Dataset Information

A system identification approach for developing model predictive controllers of antibody quality attributes in cell culture processes.

ABSTRACT: As the biopharmaceutical industry evolves to include more diverse protein formats and processes, more robust control of Critical Quality Attributes (CQAs) is needed to maintain processing flexibility without compromising quality. Active control of CQAs has been demonstrated using model predictive control techniques, which allow development of processes which are robust against disturbances associated with raw material variability and other potentially flexible operating conditions. Wide adoption of model predictive control in biopharmaceutical cell culture processes has been hampered, however, in part due to the large amount of data and expertise required to make a predictive model of controlled CQAs, a requirement for model predictive control. Here we developed a highly automated, perfusion apparatus to systematically and efficiently generate predictive models using application of system identification approaches. We successfully created a predictive model of %galactosylation using data obtained by manipulating galactose concentration in the perfusion apparatus in serialized step change experiments. We then demonstrated the use of the model in a model predictive controller in a simulated control scenario to successfully achieve a %galactosylation set point in a simulated fed-batch culture. The automated model identification approach demonstrated here can potentially be generalized to many CQAs, and could be a more efficient, faster, and highly automated alternative to batch experiments for developing predictive models in cell culture processes, and allow the wider adoption of model predictive control in biopharmaceutical processes. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 33:1647-1661, 2017.

SUBMITTER: Downey B

PROVIDER: S-EPMC5763414 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A system identification approach for developing model predictive controllers of antibody quality attributes in cell culture processes.

Downey Brandon B Schmitt John J Beller Justin J Russell Brian B Quach Anthony A Hermann Elizabeth E Lyon David D Breit Jeffrey J

Biotechnology progress 20170824 6

As the biopharmaceutical industry evolves to include more diverse protein formats and processes, more robust control of Critical Quality Attributes (CQAs) is needed to maintain processing flexibility without compromising quality. Active control of CQAs has been demonstrated using model predictive control techniques, which allow development of processes which are robust against disturbances associated with raw material variability and other potentially flexible operating conditions. Wide adoption ...[more]

PMID: 28786215

Similar Datasets

Project description:Diffuse large cell B cell lymphoma (DLBCL) accounts for approximately 30%-40% of all non-Hodgkin lymphoma (NHL) cases. Current first line DLBCL treatment results in long-term remission in more than 60% of cases. However, those patients with primary refractory disease or early relapse exhibit poor prognosis, highlighting a requirement for alternative therapies. Our aim was to develop a novel model of DLBCL that facilitates in vitro testing of current and novel therapies by replicating key components of the tumor microenvironment (TME) in a three-dimensional (3D) culture system that would enable primary DLBCL cell survival and study ex vivo. The TME is a complex ecosystem, comprising malignant and non-malignant cells, including cancer-associated fibroblasts (CAF) and tumor-associated macrophages (TAM) whose reciprocal crosstalk drives tumor initiation and growth while fostering an immunosuppressive milieu enabling its persistence. The requirement to recapitulate, at least to some degree, this complex, interactive network is exemplified by the rapid cell death of primary DLBCL cells removed from their TME and cultured alone in vitro. Building on previously described methodologies to generate lymphoid-like fibroblasts from adipocyte derived stem cells (ADSC), we confirmed lymphocytes, specifically B cells, interacted with this ADSC-derived stroma, in the presence or absence of monocyte-derived macrophages (MDM), in both two-dimensional (2D) cultures and a 3D collagen-based spheroid system. Furthermore, we demonstrated that DLBCL cells cultured in this system interact with its constituent components, resulting in their improved viability as compared to ex-vivo 2D monocultures. We then assessed the utility of this system as a platform to study therapeutics in the context of antibody-directed phagocytosis, using rituximab as a model immunotherapeutic antibody. Overall, we describe a novel 3D spheroid co-culture system comprising key components of the DLBCL TME with the potential to serve as a testbed for novel therapeutics, targeting key cellular constituents of the TME, such as CAF and/or TAM.

Project description:Adipose-derived mesenchymal stromal cells (MSC(AT)) display immunomodulatory and angiogenic properties, but an improved understanding of quantitative critical quality attributes (CQAs) that inform basal MSC(AT) fitness ranges for immunomodulatory and/or angiogenic applications is urgently needed for effective clinical translation. We constructed an in vitro matrix of multivariate readouts to identify putative CQAs that were sensitive enough to discriminate between specific critical processing parameters (CPPs) chosen for their ability to enhance MSC immunomodulatory and angiogenic potencies, with consideration for donor heterogeneity. We compared 3D aggregate culture conditions (3D normoxic, 3D-N) and 2D hypoxic (2D-H) culture as non-genetic CPP conditions that augment immunomodulatory and angiogenic fitness of MSC(AT). We measured multivariate panels of curated genes, soluble factors, and morphometric features for MSC(AT) cultured under varying CPP and licensing conditions, and we benchmarked these against two functional and therapeutically relevant anchor assays – in vitro monocyte/macrophage (MΦ) polarization and in vitro angiogenesis. Our results showed that varying CPP conditions was the primary driver of MSC(AT) immunomodulatory fitness; 3D-N conditions induced greater MSC(AT)-mediated MΦ polarization toward inflammation-resolving subtypes. In contrast, donor heterogeneity was the primary driver of MSC(AT) angiogenic fitness. Our analysis further revealed panels of putative CQAs with minimum and maximum values that consisted of twenty MSC(AT) characteristics that informed immunomodulatory fitness ranges, and ten MSC(AT) characteristics that informed angiogenic fitness ranges. Interestingly, many of the putative CQAs consisted of angiogenic genes or soluble factors that were inversely correlated with immunomodulatory functions (THBS1, CCN2, EDN1, PDGFA, VEGFA, EDIL3, ANGPT1, and ANG genes), and positively correlated to angiogenic functions (VEGF protein), respectively. We applied desirability analysis to empirically rank the putative CQAs for MSC(AT) under varying CPP conditions and donors to numerically identify the desirable CPP conditions or donors with maximal MSC(AT) immunomodulatory and/or angiogenic fitness. Taken together, our approach enabled combinatorial analysis of the matrix of multivariate readouts to provide putative quantitative CQAs that were sensitive to variations in select CPPs that enhance MSC immunomodulatory/angiogenic potency, and donor heterogeneity. These putative CQAs may be used to prospectively screen potent MSC(AT) donors or cell culture conditions to optimize for desired basal MSC(AT) immunomodulatory or angiogenic fitness.

Project description:ObjectiveDespite having a detailed MRI-safety questionnaire check at the point of referral, we have encountered a significant number of near-misses with patients being identified with MRI-Unsafe devices at the time of appointments, making this an important safety hazard.Methods and materialsA two-part survey was performed to assess referrer compliance of asking MRI-questionnaires. 120 outpatients across 3 MRI sites were interviewed at the time of appointment to confirm whether their referrers completed the MRI questionnaires with them at the time of referral.Location:Department of Radiology, Ninewells Hospital, Perth Royal Infirmary and Stracathro Hospital in Scotland.ResultsOnly 50-55 % of patients confirmed that they were asked about presence of a pacemaker at the point of referral. Less than 50 % of patients reported being asked about other potential hazards.Suggested strategies for change: (1) Risk Alert-Sent to all MRI referrers in the organization. ( 2) Changes to MRI Safety Questionnaire. (3) Feedback mechanism to referrers-NHS trust website publications on number of recorded near-misses and wasted appointments due to MRI-safety issues. (4) Compulsory education/training of future referrers (junior doctors/allied health professionals). (5) Education of patients/public on MRI safety-Displaying patient information leaflets/posters in waiting areas of the hospital.Key measures for improvement: (1) Reduction in number of recorded near-misses. (2) System improvements, referrer and patient education, reduction of wasted MRI appointments and improvement of waiting-times for MRI appointments Effects of survey and conclusions: The survey highlights the possibility of inadequate referrer attention, and poor patient communication about MRI safety questionnaire with regards to potential hazards of MRI examination in presence of undeclared implants. It initiated several interventions resulting in improved patient safety, with no events in next 12 months, whilst promoting public and referrer's understanding of potential MRI safety issues. Such actions are recommended for all NHS centres across UK since there are significant similarities in functioning across UK.

Project description:Extrusion-based 3D-printing is an easy-to-use, cheap manufacturing technique that could be used to produce tailored precision medicines. The technique has an almost unlimited versatility since a multitude of print parameters can easily be adapted. Unfortunately, little is known of the effect of these print parameters on the critical quality attributes of the resulting printlets. In this study, practical guidelines and means to adapt certain parameters in order to achieve the desired outcome (e.g., acceptable visual quality and flexible dosing) are stipulated for medical 3D-printing using a design-of-experiments approach. The current study aims at elucidating the effect of five print parameters (infill, overlap, number of shells, layer height and layer pattern) on the mechanical properties, dimensions, weight, porosity and dissolution characteristics of a fixed-size caplet consisting of Eudragit EPO (69.3%), Polyox WSR N10 (29.7%) and zolpidem hemitartrate (1%). In terms of the mechanical properties, 3D-printed caplets possessed anisotropy where the vertical compression strength and Brinell hardness exceeded the diametral strength. In general, all 3D-printed caplets possessed acceptable mechanical strength except for a small region of the knowledge space. Dimensional analysis revealed small, statistical significant differences between different runs, although the clinical relevance of this variation is likely negligible. The weight or dose of a caplet can be varied mainly using the infill and overlap and, to a lesser extent, via the layer height and number of shells. The impact on porosity was complicated as this was influenced by many factors and their interactions. Infill was the only statistically relevant factor influencing the dissolution rate of the current formulation. This study unravels the importance of the print parameter overlap, which is a regularly neglected parameter. We also discovered that small dose variations while maintaining the same dissolution profile were possible via modifying the overlap or number of shells. However, large dose variations without affecting the dissolution behaviour could only be accomplished by size modifications of the printlet.

Dataset Information

A system identification approach for developing model predictive controllers of antibody quality attributes in cell culture processes.

Publications

A system identification approach for developing model predictive controllers of antibody quality attributes in cell culture processes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets