Is progress in medicine too slow?

In which I discuss why people with different backgrounds disagree on this question

After publishing my article "Why haven't biologists cured cancer?", I experienced firsthand the benefits of a diverse readership, as responses to my piece revealed a clear and interesting divide among readers. Those working in biotechnology were overwhelmingly more likely to disagree, in public and in private, with what they perceived to be one of the central premises of the article: that progress in medicine is too slow/ underwhelming. For example,

Elliot Hershberg

, a biology PhD student and investor, argued in a thoughtful post on X (formerly Twitter) that I had significantly underestimated the extent of medical progress.

On the other side were economists, tech professionals, and various other intellectually curious individuals not directly involved in biology. This group took an even more critical stance on the pace of biological progress than I had in my article. The public wants medicines and they want them faster. 

Different perspectives from biotech professionals vs intellectually curious non-biologists

So who is right here? Is progress in medicine too slow?

By its very nature, scientific progress does not lend itself easily to measurement and quantification, dominated as it is by what could be considered “Black Swan” events and being highly concentrated temporally and geographically. To even begin to address the question one has to decide upon an anchor point with which to compare. That’s what I did in my original article, which merely observed that we have fallen short of the explicitly stated expectations that we had set for ourselves more than 50 years ago in the War on Cancer.

It’s this difference in anchor points and subsequently, in expectations, that I think makes the biotechnologist, economist and the general smart person have different opinions on the issue. One could end the essay here and consider the matter settled, but I think there is much to understand from going through how these different classes of people experience medical progress. 

The biotechnology professional

---

Earlier this year, the prestigious medical journal Lancet announced the results from a Phase II trial of a new melanoma mRNA based cancer vaccine. Its purpose is to prevent cancer recurrence by stimulating the immune system to recognize cancer-specific antigens. The trial results were promising: 79% of patients receiving the mRNA therapy alongside standard treatment remained recurrence-free for at least 18 months, compared to 62% of those receiving standard-of-care alone. While this improvement might seem modest from afar, it represents a significant advancement for those who know what it took us to get here.

The idea behind mRNA therapies is simple: mRNAs is used naturally by cells as a template to produce proteins, through a process called translation. If you want to make more of a specific protein, just synthesize the desired mRNA in a lab and administer it to patients! It was in the late 80s that scientists first showed mRNAs coated in lipid particles and administered to cells in culture could be used to direct the production of proteins. But there was much to be done in order to actually turn this neat idea into a viable therapy in humans.

At the time, mRNA was both unstable and prone to triggering strong, potentially dangerous immune responses. A major breakthrough occurred in 2004 when Katalin Kariko and Drew Weissman developed a method to address the immune response issue by adding chemical modifications to mRNA molecules, making them less recognizable to the immune system. As always in science, cancer vaccines owe much to other areas that were developing in parallel to the core mRNA technology. For example, the genomics revolution and our understanding of cancer genomes means that we can now target vaccines to specific mutations in a patient. 

Chemically modified uridine is used to prevent the immune system from recognizing the exogenously administered mRNA molecule

As the academic science started to mature, start-ups looking to commercialize the findings emerged. The now famous Moderna launched in 2011 and benefitted from lavish investment: between 2011 and 2017 it raised 2 billion in venture capital funding, an enormous sum by biotech standards. Despite this, the company struggled, coming dangerously close to failure around 2017, when its most ambitious asset proved to be too unsafe for using in humans. Moderna was lucky in the end, but many other companies failed.

All this to say that for anyone in the know, cancer mRNA vaccines are nothing short of a miracle, the result of decades of effort and investment that could have failed at any point.

And mRNA vaccines are just the tip of the iceberg when it comes to cancer immunotherapy. The 79% versus 62% figure mentioned at the start of this section somewhat undersells the advances we have made in treating melanoma. The 62% survival rate is achieved by treatment with standard-of-care only, which at the moment is another type of immunotherapy called checkpoint inhibitor. Checkpoint inhibitors are also a recent advancement, with the first such therapy, ipilimumab, receiving approval in 2011. In a minority of melanoma cases (20%), checkpoint inhibitors alone achieve something that would have seemed impossible only two decades ago: complete remission even when treatment is discontinued. If we zoom in on a small subset of patients, we have actually managed to cure cancer!

I hope at this point it’s easier to understand why biotechnology professionals, embedded as they are in the details of their industry and knowing very well the challenges that have been overcome, view the progress we have made quite positively¹. Disease is stubborn and unyielding; it does not just shrivel before our impressive technical armamentarium, sweat and hundreds of millions of dollars. Instead, it gives away ground slowly, 17% at a time, if we’re lucky. 

The economist 

---

It’s easy for biologists to focus solely on the scientific details that led to the success of cancer vaccines. But someone has to pay for all this progress. It’s economists who are best placed to remind us of this. For them, each additional step in the development process represents not so much a fascinating new way in which we have tricked nature, but an added cost. And from that perspective, the complexity of creating a new therapy is simply bad news.

Of course, one can say that this is just how biology is: complicated. I largely agree and have made this very argument in my previous article. That being said, we are experiencing a decrease in pharmaceutical R&D efficiency compared to the past. So much so that pharmaceutical consultant Jack Scannell has coined the term “Eroom’s Law”, which is “Moore’s Law” spelled backwards, to (negatively) compare pharmaceutical innovation to progress in the microprocessor field. While the number of transistors in an integrated circuit doubles every 2 years, the number of new drugs approved by the FDA per billion US dollars (inflation-adjusted) spent on research and development (R&D) has halved roughly every 9 years.

Trends in R&D efficiency by number of drugs per billion US $ R&D spending

And no matter how you slice the cake, the results hold: we are spending more money and more human effort and the results are not commensurate to that, resulting in a relative decline in productivity when it comes to medical research, as argued by four economists in the “Are ideas getting harder to find?.”

Trends in research productivity in medical research

This trend extends beyond medicine and is part of a broader phenomenon in science, as discussed by Michael Nielsen and Patrick Collison in their “Science Is Getting Less Bang for Its Buck” article in The Atlantic.

But all this is not necessarily as bad as it sounds. Imagine for example that we managed to extend a healthy human lifespan by 20 years, but the cost for that would be so high that it would show up as an overall decline in medical research productivity to an economist. In this scenario, one might be able to dismiss the buzzkill economist if the average person felt like biological progress was making tremendous advances in their life in absolute terms. So how much does medical progress impact the average person?

A layperson’s perspective

---

From this perspective, the question is even more difficult to answer. Although we have seen tremendous success in specific disease areas, the very high variability and complexity of biology means that these successes are non-uniform and do not always affect large parts of the population. Let’s consider cancer again. On one hand, we have managed to effectively cure certain cancers in a subset of patients, as seen in the 20% of patients with melanoma that experience complete remission after checkpoint inhibitor treatment. 

But, as this article from Our World in Data shows, when we zoom out and look at how mortality from various cancers has improved in aggregate, the picture is not quite as impressive (NB: the plot below somewhat undersells the gains we have made for cancers which had low mortality to begin with– so I recommend visiting the article itself and scrolling through the actual values.) And it is the aggregate data that most closely reflects what the average person is actually experiencing when it comes to medical progress. A cancer diagnosis is still a much dreaded outcome that veers a bit too closely to death to most people and their families. 

Aggregating all the data, the article shows that the age-standardized cancer death rate has decreased by around 15% since 1980 and concludes: “Given the fact that cancer is one of the world’s largest health problems, a 15% improvement in 29 years does not represent roaring success. But it does show that the world is making slow progress against it.” 

This sentence from the article probably summarizes quite well the average opinion of the intellectually curious non-biologist when it comes to medical progress

But let’s move away from cancer: perhaps the biggest source of the feeling that progress is underwhelming is that we have not moved the needle on life expectancy too much.

Of course, life expectancy is affected by many things, which are not purely determined by medicine. But an increase in 6 years at age 65 and less than 15 at birth for more than 50 years of medical advances looks quite low, no matter what. It is particularly striking to consider this in contrast to how much life expectancy at birth increased between 1900 and 1970 (mostly due to our ability to fight infectious disease.) This was an era that was comparably much less scientifically advanced. For example, the discovery of the structure of DNA, widely heralded as the birth of modern molecular biology, only took place in 1953. 

The main culprit for this is that we have not meaningfully slowed down age-related decay. To put it very simply, people still get old, with significant drops in quality of life, at roughly the same rate that they have for decades. Sure, we can prolong the time one has at the end, and we have made great strides against childhood mortality and some rare diseases that affect young people (e.g. improving life expectancy for cystic fibrosis sufferers from 4 years in 1954 to 44 now), but that does not change the basic reality that biological progress has hit the wall of aging.

This limitation becomes more apparent when examining the changes in life expectancy at various ages over time, as illustrated by data from France. Since 1967, while life expectancy at birth has seen a notable increase of approximately 11.5 years, the gains diminish significantly when looking at older age groups. For instance, life expectancy at age 80 has only increased by about 4 years during the same period. Our ability to extend life has been most effective in the early and middle years, but we face much greater challenges in significantly prolonging life in the later years.

Even if one is among the lucky ones whose cancer can be cured by modern medicine, if they are old (as most cancer patients are), it is likely they will die of another disease in the not so distant future. This is the basic intuition beyond an analysis arguing that even if we were to completely cure cancer, we would only add around three years of lifespan on average. That is not to say curing cancer would not be worth it. Three years might not sound like much, but it’s 3.6% of a human life! What’s more, even if we were to make advances in longevity, we would still have to grapple with cancer, so figuring it out beforehand would certainly come in handy. Nonetheless, it’s important to realize there is a cap on how much we can achieve by focusing on traditional disease areas.

So am I saying all biologists should just drop whatever it is they are doing and start working on ageing?

The best argument against this comes from Nobel Prize winner Sydney Brenner’s quip: "Progress in science depends on new techniques, new discoveries and new ideas, probably in that order." Is is very likely that innovations in the field of longevity will not primarily come from those studying aging per se, but from better tools to manipulate biology (think of CRISPR/Cas9 genome engineering tools or AI applied to biology.) For example, one could make the case that our ability to fight COVID was primarily determined by advances in mRNA technology and less so by a more refined understanding of virology.

Besides this, I am generally skeptical of the idea that one can really predict where innovation is going to come from² and I generally favor “casting a wide net” as a strategy for how to approach funding science. This is opposed to a more “centralized decision making” strategy, whereby an authority decides on very specific topics that should be prioritized.

That being said, it does seem like aging is undervalued compared to its potential. My personal experience with the field is that it’s very popular among tech types but generates somewhat less interest in those working on biotechnology. There are several reasons for this. One is the significant risk involved, due to the lack of precedent for a therapy actually working (and conversely, precedent for spectacular failures.) Then, there is the lack of a regulatory pathway – at the moment, it’s unclear how one would even organize a clinical trial to quantify aging, although some progress is being made in this direction and the inherent difficulty and cost of testing how a compound might affect lifespan. The field also suffers from a “hype-and-bust” problem, whereby very early aging science that looks promising gets widely overhyped and overinvested in, often by people not very familiar with the biology. In the end the idea proves to have been too early to be translational, the venture fails, people get disappointed and the field gets a somewhat bad reputation in biology circles, creating a human capital problem. 

I think there is room to work on all these issues: a concerted effort from regulatory agencies like the FDA to establish a framework for how aging drugs could be considered. A push to apply the already existing biology techniques to aging specifically. And the list goes on, although a comprehensive consideration of what these steps would be goes beyond the scope of this essay.

Thanks to everyone who provided feedback on my previous essay, feedback that inspired this current piece. Including but not limited to Shahram Seyedin-Noor, Patrick Collison, Eryney Maroggi, Willy Chertman.

And thanks to Roots of Progress Fellowship for enabling me to write the current piece.

1. I think there is yet another reason why biologists are more optimistic than the average person: there is a growing feeling in the biotechnology community that we are finally reaping rewards of decades long efforts that had previously not yielded that much and that we are standing on the cusp of what Elliot Hershberg calls “the century of biology.” As an example, the idea of harnessing the immune system to fight cancer can be traced back to a century ago, but we have only been able to successfully do it in the last two decades. There is also hope that various technologies that are now coming of age will be able to function as part of positive feedback loops. The extent to which these will have an impact in the clinic remains to be seen in the coming decades.

2. It’s an interesting question in itself to quantify how much investing money on research in a specific disease leads to advances in that specific domain – I suspect the two are less correlated than one might expect. As far as I am aware this has not been formally studied (it’s one of the unanswered questions highlighted by Alex Telford in his blog.)