The scene opens with a group of four musicians sitting on couches around a table in a studio. One of them is strumming aimlessly on his guitar, trying out various chords in sequences. Some of it sounds okay, even pleasant; other parts don’t work and are discarded.
Gradually, fragments of a vaguely familiar tune begin to emerge, scraps of a melody, but it’s not clear yet if this exercise will lead anywhere.
The lead musician begins adding a sing-song patter to his chords, mumbling something about a man named Jo-Jo, who apparently has a home in Tucson, Arizona. The chord changes gradually become more definitive, and a second guitar adds a recognizable riff, driving ever closer towards… something.
Then, over a period of just a few minutes, we hear it coalesce and take on the final shape of the song as we know it today. What we have just witnessed is the genesis of the classic Beatles’ tune “Get Back,” pulled from the air in the ultimate magic act of making something from nothing.
To my mind, the process of musical creation, as depicted in the recent film documentary “Get Back,” bears more than a passing resemblance to a lab meeting at its best: the whirling exchange of half-formed ideas; the false starts and dead ends; the trial balloons that float for a moment and are then deflated, only to be refilled and rise again; the reformulations and clarifying edits that push ideas along, remix, and meld them to their final form.
The process from notion to completion can take hours, days, months, years, or even whole careers.
Usually, the core group is small, Beatles-sized small, bringing in backing musicians as needed, maybe the scientific equivalent of a skilled keyboardist or a horn player, depending on the nature of the project. As in any creative enterprise that requires deep effort, relations between the teammates aren’t always harmonious, and personal issues must sometimes be worked through before meaningful progress can be made.
The melodies of the Beatles’ tunes are famously catchy and memorable, but it is the resolution of harmonies, the complex and often unexpected progressions from dissonance to consonance, that gives their greatest works their unique color and interest. This aspect is also true of scientific research.
We start with a dissonant observation, something that doesn’t quite fit—Why does our tailored drug not kill the targeted cancer cell? What triggers a dormant tumor cell to awaken after decades of slumber? How is it that metastatic cells home to one tissue and not another?—and we attempt to resolve it through a well-modulated series of experiments.
When it works, the process is beautiful to behold, a reminder of why one chose to become a scientist in the first place. When it fails, well, that can be instructive, too, and ideally leads to better ideas and more predictive models.
So, why doesn’t it happen more often? Why does research so often seem plodding rather than flying? Have we, the cancer research community, acting with the best of intentions, inadvertently engineered a system that discourages creativity?
One development that has sapped the creative spirit from cancer research is an overzealous faith in the power of large-scale collaboration.
The animating idea seems to be that greedy, egocentric scientists hoard precious data that properly belong to the public, and if only they could be compelled to share these taxpayer-funded findings, we’d get cancer cures more quickly.
There is a seductive, gut-level logic to this premise, as it simultaneously skewers diva-ish science superstars and explains why most metastatic tumors still can’t be cured despite a 50-year war on cancer. However, if collaboration were an unalloyed good, then adding the Rolling Stones to the Beatles would produce hot licks, when we know it would in fact produce a hot mess.
Put another way, for all the virtues of the 1980’s “We Are the World” supergroup, making great music was not among them. It may seem unsatisfying and counterintuitive, but even the most idealistic scientists are motivated at least in part by a zeal to compete, to reach an answer before one’s rivals, to be recognized as a rock star.
Getting elected to the National Academy of Sciences is akin to getting elected to the Rock & Roll Hall of Fame (and probably much easier, if we go by raw numbers), and for some researchers that is motivation enough.
But it is important to remember that the way to get famous in the cancer research world is by making discoveries that matter, a goal that perfectly aligns with the mission of the NCI and the interests of the public.
One might almost invoke a version of the invisible hand—investigators pursuing their own goals for their own reasons, within the limits of propriety and the law—as a guarantor of getting the best science at the least cost to the public. To paraphrase Adam Smith, it is not from the benevolence of the chemist, the gene jock, or the microscopist that we expect our cures, but from their regard to their own interest.
Team science isn’t inherently bad. In fact, cancer research has always been a team sport, and successful solo acts are exceedingly rare. It’s just that the size of the team matters, and bigger isn’t always better.
Many of the most remarkable discoveries have come from individual, sometimes quite small labs working alone or in small-scale collaborations. With genuine respect to NCI’s national RAS Initiative, whose work I greatly admire, the single most exciting idea for a RAS therapeutic emerged from Kevan Shokat’s group, a traditional (albeit HHMI-funded) academic laboratory. Similarly, gene editing methods, which might one day enable us to repair mutant cancer-driving genes, came out of a small number of what were then mid-sized laboratories that competed as much as they collaborated.
The process of musical creation, as depicted in the recent film documentary “Get Back,” bears more than a passing resemblance to a lab meeting at its best.
Team size and the need for collaborators will naturally be related to the job at hand. Methods to sequence DNA were discovered by Sanger and by Gilbert and their small groups in the mid- 1970s, but it took a veritable global village of collaborating academic groups, in ferocious rivalry with Venter’s private venture, to sequence the human genome.
A similar discovery-to-engineering arc describes the journey from the small-scale development of rocketry by Goddard in the 1920s to NASA’s massive efforts some forty years later—the literal moonshot—that serves, for better or worse, as the defining metaphor for President Biden’s recent efforts to speed cures for cancer.
But, if the fundamental work that underpins these advances usually comes from small teams, is there an optimal size?
In the business world, this issue has been much studied. We have, for example, the Bezos Rule, which states that any group that needs to be fed by more than two pizzas is too large to be effective.
Similarly, Brooks’ law declares that adding new team members to a late software project will make it even later. And then there is Price’s Law, which asserts that half the output of a team is produced by the square root of the number of its members.
The consensus of these and similar anecdotes and studies is that the optimal group size for research projects is about seven, plus or minus three. Luckily for scientists, this is just about the number of staff that a principal investigator can expect to fund with two R01 (or equivalent) grants.
As several of the NIH’s own reports have shown, once things exceed this size, communications become more difficult and the ‘bang for the buck’ starts to decline.
Barely a decade separated the Beatles of the Hamburg cellar clubs from the Beatles of the London rooftop session, and afterwards, the music they made alone was never as good as the music they had made together. It required a certain time and a certain place.
The creative process is a delicate thing, subject to special conditions that are hard to produce and, once lost, even harder to reproduce. Genius can’t be directed from above any more than a record company executive can order up a number-one single by fiat.
What is missing from academic cancer centers today is the equivalent of open session time for its researchers, where a lab group can occupy itself doing what it was meant to do and what it does best: testing the limits of knowledge, relatively free from distraction.
Is it too much to hope that we can get back to that era, or create a new one that adopts its best features?
