Dose individualization potential for checkpoint inhibitors

Stijn Koolen

Hospital pharmacist – Clinical pharmacologist

Department of Medical Oncology and Department of Pharmacy

Erasmus MC Cancer Institute

ICPAD

22 November 2019

Working mechanism

Immune system modulating antibodies (checkpoint inhibitors)

▪ Targeting and blocking the PD-1 receptor

PD-1 binds PD-L1 and PD-L2

▪ Inhibition of T-cell activation

Tumor cells expressing PD-L1 → escape mechanism

Problems

Ribas et al. Science 2018

• Development of immune related toxicity

• Checkpoint inhibitor monotherapy results in response in a minority of cancer patients

• Expensive

Group Indication Objective response rate (%)

High response rate Melanoma 35-70%

RCC 25%

NSCLC 20%

Intermediate response rate Bladder and urinary tract 15%

Can we use pharmacokinetic data to:

• Increase efficacy?

• Reduce side effects?

• Reduce costs?

Nivolumab

Nivolumab:

• PD-1 immune checkpoint inhibitor

• Monoclonal antibodies (IgG4; human)

• High molecular mass

• Slow distribution over tissues

• Elimination into peptides and aminoacids

• Very much alike endogeneous immunoglobulins

• T1/2 ~25 days

Factors influencing mAbPharmacokinetics

Oude Munnink et al 2016 CPT

Multomab study

Observational real-life study in patients treated with immunotherapy to:

• Explore PK in relation with effectiveness and toxicity

• Explore periperal blood immune cell characeteristics in relation with PK and outcome

• Explore effect of somatic genetic alterations on outcome after immunotherapy

Inclusion criteria

• > 18 years

• Treated with a monoclonal antibody

• Informed consent

Design

• Treatment according to standard of care

• At baseline, prior every cycle and at end of treatment a blood sample for:

• Serum → PK and biomarkers

• PBMC;

• ctDNA

Results

Between April 2016 – Sep 2019: 657 pts

Correlation between nivolumab exposure and treatment outocme in NSCLC

Basak et al. 2019 EJC - Bins presentation ICPAD 2018

A Prospective cohort study on the PK of nivolumab

• Advanced NSCLC, melanoma and RCC patients who started nivolumab treatment between April 2016 - October 2018

• Trough concentrations of nivolumab were meausered with an ELISA*

• PK data were analyzed using nonlinear mixed effect modeling

Hurkmans et al. 2019 JITC; *Basak et al. 2018 TDM

Results

• Patient characteristics

Results

1. The effect of patient factors on nivolumab pharmacokinetics

Age

Gender

Tumor type

Prior weight loss

Tumor burden

Laboratory results

Results

Model development → Initial model → Covariate incorparation → Final model

Results

• Women had 22% lower clearance than men

• The critical threshold that led to an estimated >20% increase of nivolumab clearance:

• For BSA > 2.2 m2

• For baseline serum albumin < 37.5 g/L

Hurkmans JITC 2019

1. The effect of patient factors on nivolumab pharmacokinetics

2. Relationship of nivolumab pharmacokinetics and outcome measures

Age

Gender

Tumor type

Prior weight loss

Tumor burden

Laboratory results

Radiological response

Toxicity

Results

• Pharmacokinetics vs. clinical outcome (RECIST v1.1) / toxicity (CTCAE 4.03)

Results

• Drug clearance was 42% higher in NSCLC patients with PD compared to PR/CR

• PD: mean 0.24; 95%CI: 0.22-0.27 L/day

• PR/CR: 0.17; 0.15-0.19 L/day

Hurkmans et al. JITC 2019

Results

• NSCLC patients stratified into quartiles based on drug clearance

• Low clearance (quartile 1) associated with better PFS and OS compared to patients with higher clearance (quartile 4)

Hurkmans et al. JITC 2019

Discussion

• Translational relevance?

• Dose adjustment based on patient characteristics?

• Different dosing strategy for NSCLC?

• True causal E-R relationship or reflecting the metabolic state of patient?

• Pembrolizumab at 2 and 10 mg/kg doses and also observed E-R trends within each dose level1

Turner et al., CCR 2019

• Modest E-R relationships within 1-mg/kg or the 10-mg/kg dose levels of nivolumab

Agrawal JITC 2016

Results

• Inverse clearance-response relationship nivolumab for NSCLC

• Gender, baseline BSA and serum albumin had a significant effect on nivolumab PK

• Translational relevance → individualized dosing strategy might be beneficial in the case of NSCLC - in contrast to melanoma.

Hurkmans 2019 JITC

Dose individualisation to reducecosts?

Ratain et al. 2019 JAMA oncol

Target saturation

• 90% target occupancy is reached at concentrations above 10 mg/L in an ex vivo model

• This concentration is already reached after the first cycle.*

• Median Ctrough at steady state: 60 mg/L.

• Median Ctrough after cycle 1: 19 mg/L

• Potential role for TDM to reduce dose or increase dosing interval in patients with high Ctrough levels.

→ Which cut-off level should be selected?

*Ogungbenbro et al 2018 CPT

• Example of two patients:

• with and without dose delays

Can we use pharmacokinetic data to:

• Increase efficacy? →/

• Reduce side effects? →

• Reduce costs? →

Acknowledgments

Dept of Medical Oncology

• Daan Hurkmans

• Edwin Basak

• Karlijn de Joode

• Sander Bins

• Tanja van Dijk

• Kersten Landa

• Nina Schepers

• Esther Oomen-de Hoop

• Reno Debets

• Astrid van der Veldt

• Ron Mathijssen

Dept of Pulmonology

• Darlene Mercieca

• Joachim Aerts

Dept of Immunology

• Annemarie Wijkhuis

• Marco Schreurs

Dept of Radiology and Nuclear Medicine

• Arlette Odink

Ampia Hosptial Breda, NL

Cor van der Leest

Cantonal Hospital St Gallen, Switzerland

• Marcus Joerger