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A Systems Biology Approach in Therapeutic Response Study for Different Dosing Regimens—a Modeling Study of Drug Effects on Tumor Growth using Hybrid Systems

机译:不同剂量方案的治疗反应研究中的系统生物学方法-使用混合系统的药物对肿瘤生长影响的模型研究

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Motivated by the frustration of translation of research advances in the molecular and cellular biology of cancer into treatment, this study calls for cross-disciplinary efforts and proposes a methodology of incorporating drug pharmacology information into drug therapeutic response modeling using a computational systems biology approach. The objectives are two fold. The first one is to involve effective mathematical modeling in the drug development stage to incorporate preclinical and clinical data in order to decrease costs of drug development and increase pipeline productivity, since it is extremely expensive and difficult to get the optimal compromise of dosage and schedule through empirical testing. The second objective is to provide valuable suggestions to adjust individual drug dosing regimens to improve therapeutic effects considering most anticancer agents have wide inter-individual pharmacokinetic variability and a narrow therapeutic index. A dynamic hybrid systems model is proposed to study drug antitumor effect from the perspective of tumor growth dynamics, specifically the dosing and schedule of the periodic drug intake, and a drug’s pharmacokinetics and pharmacodynamics information are linked together in the proposed model using a state-space approach. It is proved analytically that there exists an optimal drug dosage and interval administration point, and demonstrated through simulation study.
机译:出于对癌症分子和细胞生物学研究进展转化为治疗的沮丧阻挠,这项研究需要跨学科的努力,并提出了使用计算系统生物学方法将药物药理学信息纳入药物治疗反应模型的方法。目标有两个方面。第一个方法是在药物开发阶段涉及有效的数学建模,以结合临床前和临床数据,从而降低药物开发成本并提高管道生产效率,因为这非常昂贵,并且难以通过剂量和时间表获得最佳折衷实证检验。第二个目标是提供有价值的建议,以考虑到大多数抗癌药具有广泛的个体间药代动力学变异性和狭窄的治疗指数,从而调整个别药物的给药方案以改善治疗效果。提出了一种动态混合系统模型,从肿瘤生长动力学的角度,特别是周期性药物摄入的剂量和时间表,研究药物的抗肿瘤作用,并在该模型中使用状态空间将药物的药代动力学和药效学信息链接在一起方法。通过分析证明,存在最佳的药物剂量和间隔给药点,并通过模拟研究证明。

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