Narges Lali Archives - European Industrial Pharmacists Group (EIPG)

Approval of the Data Governance Act, and EMA’s consultation on the protection of personal data in the CTIS

by Giuliana Miglierini The Data Governance Act (DGA) was approved and adopted in May 2022 by the European Council, following the positive position of the EU Parliament; the new legislation will entry into force after being signed by the presidents Read more

The transition towards EMA's new Digital Application Dataset Integration (DADI) user interface

by Giuliana Miglierini The Digital Application Dataset Integration (DADI) network project is aimed to replace the current PDF-based electronic applications forms (eAFs) used for regulatory submissions with new web-forms accessible through the DADI user interface. The European Medicines Agency (EMA) has Read more

IVD regulation in force: new MDCG guidelines and criticalities for innovation in diagnostics

by Giuliana Miglierini The new regulation on in vitro diagnostic medical devices (IVDR, Regulation (EU) 2017/746) entered into force on 26 May 2022. The new rules define a completely renewed framework for the development, validation and use of these important Read more

Greatest common divisor for product traceability and batch definition in continuous biomanufacturing

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by Giuliana Miglierini

According to the draft ICH Q13 guideline on continuous manufacturing (CM), the definition of batch established by the ICH Q7 is applicable to all modes of CM, and it may refer to the quantity of output or input material, or to the run time at a defined mass flow rate. Other approaches to batch size definition are also possible and have to be justified taking into consideration their scientific rationale and the characteristics of the specific CM process.

The choice of a range for the batch size has to be justified in the regulatory dossier, including the approach used to define it. To this instance, changes in batch size that fall into the defined range can be managed through the Pharmaceutical Quality System, while variations have to be submitted (based on the availability of supporting data) to manage post-approval changes falling outside the approved range. ICH Q13 also asks manufacturers to define a suitable quantitative metric in order to establish batch-to-batch consistency and system robustness.

A possible approach to answer the complex challenges of batch definition in continuous integrated biomanufacturing has been proposed by an article published in the Journal of Chemical Technology and Biotechnology and signed by researchers of the University of Natural Resources and Life Sciences, Vienna, Austria, and the Austrian Centre of Industrial Biotechnology (ACIB). According to the authors, another important issue to be faced in CM is the ability to trace the raw materials through the entire process.

The usefulness of the greatest common divisor (GCD)

The deep understanding of a continuous manufacturing process is fundamental to support its regulatory acceptability; many are the different parameters to be considered to this instance, both regarding the attributes of input materials (e.g., potency, material flow properties) and process conditions (e.g., mass flow rates), in order to achieve the desired comprehension of the process dynamics.

The definition of the residence time distribution (RTD) for each individual unit operation, as well as for the integrated system, can be used to define the time a certain mass or fluid element remains in the continuous process. Challenges in the use of the RTD for batch definition in CM include the possibility to combine different production runs and the possible occurrence of process failures, which may cause great economic losses in case of batches of large dimensions.

The article by Lali et al. describes the use of the greatest common divisor (GCD) as a new parameter that may prove useful to lower “the spread of the RTD through continuous downstream process chains without the need for a redesign of individual unit operations for narrower RTD”.

Semi-continuous purification as the model example

The process used to model the new approach refers to the conventional semi-continuous purification of monoclonal antibodies using staphylococcal Protein A affinity chromatography, a process that may include runs performed on different columns.

The overall modelled process described in the article consists of six different steps, each characterized by a different RTD, starting from the alternating tangential flow filtration of the output material obtained from the upstream steps. A three-column periodic countercurrent chromatography (PCC) was used for protein capture, giving rise to a discrete output flow. This was collected in a surge tank or a continuous stirring tank reactor, from which a continuous outlet flow feeds the next unit operation, consisting of a fully continuous virus inactivation column. The last step of the process included polishing by flow-through chromatography and final concentration and buffer exchange obtained by ultrafiltration and diafiltration. The simulation first focused on each single step, to then consider the RTD of the integrated process.

The criticality assessed by the authors refers to the time-dependency of the RTD for the semicontinuous steps of the modelled process (whereas continuous steps are time-independent).

This is further complicated by the fact “each semicontinuous unit operation adds a periodic behavior to the product concentration profile, which leads to complex periodic behavior in the outlet of the process”.

The great common denominator is the parameter proposed in order to take into due account the time period of the semi-continuous steps, namely the time difference between elution peaks. A GCD of 2.29 hours was identified for the switching of the inlet flow to the next chromatographic column; this value was used to define batch size in comparison to a fixed arbitrary time (2 h). The same approach was also used to define outlet sections of the process and the resulting batches (also by pooling different outlet sections together to form a larger batch).

Based on different sectioning in the inlet, when we track the product profile after each unit operation, we see a chaotic pattern when using an arbitrary time of 2 h. However, when the inlets are sectioned based on the GCD of the period for semi-continuous unit operations, we see a predictable, constant periodic behavior in the outlets”, writes the authors.

According to Lali et al., the synchronisation of the semi-continuous unit operations to achieve the largest possible GCD or the smallest possible lower common multiple is the only requirement for this method to define the batch size; every multiple of the GCD can also be used. Authors provide some examples which may typically occur during the management of a CM process and suggest a possible procedure for the implementation of batch definition based on GCD.