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tmpacct19834
·قبل 4 سنوات·discuss
If you’re interested, I would recommend checking out the short film “Ala Kachuu - Take and Run”.

Can’t say if the film is an accurate portrayal, but it really angered me to imagine people having to experience this.

https://en.m.wikipedia.org/wiki/Ala_Kachuu_–_Take_and_Run
tmpacct19834
·قبل 4 سنوات·discuss
Your frustration with the pace of cancer research is valid and there is a long history of people sharing this sentiment. Since the start of the “War on Cancer”, scientists, clinicians, and patients have been torn between the sometimes opposing forces of knowledge and the urgent need for treatments. I recommend “the emperor of all maladies” by siddhartha mukherjee for a historical perspective on cancer.

However, the solutions are not as simple as you propose. There are a staggering number of experimental modalities used to investigate cancer. We sequence tens of thousands of tumors, many of which are available in public datasets. Digital pathology, single cell methods, spatial methods, etc. Large scale EHR management is a controversial issue in its own right, as is the question of breakthrough experimental therapies.

Cancer is just a very difficult problem with many facets.
tmpacct19834
·قبل 4 سنوات·discuss
PhD candidate in cancer bio, ~decade in biotech.

Cancer is an umbrella term for diseases with a shared feature: unchecked proliferation of cells. “Curing” cancer looks like developing effective therapies to mitigate this cell growth, and is usually specific to the mechanisms that led to this aberrant behavior.

Certain cancers share similar driving processes for their growth, or possess features that enable them to be specifically targeted and killed. Much of cancer research focuses on studying these mechanisms and tumor biology; some of this work is translated into drugs and therapies.

You can throw money at cancer and have no effect on the disease. But the biosciences are currently experiencing a bit of a technological renaissance, e.g. automation, labs as a service, massive reduced cost of sequencing, ai/ml.

I’d say large sums of money aren’t sufficient for effective cancer research, but they are necessary. Hopefully tech brings greater efficiency to the field.