Cachexia-associated anticancer drug toxicity is minimally mediated by alteration of drug’s pharmacokinetics: Erlotinib as case study
Yomna Nassar (1,2), Zinnia P Parra-Guillén (3,4), Kira-Lee Koster (5), Wilhelm Huisinga (6), Markus Joerger (5), and Charlotte Kloft (1)
(1) Department of Clinical Pharmacy and Biochemistry, Institute of Pharmacy, Freie Universitaet Berlin, Germany, (2) Graduate Research Training program PharMetrX, Germany, (3) Pharmacometrics & Systems Pharmacology, Department of Pharmaceutical Technology and Chemistry, School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain (4) IdiSNA, Navarra Institute for Health Research, Spain (5) Medical Oncology and Clinical Pharmacology, Department of Internal Medicine, Cantonal Hospital St. Gallen, Switzerland, (6) Institute of Mathematics, University of Potsdam, Germany
Introduction
Cachexia is an irreversible condition of muscle mass loss characterised by chronic systemic inflammation and energy imbalance. It commonly occurs in cancer patients and impacts their response to treatment and survival [1,2]. Toxicity of different chemotherapeutic compounds, and in different cancer types, has been associated with muscle mass loss [3–8]. Nevertheless, the underlying mechanism to this observed toxicity remains unclear.
We hypothesise a potential impact of cachexia-related muscle loss on the PK of anticancer drugs in mediating toxicity. Thus, we sought to identify, whether the change in body composition, represented by muscle mass loss, alters drug pharmacokinetics (PK) and exposure, and subsequently elevates drug concentration leading to toxicity. We primarily focused on erlotinib, a tyrosine kinase inhibitor widely used for the treatment of non-small cell lung cancer (NSCLC) and pancreatic cancer. We utilised computed tomography (CT) skeletal muscle measurements which linearly correlates with the body composition [9] to explore skeletal muscle impact on the PK parameters of erlotinib and its metabolite (OSI-420).
Methods
A total of 36 patients with advanced inoperable NSCLC received 150 mg once daily oral erlotinib. Plasma samples were collected at baseline, 1, 2, 3, 4, and 6 h after erlotinib administration on day 1 and at steady state at 2, 4, 8, and 10 weeks (Clinical trial: NCT01402089) [10]. Baseline skeletal muscle information was derived from CT imaging at the level of the 3rd lumbar vertebrae (L3) that was analysed and converted to area using Slice-O-Matic software. Skeletal muscle area (SMA) was then further converted to other descriptors, namely skeletal muscle volume (SMV) [11] and skeletal muscle mass (SMM) [12].
A previously developed joint erlotinib and OSI-420 NLME model, based on the 36 patients, was adopted as the base model [10]. Erlotinib and OSI-420 were each described with a one compartment PK model, parameterised in terms of CL and V. Absorption rate constant was fixed to the literature value of 1.09 h-1 [13]. Demographic characteristics and skeletal muscle measurements were available for only a subset of patients. Therefore, a sub-population dataset (n=23) was used to assess the potential impact of body size descriptors (weight, body mass index, lean body weight, height); clinical characteristics (smoking status, use of proton pump inhibitors, disease stage); and the different skeletal muscle descriptors on erlotinib and OSI-420 PK parameters, after confirming the PK model robustness for the subset population. Covariate analysis was performed univariately to exclude the influence of potential correlations of different body size and skeletal muscle descriptors.
Results
The PK model proved robust on the level of population estimates (relative percent change in structural parameters: -0.374%–26.0%; IIV: -45.1%–5.065%; residual variability: 6.39%–7.95%). The GOF plots and VPC also confirmed the model’s adequate performance and predictability. None of the different skeletal muscle descriptors significantly influenced CL or V of erlotinib or OSI-420. Similarly, none of the body size descriptors or clinical characteristics proved to be significant. Thus, the observed differences in muscle mass did not impact the distribution and exposure of erlotinib.
Conclusion
The insignificant impact of skeletal muscle or different body size descriptors on erlotinib PK indicated lack of an association between skeletal muscle loss and erlotinib PK. Consequently, cachexia-associated alteration in drug exposure and toxicity is possibly mediated through a non-PK pathway, possibly influenced by the systemic inflammatory status induced by cachexia or the co-morbid condition of the patient. Muscle mass impact on the PK of other anticancer drugs in advanced cancer patients is currently being investigated to explore whether specific drug properties (e.g. physicochemical) alter drug PK and/or exposure in response to skeletal muscle loss.
References
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