CPL - Chalmers Publication Library
| Utbildning | Forskning | Styrkeområden | Om Chalmers | In English In English Ej inloggad.

Tumor Static Concentration Curves in Combination Therapy

Tim Cardilin (Institutionen för matematiska vetenskaper, matematik) ; Joachim Almquist (Institutionen för biologi och bioteknik, Systembiologi) ; Mats Jirstrand (Institutionen för signaler och system, Reglerteknik ; Institutionen för biologi och bioteknik, Systembiologi) ; A. Sostelly ; C. Amendt ; S. El Bawab ; Johan Gabrielsson
AAPS Journal p. 1-12. (2016)
[Artikel, refereegranskad vetenskaplig]

© 2016 The Author(s) Combination therapies are widely accepted as a cornerstone for treatment of different cancer types. A tumor growth inhibition (TGI) model is developed for combinations of cetuximab and cisplatin obtained from xenograft mice. Unlike traditional TGI models, both natural cell growth and cell death are considered explicitly. The growth rate was estimated to 0.006 h−1 and the natural cell death to 0.0039 h−1 resulting in a tumor doubling time of 14 days. The tumor static concentrations (TSC) are predicted for each individual compound. When the compounds are given as single-agents, the required concentrations were computed to be 506 μg · mL−1 and 56 ng · mL−1 for cetuximab and cisplatin, respectively. A TSC curve is constructed for different combinations of the two drugs, which separates concentration combinations into regions of tumor shrinkage and tumor growth. The more concave the TSC curve is, the lower is the total exposure to test compounds necessary to achieve tumor regression. The TSC curve for cetuximab and cisplatin showed weak concavity. TSC values and TSC curves were estimated that predict tumor regression for 95% of the population by taking between-subject variability into account. The TSC concept is further discussed for different concentration-effect relationships and for combinations of three or more compounds.

Nyckelord: mixture dynamics, model-based drug development, oncology, pharmacokinetic/pharmacodynamic modeling, tumor xenograft

Den här publikationen ingår i följande styrkeområden:

Läs mer om Chalmers styrkeområden  

Denna post skapades 2016-10-10.
CPL Pubid: 243109


Läs direkt!

Länk till annan sajt (kan kräva inloggning)

Institutioner (Chalmers)

Institutionen för matematiska vetenskaper, matematik (2005-2016)
Institutionen för biologi och bioteknik, Systembiologi
Institutionen för signaler och system, Reglerteknik


Tillämpad matematik
Bioinformatik (beräkningsbiologi)
Farmaceutisk vetenskap

Chalmers infrastruktur