Originally published as JCO Early Release 10.1200/JCO.2007.14.1127 on March 10 2008

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Identifying Optimal Biologic Doses of Everolimus (RAD001) in Patients With Cancer Based on the Modeling of Preclinical and Clinical Pharmacokinetic and Pharmacodynamic Data

Chiaki Tanaka, Terence O’Reilly, John M. Kovarik, Nicholas Shand, Katharine Hazell, Ian Judson, Eric Raymond, Sabine Zumstein-Mecker, Christine Stephan, Anne Boulay, Marc Hattenberger, George Thomas, Heidi A. Lane

From the Novartis Pharmaceuticals Corp, East Hanover, NJ; Novartis Institutes for BioMedical Research Basel, Novartis Pharma AG; Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland; Institute of Cancer Research, Sutton, Surrey, United Kingdom; Hôpital Beaujon, Clichy Cedex, France; and the Genome Research Institute, University of Cincinnati, Cincinnati, OH

Corresponding author: Heidi A. Lane, PhD, Basilea Pharmaceutica Ltd, Grenzacherstrasse 487, PO Box, Basel, Switzerland CH-4005; e-mail: heidi.lane@basilea.com

	ABSTRACT

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Purpose To use preclinical and clinical pharmacokinetic (PK)/pharmacodynamic (PD) modeling to predict optimal clinical regimens of everolimus, a novel oral mammalian target of rapamycin (mTOR) inhibitor, to carry forward to expanded phase I with tumor biopsy studies in cancer patients.

Patients and Methods Inhibition of S6 kinase 1 (S6K1), a molecular marker of mTOR signaling, was selected for PD analysis in peripheral blood mononuclear cells (PBMCs) in a phase I clinical trial. PK and PD were measured up to 11 days after the fourth weekly dose. A PK/PD model was used to describe the relationship between everolimus concentrations and S6K1 inhibition in PBMCs of cancer patients and in PBMCs and tumors of everolimus-treated CA20948 pancreatic tumor-bearing rats.

Results Time- and dose-dependent S6K1 inhibition was demonstrated in human PBMCs. In the rat model, a relationship was shown between S6K1 inhibition in tumors or PBMCs and antitumor effect. This allowed development of a direct-link PK/PD model that predicted PBMC S6K1 inhibition-time profiles in patients. Comparison of rat and human profiles simulated by the model suggested that a weekly 20- to 30-mg dose of everolimus would be associated with an antitumor effect in an everolimus-sensitive tumor and that daily administration would exert a greater effect than weekly administration at higher doses.

Conclusion A direct-link PK/PD model predicting the time course of S6K1 inhibition during weekly and daily everolimus administration allowed extrapolation from preclinical studies and first clinical results to select optimal doses and regimens of everolimus to explore in future clinical trials.

	INTRODUCTION

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Everolimus (RAD001) is an orally active inhibitor of the mammalian target of rapamycin (mTOR) currently in clinical trials. mTOR is a multifunctional signal transduction kinase¹ which has been implicated in cancer,^1,2 consequently targeting this kinase in patients with cancer has received considerable attention.^2,3 mTOR regulates mRNA translation⁴ via the serine/threonine kinase p70S6 kinase (S6K), of which there are two forms (S6K1 and S6K2). S6K regulates protein translation through phosphorylation of the ribosomal protein S6. The mTOR kinase also modulates phosphorylation of eukaryotic initiation factor-4E (eIF-4E) binding protein 1 (4E-BP1), releasing its inhibition of eIF-4E, thus permitting efficient cap-dependent translation.^1,5

Everolimus blocks the mTOR pathway via a complex with the immunophilin FK506-binding protein-12 (FKBP-12), which binds with high affinity to mTOR. Everolimus acts directly on tumor cells to inhibit tumor growth both in vitro and in vivo,^1,2,4,6-9 and also has antiangiogenic activity.^10,11 Presumably, both activities occur through inhibition of mTOR signaling.⁴

The use of targeted agents, such as everolimus, in oncology should be directed by biologic end points that define a biologically active regimen in order to optimize the anticancer effect while limiting undesirable adverse effects, such as immunosuppression—a feature exploited in the use of mTOR inhibitors for the treatment of organ transplant recipients.¹² These considerations prompted us to study everolimus dosage regimens for phase I clinical trials in oncology.

Previous work has demonstrated that everolimus displays significant antitumor activity in a syngeneic CA20948 rat pancreatic tumor model.⁹ Equivalent activity was observed with daily or intermittent (weekly) treatment schedules and analysis of 4E-BP1 and S6K1 in tumor, skin, and peripheral blood mononuclear cell (PBMC) extracts demonstrated long-term modulation of mTOR activity, which correlated with antitumor activity in this sensitive model,⁹ and was consistent with in vitro observations.^13,14 Furthermore, the duration of S6K1 inactivation in PBMCs correlated with the dose-dependent suppression of tumor growth observed with weekly regimens.⁹ S6K1 activity could be reproducibly measured in human PBMCs,⁹ hence PBMC-derived S6K1 activity was chosen as a pharmacodynamic (PD) marker in patients.

The application of pharmacokinetic (PK)/PD modeling has been proposed as potentially beneficial in all phases of preclinical and clinical drug development.¹⁵ PK results are meaningful if there is a known relationship between the drug concentration and its effects. Determination of PD effects alone produces a time-effect relationship that is only valid under the assumption of a constant drug concentration at the effect site. PK/PD models link dose-concentration relationships and concentration-effect relationships, thereby facilitating the description and prediction of a time course of drug effects. Such studies are useful in developing drug administration regimens for clinical use, especially when PK/PD data from clinical studies are incorporated into the model. A phase I study of everolimus in patients with advanced cancer was conducted to investigate the safety, tolerability, PK, and PD of everolimus using inhibition of PBMC-derived S6K1 activity as the biomarker.¹⁶ We used everolimus PK data from patients with cancer and tumor-bearing rats, together with measurement of S6K1 activity in PBMCs and tumors from rats and PBMCs from patients, to provide a quantitative prediction of the PD effect of everolimus in human tumors using different clinical dosing regimens. This represented the first step to identify optimal dosages and regimens based on molecular PD considerations, for exploration in an expanded phase I study program including tumor biopsy studies.

	PATIENTS AND METHODS

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In Vitro Antiproliferative Assays
The effect of everolimus on cellular proliferation was defined using a methylene blue staining protocol. IC₅₀ was defined as the concentration required to inhibit cellular proliferation by 50% (72-hour treatment).

Animal Tumor Models
All experimental procedures were covered by permit numbers 1402 and 1672 issued by the Kantonales Veterinäramt Basel-Stadt and strictly adhered to the Eidgenössisches Tierschutzgesetz and the Eidgenössische Tierschutzverordnung. The CA20948 pancreatic tumor model has been previously reported.⁹ The dose- and time-dependent S6K1 inhibition and antitumor effects of everolimus reported by Boulay et al⁹ were used in developing the integrated PK/PD model.

Everolimus PK in Rats Bearing CA20948 Pancreatic Tumors
A microemulsion of 2% weight per volume (w/v) everolimus or vehicle was obtained from Novartis Pharmaceutical Development (Basel, Switzerland). Aliquots were stored at –20°C, and diluted with 5% w/v glucose in pyrogen-free water to administer a volume of 10 mL/kg orally. Tissues were obtained after administration of 5 mg/kg everolimus. Blood samples were withdrawn into syringes containing EDTA (approximately 0.5% w/v final), and tissues were excised, weighed, frozen in liquid nitrogen, and stored at –80°C. Everolimus concentrations were determined using a liquid chromatography/mass spectrometry method.¹⁷ PK parameters in animal tissues (half-life [t_1/2], area under the concentration-time curve [AUC], maximum concentrations [C_max], and time to reach Cmax [t_max]) were determined based on a noncompartmental model using WINNonlin (Scientific Consultant, Apex, NC) software (version 2.1; Pharsight Corp, Mountain View, CA).

Patients and Treatment/PBMC Sampling Schedules
A phase I clinical trial included a single-agent dose-escalation study of everolimus given weekly at four dose levels (5, 10, 20, 30 mg) with four patients per cohort.¹⁶ End points included blood PK and PD (PBMC-derived S6K1) measurements, safety, and Response Evaluation Criteria in Solid Tumors assessment of response. Blood was collected for PK and PD measurement during screening, immediately before everolimus treatment on weeks 1 to 4, and on days 1 through 11 after the fourth treatment. Everolimus treatment was restarted on day 14 after the fourth treatment. The study was conducted in accordance with International Conference on Harmonization good clinical practice standards, with approval by the ethics committees and health authorities of the participating institutions. All patients provided written informed consent to participate and were recruited between February and July 2002.

PK/PD Analysis
A whole-body physiologically based PK (PBPK) model was used to describe everolimus concentrations in the blood and tissues of rats.¹⁸ This model was then scaled up to humans as described by Kawai et al,¹⁹ namely by replacing the model parameters (eg, organ volume, blood flow rate, in vitro blood distribution parameters, plasma unbound fraction) for rats with those for humans. Tissue distribution parameters were assumed to be identical, per unit volume of organs. Intrinsic hepatic clearance was calculated assuming a well-stirred model.²⁰ Bioavailability and an absorption rate constant were estimated by model fitting to the PK data in cancer patients obtained from the phase I study. PK profiles from patients receiving various dosage regimens were simulated by the scaled PBPK model. A commonly used direct-link model²¹ was selected to explore first a relationship between everolimus concentrations and changes in S6K1 activity in both PBMCs and tumors derived from CA20948 pancreatic tumor-bearing rats treated with everolimus.⁹ This model is expressed by equation 1:

(1)

where I_max, IC₅₀, and Cu are maximum percent inhibition in S6K1 activity, unbound everolimus concentration that inhibits 50% of S6K1 activity, and unbound everolimus concentration derived from the PBPK model, respectively. Instead of total drug concentration, unbound everolimus concentration was considered to be pharmacologically relevant,²² which allowed correction for interspecies differences in tissue distribution caused by differences in plasma protein binding (92.4% bound in rats v 75% bound in humans/patients with cancer). Note that unbound concentration in tissues is identical to that in blood under steady-state conditions,²³ assuming that there is no significant contribution from active efflux or influx transporters. The direct-link model was also applied to describe changes in S6K1 activity in PBMCs and tumor of patients using the same model parameters (ie, I_max and IC₅₀).

Assumptions in Efficacy Assessment
The key assumption is that an effective dosage regimen should provide a degree and duration of S6K1 inhibition in PBMCs and tumor comparable with that achieved in rats bearing everolimus-sensitive tumors.⁹

Data Analysis and Computation
The parameters in the direct-link model, I_max and IC₅₀, were estimated by fitting the direct link model described above to the individual concentration S6K1 inhibition data from the rat studies. The model equations were described in advanced computer simulation language for simulations, and data fitting was performed using the program SimuSolv (The Dow Chemical Company, Midland, MI). A normally distributed error model was assumed in all the optimization procedures (ie, was set to 2; power term to the standard deviation of the error in the measurements).

	RESULTS

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Everolimus PK in CA20948 Tumor-Bearing Rats
It was shown previously that weekly administration of 5 mg/kg everolimus exhibits significant antitumor activity in the CA20948 pancreatic tumor model, similar to that obtained by daily administration.⁹ Blood and tumor PK of everolimus in this animal model were obtained after a single 5 mg/kg oral administration to tumor-bearing rats (Fig 1A), and PK parameters were determined (Fig 1B). The drug distribution to tumor was extensive with a tissue-to-blood concentration ratio of approximately 12:1. The half-life was comparable in blood (21 hours) and tumor (22 hours). The plasma free fraction of everolimus was based on the determined unbound fraction being 7.6%.¹⁸

View larger version (22K): [in this window] [in a new window] [PowerPoint Slide for Teaching]   Fig 1. Everolimus blood levels in tumor-bearing rats versus activity against tumor lines. (A) pharmacokinetic (PK) in tumor and blood, four animals per time point. Free plasma levels estimated based on 93.4% binding to rat plasma proteins, uncorrected for concentration dependency. (B) PK parameters. (C) Relationship between maximum concentrations (Cmax) in rat and in vitro concentration required to inhibit cellular proliferation by 50% (IC50) in tumor lines.

PK/PD Analysis of Everolimus Activity in Rats
Everolimus produced potent and prolonged inhibition of S6K1 activity in both PBMCs and tumor tissue in rats; being time- and dose-dependent in PBMCs. Weekly doses, which produced significant antitumor activity in the CA20948 pancreatic tumor, resulted in significant PBMC-derived S6K1 inhibition for the entire time period between administrations.⁹

Subsequent PK/PD analysis was performed using the rat data described in the previous paragraph in order to investigate whether the relationship between pharmacologically relevant everolimus concentrations (unbound concentrations) and the inhibition of S6K1 activity in both PBMCs and tumor conforms to a commonly used direct link PK/PD model. Then, the model parameters, such as I_max and IC₅₀, were estimated by curve fitting the data obtained from the rat studies. The concentration-effect relationships investigated are shown in Figures 2A and 2B. The model estimated I_max and IC₅₀ values were, respectively, 102% and 0.01 ng/mL in PBMCs and 97% and 0.05 ng/mL in tumor. Using the direct-link model with the estimated parameters for the rat, S6K1 inhibition-time profiles of PBMCs and tumor from different dosage regimens were simulated and depicted in Figures 2C and 2D. The simulations suggest a greater influence of everolimus regimen on tumor S6K1 activity relative to PBMC activity, with daily dosing giving a stronger and more sustained inhibition of tumor S6K1.

View larger version (26K): [in this window] [in a new window] [PowerPoint Slide for Teaching]   Fig 2. Modeling plots of everolimus inhibition of S6 kinase 1 (S6K1) activity in peripheral blood mononuclear cells (PBMCs) and tumor in CA20948 tumor-bearing rats. (A,B) Fit of measured data (yellow , : 0.5 mg/kg; blue , : 5 mg/kg) in (A) peripheral blood mononuclear cells (PBMC) and (B) tumor with the model estimate (line, equation 1). (C,D) Prediction of S6K1 activity in (C) PBMC and (D) tumor with daily and weekly everolimus dose regimens.

View larger version (33K): [in this window] [in a new window] [PowerPoint Slide for Teaching]   Fig 3. Modeling inhibition of S6 kinase 1 (S6K1) in patients. Fit of measured data in peripheral blood mononuclear cells (PBMCs) at 20 mg weekly (four patients; symbols) with the model (line). (A) Pharmacokinetic (PK) data and whole-body physiologically based PK model. (B) Measured and modeled S6K1 inhibition. (C,D) Predicted S6K1 activity in rat (0.5 and 5 mg/kg weekly regimens) overlaid onto predicted activity in patients (4 weekly regimens) for (C) PMBC and (D) tumor. (E,F) Predicted S6K1 activity in patients for daily versus weekly regimens.

	DISCUSSION

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Optimizing the drug regimen and obtaining an early indication of drug activity are key components of the efficient phase I evaluation of cancer therapeutics.²⁵ In our previous publication,⁹ the activity of the mTOR inhibitor everolimus was monitored via the downstream effector S6K1 in rats bearing experimental CA20948 tumors. Although suppression of S6K1 activity occurs in tumor cell lines considered "everolimus sensitive" or "indifferent"¹⁴ (Lane and Boulay, unpublished data), monitoring S6K1 activity affords a robust quantitative biomarker of the activity of everolimus. Indeed, the kinetics of PBMC-derived S6K1 inhibition correlated with antitumor activity in the everolimus-sensitive CA20948 model. The duration of S6K1 inactivation in PBMCs and tumor tissue was dose and time dependent and everolimus inactivated S6K1 in human PBMCs ex vivo.⁹

The observation that intermittent administration of everolimus to rats retained antitumor activity similar to that obtained with once-daily administration led to the design of a phase I clinical trial in patients with cancer that initially incorporated evaluation of a weekly regimen, followed by assessment of a daily regimen.¹⁶ PK/PD modeling of the effect of various everolimus regimens on S6K1 activity in tumor and PBMCs from rats yielded a model that accurately described the relationship between antitumor activity and S6K1 inhibition. Although everolimus has shown significant efficacy in a number of mouse models of human cancer,^7,26-28 a rat model, was chosen as the basis for the PK/PD model because the pharmacokinetics and drug metabolism of everolimus in rats are closer to those in man (unpublished data).

The direct-link PK/PD model, correcting only for the interspecies PK differences, reproduced S6K1 inhibition-time profiles measured in PBMCs of patients with cancer and, hence, has the potential to predict the effectiveness of everolimus in human tumors. Furthermore, it predicted which administration regimens would provide optimal target inhibition, indicating that increasing the frequency of administration from weekly to daily dosing would produce more sustained S6K1 inhibition.

This PK/PD model of S6K1 inhibition has, therefore, provided an indication of which doses and regimens should be investigated clinically, starting at 20 to 30 mg/wk and 5 mg/d, respectively. The model predicts that such doses might inhibit the molecular target sufficiently to exert anticancer effects. Consequently, by not exposing the patient to everolimus concentrations in excess of those required for adequate antitumor activity, one should be able to limit adverse effects. This modeling exercise has increased the interpretative value of early phase I clinical trial data of everolimus in patients with cancer.¹⁶ It has demonstrated the principle of integrating PK-PD modeling early in phase I development as a means of optimizing dose and schedule selection. In this example for future trials using a molecularly targeted agent, modeling was performed based on human and rat PK data, PD findings obtained using a surrogate human tissue (PBMCs), and preclinical PD data from a rodent tumor model. In the subsequent phase I expansion, daily and weekly regimens predicted to be pharmacodynamically active were explored directly in human tumor obtained from serial biopsies. Indeed, intratumoral mTOR pathway inhibition was demonstrated at doses predicted to be active through the modeling described here, with indications that daily administration was more effective than weekly.²⁹ A preliminary report of a phase II study in patients with recurrent/metastatic breast cancer also indicated more profound clinical benefit with daily everolimus dosing,³⁰ an observation supporting our conclusions and worthy of further evaluation.

	AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST

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Although all authors completed the disclosure declaration, the following author(s) indicated a financial or other interest that is relevant to the subject matter under consideration in this article. Certain relationships marked with a "U" are those for which no compensation was received; those relationships marked with a "C" were compensated. For a detailed description of the disclosure categories, or for more information about ASCO's conflict of interest policy, please refer to the Author Disclosure Declaration and the Disclosures of Potential Conflicts of Interest section in Information for Contributors.

Employment or Leadership Position: Chiaki Tanaka, Novartis Pharmaceuticals Corporation (C); Terence O’Reilly, Novartis Pharma AG (C); John M. Kovarik, Novartis Pharma AG (C); Nicholas Shand, Novartis Pharma AG (C); Katharine Hazell, Novartis Pharma AG (C); Sabine Zumstein-Mecker, Novartis Pharma AG (C); Christine Stephan, Novartis Pharma AG (C); Marc Hattenberger, Novartis Pharma AG (C); Heidi A. Lane, Novartis Pharma AG (C) Consultant or Advisory Role: Ian Judson, Novartis Pharma AG (C); Eric Raymond, Pfizer (C), AAI Pharma (C), GlaxoSmithKline (C); George Thomas, Novartis Pharma AG (C) Stock Ownership: Chiaki Tanaka, Novartis Pharmaceuticals Corporation; Terence O’Reilly, Novartis Pharma AG; John M. Kovarik, Novartis Pharma AG; Nicholas Shand, Novartis Pharma AG; Katharine Hazell, Novartis Pharma AG; Sabine Zumstein-Mecker, Novartis Pharma AG; Christine Stephan, Novartis Pharma AG; Marc Hattenberger, Novartis Pharma AG; Heidi A. Lane, Novartis Pharma AG Honoraria: Ian Judson, Novartis Pharma AG; Eric Raymond, Pfizer, Amgen; George Thomas, Novartis Pharma AG Research Funding: Ian Judson, Novartis Pharma AG; Eric Raymond, Pfizer, Amgen; Sabine Zumstein-Mecker, Novartis Pharma AG; Christine Stephan, Novartis Pharma AG; Marc Hattenberger, Novartis Pharma AG; Heidi A. Lane, Novartis Pharma AG Expert Testimony: None Other Remuneration: George Thomas, Novartis Pharma AG

	AUTHOR CONTRIBUTIONS

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Conception and design: Chiaki Tanaka, Terence O’Reilly, John M. Kovarik, Nicholas Shand, Katharine Hazell, Eric Raymond, George Thomas, Heidi A. Lane

Administrative support: Katharine Hazell

Provision of study materials or patients: Terence O’Reilly, Ian Judson, Eric Raymond

Collection and assembly of data: Chiaki Tanaka, Terence O’Reilly, John M. Kovarik, Katharine Hazell, Eric Raymond, Sabine Zumstein-Mecker, Christine Stephan, Anne Boulay, Marc Hattenberger, Heidi A. Lane

Data analysis and interpretation: Chiaki Tanaka, Terence O’Reilly, John M. Kovarik, Nicholas Shand, Eric Raymond, Sabine Zumstein-Mecker, Christine Stephan, Marc Hattenberger, Heidi A. Lane

Manuscript writing: Chiaki Tanaka, Terence O’Reilly, Nicholas Shand, Ian Judson, Eric Raymond, George Thomas, Heidi A. Lane

Final approval of manuscript: Chiaki Tanaka, Terence O’Reilly, John M. Kovarik, Katharine Hazell, Ian Judson, Eric Raymond, Sabine Zumstein-Mecker, Christine Stephan, Marc Hattenberger, George Thomas, Heidi A. Lane

	ACKNOWLEDGMENTS

 
We thank Monika Hegi, PhD (Department of Neurosurgery, University Hospital Lausanne, Switzerland, and Adrian Merlo, MD, (Laboratory of Molecular Neuro-Oncology, University Hospital Basel, Switzerland, for providing the glioblastoma cell lines, and Richard McCabe, PhD, for editorial assistance.

	NOTES

 
published online ahead of print at www.jco.org on March 10, 2008.

Supported by the National Institutes of Health Mouse Models for Human Cancer Consortium, Grants No. UO1 CA84292-06 and DK73802, and by the Strauss Chair in Cancer Research, University of Cincinnati Medical School (G.T.).

C.T. and T.O. contributed equally to this work.

Presented in part in abstract format at the 39th Annual Meeting of the American Society of Clinical Oncology, Chicago, IL, May 31 to June 3, 2003.

Authors’ disclosures of potential conflicts of interest and author contributions are found at the end of this article.

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Submitted September 9, 2007; accepted December 3, 2007.

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