AI drug discovery has attracted billions in investment over the last decade.
The thesis was straightforward: if AI can find better drug candidates faster, the economics of pharmaceutical R&D change permanently. That thesis has proven correct. AI-led discovery pipelines are now generating more candidates than the industry can develop.
That last part is worth paying attention to.
Having a candidate is not the same as having a drug. Every candidate still needs to clear preclinical studies, clinical trials, regulatory review, and real-world deployment. That process takes 12 to 15 years and costs between $1 billion and $2.6 billion per drug, regardless of how the candidate was found.
Discovery and validation move at very different speeds. AI has accelerated one. The other has not changed much.
Validation has always been the more expensive, more time-consuming part of drug development. And the coordination infrastructure that determines whether any of those candidates ever reach a patient, including the data rails, compliance frameworks, and clinical networks, has seen far less investment than the discovery side.
The validation gap is real. Whether it is a science problem, an infrastructure problem, or something in between is a question the industry is only beginning to ask seriously.
SURA SHYAMA SHARANA AAYE SAPHAL KIJE SEVA🚩
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JAI GANESH JAI GANESH JAI GANESH DEVA🚩. @grok
MATA JAKI PARVATI PITA MAHADEVA
Why Healthcare AI Needs a New Category of Infrastructure
In fintech, the infrastructure came before the applications.
Stripe did not build payments on top of the existing banking system. It rebuilt the rails. Once those rails existed, thousands of applications became possible that could not have been built before.
Healthcare AI is at the same inflection point.
The existing infrastructure, including CROs, hospital IT systems, and regulatory workflows, was built for a different era. It was designed for human coordination at human speed. It was not designed to move AI generated evidence through clinical validation at scale.
What the industry needs is not more point solutions. It needs a new coordination layer that is purpose built for regulated healthcare and designed to connect pharma, hospitals, labs, regulators, and patients around a shared set of rails.
When that layer exists, the cost and time required to develop and validate healthcare AI programs drop by an order of magnitude. Not because the science changed, but because the infrastructure finally caught up.
On Doctors' Day, greetings to our dedicated doctors, whose hard work, compassion and commitment form the backbone of India's healthcare system. Their tireless efforts, often in the most challenging circumstances, have earned the trust and gratitude of countless people.
Over the last decade, India has made significant strides in strengthening our healthcare ecosystem. The number of medical colleges has more than doubled, while undergraduate and postgraduate medical seats have expanded substantially. This unprecedented growth is creating greater opportunities for aspiring doctors, building a stronger healthcare workforce and ensuring that quality medical care reaches every corner of the country.
As we work towards building a Viksit Bharat, our doctors will continue to play a pivotal role in promoting preventive healthcare, advancing medical research, embracing innovation and delivering affordable, accessible healthcare for all.
#NationalDoctorsDay
AMAZING DARSHAN OF MAHABALI HANUMAN
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💮MAHABALI HANUMAN
@grok OM SURYA DEVAY NAMAH 🌞
@LifeNetwork_AI How can individuals actively contribute to and benefit from this coordinated AI ecosystem in managing their personal health journeys daily?
There ya have it.
This guy claims that money sent to Ukraine through USAID was funneled back to the DNC to be used to help Biden and other Democrats in their elections.
This is criminal and we want to see people go to prison for this.
This is what happens when young black men don’t have a father in the home.
Zero respect, and zero common sense.
Respect for authority used to be a thing.
We need to get back to that point.