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.
What is “Ask Dennis”?
One of the aspects of being in the E&L business that I have always enjoyed is having an open dialogue with other practioneers of this art and science. Although incremental progress is made on a local scale via individual effort and insight, breakout progress on an industry scale can only be made by the collaborative efforts of experts, across organizations, across disciplines and across interests. As the key to such collaboration is communication, opportunities to “get together and talk shop” should be surfaced, supported and encouraged by any means possible.
Often, communication starts with a question. A good question represents an opportunity for reflection, for debate, for introspection, for insight, for inspiration and for progress. People frequently ask me where the ideas for my publications come from. Well, the simple truth is they come from questions. When one hears the same question often enough, or when the question is intriguing or usual or “thought-provoking”, then the question requires an answer and is the catalyst for a dialogue.
With this in mind, I always imagined that Triad as an organization would provide a means of us keeping in touch. The only question was how to accomplish this. This is where “Ask Dennis” comes in. “Ask Dennis” is exactly that, an opportunity to ask me a general question. Now let’s be clear; “Ask Dennis” is not the means for asking definitive advice on specific situations or to address specific circumstances as there is a more appropriate means of securing that kind of service. Rather, “Ask Dennis” is a means for getting an opinion on topics of general interest to practioneers in the field. For example, a question such as “Dennis, this is my drug product formulation, what would you recommend I use as a simulating solvent and how could I justify your recommendation?” is not appropriate for “Ask Dennis” (but I would be glad to talk to you via another means). On the other hand, a more general question addressing the more general topic, such as “How does one establish and justify the pH of a simulating solvent?” is an appropriate submission to “Ask Dennis”.
Asking Dennis is accomplished by clicking on the appropriately labelled buttons, which opens the submission forms. Although submitters have the option to have their questions posted and answered anonymously, I will only take questions or comments from submitters who identify themselves to a minimum extent. In addition to providing the question or the comment, I ask submitters to provide enough context so that the motivation or reason for the question can be understood.
“Ask Dennis” questions are addressed at my discretion; thus, submitting a question or contribution is not a guarantee that the question will be answered or the contribution will be posted. If I decide not to answer a question or to post a comment, then I will provide the submitter, in confidence, an acknowledgement of this circumstance and a reason for my action.
Practically speaking, the frequency with which “Ask Dennis” is updated depends on the frequency with which appropriate submissions are received and my ability to provide an appropriate response. I will maintain an archive of all “Ask Dennis” items which have been posted on the Triad website.
Until then,
What’s on your mind?