The heterogenous group of advanced therapy medicinal products (ATMPs) are biologics with frequently limited viral safety profiles. As compared to well-established biologics such as monoclonal antibody products, the risk of virus contamination is significantly higher for some ATMPs. The standard approaches and tools used to mitigate the viral risk have limitations, leaving open the chances of missing virus contamination in an ATMP manufacturing process in both upstream and downstream. Next-generation sequencing (NGS) technology can overcome the residual risk by having the potential to detect any kind of virus contamination based on its inherent capability to detect any kind of nucleic acid in a sample. It perfectly combines the benefits and compensates for the downsides of the existing testing tools. It will replace a bunch of different established testing methods at improved turnaround times and, in the end, reduced overall costs. The combination of these characteristics is making NGS-based virus testing an in-demand and preferred approach to mitigating the virus contamination risk across all kinds of biologics mid- and long-term.
Category: <span>Risk Analysis and Management</span>
“Closed system.” The term itself appears deceptively simple. However, the definition of a closed system, its implementation, and its impact on biomanufacturing has been anything but straightforward.
The journey toward implementing closed systems spans over 20 years. The concept of closed systems was introduced in January 2000 with the draft issue of ICH Q7. Since then, other industry guidance documents emerged, defining and supporting process/system closure as a primary means of risk mitigation to meet the baseline requirement of protecting the product, as defined in cGMP.
Presently, global regulatory agencies recognize three distinct definitions of a closed system. These definitions, found in EU Annex 1, EU Annex 2, and the PIC Annex 2A, all focus on product protection where the product is not exposed to the immediate room environment during manufacturing. This is where the journey begins.
The ability to scale a cell culture effectively and efficiently, from lab to manufacturing, is critical to maximizing productivity whilst minimizing the risk of run failures and delays that can cost millions of dollars per month. The task of scaling well, however, is still considered to be a challenge by many upstream scientists, and this can be an exercise in trial and error. Traditionally, scaling has most often been performed using arithmetic in a spreadsheet and/or simple “back of an envelope” calculations. For some, it may even come in the form of support from a team of data scientists using advanced analytical software. This dependency on what some consider to be complex mathematics or statistics has resulted in the common consideration of using just one scaling parameter at a time, one scale at a time.
However, it is difficult to determine easily or optimally, from the start, whether a process successfully transfers across scales based on only one process parameter, at one scale. In this article, we describe the benefits of using a risk-based approach to scaling, and the development of a software scaling tool known as BioPAT® Process Insights for predictive scale conversion across different bioreactor scales. BioPAT Process Insights can be used to consider multiple parameters and across multiple scales simultaneously, from the start of a scaling workflow. We briefly describe how it was used in a proof-of-concept scale-up study to allow a faster, more cost-effective process transfer from 250 mL to 2000 L. In summary, using BioPAT Process Insights, in conjunction with a bioreactor range that has comparable geometry and physical similarities across scales, has the potential to help biopharma manufacturing facilities reach 2000 L production-scale volumes with fewer process transfer steps, saving both time and money during scale-up of biologics and vaccines.
The rapid and seemingly uncontrolled spread of African swine fever (ASF) throughout China and many of its neighboring countries within the last 19 months (August 2018–March 2020) has put the rest of the world on high alert. The geographic distribution of viruses of importation concern, like ASF virus (ASFV), can change very quickly, putting at risk conventional sources of porcine serum and other porcine-derived products used as ingredients in research, the manufacture of biologics, and other biomedical applications. This article reviews the 2019 information from the World Organization for Animal Health (OIE) regarding the presence or absence of eight viruses of importation concern in the swine populations of 30 countries from animal serum-producing regions of the world. Companies importing porcine raw materials for formulation into porcine products – and their customers – should be aware of the geographic location of swine diseases of importation concern. The article also identifies ten adventitious viruses of concern cited in United States Department of Agriculture (USDA) and European Union (EU) regulations that need to be tested for or eliminated through one or more barrier treatments when porcine ingredients are used in the manufacture of biologics.
While many risk analysis methods describe how execution or performance risks originate and propagate through pharmaceutical and biopharmaceutical manufacturing processes and systems, few provide methods for efficiently estimating the uncertainty of an execution risk’s occurrence. This article describes prospective causal risk modeling (PCRM) for estimating the risk’s uncertainty of failures associated with executing processes, particularly when little process performance information or data is available. Building upon a basic unit of risk, the process-based system risk structure (SRS) approach is combined with PCRM to provide a method of carrying out quality risk management (QRM) exercises that properly assess both the severity and uncertainty of process execution risks. After the risks are structured using an SRS, PCRM provides a straightforward and effective method for using subjective human judgement and thought experiments to evaluate the risk process’s causal mechanisms for analyzing, evaluating, and controlling the uncertainty, including its likelihood of occurrence, of significant risks associated with developing and manufacturing pharmaceuticals. Using an SRS/PCRM-based QRM exercise, a wide variety of process execution risks can be efficiently evaluated and accepted or rejected so that important risks requiring mitigation can be identified for additional evaluation, control, and eventual acceptance.
It is a common belief that fetal bovine serum (FBS) collected from certain geographical regions, such as New Zealand, is of superior quality to material collected from South America. Whilst it is true that origin does have an impact on the price of serum, it does not affect the quality or biological performance of the product. FBS collected under similar conditions from any geographical region will demonstrate comparable ability to support cell growth. For FBS, the term “quality” is frequently confused with “health status.” It is the health status of the geographical region from which the serum is collected that will dictate its potential use, the availability of material for import, and eventually, the price. It should be noted that health status should be considered a result of more than just the geographical source of the material, but also the regulatory infrastructure and how well regulations are enforced by the countries within that region…