Enhancing Drug Development Possibilities with Artificial Intelligence
The Bio AI Clinical Prediction Platform is a joint venture between pharma companies and artificial intelligence. It helps to determine which drug candidates work well in humans and for whom.
“Currently, drugs have been developed and tested in mice for their suitability for human use. Dr. Isaac Bentwich of Quris, founder and CEO, said BioSpace, “Mice are terrible predictors.” “89% of drug candidates in today’s market fail to pass clinical trial and in vitro testing. When you stop and consider it, 89% of drug candidates fail.
Biotechnology Innovation Organization released a report on Clinical Develop Success Rates. The report, which analyzes 12,728 regulatory and clinical phase transitions between 9,704 program development programs between 2011 to 2020, contains additional information. The likelihood of approval of developmental candidates was 7.9% according to these analyses.
Bentwich presented a creative analogy of the issue. It was about a person who desired to build a skyscraper. “They would tell them, ‘You’ve come to a good place. We are the best. Here’s how we do it: 10 skyscrapers will be planned for you. We can guarantee that nine will fall. “We do not know which.” That’s, as facetious as it might sound, is actually the economics behind the pharma industry today.
Bentwich is an aspiring medical doctor and has shared his unique journey from school to the profession. “I was just finishing medical school when I started to experiment with computerized medical information and decision support systems. It became a hobby. It was either that or pottery. After a year of being unable to continue my medical career, it became a ten years-long stint creating a computerized health record that was very successful.” He also founded three other companies related AI, computing, medicine, and biology before establishing Quris.
The company’s platform incorporates three pillars: stem cells technology, AI and what they call Patientss-on-aChip. The technology can be used to create miniature human organs such as a small liver and brain. Each miniaturized organ has a size of one third of a meter, roughly equivalent to the tip of an ordinary sewing needle.
The cells of a person are used to create mini-organs. “Then, we use precision robotics as well as nanosensors to test thousands if known drugs on these miniaturized individuals with interconnected human miniature tissue. Nano sensing is used for assessing the feelings and effects of these patients.
AI has been trained by thousands of drug tests on Patients-on a-Chip to recognize which drugs are safe and which ones are toxic. The AI is able to distinguish between the safer and toxic drugs by comparing them to a new drug. Bentwich said that, “importantly, it not only gives us a readout about the level of safety but it also shows for whom the drug can be used safely.” This is a way to find out if drug X is good for someone and not for someone else.
Their interconnectedness is a distinctive feature of the miniature-organs. Bentwich described Bentwich’s first version of this platform. It included the liver and brain as well as the blood-brain boundary. This allowed the company not only to record data about the drug’s processing in the liver but also the effects on the blood-brain barrier.
“When we tested the drug on our system we actually let it metabolize it. The drug is still metabolized by the tiny, tiny liver that lives in a tiny well. It does the same thing as the human liver, which breaks down different chemicals.” he explained. “Then, it passes the blood-brain border, which mimics its behavior and allows certain molecules to get into the brain. It then interacts and learns from the miniaturized brain.” This data is used to train AI.
Bio-AI is unique because it isn’t limited to sorting through random medical data. Instead, it is trained directly in response of known drugs being tested via Patients-on a-Chip. The platform makes informed predictions regarding drug safety and patient suitability using more specific data.
A Potential Cure for Fragile X Syndrome
The company is in the process of developing its first drug against Fractile X Syndrome. This is a genetic disorder that causes developmental delays and learning difficulties.
Bentwich explained to Quris that Quris focused on the syndrome because it was impossible to mimic in an animal model. It makes drug development challenging. The Bio-AI platform of Quris was combined with Professor Eyal Bevenisti of the Hebrew University of Jerusalem’s discovery to create the drug.
“The beauty of the drug we’re developing, is that if it succeeds it will be the very first drug that attempts to cure the disease. It seems to treat the root causes of the disease. Not just symptoms,” he stated. The drug aims at addressing the disturbance of fragile-X’s mental retardation protein ( FMRP) due to a faulty FMR1 genetic in Fragile X syndrome.
Bentwich shared that initial studies proved that it could indeed reverse the inhibition of this faulty genetic gene. He shared that if the trial is successful, it could be a breakthrough for many patients. Clinical testing of the drug will commence within the next twelve months.
Redefining Nonclinical Testing
This bill was passed by the United States House of Representatives to amend Federal Food, Drug, and Cosmetic Act. Alternatives to animal testing can now be used in drug evaluation. Such test could include cell-based assays, computer modeling, and organ chips.
Bentwich stated, “A revolution is taking place” and Quris was at the heart of it. “We believe that using new combinations of Patients on a Chip together with powerful AI we can replace obsolete and ineffective mice experimentation, or at the very least reduce them.”
He pointed out how technology can be used in order to speed up the drug development process. “A vaccine that typically takes 10 to fifteen years to develop was developed in less than a year using cutting-edge technology like Moderna’s COVID vaccine. Quris is now using this technology in drug discovery.”
Bentwich sees a future where drugs are tailored to individual needs and not to the masses. “We cut down the time it takes for a drug to be developed. We are hoping it ignites a revolution for drug development by making drugs faster, more affordable, and better personalized.
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