Spring 2017 - Current Topic
FINDING THE GOOD IN GOOD SCIENCE
Note: This document expresses Dr. Jenke’s personal views and opinions and is not a position established and supported by Triad Scientific Solutions, LLC. This document is not professional advice and does not constitute a professional service provided by either Dr. Jenke or Triad Scientific Solutions.
When members of the E&L community gather to develop standards, guidelines and best demonstrated practice recommendations, there are three principles they should obey:
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The standards must be based on “good science”,
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The standards must be effective and efficient, and
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The standards must fit every conceivable circumstance well.
It is the inability to achieve these principles that makes the generation of standards, guidelines and recommendations so frustratingly challenging.
Consider the last principle, for example. It is intuitively obvious in a diverse field such as pharmaceuticals that this principle is impossible to achieve as it is clear that a rigorous standard (which is specified set of tests coupled to a specified set of acceptable test results) cannot fit all the diverse circumstances equally well. It is the same problem as trying to design a glove that fits every human being. If the underlying purpose of the glove is “to keep one’s hands warm”, then a standardized glove can be designed that will address this requirement, to some degree, for most people. However, because the glove must keep everybody’s hands warm, it is logical that there will be design tradeoffs which will mean that while it keeps everyone’s hands warm, it does not keep everyone’s hands as warm as they would personally like it. Furthermore, there may be other trade-offs, such as “these gloves are not very sexy”, or “these gloves do not match my coat” or “these gloves make my hands itch”.
While the challenges in making standards that are generally applicable in the greatest number of circumstances are considerable, this is not the point that I want to address in this discussion. Rather, I want to address the challenges associated with good science.
Good science suffers from with the same problem as designing a standardized glove. As good scientists, we learned and we understand that there are very few universal scientific truths; rather, a scientific truth is a truth only under the rigorously defined set of circumstances upon which it is based. When we perform an experiment and draw a conclusion from that experiment, we understand the conclusion is only perfectly valid for the set of defined experimental circumstances we started out with. Extension of that same conclusion to other circumstances involves a certain measure of risk, specifically the risk that in changing the circumstances we have invalidated (knowingly or unknowingly) some fundamental principle that defines the applicability of our conclusions. Thus, we understand that there is an inherent trade-off when we make scientific generalizations and put them into standards, guidances and recommendations. That is, we sacrifice some of the good in good science for the sake of providing a direction that is generally right in the greatest number of circumstances.
The challenge we face as practitioners of good science is not in recognizing good science per say but recognizing the boundaries that differentiate between good science properly applied and good science improperly applied. When we are tempted to use a standard, or leverage a “rule of thumb” or “do this because everybody else is doing it”, as good scientists we must ask ourselves “am I taking a good idea in certain circumstances and applying it to the wrong circumstances?”. If the answer is yes, then surely this is as bad as using “bad” science in the first place.
Let me illustrate this with an example. I use this as an example not because it a particularly bad practice but because it effectively illustrates my point. The following, taken from the PQRI OINDP Best Practice recommendations, is well known and commonly applied in the E&L community.
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The Working Group recommends that analytical uncertainty be evaluated in order to establish a Final AET for any technique/method used for detecting and identifying unknown extractables/leachables.
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The Working Group proposes and recommends that analytical uncertainty in the estimated AET be defined as one (1) standard deviation in an appropriately constituted and acquired Response Factor database OR a factor of 50% of the estimated AET, whichever is greater.
The question I would ask you to consider is “where is the good science and the not so good science in these recommendations?”
Here is my answer. It is well known that response factors will vary among the universe of compounds that could be extractables and leachables. Thus, it is good science that a general concept such as the AET, which presumably is applicable to all possible extractables/leachables, take this variation into account. Furthermore, we all understand that basing actions on relevant and sufficient data is the cornerstone of good science, and thus that the requirement to consider “an appropriately constituted and acquired Response Factor database” is a requirement to do good science. However, it must be obvious that the direction to universally “use a factor of 50%” is not necessarily good science. While the derivation of the 50% is itself good science, as it was based on a response factor database (which is somewhat small in the context of the databases available today), it is obvious that the 50% is only relevant for the compounds in that database and the analytical method with which the data was generated. Universal and unquestioned application of the factor of 2 rule to compounds that were not in the original database and to analytical methods other than the method used to generate the data is not the best science; rather, it is poor science, not because the science itself is bad but because the good science aspects are being applied out of context.
To a good scientist, arguments such as “it is better than nothing” or “everybody else is doing it” are inexcusable. Certainly, the idea that “it is better than nothing” has to be examined objectively and harshly. The improper application of science is not guaranteed to be better than doing nothing because it is not the case that the improper application of science will always make things better. In fact, the history of improper application of good science is littered with examples of bad outcomes derived from applying good sciences incorrectly.
Listen, nobody said doing good science was easy. We understand that part of the driving force for recommending that the factor of 2 be universally applied is that back then few people could access a database. Thus, it was nearly impossible to practice the good science required in the recommendation and people, rather than do nothing, gravitated to the other part of the recommendation. However, today, it is virtually impossible to run into a reputable E&L laboratory that is not eager to talk about their database. Thus, in this case, our ability to do good science has finally caught up with our responsibility to do good science. It is proper that we accept that responsibility and be held accountable for meeting that responsibility.
This is true not only to adjusting the AET for analytical uncertainty but in numerous other places where our current capabilities enable our ability and address our responsibility to practice and preach a higher degree of good science than has ever been possible. Currently applied recommendations, standards, guidelines and practices must be adjusted, as appropriate, to leverage this new and higher degree of good science and new recommendations, standards and guidelines must be drafted to reflect this new and higher degree of science. We aspire to better science because we are capable of better science. More importantly, if we are going to talk the talk, we best start walking the walk.
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May, 2026 – Current Topic
Note: This document expresses Dr. Jenke’s personal views and opinions and is not a position established and supported by Triad Scientific Solutions, LLC. This document is not professional advice and does not constitute a professional service provided by either Dr. Jenke or Triad Scientific Solutions.
We do too Many Extractables Studies!
To properly frame this discussion, consider the following scenario. Four drug companies, randomly referred to as Company’s A, B, C and D, develop and market aqueous, small volume, injectable drug products packaged in a stoppered glass vial. Perhaps not surprisingly, all four companies have selected the same stopper on the basis of “reduced extractables and leachables”.
The four companies differ somewhat in terms of what stage they are in product development, registration, and commercialization. Company A’s drug product is currently marketed, having successfully received regulatory approval based in part on a rigorous, comprehensive, and compliant extractables and leachables program. Alternatively, Companies B, C, and D are still in product development, and specifically are actively designing and developing their extractables and leachables programs. All three companies have adopted the overriding strategy that the surest and quickest path to regulatory approval is to adhere to the existing published guidelines and standards for performing extractables and leachables assessments. Thus, all three companies have accepted that performing both extractables and leachables studies is required.
Nevertheless, executives at all three companies (B, C, and D), faced with the timing and cost implications of performing extractables study(s), wonder about the need to perform such study(s). The stopper’s vendor, well-established in the pharmaceutical industry, has confirmed that the stopper complies with the relevant compendial monographs, is biocompatible (as established by the proper tests properly performed), and meets the requirements of relevant indirect food contact regulations. Furthermore, the stopper’s vendor can supply compositional statements that speak to the absence of intentionally added compounds of higher toxicological concern. Moreover, the stopper’s vendor notes the stopper’s “extensive use in pharmaceutical applications”, confirmed at least in part by the fact that Company A has a marketed drug product that uses the stopper.
All three companies ask the question “in light of this prior knowledge, is performing an extractables study really necessary or can I just go directly to leachables testing?”. As all three companies recognize that in order to perform a targeted leachables study, they require an extractables profile to select and justify the targeted compounds, all three companies elect to perform an extractables study. And lo and behold, the outcomes of the studies (three extractables profiles) are different (different extractables reported at different levels), which is not so surprising considering that:
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The extraction conditions and processes used likely differed, company to company,
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Even though the analytical technologies used by the three companies were the same, the test methods themselves were different (different analytical instruments, different operating parameters, different columns, etc.).
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The data processing and reporting methods used by the companies were different.
Thus, we end up with four companies, all of which have spent the time and money to perform extractables studies, with differing extractables profiles for the same item. Surely, this is not a desirable outcome in terms of time and cost efficiency and outcome consistency. But what other approach is a viable option?
One could argue that the most viable (and superior) approach is for the stopper’s vendor to perform an extractables study whose design and results are shared with not only all potential users of the stopper but also regulators who might receive submissions for drug products that use the stopper. Such an extractables profile, produced once, would provide users and regulators with a uniform resource which would likely drive a certain consistency in leachables studies (for example, the same targets).
Although such an approach applied to packaging is novel, it is not without precedent. In fact, both the USP and the BioPhorum organizations contemporaneously (but independently) have developed similar extractables approaches for characterizing and qualifying components used in the manufacturing of pharmaceutical drug products. For USP, the approach is captured in monographs <665>, Plastic Components and Systems used to Manufacture Pharmaceutical Drug Products and Biopharmaceutical Drug Substances, and <1665>, Characterization and Qualification of Plastic Components and Systems used to Manufacture Pharmaceutical Drug Products and Biopharmaceutical Drug Substances and Products. For BioPhorum, the approach is captured in its Best Practices Guide for Evaluating Leachables Risk from Polymeric Single-use Systems used in Biopharmaceutical Manufacturing.
Regardless of the originating organization, the approaches from both organizations provide instructions on how to risk assess manufacturing components with respect to extractables (or leachables) and on how to extract material components for the purpose of extractables profiling. Arguably, any drug product developer who claims that their drug product complies with the USP will have USP <665> testing results (and toxicological risk assessment) for all manufacturing components.
It is obvious (is it not?) that neither the BioPhorum Guide or the USP monographs would be adopted by the E&L community of practice (including drug companies and regulators) unless the proposed extraction instructions were considered to be relevant for, and reflective of, manufacturing operating conditions. The operational question facing both the USP and BioPhorum was how to make this so. The answer? BioPhorum surveyed its user community and secured the necessary prior knowledge to establish what manufacturing circumstances and conditions were being used by its user community. This information was shared with the USP. Armed with this prior knowledge, the technical teams at USP and BioPhorum established their Standard Extraction Protocols.
So what would this look like for packaging components and systems? Well, certainly the universe of pharmaceutical drug products would have to be sub-divided into dosage forms which share common characteristics (such as route of administration, physical form, frequency of use, dosage, etc) as surely a proper Standard Extraction Protocol for a canister used to package an inhaled drug product would be markedly different than the Protocol for a high-density polypropylene bottle used to package aqueous ophthalmic eye drops. Then, drug companies who develop or market drug products in each dosage form category would have to be surveyed to provide the prior knowledge (composition of the drug product, conditions of storage (temperature/duration, contact surface area, etc.) to build a design space for each dosage form. Lastly, an extraction process would need to be established for each dosage form that properly encompasses that design space, ultimately producing a Standard Extraction Protocol for each dosage form.
It is historically interesting, perhaps, to note that for manufacturing components, BioPhorum and the USP used the same prior knowledge to arrive at slightly different Standard Extraction Protocols. Oversimplified somewhat, BioPhorum developed a Standard Extraction Protocol (SEP) that covered, as much as possible, the entire design space for its various classes of manufacturing components, accomplished by using multiple solvents and several extraction temperatures and durations. All organizations marketing or using a particular component were directed to perform extractions with all the specified solvents and all the specified temperatures and durations for each component type. In this way the manufacturing processes for essentially all of the users fell within the design space. However, the “penalty” for such complete coverage of the universe of manufacturing circumstances was that some users performed unnecessary testing under unnecessarily soft or harsh conditions.
On the other hand, the USP developed a SEP that “aimed for the middle”, reasoning that most users would be covered using “middle of the road” extraction conditions and that it was only those few users who were operating at the extreme conditions who would need to perform more harsh testing.
It is not my intent in this discussion to propose a specific and detailed SEP for packaging. Nevertheless, I make the following points.
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I agree with the USP approach and suggest that the proper SEP would encompass the typical composition and storage conditions relevant to a majority of the drug products that are grouped into certain dosage forms.It makes more sense to me that most drug products are extracted using relevant and appropriately (but not excessively) conservative means and that only unusual drug products need more tailored (and likely more extreme) extractions.It makes less sense to me that all drug products within a dosage form would be tested by extreme measures that overly exaggerate the drug product’s composition and storage conditions.
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An important aspect of the SEP is that it provides an estimate of the worst-case leaching potential.It seems to me that this can be accomplished in one of two ways, depending on one’s interpretation of worst-case.If by worst-case one means that the entire pool of all ingredients (intentional and unintentional) is leached, then the SEP involves exhaustive extraction.However, if one means the more logical case of a drug product reaching equilibrium with its packaging, then the SEP is accomplished via an asymptotic extraction.
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The SEP may have difficulty reflecting extractables which exhibit unusual release rate profiles (e.g., release rate profiles that differ form a classical smooth approach to an asymptote).
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Given the wide variation in the chemical composition of drug products, the SEP must include multiple extraction solvents, differing in terms of polarity and pH, to fully encompass the universe of drug products that could be stored in a particular packaging system.
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The SEP must include non-solvent extractions when such extraction appropriately reflect the nature of the interaction between a drug product and the item of interest.For example, consider two circumstances where leachables can accumulate in a packaged drug product when no actual leaching has occurred.These are:
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Stopper-related substances accumulating in a vialed lyo cake where there is no physical contact between the cake and the stopper.
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Label-related substances accumulating in a liquid drug product stored in a flexible container to which the label has been affixed (on the outside of the container).
In both cases, leaching does not occur as the drug product and the item are not in direct physical contact. Rather, substances are outgassed from the item and absorbed by the drug product.
In such circumstances, logically and appropriately the source item is not extracted by a solvent to reveal potential leachables by rather is extracted thermally to reveal potential migrants.
If such a SEP (or SEPs, one for each relevant dosage form) were developed and accepted by the community of practice, if the SEP was executed by an item’s vendor using proper and effective methodologies and techniques, and if the vendor shared the resulting extractables profiles with all users, then such profiles could be used by users of the item to properly design and enable rigorous, efficient, effective, and compliant leachables studies. So doing would eliminate the current status quo of each users performing their own largely redundant extractables studies, significantly reducing the cost and duration of extractables and leachables programs, while improving their quality and reproducibility. Despite the challenges associated with the development and acceptance of the SEPs, I am convinced that SEPs can be developed and accepted and encourage the community of practice to accept and act on this challenge.