Do We Have Clearance, Clarence?

By Dr. Scott Rudge

As in take offs and landings in civil aviation, the ability of a pharmaceutical manufacturing process to give clearance of impurities is vital to customer safety. It’s also important that clearance mechanism be clear, and not confused, as the conversation in the classic movie “Airplane!” surely was (and don’t call me Shirley).

There are two ways to demonstrate clearance of impurities.

The first is to track the actual impurity loads. That is, if an impurity comes into a purification step at 10%, and is reduced through that step to 1%, then the clearance would typically be called 1 log, or 10 fold.

The second is to spike impurities. This is typically done when an impurity is not detectable in the feed to the purification step, or when, even though detectable, it is thought desirable to demonstrate that even more of the impurity could be eliminated if need be.

The first method is very usable, but suffers from uneven loads. That is, batch to batch, the quantity and concentration of an impurity can vary considerably. And the capacity of most purification steps to remove impurities is based on quantity and concentration. Results from batch to batch can vary correspondingly. Typically, these results are averaged, but it would be better to plot them in a thermodynamic sense, with unit operation impurity load on the x-axis and efflux on the y-axis. The next figures give three of many possible outcomes of such a graph.

In the first case, there is proportionality between the load and the efflux. This would be the case if the capacity of the purification step was linearly related to the load. This is typically the case for absorbents, and adsorbents at low levels of impurity. In this case (and only this case, actually) does calculating log clearance apply across the range of possible loads. The example figure shows a constant clearance of 4.5 logs.

In the second case, the impurity saturates the purification medium. In this case, a maximum amount of impurity can be cleared, and no more. The closer to loading at just this capacity, the better the log removal looks. This would be the point where no impurity is found in the purification step effluent. All concentrations higher than this show increasing inefficiency in clearance.

In the third case, the impurity has a thermodynamic or kinetic limit in the step effluent. For example, it may have some limited solubility, and reaches that solubility in nearly all cases. The more impurity that is loaded, the more proportionally is cleared. There is always a constant amount of impurity recovered.

For these reasons, simply measuring the ratio of impurity in the load and effluent to a purification step is inadequate. This reasoning applies even more so to spiking studies, where the concentration of the impurity is made artificially high. In these cases, it is even more important to vary the concentration or mass of the impurity in the load, and to determine what the mechanism of clearance is (proportional, saturation or solubility).

Understanding the mechanism of clearance would be beneficial, in that it would allow the practitioner to make more accurate predictions of the effect of an unusual load of impurity. For example, in the unlikely event that a virus contaminates an upstream step in the manufacture of a biopharmaceutical, but the titer is lower than spiking studies had anticipated, if the virus is cleared by binding to a resin, and is below the saturation limit, it’s possible to make the argument that the clearance is much larger, perhaps complete. On the other hand, claims of log removal in a solubility limit situation can be misleading. The deck can be stacked by spiking extraordinary amounts of impurity. The reality may be that the impurity is always present at a level where it is fully soluble in the effluent, and is never actually cleared from the process.

Clearance studies are good and valuable, and help us to protect our customers, but as long as they are done as single points on the load/concentration curve, their results may be misleading. When the question comes, “Do we have clearance, Clarence?” we want to be ready to answer the call with clear and accurate information. Surely varying the concentration of the impurity to understand the nature of the clearance is a proper step beyond the single point testing that is common today.

And stop calling me Shirley.

Sizing Up Filters

By Dr. Scott Rudge

Of all the unit operations used in pharmaceutical manufacture, filtration is used the most frequently, by far. Filters are used on the air and the water that makes its way into the production suite. They are used on the buffers and chemical solutions that are used to feed the process. They are used to vent the tanks and reactors that the products are held and synthesized in. But the sizing of the filters is largely an afterthought in process design.

Liquid filters that will be used to remove an appreciable amount of solid must be sized with the aid of experimental data. Typically, a depth filter is used, or a filter that contains a filtration aid, such as diatomaceous earth. A depth filter is a filter in which there are no defined pores, rather, they are usually some kind of spun fiber, like polyethylene, that serves as a matt for capturing particulate. You probably did a depth filtration experiment in high school with glass wool. Or you’ve used a depth filter in your home aquarium with the gravel (under gravel filter) or an external filter pump (where the fibrous cartridge you install is a depth filter, such as the "blue bonded filter pads" shown below).

A depth filter uses both its fiber mesh to trap particles, but also then uses the bed of particles to capture more particles. It is actually the nature of the particles that controls most of the filtration properties of the process.

Because of the solids being deposited onto the filter, the resistance of the filter to flow increases as the volume that has been filtered increases. Therefore, knowing the exact size of filter that will be required for your application can be complicated. The complication is overcome by developing a specific solids resistance that is normalized to the volume that has been filtered, and the solids load in the slurry. Once this is done, these depth filters can be sized by measuring the volume filtered at constant pressure in a laboratory setting. The linearized equation for filtration volume is:

By measuring the volume filtered with time at constant pressure, the two filtration resistances can be found as the slope and intercept of a plot of t/(V/A) vs. (V/A). The area of a depth filter is the cross section of the flow path. On scale up, the depth of a depth filter is held constant, and this cross section is increased. An example of the laboratory data that should be taken, and the resulting plots, is shown below:

As expected, the filter starts to clog as more filtrate is filtered. The linearized plot gives a positive y-axis intercept and a positive slope, which can be used to calculate the resistance of the filter and the resistance of the solids cake on the filter.

The resistance of the filter should be a constant and independent of any changes in the feed stream. However, the specific cake resistance, α, will vary with the solids load. It is important to know the solids load in the representative sample(s) tested, and the variability in the solids load in manufacturing. The filter then should be sized for the highest load anticipated. This will result in the under-utilization of the filter area for most of the batches manufactured, but will reduce or eliminate the possibility that the filter will have to be changed mid-batch.

Of course, reducing variability in the feed stream will increase the efficiency of the filter utilization, and reduce waste in other ways, such as reducing variability in manufacturing time, reducing manufacturing investigations and defining labor costs.