In the first of this two-part series, we explored why you may not need to simulate all ingredients in a formulation.
Expanding on the topic of “why”, our next step is to look at the benefits that arise from sharing simulations more widely in the R&D team. The digital R&D solution behind simulations has often been considered the domain of theoretical scientists. However, there’s a lot to be gained from putting this technology into the hands of scientists working in more practical roles.
So, why should a solution such as RheoCube be shared amongst a broader section of the R&D team. How will this contribute to deeper scientific understandings, and help to drive the success of product development efforts?
The key is to learn why formulations work – or don’t
Having engaged with over a dozen industry leaders, we’ve noticed that companies tend to have a few R&D people focusing their energies almost entirely, if not solely, into solving formulation problems. The budget just does not afford the luxury to look deeper.
With larger R&D companies, as more investment becomes available, the scope to delve into detail with the more fundamental part of science, investigating formulations and their challenges widens, and with that the development of a deeper understanding into the “why” of formulations (discovering why they do or don’t work.)
“The fundamental part of science is what we do with simulations here at RheoCube.
RheoCube could be likened to a long and complex mathematical equation that describes most of the relevant physics / laws of nature that are known to man, that are all happening on the fundamental scale.” – Jurjen van Rees, CCO at RheoCube
Merit van der Lee, Science Team Lead at RheoCube, has done the more day-to-day R&D operational work, and can relate to the practical and theoretical aspects of science. Having spent time on both sides of this fence, her experience is that the larger the corporation, the more freedom there is to pursue investigating the “why”.
Even if the budget exists to uncover these truths however, there’s often little time available to do so. Even in larger companies, Formulators may not have the time to look into the more fundamental aspects of formulating.
Simulations are not just for theoretical scientists
All R&D professionals should be pursuing and investigating the “why”. How then, can we entice the less theoretical scientists across the R&D board to embrace exploring the “why” in their day-to-day work? How can we get more practical scientists on board?
Investigating experimental formulations at this level takes time, and many companies cannot necessarily allow for such allocations of time when the pressure of solving the immediate problems is the focus of each day in terms of the bottom line.
However, there are crucial, long-term benefits to investigating the “why”, and rewards await those who dare to ask the right questions:
In the lab, for the most part, you cannot physically see the details of what is happening in the formulation experiment, and so cannot isolate the problem/s. in the wet lab. You need to simplify the experiment in order to figure out why something happens (to the best of your ability), through the trial-and-error process.
Simulations also require trial-and-error to an extent, but in a smart way, as your focus shifts from not being able to see the details, to scanning the space in detail. Your focus shifts deeper into learning and understanding the “why” of what is happening in order to get the right result/s, as opposed to being on the back foot of trying to figure something out. These learnings are permanent and transferable, and will save time (and costs) in the long-run when added up.
If you understand WHY a certain ingredient is not compatible with another, you will never waste time in using that combination of ingredients again.
For example, if in a formulation of 20 ingredients, the formulation didn’t work but you don’t know why, the entire formulation gets scrapped with no real insights into why it didn’t work (it could have just been one ingredient, or a slight shift in temperature that threw the formulation off – easily rectifiable factors/variables).
Why are companies not tapping into the benefits?
With these clear benefits, why then, are R&D companies (both large and small) still hesitant to broaden their use of a simulation tool such as RheoCube?
Could it stem from a need for validations, coupled with possible negative experiences with expert-oriented niche simulation tools? ?
“How can I get my formulators to tap into the benefits of a solution like RheoCube? How can I drive its use amongst a larger group of experts in our company, beyond those more interested in the theoretical side of science?”
Chemical experimental scientists may feel daunted by the notion of having to figure out yet another software application – how to install it, learning how it works and understanding its code, and all the other intricacies that can come with using a simulation tool such as this. Not forgetting the time factor involved in this sort of undertaking. Our own backgrounds and experience as experimental scientists lead us to suspect this is the case. Let’s explore this further…
Most of the tools used in wet labs are fine-tuned and set up specific to each experiment, to allow for some predictive capacity and the making of approximations, to get the right result. This experimental equipment also needs to be validated and calibrated.
Oftentimes, these lab instruments are linked up to legacy computer software programs that are unintuitive and very complex to use, making the work experience more cumbersome.
This, understandably, may be the reason for the resistance towards using more current, intuitive, and user-friendly simulation tools, such as RheoCube.
As with lab instruments, RheoCube also offers predictive capacity, within a range. It allows easy user-friendly access to R&D professionals that know nothing about simulation software, because it’s been developed to be fully accessible to all R&D specialists as a cloud-based platform (requiring no installation). Further to this, all RheoCube clients have access to our in-house Scientific Consultants (all science experts themselves) for support in how RheoCube works.
Just as one would need to make interpretations and approximations in the wet lab using instruments to measure with, so too will they need to be made using RheoCube. The environments are not that far apart. The difference is down to the simplified granular view of the experiment / formulation in RheoCube. It’s possible to simultaneously conduct the experiment whilst investigating the “why” from the get-go in order to deepen understanding and continue to build on an informed knowledge base, as a collaborative R&D team, for the future.
Overcoming the perceived barriers
How do we overcome the barrier then with R&D professionals’ challenging past experiences with older software? How do we get experimental scientists to trust in current software development and that RheoCube is different to legacy software?
Firstly, context. Previous software was built as an add-on to laboratory instruments, or on the simulation side, built with the assumption that a theory/simulation expert will be operating the software RheoCube was designed and developed first and foremost as a standalone simulation platform geared towards experimentalists, and thus runs with this inherent logic and workflow at its core.
RheoCube is also completely different to other simulation software tools available on the market, in that you don’t need to be a programming expert to be able to know how to use it. It’s been developed with a “plug-and-play” philosophy.
There is also nothing to break in RheoCube: in terms of the physics and how they’ve been built into the model: 30-40% of the time has been dedicated to implementing the physics as they come from academic research and our own in-house development; the remaining 50-60% has been dedicated to ensuring that these physics interplay with the rest of the model in a way that they don’t break.
RheoCube goes through rigorous testing of the limits of what users may input, to ensure simulations run properly even when these limits are tested. We work hard on minimising the chance of a user getting results that seem correct but aren’t. This happens frequently with a first-principles-tool for simulation experts, where the results still need to be interpreted by an expert. In RheoCube we’ve done all the groundwork upfront so that the results that come out are real within the realm of the approximations we use in the models.
Depending on the groups of chemistries being used in the experiment, and whether they fall within the ones we’ve validated and checked RheoCube’s software against, you may still need to check some basic ingredients and do a bit of calibration, as you’d do with your experimental equipment (for example, needing to do a calibration curve for your specific sets or realm).
95% of the professionals and industries RheoCube speaks to have never seen anything like RheoCube before.
What inputs are needed to run simulations?
What kind of information does RheoCube actually need then to be able to give the user the best test-trial experience from this platform?
If you know the average molecular structure, which is available on your datasheets, then RheoCube can give, at the least, an approximation of results especially on the molecular scale, and can also help calculate or measure HSP. The results might only be an approximation, but even the average of this can already provide insights to be able to sell the chemical.
The majority of the information we need to input in order for RheoCube to run a simulation of a formulation is readily available. Suppliers can also supply the materials datasheets needed as it’s mandatory for them to have these for shipping. If you have the information from your datasheets, it’s generally 2 minutes worth of work in RheoCube.
The time goes into finding the data.
As a scale-up and an agile company, RheoCube has the capability to allocate resources to support our longer-term clients with their logistical boundaries. Our in-house developers can help with inputting client’s digitised information into their RheoCube environment, without having to manually capture this data. You also wouldn’t need to input all your ingredients at once, RheoCube’s Scientific Consultants would help in identifying the key ones to start off with, and then you build your database up gradually. This all saves time and money across the board.
To conclude, consider the following:
The area of simulations in experimental science is still unexplored and ripe for further innovation;
By companies investing in software such as ours, they are future-proofing their own company in the R&D space, as the more data RheoCube adds into its model, the more companies will benefit from the broader range of ingredients to select from and the subsequent higher accuracy in results;
Running complex experiments in the lab can take months and is costly for the company. A simulation software tool like RhoCube takes a few days at most, and is far cheaper, giving you the same or better results.
Computer speed will augment enormously over the next 10 years, so while some simulation tools may currently take a few hours or a day to run, onboarding onto software such as RheoCube now, will pay off in dividends over the next few years as massive advancements are made in this area.
New market demands have increased the burden on R&D departments. Complexity has escalated and there’s a growing need to reformulate everything. At the same time, digital technology and computing power have evolved to a point where they can support R&D teams like never before. Simulations help us to overcome the challenges by allowing us to see the why. They offer that perfect complement to experimentation and theory as digital R&D becomes a key element of any product development exercise.
RheoCube offers both demos and a 3-month licence trial that’s risk-free. Why not give it a try?