Nutraceutical and supplement companies now have a faster way to bring new products to market

Published: 23-Jul-2020

MedicascyAI uses artificial intelligence to predict, in just a few weeks, where ingredients will have significant impact, cutting R&D time by months or years while improving the product

Determining how specific plant-based molecules may benefit health, and identifying adverse side-effects, can require years and millions of dollars in research.

“Now artificial intelligence is accelerating this process while reducing costs and improving outcomes with more science behind it,” says computational biologist Jeffrey Skolnick, PhD, who has invested decades of his life developing an extensive library of algorithms. “Results come in weeks, not years, and are accompanied by carefully calibrated confidence indices (CIs).”

The $43 million MEDICASCY Artificial Intelligence Solutions Platform (MedicascyAI) will reduce the nutraceutical industry’s reliance on secondary science, and guide primary research toward more successful results.

MedicascyAI is scientifically proven, with documented results in more than 50 major peer-reviewed papers. This new and differentiated AI technology has been supported by the National Institutes of Health (NIH). By applying this technology, Skolnick and his science team have also been recognised by receiving awards through NIH.

“There is significant latent demand for non-drug solutions,” continues Skolnick, “but the dietary supplement industry’s pricing model doesn’t support the type of due diligence used by pharma. MedicascyAI speeds up certainty with less overall cost by using a set of sophisticated algorithms that analyse compounds for safety as well as efficacy in relation to the biological processes that jeopardise good health.”

“MedicascyAI can be used to create effective new products and identify potential new uses for existing branded products. It can also analyse current products for safety and efficacy. All we need is the chemical structure,” says efficacyAI Chairman and CEO Tony Bellezza, whose company is bringing this new and differentiated science to market.

“This is also an excellent starting point if you want to create a new product that focuses on a specific health benefit.”

MedicascyAI leads to more confidence and efficiency in your scientific development

MedicascyAI works by screening the interactions of molecules with every human protein. “A given molecule can interact with 58 different protein families. Some may do nothing. Some may be antagonistic and some may be helpful. Then we look at how those interactions may translate into potential benefits and side effects, as well as mode-of-action targets,” explains Skolnick.

Skolnick describes why this tool is useful as it has confidence indices, CIs, that predict the probability that the prediction is correct; these CIs have been extensively validated by subsequent experiments.

“We’ve already analysed 1475 GRAS molecules and approximately 300,000 natural compounds,” he explains, estimating that MedicascyAI’s algorithms cover about 97% of all proteins and make reliable predictions for about 40% of molecules found in natural products.

MedicascyAI can

  • predict what a molecule is good for. “It tells us when we may be right, which is about 70% of the time, and when we can ignore the predictions.”
  • suggest testing known supplements for other health benefits. “We have a high probability of accuracy in about 40% of these cases. With a minor investment, you may be able to repurpose your product for something you may not have considered.”
  • identify side-effects. “We are correct about 78% of the time in identifying the worst side-effects. And while we can’t say what percentage of people will suffer the worst side-effects, this tool will help you assess if the risk is appropriate to the benefit you’re trying to achieve.”

Skolnick added that another important benefit is that it doesn’t require all of the preliminary scientific experiments previously associated with AI. “MedicascyAI’s algorithm starts from the chemical structure and nothing else. Within a week or two, you’ll have an answer accompanied by the confidence index."

“The competition requires far more experimental information before making safety and effectiveness predictions (including targets, pathways, enzymes, transporters, side effects, genes and indications). Then, after you’ve invested all that time and money in the preliminary research, their algorithms can only predict yes or no.”

Skolnick concludes: “Using MedicascyAI is much faster and outperforms the competition. And although it may not cover the whole spectrum of natural ingredients, we can tell you with high confidence which items in a library will go after a specific benefit.”

Bellezza added: “The efficacyAI team has a tremendous passion for helping people.”

He stated: “Following our mantra and mission of, “We CARE About You … Your Health, Your Life & Your Knowledge,” we plan to use MedicascyAI’s analytical capabilities to accelerate life-changing solutions and to transform the way nutraceutical, supplement, pharmaceutical and medical cannabis companies develop their products.”

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