A portion (800 µl) of each sample was evaporated to dryness under nitrogen, reconstituted in 300 µl of water:methanol (MeOH; 9:1, v:v), and centrifuged at 1430g for 10 minutes. The remaining supernatants were concentrated to approximately 10 ml each under a vacuum and combined. Samples were stored at −70°C until analysis by liquid chromatography–high-resolution mass spectrometry (LTQ Orbitrap XL with electrospray ionization, Thermo Fisher, Wilmington, DE) with in-line radiochromatographic detection. Radioactivity recoveries were determined throughout the sample processing procedures. Cytochrome P450 activities of the HLMs were assessed with midazolam (1 µM).

Samples were loaded onto conditioned solid-phase extraction columns, washed with water, and eluted with 10 ml of MeOH. The MeOH eluents were combined, evaporated to dryness under nitrogen, and reconstituted in 1 ml of 9:1 (v:v) water:MeOH. The samples were then extracted twice with 3 ml of ACN, sonicated, vortex mixed, and centrifuged (1430g for 10 minutes). The combined supernatants were evaporated to dryness under nitrogen and reconstituted in 500 µl of 9:1 (v:v) water:MeOH. The sample was sonicated, vortex mixed, and centrifuged. This supernatant was removed and set aside for HPLC analysis. The remaining pellet was further reconstituted and extracted as described previously to increase the recovery. The reconstituted pellet supernatants were evaporated to dryness under nitrogen, reconstituted in 400 µl of 1:1 (v:v) water:MeOH, and centrifuged. Details for purification of combined fractions of metabolites M25 and M27 are provided in the Supplemental Methods. ACP-5862 NMR sample preparation and experiments are also described in the Supplemental Methods.

Statistical Analysis

Descriptive statistics (mean and standard deviation) were calculated and reported where appropriate.

Results

Preclinical Pharmacological Profiling

BTK enzymatic activity was measured using an IMAP assay. Acalabrutinib and ACP-5862 had comparable biochemical potencies, with an IC50 value of approximately 5 nM for both parent and major metabolite (Table 1). Additionally, BTK kinase binding assays were performed using BTK-WT and a mutant form of BTK with Cys481Ser to confirm the covalent inhibition of BTK by acalabrutinib and ACP-5862 and investigate the binding kinetics for parent and metabolite (Fig. 2). The KI is comparable for acalabrutinib and ACP-5862 (Table 2), indicating that both parent and metabolite have similar apparent affinity for BTK. The kinact was twofold lower for ACP-5862 compared with acalabrutinib (Table 2). The fit of ACP-5862 covalently bound to BTK was assessed in silico (Fig. 3), which showed the extent of folding required of the ring-opened ketone/amide of the metabolite for the binding of the electrophile. The second-order rate constants (kinact/KI) showed a twofold higher overall potency for acalabrutinib compared with ACP-5862, whereas ibrutinib and zanubrutinib covalent binding efficiency showed approximately 10-fold greater kinact/KI values (Table 2).

Fig. 2.
Fig. 2.

IC50 measurements over time for acalabrutinib and its major metabolite (ACP-5862) following incubation with BTK-WT or BTK-C481S, using the BTK LanthaScreen assay.

Fig. 3.
Fig. 3.

Binding model of ACP-5862 in PDB 5P9J. Covalent docking was performed with Molecular Operating Environment (MOE, Chemical Computing Group, Montreal, Canada). Multiple docking poses were generated, and the one with the highest score is shown. The optimal docked pose illustrates the covalent interaction of the cysteinyl thiol of Cys-481 with the butynamide of ACP-5862.

View this table:
TABLE 1

Potency of acalabrutinib and ACP-5862 on kinases with a cysteine in the same position as Cys481 in BTK Mean ± S.D. from at least three independent assay runs. Ibrutinib and zanubrutinib data included as points of reference to marketed, selective BTK inhibitors.

View this table:
TABLE 2

BTK inactivation kinetic parameters for acalabrutinib, ACP-5862, ibrutinib, and zanubrutinibKI and kinact parameters derived from IC50 values over time from BTK-WT LanthaScreen using methods described by Krippendorff et al. (2009).

In addition to BTK, there are nine other kinases that have a cysteine nucleophile in the same position as Cys481 in BTK: TEC, ITK, BMX, TXK, EGFR, ERBB2, ERBB4, BLK, and JAK3 (Barf and Kaptein, 2012). The potency of acalabrutinib and ACP-5862 was compared across a panel of kinases to which both may bind covalently (Table 1). Both acalabrutinib and ACP-5862 displayed IC50 values > 100 nM for all off-target kinases except BMX (neither compound) and ERBB4 (ACP-5862 only). To compare potential differences in selectivity, the ratio of the IC50 for the respective kinases versus the IC50 for BTK was calculated (Supplemental Table 1). Relative selectivity data show that ACP-5862 was threefold less selective than acalabrutinib against BMX and the only kinase with less than 10-fold selectivity versus BTK (selectivity values are provided in Supplemental Table 1). For ERBB4, the other kinase for which acalabrutinib showed less than 10-fold selectivity versus BTK, ACP-5862 was approximately 20-fold more selective than acalabrutinib. The IC50 values for TEC and TXK for ACP-5862 showed approximately three- and twofold greater relative selectivity, respectively, than the parent. When comparing the fold selectivity versus BTK, the metabolite ACP-5862, like the parent acalabrutinib, showed a superior relative selectivity profile compared with ibrutinib and zanubrutinib for the other kinases in this panel. For ibrutinib, all IC50s in this panel were less than or equal to 10 nM, and for zanubrutinib, all IC50 values in this panel were less than 100 nM, except JAK3, resulting in lower selectivity relative to their respective BTK potencies.

In addition, the overall kinase selectivity profile was investigated for ACP-5862 and compared with acalabrutinib and the two other approved BTK inhibitors, ibrutinib and zanubrutinib. Profiling of all compounds at a single concentration (1 µM) was conducted using a KINOMEscan assay (Fig. 4), avoiding dependence on ATP concentration or choice of substrate (Fabian et al., 2005; Smyth and Collins, 2009), and hit rates were calculated (Table 3). Acalabrutinib had the lowest hit rate at 1 µM among the three Food and Drug Administration–approved BTK inhibitors across a panel of approximately 400 nonmutant kinases. The hit rate observed for ACP-5862 is comparable to acalabrutinib, indicating a similarly high selectivity for BTK.

Fig. 4.
Fig. 4.

Comparison of acalabrutinib, ACP-5862, ibrutinib, and zanubrutinib (each at 1 µM) in competitive binding assays on wild-type and mutant kinases (KINOMEscan, DiscoverX, South San Francisco, CA). The size of the circles represents intervals of the percent inhibition versus the untreated control. For full quantitative details, refer to Table 3. Acalabrutinib and ibrutinib kinome maps reproduced with permission from Barf et al., (2017), Creative Commons license CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/legalcode).

View this table:
TABLE 3

Kinome profiling of BTK inhibitors using KINOMEscan at 1 μM

To further investigate potential differences in potency between acalabrutinib and ACP-5862, both were profiled head-to-head in human primary peripheral B cells, either using human PBMCs or human WB. Acalabrutinib and ACP-5862 inhibitory activity on BCR-mediated cell surface expression of CD69 on peripheral B cells in PBMCs and WB revealed a greater difference in potency between the metabolite and parent compound compared with the biochemical kinase assays (Table 4). ACP-5862 was seven- to ninefold less potent than acalabrutinib in the in vitro cellular assays. The differences in potency between acalabrutinib and ibrutinib or zanubrutinib were decreased in the WB assay relative to the biochemical kinases assays as all three compounds had EC50 values less than 10 nM.

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TABLE 4

Inhibition of BCR-mediated activation of human peripheral B cells by acalabrutinib and its major circulating metabolite, ACP-5862, using human PBMC and WB

Results are mean ± S.D. for four independent experiments using material from four donors.

Identification of Enzymes Responsible for Acalabrutinib and ACP-5862 Metabolism

During GST reaction phenotyping, acalabrutinib was stable in incubations with cytosol, and there was little or no formation of M5 (GSH conjugate, ACP-5530), M7 (cysteinyl-glycine conjugate, ACP-5531), and M10 (cysteine conjugate, ACP-5461), except in the presence of the highest concentration of acalabrutinib evaluated (100 µM) and only with the addition of excess GSH (0.6 mM). In incubations of acalabrutinib with a panel of recombinant human GST enzymes (rGSTA1, A2, M1, M2, P1, and T1 at 0.5 mg protein per ml), the relative contributions by GST isoforms toward the loss of acalabrutinib observed were rGSTM2 > rGSTM1 ≫ rGSTA1 and rGSTA2 (38%, 34%, 16%, and 16%, respectively; data not shown).

NADPH-dependent consumption of both acalabrutinib and ACP-5862 were observed in pooled HLMs. In incubations with individually expressed P450 enzymes, the metabolism of acalabrutinib and ACP-5862 was predominantly mediated by CYP3A4. The addition of specific CYP3A inhibitors, ketoconazole and troleandomycin, had a substantial inhibitory effect on the metabolic consumption of acalabrutinib and ACP-5862 in HLMs (Fig. 5). Specific chemical inhibitors for CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, and CYP2E1 had minimal effect on the metabolic turnover of acalabrutinib and ACP-5862. These data suggest that CYP3A4/5 appear to be the major contributors to the P450-mediated metabolism of acalabrutinib and ACP-5862. The rates of formation of ACP-5862 following incubation of acalabrutinib with HLM and human recombinant CYP3A4 exhibited Michaelis-Menten kinetics (Fig. 6), and a single-enzyme model was used to determine the Km, 17.6 ± 1.8 and 2.78 ± 0.74 µM, and Vmax, 920 ± 43 pmol/min per mg and 4.13 ± 0.23 pmol/min per pmol, values, respectively. The ACP-5862 (0.1 µM) half-life observed in HLM (0.5 mg/ml) was 58.7 minutes, and the calculated in vitro intrinsic clearance was 23.6 µl/min per mg.

Fig. 5.
Fig. 5.

Effect of P450 isoform-selective chemical inhibitors on the disappearance of acalabrutinib and ACP-5862 in human liver microsomes. *, metabolism-dependent chemical inhibitors.

Fig. 6.
Fig. 6.

Enzyme kinetics for the formation of ACP-5862 after a 6-minute incubation in pooled human liver microsomes.

UGT and P450 Inhibition by Acalabrutinib and ACP-5862

The inhibition of UGT1A1 and UGT2B7 activity by acalabrutinib or ACP-5862 was determined in HLMs (Supplemental Table 2). No inhibition of UGT1A1 and UGT2B7 activity was observed, with the exception of UGT1A1 inhibition by ACP-5862, observed at 3 μM (34.7%), which was not sufficient to determine an IC50.

The inhibition of individual P450 enzyme activities using selective substrates was evaluated in HLMs (Supplemental Table 2). Based on relevant US Food and Drug Administration–recommended calculations (https://www.fda.gov/regulatory-information/search-fda-guidance-documents/in-vitro-drug-interaction-studies-cytochrome-p450-enzyme-and-transporter-mediated-drug-interactions), acalabrutinib demonstrated weak inhibition of CYP2C8 (IC50 = 37 µM), CYP2C9 (IC50 = 28 µM), or CYP3A4/5 [IC50 = 57 µM (testosterone as substrate); IC50 = 69 µM (midazolam as substrate)]. In a similar manner, the metabolite ACP-5862 demonstrated limited inhibition of CYP2C9 (IC50 = 6.7 µM) and CYP2C19 (IC50 = 17 µM). Following a 30-minute preincubation of acalabrutinib with pooled HLMs in the presence of NADPH, a greater than 1.5-fold shift decrease in IC50 values was observed (Supplemental Table 2). Metabolism-dependent inhibition of CYP3A4/5 by acalabrutinib gave saturable inactivation rates, and kinact and KI values for inactivation of midazolam 1’-hydroxylation and testosterone 6β-hydroxylation were similar and measured to be 0.019 ± 0.001 and 0.018 ± 0.002 minute−1 and 11 ± 2 and 9.2 ± 3.6 µM, respectively. Acalabrutinib showed little or no evidence of metabolism-dependent inhibition of CYP1A2, CYP2B6, CYP2C19, and CYP2D6. Time-dependent inhibition studies of CYP2C8, CYP2C9, and CYP3A4/5 by metabolite ACP-5862 in NADPH-fortified HLMs revealed a shift to lower IC50 values (Supplemental Table 2), indicating potential for metabolism-based inactivation of these isoforms. For the most sensitive enzyme, CYP2C8, the apparent metabolism-dependent inactivation had a measured kinact value of 0.012 ± 0.003 minute−1 and KI value of 4.0 ± 2.5 µM.

P450 Induction by Acalabrutinib and ACP-5862

The potential for acalabrutinib and ACP-5862 to induce the expression of P450 enzymes was examined in primary cultures of freshly isolated human hepatocytes, each from three individual donors (data not shown). Under the conditions of the acalabrutinib study, where the positive controls caused anticipated and appropriate increases in P450 enzyme expression, the effect on CYP1A2 mRNA levels was greatest. Treatment of the cultured human hepatocytes from all three individuals with up to 50 µM acalabrutinib caused concentration-dependent increases (>2.0-fold and >20% of the positive control, up to 32.9-fold change). However, acalabrutinib caused an approximately twofold and 5.8-fold induction of CYP1A2 mRNA at 1 and 5 µM, respectively, the latter having 15% of the effect of the positive control, omeprazole, which showed a 38-fold change in CYP1A2 mRNA. The increase observed in CYP2B6 and 3A4 mRNA levels at 50 µM acalabrutinib concentrations in at least one of the hepatocyte preparations tested was up to 2.9- and 2.44-fold, respectively (also >2.0-fold and/or ≥20% of the positive control). However, acalabrutinib caused little or no induction of CYP2B6 or CYP3A4 mRNA at 10 µM concentrations.

ACP-5862 caused no induction of CYP1A2 or CYP2B6 mRNA at 50 µM concentrations. ACP-5862 caused some modest induction of CYP3A4 mRNA (2.2- to 3.5-fold, which were 1.7% to 3.5% of positive control, 20 µM rifampicin) at 10 µM concentrations.

In Vitro Efflux and Uptake Transporter Inhibition

The potential for acalabrutinib and ACP-5862 to inhibit human P-gp transport across confluent monolayers of Caco-2 cells was assessed by measuring the basolateral-to-apical transport of the probe substrate digoxin (Table 5). Neither acalabrutinib nor ACP-5862 were potent inhibitors of P-gp digoxin transport in Caco-2 cells. Similarly, acalabrutinib and ACP-5862 were not potent inhibitors of BCRP evaluated in MDCKII cells by measuring their effect on the transport of prazosin (Table 5). Acalabrutinib and ACP-5862 were also assessed as inhibitors of the hepatic uptake transporters OATP1B1 and OATP1B3 in HEK293 cells (Supplemental Table 3). Acalabrutinib was not an inhibitor of OATP1B1 and OATP1B3. ACP-5862 only moderately inhibited OATP1B1 and OATP1B3. In addition, acalabrutinib and ACP-5862 were evaluated as inhibitors of the kidney uptake transporters OAT1, OAT3, and OCT2 in HEK293 cells (Supplemental Table 3). Acalabrutinib was not an inhibitor of OAT1 and only moderately inhibited OAT3 and OCT2. ACP-5862 was not a potent inhibitor of OAT1 or OCT2 and did not inhibit OAT3. Finally, similar tests of MATE1 and MATE2-K in HEK293 cells revealed potent inhibition of MATE1 by ACP-5862 (Supplemental Table 3).

View this table:
TABLE 5

Efflux transporter inhibition by acalabrutinib and ACP-5862

Transporter Substrate Assays

The bidirectional permeability of acalabrutinib or ACP-5862 was assessed in MDCKII-P-gp and MDCKII-BCRP cell monolayers to determine their potential to be substrates of P-gp or BCRP in the presence and absence of selective inhibitors (Table 6). Acalabrutinib and ACP-5862 were good substrates for P-gp, and transport for both was strongly inhibited in the presence of a multidrug resistance protein 1 inhibitor, valspodar. The efflux ratios for both acalabrutinib and ACP-5862 were also indicative of being substrates for BCRP and were similarly inhibited by the BCRP inhibitor Ko143.

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TABLE 6

Efflux transporter substrate determination: bidirectional permeability of acalabrutinib and ACP-5862 across MDCKII cells

P-gp positive control was digoxin, and BCRP positive control was prazosin. Data are the mean ± S.D. of triplicate determinations.

The cellular uptake of acalabrutinib or ACP-5862 was assessed in cells transfected with hepatic uptake transporters OATP1B1 or OATP1B3 or vector control. The maximum influx uptake ratio for acalabrutinib observed with OATP1B1 was 1.44, and that for ACP-5862 was 1.66. The maximum uptake ratio for acalabrutinib observed with OATP1B3 was 0.918. The uptake ratio for ACP-5862 was generally <2, and for the instances in which the uptake ratio was near 2, the uptake was not reduced by the presence of rifampicin (10 µM) as inhibitor (data not shown). These data indicate that acalabrutinib and ACP-5862 are not substrates of OATP1B1 and OATP1B3. The cellular uptake of acalabrutinib was similarly assessed in cells transfected with renal uptake transporters. The maximum influx uptake ratio for acalabrutinib observed with OAT1 was 1.26, and that for OAT3 was 1.83. OAT3 acalabrutinib uptake was time-dependent and was reduced in the presence of the OAT3 inhibitor probenecid, suggesting acalabrutinib interacts with OAT3; however, the uptake ratios compared with control cells were <2 at all concentrations tested, suggesting acalabrutinib is not a substrate of OAT3 (data not shown). The maximum influx rate ratio for acalabrutinib observed with OCT2 was 1.85. These data collectively indicate that acalabrutinib is not a substrate of OAT1, OAT3, and OCT2.

Acalabrutinib Metabolite Generation by HLMs

Extracts from [14C]acalabrutinib (10 µM, MH+466) incubations with HLMs and NADPH were analyzed by radiochromatography and LC-MS using a previously described HPLC method (Podoll et al., 2019). Two prominent metabolites were observed that eluted near the parent molecule (40 minutes). The earlier peak at approximately 38 minutes had a protonated molecular ion at m/z 464 that matched the retention time and mass of previously characterized M25 and accounted for approximately 15% of the total radioactivity in the trace. At 2 mass units lower than the parent molecule, the fragmentation pattern was diagnostic for a dehydrogenation or hydroxylation-dehydration within the pyrrolidine ring. Fragment ions at m/z 370 and 342 were supportive of the assigned structure, and an ion at m/z 239 placed the loss of 2 mass units in the pyrrolidine ring (Fig. 7A) via a neutral loss of 134 mass units from the ion at m/z 370. NMR characterization was required to establish the position of the double bond in the dihydropyrrole ring (Fig. 8).

Fig. 7.
Fig. 7.

Product ion mass spectra of metabolites (A) M25 (m/z 464) and (B) M27 (m/z 482) from analysis of a 0- to 6-hour AUC pooled plasma sample obtained from a patient following repeat oral doses of acalabrutinib (100 mg).

Fig. 8.
Fig. 8.

Oxidative metabolic pathway to major active metabolite ACP-5862 (M27).

The second prominent metabolite observed in HLMs, M27, eluted after parent drug at approximately 44 minutes with a +16 Da protonated molecular ion at m/z 482 and accounted for approximately 50% of the total radioactivity in the chromatogram. Following purification by semipreparative HPLC and fraction collection, the isolated biosynthetic metabolite matched the retention time and mass of the initial incubation extract and (as determined later) matched the synthetic standard ACP-5862.

Unlike putative carbinolamide metabolites that would be formed by hydroxylation of the 2- or 5-carbons of the acalabrutinib pyrrolidine ring, hydroxy metabolites of the 3- and 4-positions were expected to be stable. Enantiomers of putative 3- and 4-hydroxypyrrolidine metabolites were synthesized for comparison with M27. All four synthetic compounds eluted earlier than M27 at less than 35 minutes (Supplemental Fig. 1) and had a protonated molecular ion at m/z 482. The fragmentation diagnostic for stable 3- and 4-hydroxylated pyrrolidine standards included fragment ions m/z 152 and 86, which were also observed for the late-eluting M27 peak (Fig. 7B). Ultimately, NMR spectroscopy was required to define the structure of M27.

Structural Elucidation of M25 and M27 by NMR

Details of the NMR results can be found in the Supplemental Results, Supplemental Figs. 2–10, and Supplemental Tables 4–6. Briefly, the analysis focused on the aliphatic regions of the spectra of M25 and M27, which were compared with prior data available for acalabrutinib. For M25, the aliphatic region revealed a splitting of the methyl protons at the end of the butynamide into two singlets (Supplemental Table 4). This was similarly found in the aliphatic region of the acalabrutinib proton NMR and ascribed to a conformational exchange around the amide bond in the intact pyrrolidine ring. In contrast, there was no evidence of inversion in the NMR of M27, wherein all three protons were ascribed to one singlet (Supplemental Fig. 6; Supplemental Table 5). Additionally, the M27 NMR revealed that the triplet, quintet, triplet proton splitting pattern of three isolated, contiguous, and freely rotating methylene groups was present, also consistent with the opening of the pyrrolidine ring. Finally, a 1H–13C 2/3-bond correlation experiment (Fig. 9) showed coupling between protons labeled Hb and Hc with an adjacent carbonyl carbon at 191 ppm. Overall, 1H NMR and 1H-13C correlation spectra indicated an acalabrutinib biotransformation mechanism wherein hydroxylation of the chiral benzylic carbon between the fused imidazole-pyrazine ring system and the pyrrolidine ring nitrogen affords an unstable carbinolamide intermediate. The carbinolamide undergoes spontaneous ring opening to the keto-amide major metabolite (M27) or dehydration to the unsaturated, dihydropyrrole M25 (Fig. 8). Taken together, the structure of metabolites M25 and M27 triangulate back to the common carbinolamide intermediate. The structure of M27 was ultimately confirmed by comparison of the NMR data to those of a synthetic standard (ACP-5862).

Fig. 9.
Fig. 9.

An expanded aliphatic region of the 1H–13C gradient selected heteronuclear 2/3-bond correlation NMR spectrum of acalabrutinib metabolite M27 (ACP-5862).

Discussion

ACP-5862 is a major metabolite of acalabrutinib that was previously observed to have systemic exposure, which justified testing whether it could contribute to the pharmacological activity of acalabrutinib therapy (Podoll et al., 2019). In this work, we further elucidated the structure of ACP-5862 as a pyrrolidine ring–opened ketone/amide that was rapidly formed and metabolized by CYP3A. The butynamide warhead was retained, and the metabolite demonstrated intrinsic activity against BTK similar to the parent molecule. The ACP-5862 primary pharmacology data were consistent with a covalent mechanism of action, demonstrated activity in cellular assays, and a selectivity profile similar to that of acalabrutinib. Taken together, these findings suggest the potential for a clinically relevant pharmacological effect by ACP-5862.

Acalabrutinib and ACP-5862 have similar overall kinase selectivity profiles and are more selective for BTK compared with ibrutinib and zanubrutinib (Fig. 4). This was demonstrated using a competitive binding assay (Fabian et al., 2005), which avoids the dependency of the assay on ATP concentration or choice of substrate as seen in previous comparisons (Guo et al., 2019; Shadman et al., 2021). The lowest overall kinase hit rates were observed for acalabrutinib and ACP-5862 when compared with ibrutinib and zanubrutinib, indicating no loss in selectivity for the major metabolite (Table 3). Similar selectivity for BTK over other kinases having Cys in the same position as the Cys481 residue in BTK was observed for parent and metabolite (Table 1), with ACP-5862 being slightly more potent on BMX and acalabrutinib more potent on ERBB4. The structural features of acalabrutinib that are retained in ACP-5862, including retention of the ATP binding site recognition of the imidazopyridine core and the butynamide warhead of acalabrutinib, impart the selectivity advantage of the parent molecule onto the metabolite compared with the acryloyl warhead–containing BTK inhibitors ibrutinib and zanubrutinib.

This is confirmed when looking at the fold selectivity versus BTK for the panel of kinases with potential for covalent binding. Both acalabrutinib and ACP-5862 showed an enhanced selectivity versus BTK for this kinase panel compared with ibrutinib and zanubrutinib. Affinity is not the only criterion for selectivity, and inclusion of both acalabrutinib and ACP-5862 inactivation kinetics may be required to fully assess acalabrutinib’s relative selectivity among covalent inhibitor therapies (Hopper et al., 2020).

The difference in inhibition potency (IC50) over time between BTK-WT and BTK-C481S (Fig. 2) indicated that both acalabrutinib and ACP-5862 bind covalently to Cys481 in the ATP binding site of BTK. The nonlinear time-dependent decrease in IC50 observed in BTK-WT reflects the time-dependent loss of BTK activity, typically observed for targeted covalent inhibitors under saturating conditions (Krippendorff et al., 2009). The serine residue in the mutant form of BTK with Cys481Ser no longer serves as a nucleophile for the covalent binding, and the modest inhibition observed reflects the reversible interaction of acalabrutinib and metabolite with BTK. These combined results are in line with a shared mechanism of BTK inhibition for both ACP-5862 and acalabrutinib—covalent binding to Cys481. The BTK inactivation rate (kinact) of ACP-5862 was twofold lower than that of acalabrutinib (Table 2) (Barf et al., 2017), which may be influenced by metabolic oxidation and opening of the pyrrolidine ring. The low flexibility between the electrophile and the imidazopyridine core in acalabrutinib provides the optimal geometry for rapid bond formation (Liu et al., 2013). In silico docking of ACP-5862 in the active site of BTK is consistent with covalent binding to Cys481 (Fig. 3). Increased flexibility of the linear butanoyl electrophile, and potentially reduced reactivity of the butynamide moiety, may explain the twofold lower kinact value of ACP-5862 compared with acalabrutinib.

Comparison of the inactivation kinetics between the acrylamide- and butynamide-containing covalent inhibitors is consistent with their anticipated relative reactivity. The kinact/KI values for ibrutinib and zanubrutinib are approximately an order of magnitude higher than acalabrutinib and ACP-5862 (Table 2), indicating higher efficiency of covalent bond formation by the more reactive acrylamide. The kinact/KI defines the relationship between the rate of bond formation, time, and the inhibitor concentration (Strelow, 2017). Model-derived estimates of occupancy based on the kinact/KI and unbound area under the curve (AUC) of a covalent inhibitor show that concentrations at and above its KI do not meaningfully increase inactivation rates. Simultaneously, higher inhibitor concentrations decrease the selectivity for the intended target (Strelow, 2017). Strelow (2017) concludes that covalent kinase inhibitors may be dosed at levels that minimize inactivation of off-target kinases by balancing the unbound AUC with the kinact/KI to optimize for the targeted kinase. Acalabrutinib is dosed to achieve exposures necessary for prolonged target coverage (BTK occupancy). When the total active moiety [acalabrutinib (100 mg twice daily) plus ACP-5862 steady-state plasma concentrations] is considered, the exposure achieved is comparable to that of ibrutinib (560 mg daily) and zanubrutinib (160 mg twice daily) alone, all at doses that have high clinical BTK occupancy (≥95%) (Edlund et al., 2022b). In the case of acalabrutinib, additional exposure to the metabolite may have provided prolonged BTK occupancy over the treatment interval at a lower dose than with acalabrutinib alone.

Because assay conditions in biochemical kinase assays affect potency (ATP concentration, kinase concentration, incubation time, etc.), comparison of potency was also conducted using cellular assays. When examining inhibition of BCR-stimulated peripheral B cells of healthy individuals, using either human PBMCs or human WB, ACP-5862 was seven- to ninefold less potent than acalabrutinib (Table 4). Ibrutinib and zanubrutinib showed an EC50 of 5.8 and 2.4 nM, respectively, in human WB, in line with previously reported data (Guo et al., 2019). Fully reversible inhibitors that show potency differences in static, cellular in vitro systems can be influenced by differences in free fraction, or cellular partitioning, and the free fraction of ACP-5862 is approximately half that of acalabrutinib (Podoll et al., 2019). However, although the initial binding kinetics may be influential, the steady-state in vivo efficacy for an irreversible inhibitor is not determined by free drug concentrations (Smith et al., 2010). The actual contribution of the ACP-5862 metabolite to clinical efficacy in humans cannot be discerned from BTK occupancy data since the assay does not distinguish between BTK bound to parent versus that to metabolite. Yet, findings from a published exposure-response analysis demonstrated similar efficacy results when assessed as a function of acalabrutinib and ACP-5862 exposure (AUC and Cmax) (Edlund et al., 2022b). The totality of the exposure and activity data denote a secondary role of the active metabolite ACP-5862 relative to the parent drug (Podoll et al., 2019).

No dose modifications with cytochrome P450 substrates are required for acalabrutinib and ACP-5862 as perpetrators based on in vitro IC50 values and clinical levels (https://den8dhaj6zs0e.cloudfront.net/50fd68b9-106b-4550-b5d0-12b045f8b184/61cc04a6-2b15-49f0-a896-192e8462ef3d/61cc04a6-2b15-49f0-a896-192e8462ef3d_viewable_rendition__v.pdf). Both are eliminated by CYP3A4, reducing the chance that the sum of the total active moieties would become the victim of CYP3A inhibitors or inducers. The Clint of acalabrutinib, 52.3 µl/min per mg for ACP-5862 product formation (Vmax/Km), was greater than the Clint of ACP-5862 metabolic clearance in HLM. These data are in agreement with clinical studies, which showed the half-life and AUC of ACP-5862 were approximately twofold higher than acalabrutinib in healthy subjects and cancer patients (Zhou et al., 2019; Edlund et al., 2022b). The effects of CYP3A inhibitors on acalabrutinib PK were evaluated in a previous study using a physiologically based pharmacokinetic model, taking into account effects on both parent and metabolite (Zhou et al., 2019). These findings were confirmed during acalabrutinib clinical evaluations as a victim with CYP3A inhibitors, which ultimately influence dose recommendations (Chen et al., 2022). This substantiates the reported data and reinforces the importance of considering all pharmacologically active entities with acalabrutinib therapy. PK of substrates of most transporters also are not likely to be altered by acalabrutinib or ACP-5862 (Supplemental Table 3). Static PK model calculations indicated modest increases in exposure to coadministered BCRP substrates via inhibition of intestinal BCRP (acalabrutinib) or renal MATE1 (ACP-5862). However, based on exposure relative to clinically impactful MATE1 inhibitors (Hibma et al., 2016; Zamek-Gliszczynski et al., 2018), this was not expected to be clinically actionable.

The prior study revealed the structure of the ACP-5862 to be a pyrrolidine ring that was oxidized at 1 of 5 positions, but full characterization was not achieved (Podoll et al., 2019). The 2-position oxidation to a carbinolamide, and its ring-opened ketone/amide congener, was proven with the NMR spectra of the biosynthetic and synthetic reference samples. The 2 position was the biotransformation most likely to result in a metabolite less polar than the parent drug (Fig. 8). The M25 metabolite was also isolated, purified, and characterized by NMR to unambiguously assign both structures (Fig. 9; Supplemental Figs. 2–10; Supplemental Tables 1–3).

In conclusion, this work characterized the structure and biologic activity of ACP-5862, the major metabolite of acalabrutinib. The current data suggest that ACP-5862 may be clinically relevant to the efficacy of acalabrutinib therapy while retaining any potential benefits of high BTK selectivity.

Acknowledgments

The authors thank the staff of XenoTech, LLC for their performance and reporting of the GST, P450, and transporter in vitro drug interaction experiments. Editorial assistance, funded by AstraZeneca, was provided by Allison Green and Cynthia Gobbel of Peloton Advantage, LLC, an OPEN Health company.

Authorship Contributions

Participated in research design: Podoll, Pearson, Kaptein, Evarts, de Bruin, Fretland, Barf, Slatter.

Conducted experiments: de Bruin, Emmelot-van Hoek, de Jong, van Lith, Sun, Byard, Hoogenboom.

Performed data analysis: Podoll, Pearson, Kaptein, Evarts, de Bruin, Emmelot-van Hoek, de Jong, van Lith, Sun, Byard, Fretland, Hoogenboom, Barf, Slatter.

Wrote or contributed to the writing of the manuscript: Podoll, Pearson, Kaptein, Evarts, de Bruin, Emmelot-van Hoek, de Jong, van Lith, Sun, Byard, Fretland, Hoogenboom, Barf, Slatter.

Footnotes

    • Received January 19, 2022.
    • Accepted October 17, 2022.

  • This study was supported by Acerta Pharma, a member of the AstraZeneca Group.

  • T.P. and J.E. were employed by Acerta Pharma at the time of the study, hold Acerta Pharma patents, and hold AstraZeneca stock. J.G.S. was employed by Acerta Pharma at the time of the study and holds AstraZeneca stock. A.F. was employed by Acerta Pharma at the time of the study. G.d.B., A.d.J., and N.H. are employees of Acerta Pharma B.V. M.E.-v.H. and B.v.L. are employees and stockholders of Acerta Pharma B.V. P.G.P. is an employee of Pearson Pharma Partners, which was hired by Acerta Pharma during the time of the study to serve in a consultancy capacity, and holds AstraZeneca stock. A.K. and T.B. are employees of Covalution Biosciences B.V., Ravenstein, The Netherlands, which was hired by Acerta Pharma during the time of the study to serve in a consultancy capacity, and hold Acerta Pharma B.V. stock. H.S. was an employee of Covance Laboratories, which was hired by Acerta Pharma during the time of the study to serve in a consultancy capacity. S.B. is an employee of Arcinova, which was hired by Acerta Pharma during the time of the study to serve in a consultancy capacity.

  • ↵1T.P., P.G.P., and A.K. contributed equally to this work.

  • dx.doi.org/10.1124/jpet.122.001116.

  • ↵Embedded ImageThis article has supplemental material available at jpet.aspetjournals.org.

Abbreviations

ACN
acetonitrile
AUC
area under the curve
BCRP
breast cancer resistance protein
BLK
B-lymphocyte kinase
BMX
BMX nonreceptor tyrosine kinase
BTK
Bruton tyrosine kinase
BTK-WT
wild-type BTK
Clint
intrinsic clearance
EGFR
epidermal growth factor receptor
ERBB2
erythroblastosis oncogene B2
ERBB4
erythroblastosis oncogene B4
GSH
glutathione
GST
glutathione S-transferase
HEK293
human embryonic kidney 293
HER
human epidermal growth factor receptor
HLM
human liver microsome
HPLC
high-performance liquid chromatography
IMAP
immobilized metal ion affinity-based fluorescence polarization
ITK
interleukin-2–inducible T-cell kinase
JAK3
Janus-associated kinase 3
KI
inhibitory constant
kinact
inactivation rate constant
kinact/KI
second-order rate constants
Km
Michaelis constant
LC-MS/MS
liquid chromatography with tandem mass spectrometry
MDCKII
Madin-Darby canine kidney
MeOH
methanol
P450
cytochrome P450
PBMC
peripheral blood mononuclear cell
P-gp
P-glycoprotein
PK
pharmacokinetic
rCYP
recombinant cytochrome P450
TEC
Tec protein tyrosine kinase
TXK
TXK tyrosine kinase/protein tyrosine kinase 4
UGT
uridine 5′-diphospho-glucuronosyltransferase
WB
whole blood

This is an open access article distributed under the CC BY-NC Attribution 4.0 International license.

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Research ArticleMetabolism, Transport, and Pharmacogenetics

ACP-5862—Major Metabolite of BTK Inhibitor Acalabrutinib

Terry Podoll, Paul G. Pearson, Allard Kaptein, Jerry Evarts, Gerjan de Bruin, Maaike Emmelot-van Hoek, Anouk de Jong, Bart van Lith, Hao Sun, Stephen Byard, Adrian Fretland, Niels Hoogenboom, Tjeerd Barf and J. Greg Slatter
Journal of Pharmacology and Experimental Therapeutics January 1, 2023, 384 (1) 173-186; DOI: https://doi.org/10.1124/jpet.122.001116
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