
==== Front
Target Oncol
Target Oncol
Targeted Oncology
1776-2596
1776-260X
Springer International Publishing Cham

39085452
1087
10.1007/s11523-024-01087-4
Original Research Article
An Evidence-Based Rationale for Dose De-escalation of Subcutaneous Atezolizumab
http://orcid.org/0000-0002-5321-0816
Kicken Mart P. mart.kicken@radboudumc.nl

12
Deenen Maarten J. 23
Moes Dirk J. A. R. 3
Hendrikx Jeroen J. M. A. 4
van den Borne Ben E. E. M. 5
Dumoulin Daphne W. 6
van der Wekken Anthonie J. 7
van den Heuvel Michiel M. 8
ter Heine Rob 1
1 https://ror.org/05wg1m734 grid.10417.33 0000 0004 0444 9382 Department of Pharmacy, Radboud University Medical Center, Radboud Institute for Health Sciences, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
2 https://ror.org/01qavk531 grid.413532.2 0000 0004 0398 8384 Department of Clinical Pharmacy, Catharina Hospital Eindhoven, Eindhoven, The Netherlands
3 grid.10419.3d 0000000089452978 Department of Clinical Pharmacy and Toxicology, Leiden University Medical Centre, Leiden, The Netherlands
4 https://ror.org/03xqtf034 grid.430814.a 0000 0001 0674 1393 Department of Pharmacy and Pharmacology, The Netherlands Cancer Institute (NKI-AVL), Amsterdam, The Netherlands
5 https://ror.org/01qavk531 grid.413532.2 0000 0004 0398 8384 Department of Pulmonology, Catharina Hospital Eindhoven, Eindhoven, The Netherlands
6 https://ror.org/018906e22 grid.5645.2 0000 0004 0459 992X Department of Pulmonary Medicine, Erasmus Medical Center Cancer Institute, University Medical Center, Rotterdam, The Netherlands
7 https://ror.org/03cv38k47 grid.4494.d 0000 0000 9558 4598 Department of Pulmonology, University of Gronigen, University Medical Centre Groningen, Groningen, The Netherlands
8 https://ror.org/05wg1m734 grid.10417.33 0000 0004 0444 9382 Department of Pulmonology, Radboud University Medical Center, Nijmegen, The Netherlands
31 7 2024
31 7 2024
2024
19 5 779787
16 7 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/.
Background

Atezolizumab is a programmed death-ligand 1 (PD-L1) checkpoint inhibitor for the treatment of different forms of cancer. The subcutaneous formulation of atezolizumab has recently received approval. However, treatment with atezolizumab continues to be expensive, and the number of patients needing treatment with this drug continues to increase.

Objective

We propose two alternative dosing regimens for subcutaneous atezolizumab to reduce drug expenses while ensuring effective exposure; one may be directly implemented in the clinic.

Patients and Methods

We developed two alternative dose interval prolongation strategies based on pharmacokinetic modeling and simulation. The first dosing regimen was based on patients’ weight while maintaining equivalent systemic drug exposure by adhering to Food and Drug Administration (FDA) guidelines for in silico dose adjustments. The second dosing regimen aimed to have a minimum atezolizumab concentration above the 6 µg/mL threshold, associated with 95% intratumoral PD-L1 receptor saturation for at least 95% of all patients.

Results

We found that, for the weight-based dosing regimen, the approved 3-week dosing interval could be extended to 5 weeks for patients < 50 kg and 4 weeks for patients weighing 50–65 kg. Besides improving patient convenience, these alternative dosing intervals led to a predicted 7% and 12% cost reduction for either the USA or European population. For the second dosing regimen, we predicted that a 6-week dosing interval would result in 95% of the patients above the 6 µg/mL threshold while reducing costs by 50%.

Conclusions

We have developed and evaluated two alternative dosing regimens that resulted in a cost reduction. Our weight-based dosing regimen can be directly implemented and complies with FDA guidelines for alternative dosing regimens of PD-L1 inhibitors. For the more progressive alternative dosing regimen aimed at the intratumoral PD-L1 receptor threshold, further evidence on efficacy and safety is needed before implementation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11523-024-01087-4.

issue-copyright-statement© Springer Nature Switzerland AG 2024
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pmcKey Points

Weight-based dosing interval prolongation of subcutaneous atezolizumab can reduce costs and improve patient convenience without compromising effective exposure.	
A theoretical even higher cost reduction and improvement of patient convenience are possible by dosing above the minimum effective concentration.	

Introduction

Atezolizumab (Tecentriq®) is a programmed death-ligand 1 (PD-L1) checkpoint inhibitor approved as a treatment for different forms of cancer, including advanced non-small cell lung cancer (NSCLC), small cell lung cancer (SCLC), and urothelial carcinoma [1, 2]. It is given as an intravenous (IV) formulation and is usually administered in a hospital setting during a 30–60 min infusion as either 840 mg administered once every 2 weeks, 1200 mg administered once every 3 weeks, or 1680 mg once every 4 weeks [2].

Recently, the subcutaneous (SC) formulation of atezolizumab received approval from the European Medicine Agency and it is currently under assessment by the Food and Drug Administration (FDA) [3, 4]. The approved subcutaneous dose is 1875 mg once every 3 weeks, based on a population pharmacokinetic (POPPK) study and a clinical study that verified the efficacy of this novel formulation in advanced NSCLC [1, 5]. The subcutaneous administration of atezolizumab potentially has several benefits for the patient (e.g., improved quality of life and at-home administration/less traveling) as well as for the healthcare provider (e.g., lower acquisition costs and lower drug administration burden) [6, 7]. The SC formulation is, therefore, expected to become the preferred treatment of cancer in the near future, as did SC monoclonal antibodies in other disease areas (i.e., diabetes, rheumatoid arthritis, multiple sclerosis, and primary immunodeficiency) [6].

However, treatment with atezolizumab is still expensive [8]. Moreover, the number of patients with cancer and accompanying treatments is increasing due to advances in effective screening and early detection, and to the rise of aging [9, 10]. For example, the USA is projected to see a 34% increase in cancer-attributable costs from 2015 to 2030 for a total of $246 billion [11]. Hence, the increasing economic burden of cancer treatment is putting a severe strain on personal and national health budgets. Moreover, with the ever-growing list of indications and the hefty price tag of atezolizumab, there is an urgent need to save costs wherever possible [12, 13].

A potential way of reducing costs for SC atezolizumab treatment is by optimizing the dose using modeling and simulation of different pharmacokinetic (PK) populations. The use of POPPK modeling to develop alternative dosing regimens for monoclonal antibodies has already been widely accepted by the medical community, drug corporations, and regulatory agencies [14–17].

The aim of the present study was, therefore, to develop an optimized dosing regimen of subcutaneous atezolizumab based on modeling and simulation, resulting in reduced drug expenses without compromising effective systemic drug exposure.

Methods

General Approach

We performed an in silico evaluation of alternative dosing regimens for two scenarios. For Scenario I, we aimed to develop a cost-saving dosing regimen for atezolizumab based on the recently published FDA guidance of “Pharmacokinetic-Based Criteria for Supporting Alternative Dosing Regimens of Programmed Cell Death Receptor-1 (PD-1) or Programmed Cell Death-Ligand 1 (PD-L1) Blocking Antibodies for Treatment of Patients with Cancer” for developing alternative dosing regimens of PD-1 or PD-L1 blocking antibodies [14]. For this scenario, we evaluated dosing interval prolongation based on weight while complying with the criteria as set out in the FDA guidance: the geometric mean (GM) of the average concentration (Caverage) and the trough concentration (Ctrough) at steady state should not be more than 20% lower than the approved dose, and the GM of the steady-state maximum concentration (Cmax) should not be more than 25% higher than the approved dose. The endpoints for Scenario I were the GMs of Ctrough, Cmax, and Caverage of the approved and alternative dosing regimens and the arithmetic mean of dose reduction per year per patient. The Caverage is defined as the area under the concentration–time curve during a dosing interval divided by the duration of the dosing interval. This pharmacokinetic endpoint can, therefore, be considered a time-corrected measure for area under the curve (AUC) and allows comparison of cumulative exposure for different dosing intervals.

For Scenario II, we evaluated the potential of dose interval prolongation irrespective of body weight to achieve theoretically effective exposure throughout the treatment period. The license holder previously defined the putative threshold for efficacy as a trough concentration (Ctrough) above 6 μg/mL, associated with 95% intratumoral PD-L1 receptor saturation [18, 19]. Since the Ctrough in the approved IV and SC dose at steady state is approximately 20-fold higher than this predefined threshold of 6 μg/mL [20], we explored extended dosing intervals where at least 95% of patients had an exposure above this threshold. The endpoints for Scenario II were the fraction of patients with a Ctrough above 6 μg/mL just before the second administration and at the pharmacokinetic steady state of the alternative dosing regimen and the arithmetic mean of dose reduction per year per patient.

Pharmacokinetic Modeling and Simulation

For the simulations, we used the population pharmacokinetic model that was previously developed by the license holder as described in the FDA review documents and by Felip et al. [5, 19]. All simulations were performed using the nonlinear mixed-effects modeling software package NONMEM V7.5 (Icon, Dublin, Ireland). The NONMEM model code is included in the Supplementary Material of the manuscript. The covariates for clearance (CL) in this model were serum albumin concentration, anti-therapeutic antibodies (ATAG), tumor burden, and body weight. Covariates for the volume of distribution in the central compartment were albumin concentration, body weight, and gender. Gender was also a covariate for the peripheral compartment. Lastly, this model contained a high interindividual variability in bioavailability after SC administration.

For our simulation, a European and a USA population of 1000 virtual individuals were generated using PopGen [21]. The European population was based on the ICRP database, and the USA population was based on the NHANES III survey. The European population comprised 46% men with a median weight of 67.3 kg [interquartile range (IQR) 57.0–77.6 kg]. In the USA population were 47% men with a median weight of 75.4 kg (IQR 63.5–87.7 kg), and probability of ethnicity of 0.673 for being white, 0.136 for being Black, and 0.191 for being non-Black Hispanic [22]. The two different populations were used to account for differences in body size composition between these populations [23]. In these populations, we assumed the following covariate distributions:A serum albumin concentration of 40 g/L with a geometric coefficient of variation of 5%, resulting in a representative distribution of serum albumin concentrations in lung cancer patients, based on the atezolizumab clinical studies [19].

ATAG prevalence of 40% [24].

The tumor burden was set to 63 mm with a variability of 30%, as observed in the clinical studies of atezolizumab [19].

The reference dosing regimen for our simulations was the approved 1875 mg SC once every 3 weeks (Q3W). Various alternative dosing regimens were tested at the discretion of the investigators.

For Scenario I, we varied the dosing interval by weeks on the basis of the knowledge that systemic exposure depends on body weight while maintaining predicted exposure for the population within the predefined equivalence criteria. For Scenario II, we varied the dosing interval by half a month (multiplicity of 2 weeks) to be more practical while maintaining at least 95% of all individuals above the 6 µg/mL threshold.

Results

Scenario I—Weight-Based Dosing while Adhering to the FDA Criteria

We found that the following alternative dosing regimen for 1875 mg SC atezolizumab resulted in equivalent exposure and maximum dose reduction: Q5W (35 days) for patients with body weight under 50 kg, Q4W (28 days) for patients 50–65 kg, and Q3W (21 days) for patients with body weight higher than 65 kg. The results of different PK parameters of the approved dosing regimen relative to the alternative dosing regimen all complied with the FDA criteria. This results in nearly completely overlapping density plots of PK parameters between the approved dosing regime and alternative dose interval. The average exposure (Caverage) in the USA population was lower, as seen in Fig. 1, than in the European population. The same relationship was observed for Ctrough and Cmax (Supplementary Figs. 1 and 2).Fig. 1 Caverage density plot of alternative dose interval versus approved dose in European and USA population

Additionally, the alternative dosing regimen resulted in a lower average exposure (Caverage) and variability (i.e., confidence interval) in patients with body weights below 65 kg compared with the approved dose in both European (Fig. 2) and USA populations (Fig. 3). As expected, the Caverage did not change in patients with body weights above 65 kg.Fig. 2 Caverage of alternative versus approved dose interval in a European population

Fig. 3 Caverage of alternative versus approved dose interval in a USA population

The GM of the Ctrough of the European population was the constraining PK parameter at 81%, whereas there was still an opportunity for decreasing the Cmax and Caverage PK parameters. Implementing our alternative dosing regimen could lead to a cost reduction of 12.0% for the European population and 7.2% for the USA population (Table 1). Table 1 Results of alternative dosing regimen in European and USA population

	Pharmacokinetic parameters	Cost reduction	
GM Ctrough (µg/mL) (CV%)	GM Cmax (µg/mL) (CV%)	GM Caverage (µg/mL) (CV%)	Average quantity of drug (mg)* [number of vials (n)**]	
EU	USA	EU	USA	EU	USA	EU	USA	
Approved

1875 mg Q3W

	285.6 (230.4%)	253.9 (229.2%)	477.7 (214.7%)	437.0 (212.2%)	369.6 (218.9%)	335.2 (216.6%)	33,750 (18)	33,750 (18)	
Alternative dosing regimen

< 50 kg 1875 mg Q5W

50–65 kg 1875 mg Q4W

> 65 1875 mg Q3W

	230.3 (223.2%)	224.2 (223.5%)	430.2 (208.5%)	411.0 (208.5%)	318.5 (211.8%)	307.3 (212.1%)	29,715 (16)	31,322 (17)	
Ratio alternative to reference	0.81	0.88	0.90	0.94	0.86	0.91	0.88 (2)	0.93 (2)	
GM geometric mean, CV% coefficient of variation, n numero, EU European population, USA United States of America

*Arithmetic mean of quantity of drug used during 1 year per patient

**Rounded up

Scenario II—Dosing at Therapeutic Threshold

Scenario II is based on dosing at least 95% of the population above the putative efficacy threshold of 6 μg/mL, irrespective of the patients’ weight. For both the European and the USA population, the maximum dosing interval was approximately 44 days for which at least 95% of patients were above the threshold of 6 μg/mL. For pragmatic reasons, a 6-week dosing interval (Q6W) was used for further simulations for both the European and the USA population to ensure adequate exposure throughout the treatment period.

Due to rounding down, the number of patients with a minimum concentration (Ctrough) above the threshold exceeded 95% at both the first cycle and steady state. At steady state, 98% of patients in the European population and 97% in the USA population had a Ctrough above 6 μg/mL (Table 2). Using the Q6W dosing regimen, the dosing interval is doubled compared with the regular 3-week dosing of atezolizumab, resulting in a cost reduction of 50.0% for both the European and the USA population. Table 2 Ctrough of dosing at therapeutic threshold

	Pharmacokinetic parameters	
GM Ctrough (first cycle) (µg/mL) (CV%)	GM Ctrough (steady state) (µg/mL) (CV%)	
EU	USA	EU	USA	
1875 mg Q6W	68.2 (227.7%)	61.0 (228.1%)	102.3 (254.2%)	88.6 (253.7%)	
Fraction of patients above 6 μg/mL (%)	96.1%	95.5%	97.4%	97.2%	
GM geometric mean, CV% coefficient of variation, n numero, EU European population, USA United States of America

The doubling of the dosing interval is reflected in the approximating halving of the Ctrough in both the first cycle and at steady state. Figure 4 shows that almost all European patients in both dosing intervals have a Ctrough above the threshold of 6 μg/mL (red dotted line is equal to 6 μg/mL). The same was seen in the USA population (Fig. 5).Fig. 4 Ctrough of Q6W dose interval versus approved dose interval in a European population in the first cycle and at steady state

Fig. 5 Ctrough of Q6W dose interval versus approved dose interval in a USA population in the first cycle and at steady state

Discussion

In this study, we aimed to develop two alternative dosing regimens for 1875 mg SC atezolizumab to minimize drug expenses while maintaining effective systemic drug exposure.

For the first alternative dosing regimen (Scenario I), we propose dosing interval prolongation for patients with a body weight below 50 kg to a 5-week interval (Q5W) and to a 4-week interval (Q4W) for patients weighting 50–65 kg, while maintaining a 3-week interval (Q3W) for patients with a body weight above 65 kg. This weight-based alternative dosing regimen will reduce drug expenses by 12% in the European and 7% in the USA population while preserving equivalent exposure compared with the approved dose in line with the FDA guidance for developing alternative dosing regimens for PD-L1 blocking antibodies in the treatment of patients with cancer, facilitating direct implementation in clinical practice without the need for a clinical study [14]. Interestingly, a recent study showed that low-dose nivolumab for a specific indication is as effective as approved (high) dose nivolumab [25]. This result encourages further investigation whether this is also the case for atezolizumab, bearing in mind that dose–response relationships for immune checkpoint inhibitors may differ by indication as shown by Agrawal et al. [26].

For the second alternative dosing regimen (Scenario II), we propose a 6-week interval (Q6W) for both the European and the USA population, resulting in at least 95% of patients with an exposure above the 6 μg/mL target threshold for intratumoral PD-L1 receptor saturation at both the first cycle and steady state, irrespective of the patients’ weight. Consequently, a reduction of 50% in drug expenses was achieved. This is in line with PK data for IV administration of atezolizumab in humans, where anti-tumor activity (i.e., 95% of patients have a minimum concentration above 6 μg/mL) was found across a dosing range of 1–20 mg/kg (Q3W) [27], which evolved to 15 mg/kg (the equivalent fixed dose of 1200 mg) Q3W [28]. In addition, a recent analysis by Chou et al. of intravenously administered atezolizumab predicted that, when decreasing the cumulative atezolizumab by twofold, no changes in the efficacy profile can be expected [29]. These results encourage investigating further tapering strategies to reduce the financial toxicity and improve the patient friendliness of subcutaneously administered atezolizumab.

The efficacy target concentration of atezolizumab of 6 μg/mL is based on the assumptions that 95% tumor receptor saturation is needed for efficacy, that the tumor-interstitial concentration to plasma ratio is 0.3 based on the tissue distribution data in tumor-bearing mice [30], and that the combination with bevacizumab will reduce tumor penetration by at least ~ 30% [18]. Although our analysis predicts sufficient target attainment in a Q6W dosing interval, such a dosing regimen should be evaluated for noninferiority in a clinical study before implementation.

Notably, because of the high variability in subcutaneous bioavailability, lower cumulative doses are likely possible using IV administration. This is due to the absence of variability in bioavailability for the fraction of the dose reaching the systemic circulation, resulting in less variability in Ctrough concentrations. Lower variability in Ctrough concentrations means one can further prolong the dosing interval before the threshold is reached. This high variability in the bioavailability of subcutaneously administered monoclonal antibodies may stem from differences in subcutaneous tissue composition and local degradation, affecting the physiochemical properties of the subcutaneous absorption [31]. Regarding IV administration, Peer et al. proposed an 840 mg Q6W IV dose to maintain 99% of the population above the proposed therapeutic threshold based on in silico simulation [32]. A recent real-world pharmacokinetic study by Marolleau et al. showed relatively long dosing intervals of intravenously administered atezolizumab might be possible based on therapeutic drug monitoring, with an extension of a 1200 mg IV dose to a mean interval of approximately 3 months, indicating that real-world pharmacokinetics may raise opportunities for further dose interval prolongation [33] . Hence the intravenous dosing regimen could also be an option to optimize patient friendliness and cost efficacy of atezolizumab. However, this option was beyond the scope of our study, which focused on improving the cost efficacy of the novel SC formulation of atezolizumab.

Besides lower drug expenses, our alternative dosing regimens also pose other benefits. These include lowering direct medical costs (e.g., decrease of the number of drug administrations and use of resources and healthcare staff costs) and indirect medical costs (e.g., less traveling costs). In addition, it may improve patient convenience and quality of life by decreasing the number of hospital visits and used resources, accommodating both patients and healthcare professionals [6, 7].

Our simulations were based on a representative European and USA population, and differences in predicted drug expenses were observed. These differences can be explained by the USA population’s higher average weight. Since lower exposure is expected in higher body weight patients, the USA population shows lower Ctrough, Cmax, and Caverage than the European population. An additional simulation conducted in the USA population found a cost reduction of 11.7% while complying with FDA criteria if patients were dosed Q5W for body weight under 50 kg, Q4W between 50 and 75 kg, and Q3W for body weight higher than 75 kg (Supplementary Table 1).

Conclusion

Our study shows a maximum 12% cost reduction for body weight-based dosing interval prolongation (Scenario I), which can be implemented directly into practice since it adheres to the FDA guideline for the development of alternative dosing regimens for PD-L1 antibodies. By implementing this alternative strategy, healthcare costs can be reduced without impacting drug efficacy and safety. For a more progressive approach, dosing aimed at maintaining receptor saturation by targeting an efficacy threshold concentration (Scenario II), further evidence on efficacy and safety is needed for implementation. We propose a prospective evaluation of this latter approach using a noninferiority study.

Supplementary Information

Below is the link to the electronic supplementary material.Supplementary file1 (PDF 221 KB)

Author's contributions

All authors contributed to the study conception and design. Data preparation and data simulation were performed by M.P. Kicken. Data analysis was performed by M.P. Kicken and R. ter Heine. The first draft of the manuscript was written by M.P. Kicken, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Declarations

Funding

No external funding was used in the preparation of this manuscript.

Conflicts of interest

Financial interests: Dr. R. ter Heine receives research funding from AMGEN. All payments are outside of the submitted work. Dr. A. J. van der Wekken reports research grants from Astra-Zeneca, Boehringer-Ingelheim, Roche, Pifeze, and Takeda; consulting fees from Amgen, Astra-Zeneca, Boehringer-Ingelheidm, Janssen, Lilly, Merck, Novartis, Roche, Pfizer, and Takeda; and honoraria for lectures from Astra-Zeneca and Roche. All payments are outside of the submitted work. Nonfinancial interests: Dr. A.J. van der Wekken is a member of Leadership in FMS and NVALT ‘dure geneesmiddelen’, NFU quickscan group, Guideline committee member NSCLC and CUP, KNT committee and ROS1ders advisory board. All intuitions are outside of the submitted work. Authors MSc. M.P. Kicken, Dr. M.J. Deenen, Dr. D.J.A.R. Moes, Dr. J.J.M.A. Hendrikx, Dr. B.E.E.M. van den Borne, Dr. D.W. Dumoulin, and Dr. M. M. van den Heuvel declare that they have no conflicts of interest that might be relevant to the contents of this manuscript.

Ethics approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Data and code availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. The model code used for simulation of different dose regimens is found in the Supplementary Material.

Inclusion of data availability

We used simulated data as mentioned in the methods. We provided references and settings/distribution of our simulated population in the methods section using PopGen [21].
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References

1. Burotto M Zvirbule Z Mochalova A Runglodvatana Y Herraez-Baranda L Liu SN IMscin001 Part 2: a randomised phase III, open-label, multicentre study examining the pharmacokinetics, efficacy, immunogenicity, and safety of atezolizumab subcutaneous versus intravenous administration in previously treated locally advanced or metastatic non-small-cell lung cancer and pharmacokinetics comparison with other approved indications Ann Oncol 2023 34 8 693 702 10.1016/j.annonc.2023.05.009 37268157
Burotto M, Zvirbule Z, Mochalova A, Runglodvatana Y, Herraez-Baranda L, Liu SN, et al. IMscin001 Part 2: a randomised phase III, open-label, multicentre study examining the pharmacokinetics, efficacy, immunogenicity, and safety of atezolizumab subcutaneous versus intravenous administration in previously treated locally advanced or metastatic non-small-cell lung cancer and pharmacokinetics comparison with other approved indications. Ann Oncol. 2023;34(8):693–702.37268157 10.1016/j.annonc.2023.05.009
2. Tecentriq. SUMMARY OF PRODUCT CHARACTERISTIC - Tecentriq. 2023.
3. Pharma F. Roche hits FDA delay with subcutaneous version of Tecentriq amid manufacturing process changes 2023 [Available from: https://www.fiercepharma.com/pharma/roches-subcutaneous-tecentriq-hits-fda-delay-amid-manufacturing-process-changes].
4. Roche. Roche’s subcutaneous injection of Tecentriq recommended by the EU’s CHMP for multiple cancer types 2023 [Available from: https://www.roche.com/media/releases/med-cor-2023-11-14].
5. Felip E Burotto M Zvirbule Z Herraez-Baranda LA Chanu P Kshirsagar S Results of a dose-finding phase 1b study of subcutaneous atezolizumab in patients with locally advanced or metastatic non-small cell lung cancer Clin Pharmacol Drug Dev. 2021 10 10 1142 1155 10.1002/cpdd.936 33788415
Felip E, Burotto M, Zvirbule Z, Herraez-Baranda LA, Chanu P, Kshirsagar S, et al. Results of a dose-finding phase 1b study of subcutaneous atezolizumab in patients with locally advanced or metastatic non-small cell lung cancer. Clin Pharmacol Drug Dev. 2021;10(10):1142–55.33788415 10.1002/cpdd.936
6. Bittner B Richter W Schmidt J Subcutaneous administration of biotherapeutics: an overview of current challenges and opportunities BioDrugs 2018 32 5 425 440 10.1007/s40259-018-0295-0 30043229
Bittner B, Richter W, Schmidt J. Subcutaneous administration of biotherapeutics: an overview of current challenges and opportunities. BioDrugs. 2018;32(5):425–40.30043229 10.1007/s40259-018-0295-0
7. Turner MR Balu-Iyer SV Challenges and opportunities for the subcutaneous delivery of therapeutic proteins J Pharm Sci 2018 107 5 1247 1260 10.1016/j.xphs.2018.01.007 29336981
Turner MR, Balu-Iyer SV. Challenges and opportunities for the subcutaneous delivery of therapeutic proteins. J Pharm Sci. 2018;107(5):1247–60.29336981 10.1016/j.xphs.2018.01.007
8. Das M Ogale S Jovanoski N Johnson A Nguyen C Bhagwakar J Lee JS Cost-effectiveness of adjuvant atezolizumab for patients with stage II-IIIA PD-L1+ non-small-cell lung cancer Immunotherapy 2023 15 8 573 581 10.2217/imt-2022-0311 37021770
Das M, Ogale S, Jovanoski N, Johnson A, Nguyen C, Bhagwakar J, Lee JS. Cost-effectiveness of adjuvant atezolizumab for patients with stage II-IIIA PD-L1+ non-small-cell lung cancer. Immunotherapy. 2023;15(8):573–81.37021770 10.2217/imt-2022-0311
9. Bluethmann SM Mariotto AB Rowland JH Anticipating the "Silver Tsunami": prevalence trajectories and comorbidity burden among older cancer survivors in the United States Cancer Epidemiol Biomarkers Prev 2016 25 7 1029 1036 10.1158/1055-9965.EPI-16-0133 27371756
Bluethmann SM, Mariotto AB, Rowland JH. Anticipating the “Silver Tsunami”: prevalence trajectories and comorbidity burden among older cancer survivors in the United States. Cancer Epidemiol Biomarkers Prev. 2016;25(7):1029–36.27371756 10.1158/1055-9965.EPI-16-0133
10. Leighl NB Nirmalakumar S Ezeife DA Gyawali B An arm and a leg: the rising cost of cancer drugs and impact on access Am Soc Clin Oncol Educ Book 2021 41 1 12 10.1200/EDBK_100028 33956494
Leighl NB, Nirmalakumar S, Ezeife DA, Gyawali B. An arm and a leg: the rising cost of cancer drugs and impact on access. Am Soc Clin Oncol Educ Book. 2021;41:1–12.33956494 10.1200/EDBK_100028
11. Mariotto AB Enewold L Zhao J Zeruto CA Yabroff KR Medical care costs associated with cancer survivorship in the United States Cancer Epidemiol Biomarkers Prev 2020 29 7 1304 1312 10.1158/1055-9965.EPI-19-1534 32522832
Mariotto AB, Enewold L, Zhao J, Zeruto CA, Yabroff KR. Medical care costs associated with cancer survivorship in the United States. Cancer Epidemiol Biomarkers Prev. 2020;29(7):1304–12.32522832 10.1158/1055-9965.EPI-19-1534
12. Desai A Gyawali B Financial toxicity of cancer treatment: Moving the discussion from acknowledgement of the problem to identifying solutions EClinicalMedicine. 2020 20 100269 10.1016/j.eclinm.2020.100269 32300733
Desai A, Gyawali B. Financial toxicity of cancer treatment: Moving the discussion from acknowledgement of the problem to identifying solutions. EClinicalMedicine. 2020;20: 100269.32300733 10.1016/j.eclinm.2020.100269
13. Pisu M Martin MY Financial toxicity: a common problem affecting patient care and health Nat Rev Dis Primers 2022 8 1 7 10.1038/s41572-022-00341-1 35145106
Pisu M, Martin MY. Financial toxicity: a common problem affecting patient care and health. Nat Rev Dis Primers. 2022;8(1):7.35145106 10.1038/s41572-022-00341-1
14. FDA. Pharmacokinetic-Based criteria for supporting alternative dosing regimens of programmed cell death receptor-1 (PD-1) or programmed cell death-ligand 1 (PD-L1) blocking antibodies for treatment of patients with cancer guidance for industry. 2022. [Available from https://www.fda.gov/regulatory-information/search-fda-guidance-documents/pharmacokinetic-based-criteria-supporting-alternative-dosing-regimens-programmed-cell-death-receptor].
15. Hendrikx J Haanen J Voest EE Schellens JHM Huitema ADR Beijnen JH Fixed dosing of monoclonal antibodies in oncology Oncologist 2017 22 10 1212 1221 10.1634/theoncologist.2017-0167 28754722
Hendrikx J, Haanen J, Voest EE, Schellens JHM, Huitema ADR, Beijnen JH. Fixed dosing of monoclonal antibodies in oncology. Oncologist. 2017;22(10):1212–21.28754722 10.1634/theoncologist.2017-0167
16. Zhao X Suryawanshi S Hruska M Feng Y Wang X Shen J Assessment of nivolumab benefit-risk profile of a 240-mg flat dose relative to a 3-mg/kg dosing regimen in patients with advanced tumors Ann Oncol 2017 28 8 2002 2008 10.1093/annonc/mdx235 28520840
Zhao X, Suryawanshi S, Hruska M, Feng Y, Wang X, Shen J, et al. Assessment of nivolumab benefit-risk profile of a 240-mg flat dose relative to a 3-mg/kg dosing regimen in patients with advanced tumors. Ann Oncol. 2017;28(8):2002–8.28520840 10.1093/annonc/mdx235
17. Freshwater T Kondic A Ahamadi M Li CH de Greef R de Alwis D Stone JA Evaluation of dosing strategy for pembrolizumab for oncology indications J Immunother Cancer 2017 5 43 10.1186/s40425-017-0242-5 28515943
Freshwater T, Kondic A, Ahamadi M, Li CH, de Greef R, de Alwis D, Stone JA. Evaluation of dosing strategy for pembrolizumab for oncology indications. J Immunother Cancer. 2017;5:43.28515943 10.1186/s40425-017-0242-5
18. Deng R Bumbaca D Pastuskovas CV Boswell CA West D Cowan KJ Preclinical pharmacokinetics, pharmacodynamics, tissue distribution, and tumor penetration of anti-PD-L1 monoclonal antibody, an immune checkpoint inhibitor MAbs 2016 8 3 593 603 10.1080/19420862.2015.1136043 26918260
Deng R, Bumbaca D, Pastuskovas CV, Boswell CA, West D, Cowan KJ, et al. Preclinical pharmacokinetics, pharmacodynamics, tissue distribution, and tumor penetration of anti-PD-L1 monoclonal antibody, an immune checkpoint inhibitor. MAbs. 2016;8(3):593–603.26918260 10.1080/19420862.2015.1136043
19. FDA. Center for drug evaluation and research. Application number: 761034orig1s000. Clinical pharmacology and biopharmaceutics review(s). 2016. [Available from https://www.accessdata.fda.gov/drugsatfda_docs/nda/2016/761034orig1s000clinpharmr.pdf].
20. Peer CJ Zimmerman SM Figg WD Goldstein DA Ratain MJ Subcutaneous atezolizumab: a jab without a benefit Clin Pharmacol Drug Dev. 2022 11 1 134 135 10.1002/cpdd.1061 34951144
Peer CJ, Zimmerman SM, Figg WD, Goldstein DA, Ratain MJ. Subcutaneous atezolizumab: a jab without a benefit. Clin Pharmacol Drug Dev. 2022;11(1):134–5.34951144 10.1002/cpdd.1061
21. Willmann S Höhn K Edginton A Sevestre M Solodenko J Weiss W Development of a physiology-based whole-body population model for assessing the influence of individual variability on the pharmacokinetics of drugs J Pharmacokinet Pharmacodyn 2007 34 3 401 431 10.1007/s10928-007-9053-5 17431751
Willmann S, Höhn K, Edginton A, Sevestre M, Solodenko J, Weiss W, et al. Development of a physiology-based whole-body population model for assessing the influence of individual variability on the pharmacokinetics of drugs. J Pharmacokinet Pharmacodyn. 2007;34(3):401–31.17431751 10.1007/s10928-007-9053-5
22. Bureau USC. QuickFacts - Population estimates 2023 [Available from:https://www.census.gov/quickfacts/fact/tableUS/PST045223.
23. Seidell JC Epidemiology of obesity Semin Vasc Med. 2005 5 1 3 14 10.1055/s-2005-871737 15968575
Seidell JC. Epidemiology of obesity. Semin Vasc Med. 2005;5(1):3–14.15968575 10.1055/s-2005-871737
24. Wu B Sternheim N Agarwal P Suchomel J Vadhavkar S Bruno R Evaluation of atezolizumab immunogenicity: clinical pharmacology (part 1) Clin Transl Sci 2022 15 1 130 140 10.1111/cts.13127 34432389
Wu B, Sternheim N, Agarwal P, Suchomel J, Vadhavkar S, Bruno R, et al. Evaluation of atezolizumab immunogenicity: clinical pharmacology (part 1). Clin Transl Sci. 2022;15(1):130–40.34432389 10.1111/cts.13127
25. Patel A Hande V Mr K Dange H Das AK Murugesan V Effectiveness of immune checkpoint inhibitors in various tumor types treated by low, per-weight, and conventional doses at a tertiary care center in Mumbai JCO Glob Oncol. 2024 10 e2300312 10.1200/GO.23.00312 38181308
Patel A, Hande V, Mr K, Dange H, Das AK, Murugesan V, et al. Effectiveness of immune checkpoint inhibitors in various tumor types treated by low, per-weight, and conventional doses at a tertiary care center in Mumbai. JCO Glob Oncol. 2024;10: e2300312.38181308 10.1200/GO.23.00312
26. Agrawal S Feng Y Roy A Kollia G Lestini B Nivolumab dose selection: challenges, opportunities, and lessons learned for cancer immunotherapy J Immunother Cancer 2016 4 72 10.1186/s40425-016-0177-2 27879974
Agrawal S, Feng Y, Roy A, Kollia G, Lestini B. Nivolumab dose selection: challenges, opportunities, and lessons learned for cancer immunotherapy. J Immunother Cancer. 2016;4:72.27879974 10.1186/s40425-016-0177-2
27. Herbst RS Soria JC Kowanetz M Fine GD Hamid O Gordon MS Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients Nature 2014 515 7528 563 567 10.1038/nature14011 25428504
Herbst RS, Soria JC, Kowanetz M, Fine GD, Hamid O, Gordon MS, et al. Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients. Nature. 2014;515(7528):563–7.25428504 10.1038/nature14011
28. Powles T Eder JP Fine GD Braiteh FS Loriot Y Cruz C MPDL3280A (anti-PD-L1) treatment leads to clinical activity in metastatic bladder cancer Nature 2014 515 7528 558 562 10.1038/nature13904 25428503
Powles T, Eder JP, Fine GD, Braiteh FS, Loriot Y, Cruz C, et al. MPDL3280A (anti-PD-L1) treatment leads to clinical activity in metastatic bladder cancer. Nature. 2014;515(7528):558–62.25428503 10.1038/nature13904
29. Chou CH Hsu LF Model-based simulation to support the extended dosing regimens of atezolizumab Eur J Clin Pharmacol 2021 77 1 87 93 10.1007/s00228-020-02980-3 32808071
Chou CH, Hsu LF. Model-based simulation to support the extended dosing regimens of atezolizumab. Eur J Clin Pharmacol. 2021;77(1):87–93.32808071 10.1007/s00228-020-02980-3
30. Stroh M Winter H Marchand M Claret L Eppler S Ruppel J Clinical pharmacokinetics and pharmacodynamics of atezolizumab in metastatic urothelial carcinoma Clin Pharmacol Ther 2017 102 2 305 312 10.1002/cpt.587 27981577
Stroh M, Winter H, Marchand M, Claret L, Eppler S, Ruppel J, et al. Clinical pharmacokinetics and pharmacodynamics of atezolizumab in metastatic urothelial carcinoma. Clin Pharmacol Ther. 2017;102(2):305–12.27981577 10.1002/cpt.587
31. Datta-Mannan A Estwick S Zhou C Choi H Douglass NE Witcher DR Influence of physiochemical properties on the subcutaneous absorption and bioavailability of monoclonal antibodies MAbs 2020 12 1 1770028 10.1080/19420862.2020.1770028 32486889
Datta-Mannan A, Estwick S, Zhou C, Choi H, Douglass NE, Witcher DR, et al. Influence of physiochemical properties on the subcutaneous absorption and bioavailability of monoclonal antibodies. MAbs. 2020;12(1):1770028.32486889 10.1080/19420862.2020.1770028
32. Peer CJ Schmidt KT Arisa O Richardson WJ Paydary K Goldstein DA In silico re-optimization of atezolizumab dosing using population pharmacokinetic simulation and exposure-response simulation J Clin Pharmacol 2023 63 6 672 680 10.1002/jcph.2203 36624662
Peer CJ, Schmidt KT, Arisa O, Richardson WJ, Paydary K, Goldstein DA, et al. In silico re-optimization of atezolizumab dosing using population pharmacokinetic simulation and exposure-response simulation. J Clin Pharmacol. 2023;63(6):672–80.36624662 10.1002/jcph.2203
33. Marolleau S Mogenet A Boeri C Hamimed M Ciccolini J Greillier L Killing a fly with a sledgehammer: atezolizumab exposure in real-world lung cancer patients CPT Pharmacometr Syst Pharmacol 2023 12 11 1795 1803 10.1002/psp4.13063
Marolleau S, Mogenet A, Boeri C, Hamimed M, Ciccolini J, Greillier L. Killing a fly with a sledgehammer: atezolizumab exposure in real-world lung cancer patients. CPT Pharmacometr Syst Pharmacol. 2023;12(11):1795–803.10.1002/psp4.13063
