Top

Cancer Chemotherapy and Pharmacology

Published in:

Open Access 01-02-2021 | Pharmacokinetics | Original Article

Population pharmacokinetics of ATR inhibitor berzosertib in phase I studies for different cancer types

Authors: Nadia Terranova, Mendel Jansen, Martin Falk, Bart S. Hendriks

Published in: Cancer Chemotherapy and Pharmacology | Issue 2/2021

Abstract

Purpose

Berzosertib (formerly M6620) is the first-in-class inhibitor of ataxia–telangiectasia and Rad3-related protein, a key component of the DNA damage response, and being developed in combination with chemotherapy for the treatment of patients with advanced cancers. The objectives of this analysis were to characterize the pharmacokinetics (PK) of berzosertib across multiple studies and parts, estimate inter-individual variability, and identify covariates that could explain such variability.

Methods

A population PK analysis was performed using the combined dataset from two phase I clinical studies (NCT02157792, EudraCT 2013-005100-34) in patients with advanced cancers receiving an intravenous infusion of berzosertib alone or in combination with chemotherapy. The analysis included data from 240 patients across 11 dose levels (18–480 mg/m²). Plasma concentration data were modeled with a non-linear mixed-effect approach and clinical covariates were evaluated.

Results

PK data were best described by a two-compartment linear model. For a typical patient, the estimated clearance (CL) and intercompartmental CL were 65 L/h and 295 L/h, respectively, with central and peripheral volumes estimated to be 118 L and 1030 L, respectively. Several intrinsic factors were found to influence berzosertib PK, but none were considered clinically meaningful due to a very limited effect. Model simulations indicated that concentrations of berzosertib exceeded p-Chk1 (proximal pharmacodynamic biomarker) IC₅₀ at recommended phase II doses in combination with carboplatin, cisplatin, and gemcitabine.

Conclusions

There was no evidence of a clinically significant PK interaction between berzosertib and evaluated chemo-combinations. The covariate analysis did not highlight any need for dosing adjustments in the population studied to date.

Clinical Trial information

NCT02157792, EudraCT 2013-005100-34

Available only for authorised users

Reaper PM, Griffiths MR, Long JM, Charrier JD, Maccormick S, Charlton PA, Golec JM, Pollard JR (2011) Selective killing of ATM- or p53-deficient cancer cells through inhibition of ATR. Nat Chem Biol 7(7):428–430. https://doi.org/10.1038/nchembio.573CrossRefPubMed

Knegtel R, Charrier JD, Durrant S, Davis C, O’Donnell M, Storck P, MacCormick S, Kay D, Pinder J, Virani A, Twin H, Griffiths M, Reaper P, Littlewood P, Young S, Golec J, Pollard J (2019) Rational Design of 5-(4-(Isopropylsulfonyl)phenyl)-3-(3-(4-((methylamino)methyl)phenyl)isoxazol-5-yl )pyrazin-2-amine (VX-970, M6620): optimization of intra- and intermolecular polar interactions of a new ataxia telangiectasia mutated and Rad3-related (ATR) kinase inhibitor. J Med Chem 62(11):5547–5561. https://doi.org/10.1021/acs.jmedchem.9b00426CrossRefPubMed

Puigvert JC, Sanjiv K, Helleday T (2016) Targeting DNA repair, DNA metabolism and replication stress as anti-cancer strategies. Febs j 283(2):232–245. https://doi.org/10.1111/febs.13574CrossRefPubMed

Cimprich KA, Cortez D (2008) ATR: an essential regulator of genome integrity. Nat Rev Mol Cell Biol 9(8):616–627. https://doi.org/10.1038/nrm2450CrossRefPubMedPubMedCentral

Blackford AN, Jackson SP (2017) ATM, ATR, and DNA-PK: the trinity at the heart of the DNA damage response. Mol Cell 66(6):801–817. https://doi.org/10.1016/j.molcel.2017.05.015CrossRefPubMed

Yazinski SA, Zou L (2016) Functions, regulation, and therapeutic implications of the ATR checkpoint pathway. Annu Rev Genet 50:155–173. https://doi.org/10.1146/annurev-genet-121415-121658CrossRefPubMed

Gaillard H, Garcia-Muse T, Aguilera A (2015) Replication stress and cancer. Nat Rev Cancer 15(5):276–289. https://doi.org/10.1038/nrc3916CrossRefPubMed

O’Connor MJ (2015) Targeting the DNA damage response in cancer. Mol Cell 60(4):547–560. https://doi.org/10.1016/j.molcel.2015.10.040CrossRefPubMed

Flynn RL, Cox KE, Jeitany M, Wakimoto H, Bryll AR, Ganem NJ, Bersani F, Pineda JR, Suva ML, Benes CH, Haber DA, Boussin FD, Zou L (2015) Alternative lengthening of telomeres renders cancer cells hypersensitive to ATR inhibitors. Science 347(6219):273–277. https://doi.org/10.1126/science.1257216CrossRefPubMedPubMedCentral

10.

Kotsantis P, Petermann E, Boulton SJ (2018) Mechanisms of oncogene-induced replication stress: jigsaw falling into place. Cancer Discov 8(5):537–555. https://doi.org/10.1158/2159-8290.Cd-17-1461CrossRefPubMedPubMedCentral

11.

Hall AB, Newsome D, Wang Y, Boucher DM, Eustace B, Gu Y, Hare B, Johnson MA, Milton S, Murphy CE, Takemoto D, Tolman C, Wood M, Charlton P, Charrier JD, Furey B, Golec J, Reaper PM, Pollard JR (2014) Potentiation of tumor responses to DNA damaging therapy by the selective ATR inhibitor VX-970. Oncotarget 5(14):5674–5685. https://doi.org/10.18632/oncotarget.2158CrossRefPubMedPubMedCentral

12.

Fordham SE, Blair HJ, Elstob CJ, Plummer R, Drew Y, Curtin NJ, Heidenreich O, Pal D, Jamieson D, Park C, Pollard J, Fields S, Milne P, Jackson GH, Marr HJ, Menne T, Jones GL, Allan JM (2018) Inhibition of ATR acutely sensitizes acute myeloid leukemia cells to nucleoside analogs that target ribonucleotide reductase. Blood Adv 2(10):1157–1169. https://doi.org/10.1182/bloodadvances.2017015214CrossRefPubMedPubMedCentral

13.

Fokas E, Prevo R, Pollard JR, Reaper PM, Charlton PA, Cornelissen B, Vallis KA, Hammond EM, Olcina MM, Gillies McKenna W, Muschel RJ, Brunner TB (2012) Targeting ATR in vivo using the novel inhibitor VE-822 results in selective sensitization of pancreatic tumors to radiation. Cell Death Dis 3(12):e441. https://doi.org/10.1038/cddis.2012.181CrossRefPubMedPubMedCentral

14.

Prevo R, Fokas E, Reaper PM, Charlton PA, Pollard JR, McKenna WG, Muschel RJ, Brunner TB (2012) The novel ATR inhibitor VE-821 increases sensitivity of pancreatic cancer cells to radiation and chemotherapy. Cancer Biol Ther 13(11):1072–1081. https://doi.org/10.4161/cbt.21093CrossRefPubMedPubMedCentral

15.

Parsels LA, Qian Y, Tanska DM, Gross M, Zhao L, Hassan MC, Arumugarajah S, Parsels JD, Hylander-Gans L, Simeone DM, Morosini D, Brown JL, Zabludoff SD, Maybaum J, Lawrence TS, Morgan MA (2011) Assessment of chk1 phosphorylation as a pharmacodynamic biomarker of chk1 inhibition. Clin Cancer Res 17(11):3706–3715. https://doi.org/10.1158/1078-0432.CCR-10-3082CrossRefPubMedPubMedCentral

16.

Pollard J, Reaper P, Peek A, Hughes S, Gladwell S, Jones J, Chiu P, Wood M, Tolman C, Johnson M, Littlewood P, Penney M, McDermott K, Hare B, Fields SZ, Asmal M, O’ Carrigan B, Yap TA (2016) Defining optimal dose schedules for ATR inhibitors in combination with DNA damaging drugs: Informing clinical studies of VX-970, the first-inclass ATR inhibitor. Cancer Res. https://doi.org/10.1158/1538-7445.AM2016-3717CrossRefPubMed

17.

Hare B, Haseltine E, Penney M, Viswanathan L, Brown J, Ganegoda M, Pollard J, Yap T, Fields SZ (2016) PK/PD modeling predicts robust target engagement and low probability of grade 4 hematological toxicity at recommended phase 2 starting dose of VX-970 in combination with carboplatin (AUC=5). Presented at ACOP7, Bellevue, Washington, USA, 24–26 October 2016. Poster M-07

18.

Shapiro G, Wesolowski R, Middleton M, Devoe C, Constantinidou A, Papadatos-Pastos D, Fricano M, Zhang Y, Karan S, Pollard J, Penney M, Asmal M, Renshaw FG, Fields SZ, Yap TA (2016) Phase 1 trial of first-in-class ATR inhibitor VX-970 in combination with cisplatin (Cis) in patients (pts) with advanced solid tumors (NCT02157792). Cancer Res. https://doi.org/10.1158/1538-7445.AM2016-CT012CrossRefPubMedPubMedCentral

19.

Yap TA, O’Carrigan B, Penney MS, Lim JS, Brown JS, de Miguel Luken MJ, Tunariu N, Perez-Lopez R, Rodrigues DN, Riisnaes R, Figueiredo I, Carreira S, Hare B, McDermott K, Khalique S, Williamson CT, Natrajan R, Pettitt SJ, Lord CJ, Banerji U, Pollard J, Lopez J, de Bono JS (2020) Phase I trial of first-in-class ATR inhibitor M6620 (VX-970) as monotherapy or in combination with carboplatin in patients with advanced solid tumors. J Clin Oncol. https://doi.org/10.1200/JCO.19.02404CrossRefPubMedPubMedCentral

20.

Plummer ER, Dean EJ, Evans TRJ, Greystoke A, Herbschleb K, Ranson M, Brown J, Zhang Y, Karan S, Pollard J, Penney MS, Asmal M, Fields SZ, Middleton MR (2016) Phase I trial of first-in-class ATR inhibitor VX-970 in combination with gemcitabine (Gem) in advanced solid tumors (NCT02157792). J Clin Oncol 34(15_suppl):2513. https://doi.org/10.1200/JCO.2016.34.15_suppl.2513CrossRef

21.

Gastonguay M (2011) Full covariate models as an alternative to methods relying on statistical significance for inferences about covariate effects: a review of methodology and 42 case studies. Presented at PAGE Annual Meeting, Athens, Greece, June 7–10 2011. Abstract 2229

22.

US Food and Drug Administration F (2010) Pharmacokinetics in Patients with Impaired Renal Function — Study Design, Data Analysis, and Impact on Dosing and Labeling. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/pharmacokinetics-patients-impaired-renal-function-study-design-data-analysis-and-impact-dosing-and. Accessed 30 Mar 2020

23.

Mansfield AS, Rudek MA, Vulih D, Smith GL, Harris PJ, Ivy SP, Group NCIODW (2016) The effect of hepatic impairment on outcomes in Phase I clinical trials in cancer subjects. Clin Cancer Res 22(22):5472–5479. https://doi.org/10.1158/1078-0432.CCR-16-0449CrossRefPubMedPubMedCentral

24.

Beal S, Sheiner L, Boeckmann A, Bauer R (1989) NONMEM users guides. Icon Development Solutions, Ellicott City

25.

Keizer RJ, Karlsson MO, Hooker A (2013) Modeling and simulation workbench for NONMEM: tutorial on pirana, PsN, and Xpose. CPT Pharmacomet Syst Pharmacol 2(6):e50. https://doi.org/10.1038/psp.2013.24CrossRef

26.

Lindbom L, Ribbing J, Jonsson EN (2004) Perl-speaks-NONMEM (PsN)–a Perl module for NONMEM related programming. Comput Methods Programs Biomed 75(2):85–94. https://doi.org/10.1016/j.cmpb.2003.11.003CrossRefPubMed

27.

Keizer RJ, van Benten M, Beijnen JH, Schellens JH, Huitema AD (2011) Piraña and PCluster: a modeling environment and cluster infrastructure for NONMEM. Comput Methods Programs Biomed 101(1):72–79. https://doi.org/10.1016/j.cmpb.2010.04.018CrossRefPubMed

28.

R Development Core Team (2013) R: a language and environment for statistical computing. Vol. 3.3.1. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/. Accessed 10 Mar 2020

29.

Wählby U, Bouw MR, Jonsson EN, Karlsson MO (2002) Assessment of type I error rates for the statistical sub-model in NONMEM. J Pharmacokinet Pharmacodyn 29(3):251–269. https://doi.org/10.1023/a:1020254823597CrossRefPubMed

30.

Bergstrand M, Hooker AC, Wallin JE, Karlsson MO (2011) Prediction-corrected visual predictive checks for diagnosing nonlinear mixed-effects models. AAPS J 13(2):143–151. https://doi.org/10.1208/s12248-011-9255-zCrossRefPubMedPubMedCentral

31.

van Rongen A, Kervezee L, Brill M, van Meir H, den Hartigh J, Guchelaar HJ, Meijer JH, Burggraaf J, van Oosterhout F (2015) Population pharmacokinetic model characterizing 24-hour variation in the pharmacokinetics of oral and intravenous midazolam in healthy volunteers. CPT Pharmacomet Syst Pharmacol 4(8):454–464. https://doi.org/10.1002/psp4.12007CrossRef

32.

Baker SD, van Schaik RH, Rivory LP, Ten Tije AJ, Dinh K, Graveland WJ, Schenk PW, Charles KA, Clarke SJ, Carducci MA, McGuire WP, Dawkins F, Gelderblom H, Verweij J, Sparreboom A (2004) Factors affecting cytochrome P-450 3A activity in cancer patients. Clin Cancer Res 10(24):8341–8350. https://doi.org/10.1158/1078-0432.Ccr-04-1371CrossRefPubMed

33.

Thomas A, Redon CE, Sciuto L, Padiernos E, Ji J, Lee MJ, Yuno A, Lee S, Zhang Y, Tran L, Yutzy W, Rajan A, Guha U, Chen H, Hassan R, Alewine CC, Szabo E, Bates SE, Kinders RJ, Steinberg SM, Doroshow JH, Aladjem MI, Trepel JB, Pommier Y (2018) Phase I study of ATR inhibitor M6620 in combination with topotecan in patients with advanced solid tumors. J Clin Oncol 36(16):1594–1602. https://doi.org/10.1200/jco.2017.76.6915CrossRefPubMed

Title: Population pharmacokinetics of ATR inhibitor berzosertib in phase I studies for different cancer types
Authors: Nadia Terranova
Mendel Jansen
Martin Falk
Bart S. Hendriks
Publication date: 01-02-2021
Publisher: Springer Berlin Heidelberg
Keywords: Pharmacokinetics
Cytostatic Therapy
Published in: Cancer Chemotherapy and Pharmacology / Issue 2/2021
Print ISSN: 0344-5704
Electronic ISSN: 1432-0843
DOI: https://doi.org/10.1007/s00280-020-04184-z

Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Watch now

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras

Prof. Fabrice Barlesi

Developed by: Springer Medicine

Keynote webinar | Spotlight on sleep in brain health

Springer Medicine

Abstract

Purpose

Methods

Results

Conclusions

Clinical Trial information

Please log in to get access to this content

Other articles of this Issue 2/2021

Cyclooxygenase activity mediates colorectal cancer cell resistance to the omega-3 polyunsaturated fatty acid eicosapentaenoic acid

PDK4 promotes tumorigenesis and cisplatin resistance in lung adenocarcinoma via transcriptional regulation of EPAS1

Overriding sorafenib resistance via blocking lipid metabolism and Ras by sphingomyelin synthase 1 inhibition in hepatocellular carcinoma

Monitoring of EGFR mutations in circulating tumor DNA of non-small cell lung cancer patients treated with EGFR inhibitors

Tumor microenvironment promotes breast cancer chemoresistance

Population pharmacokinetic and pharmacodynamic modeling of capecitabine and its metabolites in breast cancer patients

Keynote webinar | Spotlight on antibody–drug conjugates in cancer