FI-Asia 2019

AI ingredient: BASF studies anti-inflammatory effects of new peptides amongst Malaysian university athletes

By Tingmin Koe contact

- Last updated on GMT

BASF is working with researchers to find out the efficacy of PeptAlde in modulating inflammation in university soccer players. ©Getty Images
BASF is working with researchers to find out the efficacy of PeptAlde in modulating inflammation in university soccer players. ©Getty Images

Related tags: Basf, peptides, Malaysia

BASF is conducting a clinical trial amongst Malaysia’s university athletes with its peptide ingredient that was developed via artificial intelligence (AI).

The ingredient, known as PeptAlde, consists of several bioactive peptides cleaved from a long chain of brown rice protein. 

It is meant to support sports recovery by modulating the inflammatory markers and can be incorporated into chocolate bars and coffee shakes. The ingredient was developed via a partnership with Irish biotech start-up Nuritas.

Speaking to NutraIngredients-Asia ​at the Food Ingredients Asia show in Bangkok, Shawn Lee, marketing manager from BASF APAC’s Human Nutrition team, revealed that the firm was in the midst of validating its benefits via clinical trials.

The study involves researchers from the Universiti Teknologi MARA in Malaysia. Its purpose is to find out the efficacy of PeptAlde in modulating inflammation in university soccer players.

Earlier on, the firm also published a study in the scientific journal Food and Function, which showed that​ the ingredient may modulate inflammation markers.

Strong interest and future plans

First launched in Supplyside West last year, Lee said the firm had seen “very strong customer interest” ​in the ingredient.

“I think in all the regions, even in Europe, we have seen very strong customer interest, because number one, sports nutrition is obviously a very interesting area.

“Number two, when you talk about plant-based and natural products, it is obviously very interesting as well.

“Again, it is also about being the first peptide ingredient to be identified using AI technology…I think is something that will stand out from the crowd.”​ 

Moving forward, the firm will work with Nuritas to develop other ingredients using AI.

“So far, what we are working on is very promising, and the accuracy level and quality of what we put together is very good, that's why we are embarking on more.”

How it all started

The search for a new ingredient for promoting sports recovery led the firm to the use of AI.

Using AI, the firm scanned through a plethora of scientific studies recorded in the AI database.

The AI then picked up the relevant peptides and provided an explanation on the mechanism of actions.

This is in contrary to the traditional high throughput screening method, where different peptides need to go through lab test to find out their benefits.

“Using AI, we can first start with the biological context, which is to find the peptides relevant for sports recovery, and from there, the AI system is able to scan and analyse all the applications, pick the relevant ones and identify their mechanism of actions.

“The AI will run the model to understand which peptide will react with which biomarker, and how does it react to reduce or delay inflammation,” ​Lee said.

For the firm, AI has helped to identify peptides that aid sports recovery by modulating the relevant inflammation markers.

Specifically, the peptides modulate the secretion of a complex network of cytokines, one of which is the Tumour Necrosis Factor alpha.

Quicker and more accurate

A benefit of using AI is developing new products at a faster speed.

“Instead of putting hundreds of different peptides to a test as in the case of high throughput screening, how AI helps is that it provides a much more specific shortlist of peptides,”​ Lee said.

With the shortlist of peptides, the firm then conducts lab tests to validate the peptides’ efficacy in modulating inflammation markers.

“From there, we will still do our in-vitro lab test to check on how it really works, and this is a very important stage, because we need to validate the actual activity and find out if it works in the same way as what the AI model has predicted.”

Doing so has helped to cut short the NPD process to less than two years, he said.

“In our case, we spent about one to two years, which is really quite short, considering sometimes when you develop new ingredients, you have to do some of these breakthrough or innovative, it could be much longer, three, four or even five years.”

Why brown rice?

Brown rice was chosen as it is commonly available and is a widely accepted food source in Asia. 

“From the consumer surveys, we wanted [to cleave the peptides from] a known food source, so rice is obviously one of them, since it is one of the most widely consumed food source. It is also plant-based, and so I think that will meet the needs of consumers.

“In terms of being able to get stable, reliable quality supply, rice is also a good candidate.

“Again, AI is able to help, because it is able to tell you that a particular peptide is available in which sources, and from there, it also narrows down the food sources and speeds up our product development process.”

The peptides are then cleaved from the brown rice with the firm’s patented in-house technology.

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