NextGen Medicine ...
- HanseaticHunter
- Feb 7, 2022
- 4 min read
... was touted much already 20 years ago after the deciphering of the human genome, but is now becoming reality
This is how Ronald Bailey, one of the best American science writers, began his book “Liberation Biology” (2005) with a family reunion end-21st century (1-page read):
A wonderful, yet naïve scenario? Maybe not.
In Bailey's own words: “This idyllic fantasy is more realistic, given reasonably expected breakthroughs and extensions of our knowledge of human, plant, and animal biology, and mastery of the techniques…”.
The following real life story also confirms this breakthrough: In 1996 at the age of 49, Doug O. of New Hampshire received the devastating diagnosis that he had chronic lymphocytic leukemia. At the time, survival time for this cancer was low. Twenty-two years later, Doug, at 71, was still running half-marathons and today at 75, he still leads a very active life. What happened? He endured and managed to survive the traditional chemotherapy, but was far from cured. Then in 2010, he was one of the early patients taking the experimental CAR-T cell therapy, a gene therapy that transforms some of the blood cells into cancer killer cells.
Nowadays, tens of thousands of patients are being treated with approved CAR-T cell therapies (initial approval in 2017). But challenges remain in both costs (often hundreds of thousands of dollars) and in significant side effects (immune overreaction).
Modern biotechnology has been around for decades (check out this excellent timeline: Timeline | An Introduction to Biotechnology (amgen.com)). In 1985, the first biopharmaceutical product was approved. Now, we have over 2,000 approved bio drugs and many times that number in development. However, the real revolution had its roots in 2001 when the complete human genome was decoded. This started the data revolution and the use of the term “nextgen” for next generation, as it moved from hardware to software and now on to medicine. The more abstract term “genetics” has morphed into the more apt term “personalized medicine”. The field of oncology has become a key beneficiary of this trend. 400 cancer drugs were in development in the US in 2005 and that number grew to over 1,100 in 2018. Over the last decade, no other category has grown as much in terms of approved drugs than cancer (Trends in FDA drug approvals over last 2 decades: An observational study (nih.gov)).
An early leader in biotechnology and the most valuable company in the sector, Amgen, summarizes the complexity with one simple picture: aspirin with its 21 atoms versus a human protein (erythropoietin) with 2,634 atoms:
Herein lies the challenge for the medical profession. Modern oncologists are facing information overload with ever more sophisticated diagnosis data, number of drugs, number of therapy plans, formulation of biologic treatment, etc.
This is where Moore’s law comes in. Gordon Moore, co-founder of Intel, posited back in 1975 that computing power would double every 2 years, which remarkably has quite nearly come true. We have probably all heard the comparison of the guidance system of the original successful moonshot, Apollo 11, with that of a current day washing machine (your smart phone is much, much more powerful). Present-day computing power allows not only for faster drug development, but also for better decision-making tools for the tech-savvy oncologist.
Survival rates have steadily improved as cancer care improves. The US National Cancer Institute calculates 5-year survival rates for all cancer types. Comparing the decade of the 1970s with the most recent decade, the 2010s, we can observe an overall improvement from 49% to 70% survival rate, with the most striking:
· Prostate 68% --> 98%
· Non-H. Lymphoma 46% --> 75%
· Leukemia 34% --> 66%
· Myeloma 25% --> 55%
Now comes the time to accelerate this further. Here, the current global health crisis acts as a twofold catalyst. First, much R&D gets accelerated (mRNA-based vaccines come directly from cancer therapy research), and second, weaknesses in the health system get exposed. The success of the public policy health response has been, to put it politely, mixed. Some countries did a decent job while others caused unnecessary hardship based on inaccurate data. A core problem causing the latter was the lack of digitalisation. Inversely, companies such as Moderna and BioNTech were able to formulate a vaccine within months. As a good rule-of-thumb, bureaucracies are slow, and small decentralized teams are fast.
Translating this back to the field on oncology, how can it be that even leading hospitals in Germany still use paper and faxes when discussing patients’ therapies in tumor conferences? There is still much potential for improvement as the average oncologist has not yet arrived in the 21st century, while the best are already working with artificial intelligence. It is high time for “nextgen oncology” or as the final paragraph of “Liberation Biology” reads:
“Nobody said the future would be risk free and the moral choices easy, but the future also brings wondrous new opportunities to cure disease, alleviate suffering, end hunger, and lengthen healthy lives. We would be less than human not to seize those opportunities.”
The HanseaticHunter
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