3) In many cases clinical trial trends are driven by consumer data trends. At the point of sale where consumers make decisions based on their health concerns, has a backward flow to the decision makers on what type of research may be of most commercial benefit to an organisation. In the recent past we have seen a dramatic increase in Low mood, Stress, and anxiety studies across a broad array of product areas including probiotics and botanical extracts. Another area which has seen an increase in trial numbers is memory decline both self-reported memory loss and in early onset of dementia. We have even looked at patient cohorts in the early stages of Alzheimer’s disease.

8a) No, I feel that this type of technology can be very complimentary to some players in the supplement space. It, I feel, shines a light on companies who invest in their research and can show credible results to their consumer base. Wearable technology can serve to reinforce this message when consumers start to see and feel the results of a well-researched and well formulated product.

8b) Possibly yes, as they certainly are more focused on particular health areas, they choose their supplement regimes accordingly.

8c) While this is not directly applicable to our company, we certainly have developed a suite of apps and software to help our trial participants to track, monitor and report on certain clinical outcomes. This software makes participating in our studies easier, but also drives compliance among participants and allows for seamless continuous data collection.

9a) The term AI is recently thrown about in all manner of contexts and so for clarity let me offer a definition: Artificial intelligence can be defined as “a system’s ability to interpret external data correctly, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaption.” (1)
Artificial intelligence (AI), machine learning (ML) and natural language processing (NLP) in combination with other, more established technologies like robotic process automation (RPA) and business process management (BPM) are collectively referred to as Intelligent automation. 
At Atlantia we already use a lot of these tools in our everyday activities but I believe the question is more, are consumers willing to accept or believe data that has been generated through AI trials and the answer is that in some cases yes, they are. We offer 3 models, full clinic bases trials, hybrid clinic remote trials or full remote. Each design has its positives and negatives but on mass is balanced by cost speed and geographical reach. For safety trials, on site control is required and if clinical samples like blood or microbiomes are to be collected then clinic based is usually better. Having said that we offer a remote design for consumer type research where primarily questionnaires or apps are the central data source. These types of studies are highly suited for this AI driven model. 

9b) We are the CRO with AI capability.

9c) We have worked with pre-clinical partners that use algorithms to generate formulations that could be tested in humans for a particular indication. This type of large data analytics is much more commonplace and I believe we will see more and more of these types of service companies emerge as AI technology advances. 

9d) Then yes. Many tools already exist today that can hold track and analyse data in a trial combining all the very many functions that need to be performed across the lifespan of a clinical trial. As AI tech improves and the integration of data among sources improves (while maintaining data owner integrity) such as wearables, phones and the Internet of things(IoT) we will see much greater continuity in data and more Real World Data, informing future development of products.

For the production of 1 kg meat approx. 1 thousand times more water is needed than for 1 kg grain. And furthermore 60% of grain production in Germany is used for feeding cattle and pork.

The development of automated production equipment for tailor-made cultured meat using 3D bioprinting will help to feed the world (4).

The 3D bioprinting technology was developed by Professor Matsusaki of the Osaka University to create muscle tissue structures. This technology is expected to be utilized in the field of food, for production of cultured meat with controlled arrangement of muscle, fat, and blood vessels.

Most of the cultured meats reported so far have a minced structure consisting only of muscle cells, making it difficult to reproduce complex structures. To solve this problem, Matsusaki and co-workers developed a 3D bioprinting technology that uses 3D printing to produce different fibrous tissues (muscle, fat, and blood vessels) and integrates them into a bundle. This technology has made it possible not only to reproduce the famous Wagyu beef, but also to delicately adjust the fat and muscle components. Osaka University and Shimadzu will jointly develop equipment to automate the production of cultured meat using this technology. (5).

Bad experience in terms of taste and texture

Raw meat on its own has little aroma; therefore, almost all aromas associated with “meatiness” are created during the cooking process by the Maillard Reaction between amino acids and reducing sugars. That reaction determines which non-volatile precursors release volatile aroma compounds. Plant-based meat (PBM), products created to resemble animal meat in both look and taste, are growing in popularity. A plant protein such as soy protein concentrate, along with colors, stabilizers, and oils, is used to successfully mimic meat flavor and texture. And, just like in animal meat, the amino acids of that protein undergo the Maillard Reaction.

Samples of PBM were run with the solid phase microextraction GC-MS and the volatile profile was compared against that of the organic beef. Similar compounds, such as fatty acids and Maillard browning reaction products, were found in both types of meat (Figure 1).

The differences can be explained by the different and wide variety of precursors present in PBM since it contains amino acids and sugars from various sources as opposed to regular meat.

There are five basic tastes, including deliciousness, which are perceived by people. The amount and kind of amino acids contribute to taste components. Of all the amino acids, glutamic acid is widely known as a component of the delicious taste. Further, the types and component ratios of amino acids largely control the flavor of food products. For example, glycine and alanine are associated with sweetness, valine and leucine with bitterness, and aspartic acid and glutamic acid with deliciousness.

The texture of food, including the sense of crispness, springiness, firmness, and the feeling on the tongue, is an important element that together with taste has an impact on the deliciousness of food. Food texture is normally evaluated using sensory tests. However, sensory tests are often difficult to reproduce, due to individual differences in people’s sensations and physical condition.

A texture analyzer can support sensory test with objective results in the form of numerical values for use in the field of food development. The texture analyzer evaluates the texture characteristics and allows a comparison of the texture of plant-based meat (PBM) and, for instance, chicken meatballs. Compared to chicken-derived products, plant-based meatballs had a higher force under loading conditions with less elasticity, which is the property to restore deformation (6). It is consistent with the result of the sensory test.