“To boldly go where no one has gone before…” (Star Trek)
If a project is worth the investment of a high throughput laboratory, it must have an important element of discovery, pushing away from the familiar into different spaces. But the simple facts of chemistry generate enormous numbers of combinations that quickly become a nightmare to manage.
There are 70,000 possible ternary combinations of the usable chemical elements. The pharmaceutical community has calculated that there are >1063 organic compounds that fit a basic description of “drug”. If we combine those and add concentration and process variables, we exceed the dimensions of the universe.
One of the critical intellectual tasks in the planning of a HT experiment is selection of a chemical space that is the right size. The team must first free itself from the “moth around the flame” trap. The high cost of experiments had confined them to timid excursions around a known (pretty good) system. Adding even a few variables would far exceed the budget.
It then must avoid the “boil the ocean” abyss of wanting to try all combinations of everything! In its initial enthusiasm a team will come up with dozens or hundreds of possibilities for each component in the system. This is good – but skillful pruning is needed to keep the run count within the capability of the HT system. This requires:
- Relevant Background Knowledge
- Team Participation
- Definition of an Experimental Space
- Selection of Materials
- Selection of Process Conditions
Relevant Background Knowledge:
What are the known theoretical relationships, practical knowledge, and results of previous experiments?
The purpose of this information is:
- To establish a context for the experiment and a clear understanding of what new knowledge can be gained.
- To motivate discussions about the relevant knowledge.
- To uncover experimental regions of particular interest – especially the new and untried – and regions that should be avoided.
No individual or even small group knows it all! Thus:
Every effort must be made to get maximum participation from all involved parties – the experimental team, management, and customers.
The flowdown exercises in Steps 1 and 2 are admirable places to begin to assemble the team.
Tools such as brainstorming, process mapping and Fishbone Diagrams are invaluable for sparking the discussion among the team on the possible root causes that need to be studied.
It is best to be radically inclusive, both of team members and of ideas, at this point. This is important because we are defining an entire experimental space.
The experimental space consists (in the abstract) of all combinations of factors (independent variables). They will be of various experimental types:
- Qualitative (type of material, technique, machine…)
- Quantitative Process factors (temperature, flow, concentration…)
- Quantitative formulation factors (adding up to a constant such as 100%)
- Permutations of substituents on chemical structures.
The possible number of combinations of these factors has no limit. The crux of the problem is selection of an experimental space that is the right size.
Finding the right size space is crucial because the desired outcome is identification of interactions – also known as synergy – also known as inventions! In several thousand runs you only have the ability to look for the interactions of a few dozen materials in each of three or four classes.
First, select the materials that will be studied. Materials can most easily be organized in sets or classes. Typical classes for different project types might include:
|Heterogeneous catalysts||Homogeneous catalysts||Copolymers|
|Primary catalytic elements||Primary catalytic elements||Site A monomers|
|Dopants||Organic co-catalysts||Site B Monomers|
In some cases, these classes may be quite limited, such as primary catalysts, which are often just some of the six platinum group metals. Dopants are a larger but still limited group, typically a dozen or two transition metals.
When we turn to organic compounds, however, the number of combinations explodes. Presumably, the chemistry team has a rough mental picture of the general type of molecules that will (for example) bind to the catalytic elements in a useful way.
Careful consideration by the chemist team is required to select enough candidates to explore the space moderately well. This typically begins with a scan of the commercial catalogs to find easily attainable candidates. From these materials, a table of quantitative or qualitative “descriptors” can be generated and then examined for gaps that might be filled by synthesis.
These sets of materials must then be combined in a mixture design, which must be repeated for each permutation of the materials classes. An example from a lipid drug delivery program shows that tens of thousands of possible runs quickly emerge. Interactions and “forbidden” regions complicate the calculation of possible points.
Finally, the physical process conditions must be considered as well. These should be selected to the absolute minimum and the design should be fractionated to the maximum extent reasonable, since all these choices multiply!
You now have a DOE strategy that
- Captures the factors that are relevant to the organization’s goals and objectives, and
- Contains the best understanding of all the team members as to which factors are important.
- Gives an (almost) overwhelming picture of the magnitude of what you’re trying to do!
In the next section, we’ll use this information to get a first estimate of the resources required.
If you want to jump right to the whole strategy, contact me at +1 413 822 5006 or firstname.lastname@example.org!