Evaluation and translation of combination therapies in oncology – A quantitative approach
Artikel i vetenskaplig tidskrift, 2018

Quantitative techniques improve our understanding of tumor volume data for combination treatments and its translation across in vivo models and species. The focus of this paper is therefore on understanding in vivo data, highlighting key structural elements of pharmacodynamic tumor models, and challenging these methods from a translational point of view. We introduce the concept of Tumor Static Exposure (TSE) both for single and multiple combined anticancer agents. The TSE curve separates all possible exposure combinations into regions of tumor growth and tumor shrinkage. Moreover, the degree of curvature of the TSE curve indicates the degree of synergy or antagonism. We demonstrate the TSE approach by two case studies. The first examines a combination of the drugs cetuximab and cisplatin. The TSE curve associated with this combination reveals a weak synergistic effect, suggesting only modest gains from combination therapy. The second case study examines combinations of ionizing radiation and a radiosensitizing agent. In this case, the TSE curve exhibits a pronounced curvature, indicating a strong synergistic effect; tumor regression can be achieved at significantly lower exposure levels and/or radiation doses. Finally, an allometric approach to human dose prediction demonstrates the translational power of the model and the TSE concept. We conclude that the TSE approach, which embodies model-based measures of both drug (potency) and target properties (tumor growth rate), has a strong potential for ranking of compounds, supporting compound selection, and translating preclinical findings to humans.

Tumor static exposure

Dose optimization

Pharmacokinetic/pharmacodynamic modeling

Inter-species scaling

Författare

Tim Cardilin

Stiftelsen Fraunhofer-Chalmers Centrum för Industrimatematik

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Joachim Almquist

AstraZeneca AB

Stiftelsen Fraunhofer-Chalmers Centrum för Industrimatematik

Mats Jirstrand

Stiftelsen Fraunhofer-Chalmers Centrum för Industrimatematik

Johan Gabrielsson

Sveriges lantbruksuniversitet (SLU)

European Journal of Pharmacology

0014-2999 (ISSN)

Vol. 834 327-336

Ämneskategorier

Farmaceutisk vetenskap

Bioinformatik (beräkningsbiologi)

Radiologi och bildbehandling

DOI

10.1016/j.ejphar.2018.07.041

Mer information

Senast uppdaterat

2018-09-14