Millions of animals are used in drug testing every year all around the world. It is a severe problem for two fundamental reasons- firstly, it is cruel towards animals, and Secondly, 89% of drugs fail on humans despite being successfully tested on these animals.

An Israel-based pharmaceutical startup, Quris claims to solve these problems with the world’s first automated Bio-AI platform that predicts which drug candidate will safely work in humans. It is yet another instance of revolutionary AI applications in the health sector.

Quris uses AI-powered miniatured “patients-on-a-chip” to develop drugs that eliminate the need for animal testing and costs associated with failed clinical trials. Backed by scientific pioneers and industry experts, the company has raised $9 million in the seed round led by Kobi Ritcher and Dr. Judith Ritcher, founders of Medinol, along with Moshe Yanai.

“Put simply: We are not mice, so what works in animal-based trials is not a proper indicator of what will work for people,”

Nobel Laureate Aaron Ciechanover explained about Quris’ Bio-AI.

“Using a breakthrough way to test drug candidates on miniaturized patients on chips, Quris can demonstrate their safety and efficacy, or lack thereof, through preliminary chip-based clinical trials.”

What is Quris’ Bio-AI Chip-on-Chip Platform?

Quris has developed a unique chip-on-chip platform that trains its AI engine to predict drug efficacy and safety through machine learning.

For this, the platform has 18 granted and pending patents that conduct automated testing of known and unknown drugs on multiple, miniaturized ‘patients on a chip’ that refers to systems simulating human organs on a micro-level. Quris’ Bio-AI platform comes with nano-sensors that monitor how the miniaturized organs respond to these drugs.

This data is collected and automatically classified to retrain machine learning continuously. As the AI keeps cataloging more data, it gets highly predictive at determining whether a drug candidate is safe for humans from a relatively lesser number of tests. 

To take the entire system to the next level, Quris has joined hands with New York Stem Cell Foundation to develop multiple ‘patients on a chip’ derived from hundreds of stem cells of diverse genomes. This allows the AI to train itself on a massive biological dataset that can be revolutionary in predicting the effect of drugs against broadly different genetic factors.

What can the Quris’ Bio-AI Platform mean for the Pharma Industry?

Determining drug candidates for clinical trials can cost companies hundreds of millions, and even then, the success rate of these drugs on humans is only about 10%.

Quris’ Bio-AI platform is a promising technology for ruling out several unsuitable drug candidates before they reach clinical trials. This development process can prove to be both time-saving and cost-effective for the pharma industry. 

“Say you’re a pharma company. Do you want to wait until you’re at the brink of going to clinical testing to find out whether a molecule that looks good on paper is effective? You can make all the genomics discoveries you want, but it won’t get you past mice experiments, where it fails 90% of the time. This lets you pick the winning horse before you go to the race.”

Isaac Bentwich, Founder and CEO of Quris, explained in an interview.

While the AI may not completely replace the traditional testing, it shows the capability to narrow down the entire process that can speed things up without the need for hundreds of mice during pre-clinical testing. 

As the first step towards Quris’ Bio-AI Clinical Prediction platform validation in the industry, the company has also announced the clinical test preparation for the first drug developed on its platform, targeting Fragile-X Syndrome, the most common inherited cause of intellectual disabilities and autism. 

Final Thoughts

From assisting surgeries to studying critical diseases, AI has evolved to be an integral part of the medical industry. But Quris CEO Bentwich mentions that one part that remains untouched is the drug discovery process.

Integrating NYSCF’s stem-cell automation technology and Quris’ AI-based clinical prediction, the Bio-AI platform can be used to monitor potential drug formulations on hundreds of genetically diverse, miniaturized ‘patients on a chip’ to determine their efficacy at a small fraction of the cost. 

This is not only revolutionary for pharma companies, saving them millions otherwise spent on inefficient pre-clinical testing but can also lead to more personalized medicines for humans.

As Bentwich said,

“If you think about it, it’s actually kind of barbaric how we’re living now. You go to the pharmacist, and they list the possible side effects, but you don’t know for sure. What, are you the guinea pig? The answer is: yes, we’re all guinea pigs. But this is a first step away from that.”