Author Archives: Naveenganesh Muralidharan

Identifying False Metabolite Measurements During Cell-Culture Monitoring Effective Application of the Multivariate Hotelling’s T2 Statistic

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Upstream process scientists and engineers actively monitor bioreactor metabolite levels during cell culture using off-line blood-gas analyzers (BGAs) and related instrumentation. But such tools introduce inherent variability into metabolite measurements. The magnitude of that variability depends on the measurement range. Mammalian cells are sensitive to concentrations of one such metabolite: dissolved CO2. In cell cultures, CO2 levels often are reported as partial pressure (pCO2) in millimeters of mercury (mmHg). Available literature frequently reports that elevated pCO2 concentrations have adverse impacts…

Validating Prefiltration Dirty-Hold Times for Upstream Media and Feed Solutions: Implications for Establishing In-Process Microbial Control

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Biopharmaceutical manufacturing processes require that prepared raw materials and product intermediates be held at different stages. During hold times, however, process and product intermediates are susceptible to microbial risks from bioburden, endotoxins, and exotoxins. Such risks arise from multiple sources, including bioproduction facilities, equipment, operations, and raw materials. Even a prepared intermediate can help microbes to grow. The US Food and Drug Administration’s (FDA’s) guidance on Sterile Drug Products Produced By Aseptic Processing states that “the time limits established for…

September 19, 2023

Specification Limits for Biomanufacturing Processes: Comparing Tolerance-Interval and Process-Capability Methods

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Critical quality attributes (CQAs) such as safety, efficacy, purity, and identity must be monitored and controlled in biopharmaceutical products to meet predefined specification limits. Setting such parameters is critical but challenging. Unduly narrow specification limits increase risks for rejecting good product batches, whereas overbroad limits can lead to acceptance of bad batches (1). Limited sample sizes, homogeneous results obtained from testing of raw materials exhibiting scant variability, and variability inherent to testing methodologies can add up, encouraging quality teams to…

June 26, 2023
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Process Validation: Calculating the Necessary Number of Process Performance Qualification Runs

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The 2011 process validation (PV) guidance document from the US Food and Drug Administration (FDA) states that the number of samples used for PV “should be adequate to provide sufficient statistical confidence of quality both within a batch and between batches. The confidence level selected can be based on risk analysis as it relates to the particular attribute under examination” (1). In alignment with those expectations, I present herein two statistical methodologies for calculating the necessary number of process performance…

May 17, 2023

Quantitative Risk Assessment of Limits for Residual Host-Cell DNA: Ensuring Patient Safety for In Vitro Gene Therapies Produced Using Human-Derived Cell Lines

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Viral-vector gene therapies (GTs) manufactured from cell-substrate production systems can contain residual amounts of host-cell DNA (hcDNA), which in a final product presents safety risks to treated patients. Therefore, drug manufacturers monitor and control residual hcDNA levels in purified products (1, 2). The US Food and Drug Administration (FDA) and other global regulatory agencies recommend tight, quantifiable limits for hcDNA levels: 10 ng/dose, with DNA fragments smaller than the functional gene size of 200 base pairs (bp) (3). However, because…

April 20, 2023

Shear-Proof Design Space: Scaling Stirred-Tank Bioreactors for Cell Culture Processes

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Establishing a cell culture process across different scales and models of bioreactors involves maintaining constant scale-independent parameters such as pH, temperature, and dissolved oxygen (DO). However, nonlinear and scale-dependent criteria (impeller agitation and gas flow rates) are adjusted on the basis of multiple normalized engineering parameters to accommodate the geometrical and design differences among bioreactors (1–3). Normalized engineering approaches for scaling parameterization often are based on the shear generated by impeller speed and gas flow rates. Kinetic energy transmitted into…

February 9, 2023

Statistical Method for Establishing Control Limits for Nonnormal Data Distribution: Focus on Continued Process Verification Monitoring

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According to the US Food and Drug Administration’s (FDA’s) process validation guidance, critical quality attributes (CQAs) and critical process parameters (CPPs) are used to assess the statistical stability of a bioprocess and its ability to meet acceptable criteria as a part of a continued process verification (CPV) program using control charts (1). For those control charts, control limits are used to assess the statistical stability of process parameters and attributes. When data are normally distributed, control limits are established straightforwardly…

October 20, 2022