RESUMO
The commercial production of recombinant human monoclonal antibody therapeutics demands robust processes. In this article we describe the development of a pH-conductivity hybrid gradient for a cation-exchange chromatography step to obtain high binding capacity and consistent purification resolution in scale process. Operational parameters and their ranges were characterized with DOE statistical method. Aggregate, DNA and leached protein A removal were examined during development. The advantages and disadvantages of hybrid gradient elution compared to sodium chloride gradient elution were explored. As this step was designed as a good fit for the compatibility of the feed and operating pH/conductivity conditions for next step, the effects of elution by either changing sodium chloride concentration or changing pH of elution buffers on overall separation efficiency were compared. The operation condition was further confirmed in six 2000 L scale runs. The thorough evaluation demonstrated process reliability of hybrid gradient cation-exchange chromatography with high step purity and yield.
Assuntos
Anticorpos Monoclonais/isolamento & purificação , Cromatografia por Troca Iônica/métodos , Animais , Soluções Tampão , Células CHO , Cátions , Fracionamento Químico , Cromatografia em Gel , Cricetinae , Cricetulus , DNA/isolamento & purificação , Humanos , Concentração de Íons de Hidrogênio , Polímeros/química , Resinas Sintéticas/química , Acetato de Sódio/química , Cloreto de Sódio/química , Proteína Estafilocócica A/isolamento & purificação , TemperaturaRESUMO
This paper presents an overview of large-scale downstream processing of monoclonal antibodies and Fc fusion proteins (mAbs). This therapeutic modality has become increasingly important with the recent approval of several drugs from this product class for a range of critical illnesses. Taking advantage of the biochemical similarities in this product class, several templated purification schemes have emerged in the literature. In our experience, significant biochemical differences and the variety of challenges to downstream purification make the use of a completely generic downstream process impractical. Here, we describe the key elements of a flexible, generic downstream process platform for mAbs that we have adopted at Amgen. This platform consists of a well-defined sequence of unit operations with most operating parameters being pre-defined and a small subset of parameters requiring development effort. The platform hinges on the successful use of Protein A chromatography as a highly selective capture step for the process. Key elements of each type of unit operation are discussed along with data from 14 mAbs that have undergone process development. Aspects that can be readily templated as well as those that require focused development effort are identified for each unit operation. A brief description of process characterization and validation activities for these molecules is also provided. Finally, future directions in mAb processing are summarized.
Assuntos
Anticorpos Monoclonais/química , Anticorpos Monoclonais/isolamento & purificação , Anticorpos Monoclonais/genética , Cromatografia de Afinidade/métodos , Fragmentos Fc das Imunoglobulinas/química , Fragmentos Fc das Imunoglobulinas/genética , Fragmentos Fc das Imunoglobulinas/isolamento & purificação , Modelos Moleculares , Proteínas Recombinantes de Fusão/química , Proteínas Recombinantes de Fusão/genética , Proteínas Recombinantes de Fusão/isolamento & purificação , Proteína Estafilocócica A/química , Proteína Estafilocócica A/genéticaRESUMO
We describe the development, attributes and capabilities of a novel type of artificial intelligence system, called LabExpert, for automation of HPLC method development. Unlike other computerised method development systems, LabExpert operates in real-time, using an artificial intelligence system and design engine to provide experimental decision outcomes relevant to the optimisation of complex separations as well as the control of the instrumentation, column selection, mobile phase choice and other experimental parameters. LabExpert manages every input parameter to a HPLC data station and evaluates each output parameter of the HPLC data station in real-time as part of its decision process. Based on a combination of inherent and user-defined evaluation criteria, the artificial intelligence system programs use a reasoning process, applying chromatographic principles and acquired experimental observations to iteratively provide a regime for a priori development of an acceptable HPLC separation method. Because remote monitoring and control are also functions of LabExpert, the system allows full-time utilisation of analytical instrumentation and associated laboratory resources. Based on our experience with LabExpert with a wide range of analyte mixtures, this artificial intelligence system consistently identified in a similar or faster time-frame preferred sets of analytical conditions that are equal in resolution, efficiency and throughput to those empirically determined by highly experienced chromatographic scientists. An illustrative example, demonstrating the potential of LabExpert in the process of method development of drug substances, is provided.