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Event Reviews: ABIM and SCS Formulate

By David Calvert, December 2024

I recently made a flying one-day visit to the Annual Biocontrol Industry Meeting (ABIM) which took place in Basel between 21st and 23rd October. The event is a great mix of conference, exhibition and facilitated meetings and this year welcomed 2040 participants from 67 countries.

The exhibition space was expanded to two floors this year and seemed to give more space for those important introductions and re-unions. It was great to meet up with many old colleagues and to make some new connections. The growth of the event shows how important the biocontrol market has become and formulation continues to play a role with a number of ingredient suppliers exhibiting for the first time.

“Natural” solutions continue to be welcomed by consumers, and this has become a regular feature at SCS Formulate, an annual exhibition organised by the Society of Cosmetic Scientists that took place this year in Coventry between 12th  and 13th  November. For the past few years, they have organised the Laura Marshall Memorial Award in two categories, one for Innovation in Sustainability and Ethics and the other for Innovation in Technology and Disruption. The three shortlisted in each category were all impressive. Beauty UnMASKED won the Sustainability and Ethics award for an over 99% natural, biodegradable, microplastic-free, dissolvable sheet mask formulation, composed of a cellulose gum film, that doesn’t dry out over time. The film has been developed to be active-infused and water-activated, thus not requiring a co-packaged essence. The mask dissolves in contact with water after use. The Technology and Disruption winner was Boost My Cycle, a 4-in-1 product that has been specifically designed around knowledge of the impact hormones can have on the skin. You can find more details of the winners and the other shortlisted products here.

Often at exhibitions there are very interesting talks given by suppliers but these are frequently difficult to follow due to background noise from the exhibition itself. At SCS Formulate I was impressed by the use of the “Silent Disco” headphones which was a new innovation to me and was certainly a significant improvement for all concerned. 

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Design for Formulation – Experimental Design

By David Calvert, October 2024

It has been a while since the last post on our approach to Design for Formulation but now we come back to an element that is common to all science projects, namely experimental design.

So, there can be many ways of approaching your design and in many cases you use a combination of these approaches (after all a formulator is not a robot, powered by AI!). We often talk about five approaches but in recent times a sixth has been developed, but more about that later. The first approach (we call it Trial and Error) involves a large amount of risk but is based often on experience in that a formulation worked well in the past and we start from there. This “bottle picking” can be successful but any advances are likely to just be incremental and not revolutionary.

The second approach moves up the scale and again relies upon experience but combines this with some rules of thumb, such as recommendations from a supplier, or an understanding of ingredients having worked previously with a chemically similar active ingredient. The next level of complexity involves Statistical Design of Experiments and this approach has been made much more accessible with software developments. Caution is still required and you should avoid using this as a “black box” and not giving findings some scrutiny. We have worked with clients where the noise from the test method has exceeded the relationship they were claiming. A good statistical design and analysis can help you to reach the global optimum formulation, however, and bring some radical understanding and changes. You can listen to an old webinar with more details on Statistical Design of Experiments on our web-site.

A modification of the rule of thumb approach is to make use of some theories and models that have tried to rationalise results. This could be the use of Hydrophilic Lipophilic Balance (HLB) to help with choice of surfactant or Stokes Law to improve stability of suspensions and emulsions. Another theory that we have found useful has been Hansen Solubility Parameters (HSP). We have a webinar recording on our web-site which explains more on HSP.

The most complex approach to implement is the use of fully predictive models for formulation. This “in silico” formulation has been investigated most in pharmaceuticals and can be costly although it can lead to the evaluation of more radical formulations.

It is impossible to discuss any topic these days without mentioning the use of artificial intelligence and as we have discussed a number of times, this is being looked at by formulators. An interesting approach using machine learning is being developed by Intellegens and their system can use sparse, noisy data to develop further experiments and optimise formulations. All of course still need the principles we have outlined in previous posts on Design for Formulation such as customer promise, critical attributes and risk assessment.

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Hidden Formulation – Same Actives, Different Formats

By David Calvert, August 2024

We always state that formulation plays a key role in almost every product and that a different format can lead to different applications and opportunities. Recently I came across a couple of examples where different formulation formats have been instrumental in the success of the same active and where different formats have been used for different applications.

So, I am a Type 2 diabetic and have been so for over 10 years now. At the start of the year, I was invited to take part in a clinical trial for a drug to control blood glucose levels where they wished to make an additional claim that it also reduced the risk of a heart attack or stroke. The trial involved taking a drug called “Semiglutide” in tablet format over a period of five years and then answering a series of questionnaires. Now some of you may recognise that active but until a friend said to me “Oh, that’s Ozempic®” I had not made the link to the weight loss drug which has been in the media a lot recently. Ozempic® and Wegovy® are both in injectable format that are injected weekly. There is a tablet version of semiglutide called Rybelsus®.

So why the different formats? Well, I guess one reason may be intellectual property and another will undoubtedly be the regulatory approval for the formats. Another could be the consumer needs and preference, which in drug use plays a large part in conformance. Tablets do not require the use of needles but can have side effects such as nausea and abdominal pain and often need to be taken on an empty stomach, or with food. Tablets also need to be able to withstand the acid environment of the stomach to get into the blood stream. Needles can have similar side effects but in the case of Ozempic® and Wegovy® only need to be administered once a week and have no issues regarding timing of food and drink. Formulators need to take all of these factors into consideration right at the start of the formulation design and we have written a number of articles on this design for formulation approach.

My experience with semiglutide got me thinking further about my medication for diabetes and then I discovered that a drug I had taken for a while called Gliclazide was described as a sulfonylurea. iFormulate carry out many projects in agrochemicals and sulfonylureas are a prominently used herbicide. Although sulfonylureas are water soluble, they are not hydrolytically stable. This has led to the development of the Oil Dispersion (OD) format, where particles are suspended in an oil, thus eliminating water until the product is mixed in the spray tank. So, a family of actives which require different formulations in order to be acceptable in the application.

These two simple examples demonstrate to me the value of formulation, and the formulator and show how a well-designed formulation can bring significant commercial success.   

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Formulation 4.0: Event Review

By Jim Bullock, August 2024

I recently attended Formulation 4.0 an event organised by the Formulation Science and Technology Group (FSTG) of the Royal Society of Chemistry which promised to continue “the story of bringing digital to all aspects of formulation”. There is no doubt that the use of automation and digitisation tools by formulators has grown rapidly in the last dozen years, with AI (artificial intelligence) coming to the fore more recently.

FSTG events are usually well-attended, varied and interesting and this was no exception with a nice balance of industry and academia amongst the attendees and speakers. All of the speakers did a fine job of presenting their areas of expertise, but for me the highlights were:

  • Sam Munday (Data Revival) who is using AI to tackle the perennial challenge of getting disparate (and often historic) data and information into digital systems so that it can be made better use of by scientists. Given that this information can include a wide variety of handwritten lab notebooks, chemical structures, numerical tables, graphs and publications, it was impressive to see the progress being made.
  • Roberto Hart-Villamil (University of Birmingham) who has built digital models of ploughshare mixers using CFD (computational fluid dynamics) and validated those models experimentally by tracking mixing behaviour using PEPT (positron emission particle tracking). So far so good, but the next step was for me the most interesting. An evolutionary algorithm was used to generate a set of new mixer geometries which were modelled, with the best design (i.e. that with the most efficient mixing) being selected to produce a further generation of geometries – and so on until an optimum was reached. Despite requiring a lot of computational power and some fancy hardware I think Darwin would have been intrigued with this example of “not-so-natural” selection.
  • Karen Ho (Gravel AI) who described a completely different approach with AI. She has taken a different approach to produce a tool for the personal care industry which can generate a commercial and technical analysis of the current market for formulations and ingredients as well being able to profile the activity of manufacturers. Clearly something which could be of great commercial value to many companies in the industry.

So congratulations to FSTG for highlighting this important area, I suspect that in a few years time, the way that many of us tackle formulation will be radically altered by these new approaches.

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Design for Formulation – Preliminary Risk Assessment

By David Calvert, June 2024

In our last post in this “Design for Formulation” series we discussed what should be done before you go into the laboratory, highlighting technical briefs and sources of previous knowledge. We ended by saying that a preliminary risk assessment should be carried out and here we briefly give an example.

Let’s take a look at a simple gel-based herbicide for consumer use. It has four components, the active ingredient, an adjuvant, a gelling agent (rheology modifier) and water. For the purposes of this example, the customer promise includes the statement “Will work in one application and 100% of the gel is applied to the weed.”.

From this we established that two of the critical quality attributes were the amount and quality of active applied in one dose and that all of the applied product must stay on the weed. An initial risk assessment would establish the role each of the four ingredients would play in delivering the critical quality attribute. The effect/risk would be simply graded “high”, “medium” or “low”.

For the critical quality attribute “Will work in one go”, we assessed that the active ingredient, adjuvant and water were all “high”, whereas the gelling agent would be “low”. What this means is that if something was wrong with the active ingredient or adjuvant, then the “risk” of not delivering on the customer promise was high. The water was deemed as “high” as it is known that the hardness of water can sometimes impact negatively on performance of some actives in herbicides.

For the critical quality attribute “Doesn’t flow off leaf” then we assessed that the gelling agent is deemed “high”, the adjuvant is “medium” and water and active are both “low”. The reason that the gelling agent is “high” is obvious as the primary function of including this is to establish the correct rheology profile. The reason behind the adjuvant being medium is that sometimes these may be a surfactant and that these can help/hinder with structure formation.

So, this preliminary risk assessment highlights the areas to investigate initially with the aim of establishing more quantitative detail on for example impurities in the active ingredient and ranges for acceptable levels of the active and gelling agent. They also serve as troubleshooting guides if in the future there are any issues with efficacy or rheology.

A similar risk assessment would be used to look at process parameters, which in this hypothetical case could be “dispensing”, “Blending”, “Addition of Gelling Agent” and “Packing/Filling”. In our assessment we deemed Dispensing and Addition of Gelling Agent to be high risk relating to “Will work in one go” and “Addition of Gelling Agent” to be high risk for “Doesn’t Flow off Leaf”.

Often risk assessments are presented in a tabular format and these are shown below:

So now we are ready to get to work and in the next post we will look at various approaches to designing experiments.

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Article: Agrochemical Formulators – You are Not Alone

By Dr David Calvert, iFormulate Ltd, April 2024

For the full article, see  AgroPages 2024 Formulation & Adjuvant Technology magazine and website pages.

Whilst there are many definitions of formulation science, one which is most applicable is “a  technology used to deliver an active ingredient safely and effectively to the right place at the right time″. Looking at this closely it is obvious that this applies to a large number of applications such as pharmaceuticals, inks, coatings, homecare, food, drink, cosmetics and of course agrochemicals. A skilled formulator will often look outside their own industry for solutions and in this article, we examine examples and opportunities where the agrochemical formulator could learn from other sectors.

To read the rest of this article go to AgroPages 2024 Formulation & Adjuvant Technology.

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Design for Formulation – Getting Started

By David Calvert, April 2024

Previously we made the case for a structured approach to “Design for Formulation” and looked at some of the important terms used in the process. Now we look at the important phase of work before you even go in the lab. We mentioned business and technical briefs previously but as these are the formal basis of deliverables and verification of success it is worth some time discussing their content.

It needs to be stated is that these should never be done in isolation by the technical team and that sales, marketing, regulatory and production should be involved. The business brief makes the business case for the project to go forward and would include elements such as market size, projected sales price and margins, competitive landscape, target customers, regions, resource requirements and sales projections. Once the business case has been accepted then the technical team can lead the definition of the technical brief.

From the Customer Promise, claims will be made and included in the technical brief. What is the shelf life and under what environments? What regulations apply to the product and the region where it is to be manufactured and sold? Based on margins and price, are there defined cost targets? Are there any manufacturing requirements/restraints? What type of packing/dosage mechanism is envisaged? Is there a competitive benchmark? What are the performance targets leading from this and are there any new tests that need to be developed? There will be many more elements in the final technical brief which should be quantified as far as possible and signed off by all.

At this stage it is then easy to rush off and start some work in the lab but the first thing you should do is… nothing! Well not quite, but you should start to look at what prior knowledge you have regarding the project. This will be internal looking at previous similar projects, considering what is different and how previous challenges were met. There will of course be internal experts and it is important to take these into account whilst still remembering that a previous project may have not been successful due to lack of materials, or different market conditions for example.

As mentioned in the technical brief, it may be worth looking at competitor products, literature and any patents. The latter can of course provide valuable background but also avoid potential infringement. Further external resource is obviously available from the internet and you may even want to ask some questions of artificial intelligence engines but as we have stated before you need to consider the quality of this information. The final source of the external information is from consultants and of course if you are looking for formulation consultants, then contact us and we may be able to help!

So now you can finally get on with some practical work? Well, not quite – and in the next article we will walk you through an example of a preliminary risk assessment.

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Design for Formulation – Demystifying the Language

By David Calvert, 19th March 2024

We have previously made the case for a structured approach to “Design for Formulation” and in this post we look at some of the important terms used in the process.

The whole process starts with a “Customer Promise”, namely what your customer expects from the product and what you promise to deliver. It may seem blindingly obvious, but we have seen in many instances that, when pressed, companies find it difficult to express in a succinct way what they are going to deliver. Developments are often driven by an internal technology development or a vague perception of what the market needs. At its best the customer promise can be expressed in one, maybe two sentences.

From the “Customer Promise”, business and technical briefs will be developed. We will say  more about those in the next article but these lead to definitions of what are the “Product Quality Attributes”. These are the properties of the final product that can be measured to determine that the product delivers on the “Customer Promise”. From these you start to define “Raw Material Attributes”, which are the properties of the raw material which are required to deliver the “Product Quality Attributes”. It is important to note that these are not necessarily measures you find on the raw material specification. As an example, the specification for the particle size of a powder may include a value for the D50, but you may find that the D10 or D90 are more relevant measures and could discuss this with your supplier.

The full list of these attributes may seem long and daunting and it is here that the “Risk Assessment” exercise is invaluable. This is not the typical risk assessment to decide whether a chemical is safe to use in the laboratory or in manufacturing but is an assessment of the consequences of what would happen to the product, and your promise, if you did not achieve the specific product or raw material attribute. Initially this assessment is based on “Prior Knowledge” (more of this in the next article) but as the process continues it is based on experimental or process data generated. By carrying out the risk assessment exercise, you develop an understanding of what is believed to be “Critical” and in your experiments you focus on quantifying this risk.

A similar exercise covers your formulation and manufacturing process and understanding the “Critical Process Parameters” which we will also cover in a future article.

In the next article, we will outline the five stages in the Design for Formulation process with a focus on the first stage “Getting Started” which is carried out before you even go into the lab. 

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The “Real IQ” and Validity of Artificial Intelligence (AI) for Formulators

By David Calvert 7th March 2024

The topic of AI and systems such as ChatGPT is much discussed and opinions on the validity and value of these approaches varies widely. At iFormulate, Jim Bullock recently gave a video presentation on how AI, Machine Learning (ML) and automation are being used in formulation development and we have even investigated ChatGPT .

A recent article in ChemEurope piqued our interest further when it discussed how to measure the actual value that AI-driven chemistry labs actually deliver by establishing some common metrics. Whilst the article focusses on researchers and chemistry, we think this has significant applicability to those working in the formulation space. The target of “producing trustworthy, reproducible results that make the most of AI programs that capitalize on the large, high-quality data sets produced by self-driving labs” made us reflect on some work we carried out a few years back on open data and how this could be applied to formulations. Whilst there was enthusiasm for using and compiling formulation data from a number of sources, there was considerable concern around quality of data used, and in particular how realistic it was to expect all research to use standardised test methods. Even for something as seemingly “straightforward” as particle size measurement, how could an open data set deal with different techniques? A measure for “stability”, which is still our most common consultancy request, presents more questions than answers.

We do not wish to be viewed as holding back new technology and becoming “luddites” with regard to AI. There are clear signs that using AI for internal data which is well controlled can bring significant benefits. Croda recently published an article how they are using AI to not only improve their formulation development but also reduce carbon footprint and assess business risk. There will no doubt be other examples of applying digital technologies to formulation at the RSC event, Formulation 4.0, in July of this year.

We do believe that AI will be a game changer but as with all new technology there must be some critical evaluation and there will still be room for “non-artificial intelligence” in formulation! 

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Design for Formulation – The Why

By David Calvert 6th March 2024

At iFormulate, we have long been proponents of a structured, yet flexible, approach to formulation which we have commonly called the “Design for Formulation” approach. This has been embraced by many of our clients and has formed a part of a number of customised training and workshop sessions. During these projects, we have taken clients through the approach with specific reference to their products (frequently with a Non-Disclosure Agreement in place).

Over the next few weeks, we thought it would be of value to go through the process and its different stages. Before delving into these, it is important to make the case for a structured process in the first place and that is the purpose of this first article.

In many mature organisations the development of formulations has taken an organic, evolutionary approach and often when you step back and take an objective view of the process the phrase “if I were you, I wouldn’t start there” can come to mind. Whilst this can lead to a successful development, there can often be issues such as:

·      A late product launch
·      High production costs
·      An unreliable process
·      Batch failures due to formulation not being robust
·      Inability to change manufacturing site or equipment
·      No flexibility in raw material suppliers
·      Loss of expertise and experience  

Whilst there is no guarantee that our preferred development process will eliminate all of these issues, it will minimise the risk of these occurring.

When outlining the process, we aim to remove some of the mystique and perceived bureaucracy of a well-structured approach. It cannot be denied that knowing what you did, why you did it and what the results were is not valuable and can be of significant benefit when starting new projects. Even with developments such as artificial intelligence (AI), there will always be the need for experience and subjecting decisions to some friendly scrutiny.

Through the next few weeks, we will expand on how to maximise benefits from the “Design for Formulation” approach and the next article will look at some of the terminology and how these help to drive the process  

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