التفاصيل البيبلوغرافية
| العنوان: |
Systematic review of computational methods for drug combination prediction |
| المؤلفون: |
Weikaixin Kong, Gianmarco Midena, Yingjia Chen, Paschalis Athanasiadis, Tianduanyi Wang, Juho Rousu, Liye He, Tero Aittokallio |
| المصدر: |
Computational and Structural Biotechnology Journal, Vol 20, Iss , Pp 2807-2814 (2022) |
| بيانات النشر: |
Elsevier, 2022. |
| سنة النشر: |
2022 |
| المجموعة: |
LCC:Biotechnology |
| مصطلحات موضوعية: |
Drug combinations, Synergistic effect, Selective effect, Literature review, Dose–response assay, Cancer, Biotechnology, TP248.13-248.65 |
| الوصف: |
Synergistic effects between drugs are rare and highly context-dependent and patient-specific. Hence, there is a need to develop novel approaches to stratify patients for optimal therapy regimens, especially in the context of personalized design of combinatorial treatments. Computational methods enable systematic in-silico screening of combination effects, and can thereby prioritize most potent combinations for further testing, among the massive number of potential combinations. To help researchers to choose a prediction method that best fits for various real-world applications, we carried out a systematic literature review of 117 computational methods developed to date for drug combination prediction, and classified the methods in terms of their combination prediction tasks and input data requirements. Most current methods focus on prediction or classification of combination synergy, and only a few methods consider the efficacy and potential toxicity of the combinations, which are the key determinants of therapeutic success of drug treatments. Furthermore, there is a need to further develop methods that enable dose-specific predictions of combination effects across multiple doses, which is important for clinical translation of the predictions, as well as model-based identification of biomarkers predictive of heterogeneous drug combination responses. Even if most of the computational methods reviewed focus on anticancer applications, many of the modelling approaches are also applicable to antiviral and other diseases or indications. |
| نوع الوثيقة: |
article |
| وصف الملف: |
electronic resource |
| اللغة: |
English |
| تدمد: |
2001-0370 |
| Relation: |
http://www.sciencedirect.com/science/article/pii/S2001037022002100; https://doaj.org/toc/2001-0370 |
| DOI: |
10.1016/j.csbj.2022.05.055 |
| URL الوصول: |
https://doaj.org/article/175a067dc4514c28b5498d1175b594cd |
| رقم الانضمام: |
edsdoj.175a067dc4514c28b5498d1175b594cd |
| قاعدة البيانات: |
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