As a doctor, I’ve grown increasingly frustrated with how big pharma and the medical system approach patient care—focusing more on symptom management than real healing. But it wasn’t until I tore my ACL that I truly saw the gaps firsthand.
Like most people, I was told recovery would take months, maybe even surgery. Unsatisfied, I started digging deeper, researching alternative solutions. That’s when I stumbled upon peptides (BPC-157). I decided to try it, and within a month, I had nearly regained full function of my knee.
That experience changed everything for me. If powerful, science-backed solutions like peptides exist, why aren’t they more accessible? Why are people left in the dark?
So I built PeptideHub — (https://t.co/gYLsXIlO9n) — a platform where people can share their experiences, n=1 research, and real-world results in tackling injuries, chronic conditions, and athletic performance.
This isn’t just about peptides; it’s about giving people the knowledge to take control of their health—something the system doesn’t always encourage.
If you’ve ever felt like there’s more to healing than what you’re being told, I invite you to check it out. Let’s build a community where we can learn, share, and take back our health together.
also any advice from you guys would be greatly appreciated, im not a programmer but with the help of LLM's and other AI models creating this dream project has been easier than ever before.
Creatine was first known for its MSK benefits, but newer research has uncovered its neurological effects too.
BPC could follow the same path.
A few takeaways from @AbudBakri’s episode with @hubermanlab.
Until now, physicians using AI in clinic had to assemble the patient’s context themselves. Allergies, comorbidities, medications, prior procedures, copy-pasted in from the chart.
Today we’re announcing a partnership with @CedarsSinai. OpenEvidence now works directly inside Epic, drawing on the patient’s full record and interpreting the medical literature through the lens of that specific patient.
Cedars-Sinai is the first academic health system to deploy patient-aware clinical intelligence at enterprise scale. The clinician asks a complex question in natural language. The answer reflects both the best available evidence and the patient in front of them.
Patient data is never stored after the clinical session or used for any other purpose.