Primordial AI specializes in metabolic drug target discovery, leveraging data from evolutionary biology to identify and rank drug targets for various diseases.

Primordial AI

Primordial AI | 67 followers on LinkedIn. We are the world leaders in learning from evolution &amp; metabolism to solve human disease.  | Primordial AI uncovers, translates, and ranks Master Regulator Gene Drug Targets. https://primordialbio.com

Co-founder & CEO of Storyline (Precision Behavioral A.I.) Co-founder Primordial AI (Algorithms as Drugs) Champion of rogue ingenuity and underdog…

Jeff Barson

MDMA therapy crashed and burned at the FDA, but it didn’t have to. If your clinical trial results are still relying on self-reported mood scales, you might as well be using a Magic 8-Ball. Here’s what the FDA rejection of MDMA therapy is really telling us.

Storyline Health

Most cancer research focuses on the tumor cells and we are neglecting the patient experience. Drug companies make drugs aimed to kill cancer but these are often detrimental to the patient’s health and quality of life. This is a problem and an opportunity.

In the ever-evolving landscape of #pharmaceutical #innovation , a seismic shift is underway. The industry that brought us life-saving antibiotics and game-changing vaccines now faces a sobering reality: 90% of drugs fail in clinical trials, with the majority stumbling in Phase II and III due to lack of efficacy. Only 30% fail in Phase I for safety reasons. It's a wake-up call that echoes through every #pharma lab and boardroom. But here's the kicker: what if the key to unlocking unprecedented success in drug development has been hiding in plain sight for millions of years? Enter the concept of Master Regulator Genes (MRGs) - the holy grail of drug targets that could revolutionize how we approach disease treatment. Imagine a world where drugs don't just treat symptoms but address the root cause of multiple diseases simultaneously. A world where obesity, Alzheimer's, cancer, and a host of other conditions aren't separate battles, but part of a unified war we're finally equipped to win. This isn't science fiction; it's the near future. Note: We call them Primordial Genes. ; ) But here's the rub: finding these MRGs is like searching for a needle in a haystack the size of the Milky Way. Traditional approaches, including human GWAS data, have fallen short. It's as if we've been trying to solve a 3D puzzle with 2D tools. This is where the convergence of AI and evolutionary biology comes into play. By harnessing the power of machine learning and applying it to 100 million years of evolutionary data across hundreds of species, we're on the cusp of uncovering these elusive MRGs. It's like having Darwin, Turing, and Watson (the AI, not the DNA guy) team up to solve the ultimate biological riddle. The implications are staggering. Imagine drugs that work not just for a subset of patients but for nearly everyone. Treatments that don't just mask symptoms but fundamentally alter the course of diseases. We're talking about the potential to develop the blockbusters of blockbusters - drugs that could reshape the entire pharmaceutical landscape. But let's be clear: this isn't about replacing human ingenuity with artificial intelligence. It's about augmenting our capabilities, allowing us to see patterns and connections that have been invisible to us until now. It's about learning from the greatest teacher of all - evolution itself - to solve the most pressing health challenges of our time. The road ahead is long, and the challenges are significant. But for the first time, we have a map that could lead us to truly transformative medicine. The question isn't whether this approach will change the industry - it's how quickly we'll embrace this new frontier and who will lead the charge. One thing is clear: the future of medicine is about understanding the fundamental language of life itself. And for those willing to listen, evolution has quite a story to tell. Primordial AI uncovers, translates, and ranks Master Regulator Gene Drug Targets. https://primordialbio.com

In the world of pharma, small molecule patents reign supreme. These patents guard the unique molecular blueprints of new drugs, giving companies exclusive rights—a make-or-break advantage for getting treatments adopted clinically. But, let's talk price tags. Phase I trials clock in around $3.4 million, while Phase II and III ramp up to $8.6 million and a jaw-dropping $21.4 million, respectively. And here's the kicker: over 90% of these drugs don't even make it past the bouncer and into the market. Alert: That's a staggering $2.3 billion on average per approved drug to cover the losses from the failures. So, what's the problem? It's all about attracting big-league investors who want big-league returns. And those returns? They hinge on locking down those small molecule patents tight as a drum in the marketplace. The small molecule patent creates a monopoly so that pharma can recoup these costs with pricing power. But here's the twist: while these patents secure the financial fort, they inadvertently handcuff innovation by making the bill so big that only massive profits can offset the costs. These market forces mean that the current idea of 'Precision Medicine' will utterly fail in pharma because there is no way to target increasingly small patient populations with drugs that cost the same or more. Precision Pharma is not creating ever more targeted drugs, it is focusing on the patient and using existing drug effectively for that specific person. It's complex, convoluted, and requires new approaches that include technology beyond simple chemistry. but it's now here: https://primordialbio.com

Adopting agentic systems in drug discovery, leveraging multi-modal AI and evolutionary principles to iteratively refine and optimize the identification of high-value drug targets. #Agentic #DrugTargets #Pharma #PrecisionMedicine

Welcome to the most exciting and important drug development revolution since the genomics revolution began 35 years ago. Back in 2019, we dropped our first bombshell papers after a decade of grinding - showing clinically relevant traits including mutation and cancer resistance and revealing cis elements and genetic circuits regulating obesity. We knew it was pure gold, but we figured it’d take some time for the big brains to catch on. Surprise! VC-fueled startups couldn’t wait to jump on our science bandwagon. But we didn’t sit on our thumbs. As leaders in evolutionary genomics we were aware long ago that natural selection had evolved solutions for the same diseases many times in unrelated species, and that these solutions were key to human disease. For years, o scientists have delved into the genomic data of species evolution and human disease to uncover and understand novel gene pathways from hundreds of multi-omics datasets. We analyzed genomes and annotated biomedical phenotypes for hundreds of species, identifying gene-trait associations. Our functionally validated algorithms for drug target discovery and ranking present the first comprehensive genetic map for mammalian and human metabolic control. For the last five years, we've put our AI-driven drug discovery platform through the wringer with rigorous wet lab and knockout mouse validations. Tackling issues like metabolism, obesity, brain aging, and behavior, we've ensured our findings aren't just theoretical—they're the real deal. We've already discovered and ranked primary targets for major chronic human diseases, with proprietary metabolic, genetic and cellular recipes for disease recovery. We call them Primordial Pathways. We’re pumped to compete in the colossal mission of bringing way more effective drugs to the world, our functionally validated algorithms reveal the ultimate cheat sheet for drug discovery, straight from nature’s playbook. Let's roll.

Primordial AI utilizes evolutionary data and artificial intelligence to discover drug targets, focusing on achieving next-generation drug development.

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