PKPD-Based Translational Modeling of Calaspargase Pegol Preclinical Activity in Hepatocellular Carcinoma

BACKGROUND AND OBJECTIVE: Calaspargase pegol (CalPEG) is a PEGylated conjugate of L-Asparaginase (L-Asp) and an asparagine specific enzyme approved by the Food and Drug Administration (FDA) as a component of a multi-agent chemotherapeutic regimen for the treatment of acute lymphoblastic leukemia (ALL) in children and young adults. Although CalPEG is an established and effective treatment for childhood ALL, its potential in solid tumors is still underexplored. Recent reports illustrated that L-Asp may also have potential for the treatment of certain aggressive solid tumors, including hepatocellular carcinoma (HCC)[1-5]. In order to investigate this potential, clinical and preclinical data were integrated using model-informed drug development (MIDD) approaches, which are among the most adequate tools to facilitate the translation of preclinical into clinical data [6-9]. This work explores the potential of pharmacokinetic/pharmacodynamic tumor growth inhibition (PKPD TGI) modeling to maximize the use of in vivo preclinical data and PK data in patients with ALL for translation of preclinical observed antitumor activity to clinical efficacy. METHODS: A PKPD TGI model was developed that described tumor volumes (TVs) versus time in a preclinical hypermethylated xenograft mouse model relevant for HCC. Translation of the PKPD TGI model to human was performed by linking the structural TGI model developed in mice with human PK model of CalPEG. This model was developed on PK data, i.e., plasma Asp activity (PAA), obtained in pediatric and adult patients with ALL and was used to predict TGI profiles of CalPEG in adult patients with HCC. RESULTS: The developed PKPD TGI model adequately described the TV versus time profiles in tumor bearing (TB) mice and quantified the PKPD relationship between PAA and TGI in TB mice. The structural mouse TGI model was linked to predicted human PK parameters and this human PKPD TGI model was used to perform simulations and to predict antitumor activity of CalPEG at different doses/schedule in patients with HCC. CONCLUSIONS: The results indicate that PKPD TGI modeling can be used to build a preclinical to clinical translational framework to predict the exposure-response relationship in patients with HCC and to inform dosing strategies or trial designs for solid tumors.