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Integrating disease progression models, non-clinical pharmacokinetic data and treatment response endpoints to optimize intravitreal dosing regimens

机译:整合疾病进展模型,非临床药代动力学数据和治疗反应终点,以优化玻璃体内给药方案

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摘要

To rapidly identify patients who will ultimately respond to I year of therapy, and optimize their inter- dose interval. Materials and methods: An intravitreal (IVT) ophthalmic dosing paradigm was designed based on clinical efficacy, nonclinical pharmacokinetics (PK), and disease progression modeling. Relevant non-clinical PK models were used to extrapolate IVT drug concentrations to patients. Results: Modeling predicted that > 80% of patients who would respond to 1 year of IVT treat-ment with an improvement in best-corrected visual acuity (BCVA) could be identified after the first 2 doses of treatment. These 2 initial doses produced ~ 75% of the maximum improvement in BCVA attainable. Moreover, the models also predicted those patients who responded after 1 year of treatment may tolerate an extension of the interdose interval to 12 weeks without significant deterioration of BCVA. In contrast, > 70% of responsive patients who did not respond to 1 year of treatment showed inadequate responses after 2 doses. Conclusions: These models use data from 2 doses to identify those patients likely to benefit after 1 year of treatment, and thereafter can lengthen their interdose interval without deleterious effects. This method identifies potential treatment responders early, and lengthens the interdose interval during long- Term administration while allowing non-responders to pursue alternative therapies earlier, thereby minimizing risk to the patient.
机译:快速确定最终对治疗一年有效的患者,并优化他们的剂量间隔。材料和方法:根据临床疗效,非临床药代动力学(PK)和疾病进展模型设计了玻璃体内(IVT)眼药剂量范例。相关的非临床PK模型用于将IVT药物浓度外推至患者。结果:模型预测,在前2剂治疗后,可以识别出对80%以上对IVT治疗1年有反应,最佳矫正视敏度(BCVA)有所改善的患者。这两个初始剂量约可达到BCVA最大改善的75%。此外,该模型还预测,在治疗1年后有反应的患者可以耐受剂量间隔延长至12周,而BCVA不会明显恶化。相反,超过70%的对1年治疗无反应的反应患者在2剂给药后显示反应不足。结论:这些模型使用来自2剂的数据来确定那些在治疗1年后可能受益的患者,然后可以延长其用药间隔时间而不会产生有害影响。这种方法可以及早发现潜在的治疗反应者,并延长长期给药期间的给药间隔,同时允许无反应者尽早采用替代疗法,从而将患者的风险降至最低。

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