The universe bows to those who dare, who push past the ordinary and chase what others deem impossible.
For too long, drug discovery has been chained by gatekeepers, rigid institutions, stale ideas, and a culture that shuns the bold. But the ground is shifting. The discussion isn't how AI is streamlining drug discovery, but what happens when researchers have ideas, that pharma or the company doesn't fund it- they can still finally test them. AI has democratized who gets to reimagine innovation and precision medicine.
At the end, big pharma already had AI to make remarkable drugs. However, the real revolution is the new leverage that comes to academic labs and start ups to fail fast, test new drugs and as a result create bolder drugs and medical device solutions. Pharma has had massive investment in discovery infrastructure and as a result of that we see bispecifics, binders to membrane proteins like ion channels, ATP or pH controlled antibodies, protacs, lytacs etc.
When a program of a specific modality is launched in pharma, they attack it from every angle. From high throughput screening, transgenic mice with human antibodies, medicinal chemistry and computational methods etc which is a testimony of that pharma always could make any drug possible should they come to commit to its modality.
For too long, drug discovery has been chained by gatekeepers, rigid institutions, stale ideas, and a culture that shuns the bold. But the ground is shifting. The discussion isn't how AI is streamlining drug discovery, but what happens when researchers have ideas, that pharma or the company doesn't fund it- they can still finally test them. AI has democratized who gets to reimagine innovation and precision medicine.
At the end, big pharma already had AI to make remarkable drugs. However, the real revolution is the new leverage that comes to academic labs and start ups to fail fast, test new drugs and as a result create bolder drugs and medical device solutions. Pharma has had massive investment in discovery infrastructure and as a result of that we see bispecifics, binders to membrane proteins like ion channels, ATP or pH controlled antibodies, protacs, lytacs etc.
When a program of a specific modality is launched in pharma, they attack it from every angle. From high throughput screening, transgenic mice with human antibodies, medicinal chemistry and computational methods etc which is a testimony of that pharma always could make any drug possible should they come to commit to its modality.
The Fall of Walls, the Rise of the Unorthodox
The realm of possible medicines is huge, stretching beyond the horizon. Yet, for decades, we’ve explored it cautiously. Most times, the tools were costly, the knowledge guarded, the gatekeepers would keep information. Only a privileged few could enter, and they played it safe, chasing small wins, rehashing old paths, avoiding the radical. The result? A pipeline of drugs that’s often safe, predictable, and uninspired.
Nearly 90% of drugs fail in clinical trials despite compelling preclinical data. AI doesn't accelerate manufacturing scale-up. It doesn't speed up the months of GLP toxicology studies. It doesn't shortcut the regulatory maze between a promising molecule and a first-in-human trial. The most elegant AI-designed protein still needs to navigate the same treacherous path from bench to bedside.
So what is the outcome of this wave of AI in our career? New tools, accessible to all, are tearing down the barriers that once locked out the curious. It is lowering the entry barrier and increasing the possible stakeholders at the table for the future of medicine. A lone thinker with a bold idea and a laptop can now step into the game. Usually this situation would amount to a maddening catch 22 for such stakeholders, where in order to provide an innovative solution one has to either sign a check or $200000 or pay royalty stacks to make a profitable business in healthcare.
Not a Shortcut, but a Springboard
This shift fundamentally rewrites the economics of early-stage drug development. One of the steepest value inflection points in any therapeutic program happens at pharmacologic proof of concept—that magical moment when you prove your hypothesis actually works in a living system.
Previously, reaching this milestone required either massive institutional resources or painful compromises. I've watched brilliant researchers shelve transformative ideas simply because they couldn't access the tools to test them. The gap between "compelling hypothesis" and "testable compound" was too wide to bridge.
Now? An academic lab can go from target identification to designed binders in days. A startup can iterate through multiple approaches for the cost of a single traditional screening campaign. Most crucially, they can walk into investor meetings not with PowerPoint promises but with IND-ready molecules less than a year from the clinic.
This isn't about competing with pharma on their terms. It's about changing the terms entirely.
The Future Belongs to the Fearless
The story of medicine is written in leaps like example of penicillin, vaccines, CRISPR. Each was a bold innovation, born from minds that broke the rules. But somewhere along the way, we traded leaps for caution, vision for safety. The cost? Millions still suffer from diseases we haven’t dared to cure, not for lack of tools, but for lack of courage.
That ends now. The fall of barriers is a call to the bold. It’s a summons to every dreamer, every rebel, every soul who sees the world not as it is, but as it could be. The best ideas for new medicines don’t come from boardrooms or ivory towers. They come from the edges, the margins, the places where the strange and the fearless collide.
AI literacy and data literacy makes The realms of possible cures boundless. The only limit is our willingness to chase it. I frequently wonder "What happens when anyone can make a drug?" Let me provide an answer. It means exponentially more attempts at genuine moonshots. A massive expansion of the therapeutic search space. When barrier-to-entry collapses, conformity collapses with it. Drug discovery is going to get weirder and that's exactly what medicine needs. AI won't make drugs 10x cheaper or deliver them 10x faster. It will make our drug pipeline 10x more innovative.
