A computational dynamic model of combination treatment for type II inhibitors with asciminib
J Roadnight Sheehan1, Astrid S de Wijn1, Ran Friedman2
1Department of Mechanical and Industrial Engineering, Norwegian University of Science and Technology, Trondheim, Norway.
Abstract:
Despite continuous strides forward in drug development, resistance to treatment looms large in the battle against cancer as well as communicable diseases. Chronic myeloid leukemia (CML) is treated with targeted therapy and treatment is personalized when resistance arises. It has been extensively studied and is used as a model for targeted therapy. In this study, we examine combination treatments of type II Abl1 inhibitors and asciminib (an allosteric regulator) through a computational model at patient relevant concentrations. Due to the separate binding sites of type II inhibitors and asciminib, we propose their combination treatment as potentially robust to resistance. We find that the simultaneous cobinding of type II inhibitors and asciminib is high in synergetic combinations. As an aid to designing and comparing combination treatments, we put forward an equation that expands on the previously published effective ratio of IC50 (ERIC). Unlike usual comparisons of IC50 values, ERIC takes patient plasma concentrations into account. This study shows that the product of two ERIC values ( ) creates comparable approximations of the effectiveness of combination treatments with low levels of synergy or antagonism at different concentrations. Its simple formulation is done without experiments and requires less computation and input data than the current standard of ZIP values. As such, the new scheme is a useful complement to experiments that deal with synergy in drug use.
Insights
This study explores combining type II Abl1 inhibitors with asciminib to overcome cancer treatment resistance. The new ERIC combo metric effectively predicts combination therapy synergy without extensive experiments.
Area of Science:
- Oncology
- Pharmacology
- Computational Biology
Background:
- Drug resistance is a major challenge in treating cancers like chronic myeloid leukemia (CML).
- Targeted therapies and personalized medicine are crucial for managing resistance.
- CML serves as a model for studying targeted therapy resistance.
Purpose of the Study:
- To investigate the synergistic potential of combining type II Abl1 inhibitors with asciminib for cancer treatment.
- To develop a novel computational metric (ERIC combo) for evaluating drug combination effectiveness at patient-relevant concentrations.
- To propose a combination strategy robust against treatment resistance due to distinct drug binding sites.
Main Methods:
- Utilizing a computational model to simulate drug interactions at patient-relevant concentrations.
- Examining the simultaneous co-binding of type II Abl1 inhibitors and asciminib.
- Developing and applying the effective ratio of IC50 (ERIC) and its extension, ERIC combo, for synergy assessment.
Main Results:
- Simultaneous co-binding of type II Abl1 inhibitors and asciminib demonstrates high synergy.
- The ERIC combo metric accurately approximates combination treatment effectiveness across various concentrations.
- The proposed combination strategy shows potential robustness against resistance.
Conclusions:
- Combination therapy with type II Abl1 inhibitors and asciminib is a promising strategy against CML resistance.
- The ERIC combo metric offers a computationally efficient and data-light alternative to existing synergy assessment methods like ZIP values.
- This approach aids in designing and comparing drug combinations, complementing experimental studies on drug synergy.
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