Eli Lilly and Company , Indianapolis, Indiana 46285, United States.
Anal Chem. 2017 Sep 5;89(17):9175-9183. doi: 10.1021/acs.analchem.7b01907. Epub 2017 Aug 17.
A near-infrared (NIR) calibration was developed using an efficient offline approach to enable a quantitative partial least-squares (PLS) chemometric model to measure and monitor the concentration of active pharmaceutical ingredients (API) in powder blends in the feed frame (FF) of a tablet press. The approach leveraged an offline "feed frame table," which was designed to mimic the full process from a NIR measurement perspective, thereby facilitating a more robust model by allowing more sources of variability to be included in the calibration by minimizing the consumption of API and other raw materials. The design of experiment (DOE) for the calibration was established by an initial risk assessment and included anticipated variability from factors related to formulation, process, environment, and instrumentation. A test set collected on the feed frame table was used to refine the PLS model. Additional fully independent test sets collected from the continuous drug product manufacturing process not only demonstrated the accuracy and precision of the model but also illustrated its robustness to material variability and process variability including mass flow rate and feed frame paddle speed. Further, it demonstrated that a calibration can be generated on the offline feed frame table and then successfully implemented on the full process equipment in a robust manner. Additional benefits of using the feed frame table include streamline model monitoring and maintenance activities in a manufacturing setting. The real-time monitoring enabled by this offline calibration approach can be useful as a key component of the control strategy for continuous manufacturing processes for drug products, including detecting special cause variations such as transient disturbances and enabling product collection/rejection based upon predetermined concentration limits, and may play an important role in enabling real-time release testing (RTRt) for manufactured pharmaceutical products.
建立了一种近红外（NIR）校准方法，采用高效的离线方法，使定量偏最小二乘（PLS）化学计量模型能够测量和监测压片机进料框架（FF）中粉末混合物中活性药物成分（API）的浓度。该方法利用了离线“进料框架表”，其设计从 NIR 测量的角度模拟了整个过程，从而通过允许更多的变异性源包含在定标中，通过最小化 API 和其他原材料的消耗，使模型更加稳健。校准的实验设计（DoE）是通过初始风险评估建立的，包括与配方、工艺、环境和仪器相关的因素引起的预期变异性。在进料框架表上收集的测试集用于精炼 PLS 模型。从连续药物产品制造过程中收集的其他完全独立的测试集不仅证明了模型的准确性和精密度，还说明了其对材料变异性和工艺变异性（包括质量流率和进料框架桨叶速度）的稳健性。此外，它还表明可以在离线进料框架表上生成校准，然后以稳健的方式成功地在全过程设备上实施。在制造环境中使用进料框架表的其他好处包括简化模型监控和维护活动。这种离线校准方法实现的实时监控对于药物产品连续制造过程的控制策略非常有用，包括检测特殊原因变化，如瞬态干扰，并根据预定的浓度限制进行产品收集/拒收，并且可能在实现实时放行测试（RTRt）方面发挥重要作用用于制造的医药产品。
