Physics, biology and models: A view from 1993 and now

Twenty three years ago the computer scientist Danny Hillis wrote an essay titled "Why physicists like models, and why biologists should." The essay gently took biologists to task for not borrowing model-building tricks from the physicists' trade. Hillis's contention was that simplified models have been hugely successful in physics, from Newton to Einstein, and that biologists seem to have largely dismissed model building by invoking the knee-jerk reason that biological systems are far too complex.

There is a grain of truth in what Hillis says about biologists not adopting modeling and simulation to understand reality. While some of it probably is still a matter of training - most experimental biologists do not receive training in statistics and computer science as a formal part of their education - the real reasons probably have more to do with culture and philosophy. Historically too biology has always been a much more experimental science compared to physics; Carl Linnaeus was still classifying animals and plants while Isaac Newton was mathematizing all of classical mechanics. 

Hillis documents three reasons why biologists aren't quick to use models.

For various reasons, biologists who are willing to accept a living model as a source of insight are unwilling to apply the same criterion to a computational model. Some of the reasons for this are legitimate, others are not. For example, some fields of biology are so swamped with information that new sources of ideas are unwelcome. A Nobel Prize winning molecular biologist said to me recently, "There may be some good ideas there, but we don't really need any more good ideas right now." He might be right. 

A second reason for biologists' general lack of interest in computational models is that they are often expressed in mathematical terms. Because most mathematics is not very useful in biology, biologists have little reason to learn much beyond statistics and calculus. The result is that the time investment required for many biologists to understand what is going on in computational models is not worth the payoff. 

A third reason why biologists prefer living models is that all known life is related by common ancestry. Two living organisms may have many things in common that are beyond our ability to observe. Computational models are only similar by construction; life is similar by descent.

Many of these reasons still apply but have evolved for the better since 1993. The information glut has, if anything, increased in important fields of biology like genomics and neuroscience. Hillis did not live in the age of 'Big Data' but his observation precedes it. However data by itself should not preclude the infusion of modeling; if anything it should encourage it even more. Also, the idea that "most mathematics is not very useful in biology" pertains to the difficulty (or even impossibility) or writing down, say, a mathematical description of a cat. But you don't have to always go that far in order to use mathematics effectively. For instance ecologists have used simple differential equations to model the rise and fall of predator and prey populations, and systems biologists are now using similar equations to model the flux of nutrients, metabolites and chemical reactions in a cell. Mathematics is certainly more useful in biology now than what it was in 1993, and much of this resurgence has been enabled by the rise of high speed computing and better algorithms. 

The emergence of better computing also speaks to the difficulty in understanding computational models that Hillis talks about; to a large extent it has now mitigated this difficulty. When Hillis was writing, it took a supercomputer to perform the kind of calculation than you can now do on your laptop in a few hours. The advent of Moore's Law-enabled software and hardware has enormously enabled number-crunching in biology. The third objection - that living things are similar by descent rather than construction - is a trivial one in my opinion. If anything it makes the use of computational models even more important, since by comparing similarities across various species one can actually get insights into potential causal relationships between them. Another reason Hillis gives for biologists not embracing computation is because they are emotionally invested in living things rather than non-living material things. This is probably much less of a problem now, especially since computers are used commonly even by biologists to perform routine calculations like graphing.

While the problems responsible for biologists' lukewarm response to computational models are legitimate, Hillis then talks about why biologists should still borrow from the physicists' modeling toolkit. The basic reason is that by constructing a simple system with analogous behavior, models can capture the essential features of a more complex system: This is in fact the sine qua non of model building. The tricky part of course is in figuring out whether the simple features truly reproduce the behavior of the real world system. The funny thing about models however is that they simply need to be useful, so they need not correspond to any of our beliefs about real world systems. In fact, trying to incorporate too much reality into models can make them worse and less accurate.

A good example I know is this paper from Merck that correlated simple minimized energies of a set of HIV protease inhibitor drugs to their inhibition values (IC50s) against the enzyme. Now, nobody believes that the very simple force field underlying this calculation actually reproduces the complex interplay of protein, small molecules and solvent that takes place in the enzyme. But the point is that they don't care: as far as the model is predictive it's all good. Hillis though is making the point that models in physics have been more than just predictive, they have been explanatory. He extols biologists to move away from simple prediction, as useful as it might be, and towards explanation. 

I agree with this sentiment, especially since prediction alone can lead you down a beatific path in which you may get more and more divorced from reality. Something similar can happen especially in fields like machine learning, where combinations of abstract descriptors that defy real world interpretation are used merely because they are predictive. These kinds of models are very risky in the sense that you can't really figure out what went wrong if their break down; at that point you have a giant morass of descriptors and relationships to sort through, very few of which make any physical sense. This dilemma is true of biological models as a whole, so one needs to tread a fine line between keeping a model simple and descriptive and incorporating enough real world variables to make it scientifically sensible.

Later the article talks about models separating out the important variables from the trivial ones, and that's certainly true. He also talks about models being able to synthesize experimental variables into a seamless whole, and I think machine learning and multiparameter optimization in drug discovery for instance can achieve this kind of data fusion. There is a twist here though, since the kinds of emergent variables that are rampant in biology are not usually seen in physics. Thus, modeling in biology needs to account for the mechanisms underlying the generation of emergent phenomena. We are still not at the point where we can do this successfully, but we seem to be getting there. Finally, I also like to emphasize one very important utility of models: as negative filters. They can tell you what experiment not to do or what variable to ignore or what molecule not to make. That at the very least leads to a saving of time and resources.

The bottom line is that there is certainly more cause for biologists to embrace computational models than there was in 1993. And it should have nothing to do with physics envy.

Portrait of the human as a tangled bank: A review of "I Contain Multitudes: The Microbes Within Us and a Grander View of Life"

It’s time we became friends with microbes. And not just with them but with their very idea, because it’s likely going to be crucial to our lives on this planet and beyond. For a long time most humans have regarded bacteria as a nuisance. This is because we become aware of them only when something goes wrong, only when they cause diseases like tuberculosis and diarrhea. But as Ed Yong reveals in this sweeping, exciting tour of biology, ecology and medicine which is pregnant with possibility, the vast majority of microbes help us in ways which we cannot possibly fathom, which permeate not just our existence but that of every single other life form on our planet. The knowledge that this microbial universe is uncovering holds tantalizing clues to treating diseases, changing how we eat and live and potentially effecting a philosophical upheaval in our view of our relationship with each other and with the rest of life.

Yong’s book shines in three ways. Firstly it’s not just a book about the much heralded ‘microbiome’ – the densely populated and ubiquitous universe of bacteria which lives on and within us and which rivals our cells in terms of numbers – but it’s about the much larger universe of microbes in all its guises. Yong dispels many misconceptions, such as the blanket statements that bacteria are good or bad for us, or that antibiotics are always good or bad for us. His narrative sweeps over vast landscape, from the role of bacteria in the origins of life to their key functions in helping animals bond on the savannah, to new therapies that could emerge from understanding their roles in diseases like allergies and IBD. One fascinating subject which I think Yong could have touched on is the potential role of microbes in seeding extraterrestrial life.

The universal theme threading through the book is symbiosis: how bacteria and all other life forms function together, mostly peacefully but sometimes in a hostile manner. The first complex cell likely evolved when a primitive life form swallowed an ancient bacterium, and since this seminal event life on earth has never been the same. They are involved in literally every imaginable life process: gut bacteria break down food in mammals’ stomachs, nitrogen fixing bacteria construct the basic building blocks of life, others play critical roles in the water, carbon and oxygen cycle. Some enable insects, aphids and a variety of other animals to wage chemical warfare, yet others keep coral reefs fresh and stable. There’s even a species that can cause a sex change in wasps. Perhaps the most important ones are those which break down environmental chemicals as well as food into myriad interesting and far-ranging molecules affecting everything, from mate-finding to distinguishing friends from foes to nurturing babies’ immune systems through their ability to break down sugars in mother’s milk. This critical role that bacterial symbiosis plays in human disease, health and even behavior is probably the most fascinating aspect of human-bacteria co-existence, and one which is only now being gradually teased out. Yong’s central message is that the reason bacteria are so fully integrated into living beings is simple: we evolved in a sweltering, ubiquitous pool of them that was present and evolving billions of years before we arrived on the scene. Our relationship with them is thus complex and multifaceted, and as Yong demonstrates, has been forged through billions of years of messy and haphazard evolution. For one thing, this therefore makes any kind of simple generalization about them almost certainly false. And it makes us realize how humanity would rapidly become extinct in a world suddenly devoid of microbes.

Secondly, Yong is adept at painting vivid portraits of the men and women who are unraveling the secrets of the microbial universe. Old pioneers like Pasteur, Leeuwenhoek and Koch come alive in crisp portraits (for longer ones, I would recommend Paul DeKruif's captivating classic, "Microbe Hunters"). At the same time, new pioneers herald new visions. Yong crisscrosses the globe, from the San Diego Zoo to the coral reefs of Australia to the savannah, talking to adventurous researchers about wasps, aphids, hyenas, squid, pangolins, spiders, human infants and all the microbes that are intimately sharing their genes with these life forms. He is also a sure guide to the latest technology including gene sequencing that has revolutionized our understanding of these fascinating creatures (although I would have appreciated a longer discussion on the so-called CRISPR genetic technology that has recently taken the world by storm). Yong’s narrative makes it clear that innovative ideas come from the best researchers combining their acumen with the best technology. At the same time his sometimes-wondrous narrative is tempered with caution, and he makes it clear that the true implications of the findings emerging from the microbiome will take years and perhaps decades to unravel. The good news is that we're just getting started.

Thirdly, Yong delves deeply into the fascinating functions of bacteria in health and disease, and this involves diseases which go way beyond the familiar pandemics that have bedeviled humanity throughout its history. Antibiotics, antibiotic resistance and the marvelous process of horizontal gene transfer that allows bacteria to rapidly share genes and evolve all get a nod. Yong also leads us through the reasonable but still debated 'hygiene hypothesis' which lays blame for an increased prevalence of allergies and autoimmune disorders at the feet of overly and deliberately clean environments and suburban living. He discusses the novel practice of fecal transplants that promises to cure serious intestinal inflammation and ailments like IBD and Crohn’s disease, but is also wary about its unpredictable and unknown consequences. He also talks about the fascinating role that bacteria in newborn infants’ bodies play when they digest crucial sugars in mother’s milk and affect multiple functions of the developing baby’s body and brain. Unlike proteins and nucleic acids, sugars have been the poor cousins of biochemistry for a long time, and reading about their key role in microbial symbiosis warmed this chemist's heart. Finally and most tantalizingly, the book describes potential impacts that the body’s microbiome and its outside guests might have on animal and human behavior itself, leading to potential breakthrough treatments in psychiatry. The real implications of these roles will have to be unraveled through the patient, thoroughgoing process that is the mainstay of science, but there is little doubt that the arrows seem to be pointing in very promising directions.

“There is grandeur in this view of life”, Darwin said in his magnum opus “The Origin of Species”. And just how much grandeur there exactly is becomes apparent with the realization that Darwin was dimly aware at best of microbes and their seminal role in the origin and propagation of life. Darwin saw life as an 'entangled bank' full of wondrous species: I can only imagine that he would have been enthralled and stupefied by the vision of this entangled bank presented in Ed Yong's book.

Protein-protein interactions: Can't live without 'em, can't easily drug 'em

The many varieties of protein-protein interactions

Here's a pretty good survey of efforts to classify and drug protein-protein interaction (PPI) targets by a group from Cambridge University in Nature Review Drug Discovery. Most drug developers have been aware of the looming mountain of these ubiquitous interactions - there's at least 300,000 of them at last count and most likely many more - and have been trying to attack them in one way or another for more than a decade. There's also no doubt that many PPIs are involved in crucial ways in disease like cancer and inflammation. By any token PPIs are important.

As the review indicates though, attacking these interactions has been daunting to say the least. They present several challenges that seem to ask for both new scientific and institutional models of strategy. From the scientific standpoint PPIs present a nightmarish panoply of difficulties: proteins that change conformation when they comes together, water molecules that may or may not be involved in key interactions, the universal challenges of designing 'beyond rule of 5' drugs for such targets and the challenges of developing highly sensitive new biophysical techniques to detect ligand binding to begin with.

Consider protein flexibility, a factor which often is the nemesis of even 'regular', non PPI projects. Protein flexibility not only make crystallization hard and its results dicey, but it decidedly thwarts computational predictions, especially if the conformational changes are large. PPIs however regularly present cases in which the conformations of the unbound proteins are different from the bound ones, so at the very minimum you need crystal or NMR structures of both bound and unbound forms. This is even harder if one of the partners is a peptide, in which case it's likely going to undergo even more conformational changes when it binds to a protein target. The hardest case is two peptides such as Myc and Max, both of which are unstable and disordered by themselves, which stabilize only when they bind to each other. That's quite certainly an interaction forged in the fires of Mount Doom; good luck getting any kind of concrete structural data on that gem.

The screening challenges involved in studying PPIs are as if not harder than the structural challenges. NMR is probably the only technique that can reliably detect weak binding between proteins and ligands in as much of a 'natural' state as possible. although it presents its own difficulties like protein size and other technical challenges. SPR and FRET can help, but you are really testing the limits of these binding assays in such cases. Finding reliable, more or less universal methods that combine high throughput with good sensitivity has been an elusive goal, and most data we have on this front is anecdotal.

Finally, the medicinal chemistry challenges can never be underestimated, and that's where the institutional challenges also come in. In many PPI projects you are basically trying to approximate a giant block of protein or peptide by a small molecule with good pharmacological properties. In most cases this small molecule is likely going to fall outside the not-so-hallowed-anymore Lipinski Rule of 5 space. I should know something about this since I have worked in the area myself and can attest to the challenges of modeling large, greasy, floppy compounds. These molecules can cause havoc on multiple levels: by aggregating among themselves, by sticking non-specifically to other proteins and by causing weird conformational changes that can only be 'predicted' when observed (remember that old adage about the moon...). Not only do you need to discover new ways of discovering large PPI inhibitors that can make it across cell membranes and are not chewed up the moment they get into the body, but you also need new management structures that encourage the exploration of such target space (especially in applications like CNS drug discovery: in oncology, as happens depressingly often, you can get away with almost anything). If there's one thing harder than science, it's psychology.

In spite of these hurdles which are reflected in the sparse number of bonafide drugs that have emerged from PPI campaigns, the review talks about a number of successful pre-clinical PPI projects involving new modalities like stapled peptides, macrocycles and fragment-based screening that at the very least shine light on the unique properties of two or more proteins coming together. One of the more promising strategies is to find an amino acid residue in one partner of a PPI that acts like an 'anchor' and provides binding energy. There have been some successful efforts to approximate this anchor residue with a small molecule, although it's worth remembering that nature designed the rest of the native protein or peptide for a reason. 

Another point from the review which seems to me like it should be highlighted is the importance of academia in discovering more novel features of PPIs and their inhibitors. In a new field even the basics are not as well known, it seems logical to devote as many efforts to discovering the science as to applying it. At the very least we can bang our collective heads against the giant PPI wall and hope for some cracks to emerge.

DNA-encoded libraries: Bring me the drugs

There's a good overview of DNA-encoded libraries from Raphael Franzini and Cassie Randolph from Utah that's worth a look for anyone wanting to quickly bring themselves up to speed on this promising new technology. As the article indicates, the whole field of DNA-encoded libraries, characterized by several related but distinct methods, has come of age in the sense of being transformed from a technology platform development paradigm to a more or less reliable springboard for screening large numbers of novel chemical entities against challenging protein targets.

The field is not free of roadblocks, however. As the authors reveal, much of encoded library technology runs into the same problems as traditional combinatorial libraries, only some of the problems are worse. Foremost among these are the size and molecular weight of the resulting molecules. The basic framework of a DNA-encoded library consists of 2, 3, 4 or more building blocks (BBs) that are strung together, either linearly or in a branched manner or in the form of a macrocycle. The BBs can be mono, di, trifunctional etc. and this feature directly impacts their availability, number and price as well as the versatility of the resulting library. It's not hard to see that you are going to get a rapid, almost exponential explosion in molecular weight with the number of building blocks, especially if you add in linkers connecting them together. Many of the millions or even billions of compounds emerging from these campaigns therefore are large, floppy. The problem is especially glaring for macrocycles; while there are very distinct advantages to them, the one big disadvantage is that you cannot easily take out a building block from a macrocycle without impacting its structural integrity, even if that building block is found to be extraneous to binding the target. The good news on the other hand is that the ClogP stays within reasonable limits in most cases.

The article explores other properties and challenges of encoded library technology. While the very high throughput and low cost enabled by cheap DNA sequencing make these libraries attractive, they are also plagued by problems of side reactions and impurities more often than you would like. These problems affect both the potency of the resulting molecules as well as subtleties in SAR, both of which are issues which you don't really want to deal with and can spend days pursuing. In addition, one big drawback of this technology is that because the chemistry used in them has to be compatible with DNA, the reaction space is quite limited relative to the medicinal chemist's toolkit: there's not much beyond amide coupling and click chemistry that you can use. Making more reaction space compatible with these libraries is definitely a big area for development.

Nonetheless, the article explores several novel chemotypes for promising targets emerging from screening such libraries which have been optimized into nanomolar hits and leads. In some cases the novelty of the chemotypes compares favorably with HTS campaigns. My one big question about the chemical matter from these libraries, and one which the review does not address, is the quality of the leads in terms of pharmacokinetic properties, especially cell permeability and clearance. Generally speaking it's going to be very hard to get large and floppy molecules past the cell membranes (cyclosporine notwithstanding, which seems to be very much of an exception in terms of its unique properties). In addition for something like a polyamide library, I would be worried about stability and clearance. Something tells me that it's going to be relatively easy to get potent binders from these libraries, but it's going to be much harder to turn them into bonafide drugs with good pharmacological properties than it is for 'ordinary' druglike molecules.

Notwithstanding the limitations, it's definitely true that all kinds of DNA-encoded libraries have now reached a stage where both small and big companies wanting to find hits for novel targets on the cheap can seriously think of at least wanting to collaborate with companies like GSK which have been longstanding players in the field. I would think the same promise and criticism would apply to outfits like XChem and Peptidream which are also using novel technology for generating combinatorial libraries. While the occasional success from these libraries would be welcome, you hope that whatever failings the libraries have would almost certainly be revealed in the ruthless attrition that drug discovery routinely faces. It's both the promise and curse of complex biology.

What Oliver Sacks could teach us about the value of anecdotal information in drug discovery research

Oliver Sacks was a writer who elevated the art of anecdote to an art form. He did not write authoritative medical books filled with numbers, graphs and statistics. Instead he focused on individual cases and the human element in medicine. A 2015 Wired magazine profile of Sacks highlighted his signature achievement in resurrecting the value of anecdote in medical research.

By restoring narrative to a central place in the practice of medicine, Sacks has regrafted his profession to its roots. Before the science of medicine thought of itself as a science, at the crux of the healing arts was an exchange of stories. The patient related a confusing odyssey of symptoms to the doctor, who interpreted the tale and recast it as a course of treatment. The compiling of detailed case histories was considered an indispensable tool of physicians from the time of Hippocrates. It fell into disrepute in the 20th century, as lab tests replaced time-consuming observation, merely “anecdotal” evidence was dismissed in favor of generalizable data, and the house call was rendered quaintly obsolete. 

...By exiling the clinical anecdote to the margins of medical practice—to stories passed down in hallways from attending physician to resident—the culture of medicine had blinded itself, forgetting things it had once known. Sacks calls these knowledge gaps “scotomas,” the clinical term for blind spots or shadows in the field of vision. 

...Sacks immersed himself in the neglected anecdotal literature of migraine, feeling that every one of his patients “opened out into an entire encyclopedia of neurology.” 

By studying individual patients with unusual or bizarre neurological symptoms or personality changes, not only the infamous sleeping sickness in "Awakenings" but insomnia, migraines and Tourette's syndrome all revealed their intricacies under Sacks's skillful and empathetic dissection.

Sacks's explorations of anecdotal data were on my mind as I contemplated the pros and cons of anecdotal data in drug discovery, and especially in molecular modeling. It's a topic that is the subject of much discussion, and occasional pugnacious debate. One of the smartest people I know in the field often scorns individual stories of successes in modeling chemical and biological data. If you read about or listen to case studies in the field, you will often find scientists attributing success in a particular drug design study to a particular method, software algorithm or physicochemical factors like electrostatic effects or hydrophobic effects. 

My statistically enlightened colleague has a tendency to dismiss these individual stories: Where, he asks, are the comparisons, often with simpler techniques? Where are the controls? How do you know for certain that there is a causal relationship between a particular method or factor and the success of a particular drug design?

My colleague is absolutely right about the difficulty of extrapolating to causal explanations or general rules based on individual studies. Not a day passes when I don't hear the words "Method X worked for us" or "Method X failed abysmally for us". "Method X" could be a particular assay, chemical reagent, cell line or computational algorithm. The problem is when these statements are extrapolated to "Therefore Method X works" or "Method X does not work". The difference between "works for me" and simply "works" can be the difference between storytelling and actual science.

And yet I cannot help but think, partly based on Oliver Sacks's career, that storytelling has a unique place in drug discovery. And this is not just because of the cultural and community-building role of storytelling that sociologists often extol. It's because I see anecdotes not as data but as starting points for gathering data. And this is because of the sheer complexity of biology, and of drug discovery by extension. The problem is that when you are dealing with a very complex and multifactorial system, one in which the variance of success is large, it's often impossible to find general rules even by running well-designed statistical studies. Do you then completely dismiss individual data points? I think that would be a mistake. 

If a colleague tells me that using a method for optimizing electrostatic interactions worked well for his system, I would try to use that method for my system within time and resource constraints, especially if his study is well documented and carefully done. I would certainly try it out if both of us were working on similar systems (say, kinases) but even if the systems were different I would give it a shot. That's because we know for a fact that similar laws of physics and chemistry operate even in very different systems; often it's a matter of teasing apart which laws among them are dominant and which ones are weaker.

Then there's also Sacks's quote about each one of his patients providing openings into entire encyclopedias of discovery. What Sacks is really talking about here are model systems which highlight a particular feature that is present in other systems. For instance, a patient with memory loss may not be representative of the population as a whole, but he can shed some very valuable insights into the workings of the mechanisms of memory (sadly although illuminatingly, it's only by observing certain damaged neurological mechanisms that you can know more about normal, undamaged ones). 

Model systems are similarly invaluable in fundamental drug discovery research. A good example is a hydrophobic protein cavity in which a single engineered polar amino acid residue can provide information on the role of electrostatics in small molecule binding. There also "virtual" model systems; for instance a molecular mechanics force field in which the electrostatic interactions are turned off to study only the influence of the Van der Waals interactions. Synthetic chemists can also tell you about scores of model systems that are constructed to demonstrate the feasibility of certain reactions or conformational effects. These model systems are not infallible, and they are certainly not data by themselves. But what they are are invitations to discovery, curious starting points, hints that point the way to interesting phenomena. Whether one uses them depends to some extent on time and resource availability, but we would be naive to simply discard them because they represent isolated or anecdotal cases.

That brings me to the value of outliers. Outliers are interesting in almost any investigation, but they are especially important in a paradigm like biology or medicine where the emergent, non-linear nature of the system leads to significant variance. In fact one could argue that medicine is currently being revolutionized by the study of outliers in clinical trials. Outliers can point the way to selecting subgroups of patient populations, so-called 'extraordinary responders" who elicit an unusual response to certain drugs. A great recent example is the anticancer drug Iressa which was withdrawn from the market because of lack of efficacy. However, a few years later AstraZeneca could introduce the drug back into the market when it found out that patients with EGFR mutations responded much better to it than the general population. It was thus the outliers that could help repurpose a drug, one which is saving lives today. And as the genetic basis of medicine is unraveled more and more, we can be sure that specific outlier patients who are distinguished by unique genetic signatures will be critical not only in targeting specific drugs but also in advancing basic science; a great example along these lines is the aerobics instructor in Texas who had a mutation in a protein called PCSK9, now a lucrative target for heart disease drugs. It would have been a shame if her particular case had simply been dismissed as a statistical anomaly.

That then is the great value of anecdotes, not as markers of scientific laws in themselves but as starting points for experiment and theory, as signposts leading us to intellectual forests and mountaintops. Whether these forests and mountaintops contain anything of value is a separate question, but without the anecdotes we may never know about their existence.

The Billion-Dollar Heartbreak

Fellow blogger, current colleague and friend Keith and I spent an enjoyable evening two days ago at an event which I wouldn’t have anticipated if you had asked me about it before: a sort of fund-raiser/pitch for a movie based on Barry Werth’s book about the creation of Vertex Pharmaceuticals, “The Billion-Dollar Molecule”.

I have to confess being blown away by the book when I first read it in graduate school. The breathless descriptions of the science and the scientists, the glitter of structure based drug design and and the sheer effort of drug discovery really left an impression of me. After working in the reality of drug discovery for a decade or so, I perhaps don’t feel as breathless as I did the first time around. Yes, drug design is exciting, but no, most of the work that we do in the field is far more mundane and boring than what appears in the book (and this is true for the rest of science). And the science of drug design is also far more sobering and limited than what it seemed in the 80s. Nonetheless, if there was a short list of books on biopharmaceutical research that would seem likely to transition to the silver screen, Werth’s volume would probably be on top of that list for me because of its sheer novelistic qualities.

The event itself featured a panel of three scientists and one lawyer who were present at the creation and subsequent developments at Vertex in the late 80s and early 90s: Manuel Navia, Mark Murcko, Roger Tung and Ken Boger would all be familiar to anyone who has read the book. The event was fittingly organized in the old Vertex building near 3^rd street in Cambridge, and not surprisingly it drew a lot of Vertex old timers which inadvertently turned it into a Vertex reunion. An ancillary side session featured a silent auction for photographs taken by Nobel Laureate (and Keith’s graduate school co-advisor) Wally Gilbert who was also there.

Much of the discussion really focused on the scientists’ views of what they thought should really come across from the movie, and I largely agreed with their suggestions. The overwhelming consensus was that the movie needs to communicate the sheer and appalling rate of failure – probably unprecedented relative to any other industry – that we in pharma and biotech have to deal with. 99% of everything that we do, right from the most basic research to the most applied clinical work, simply fails. Almost all of us go through our entire careers without contributing to the discovery of a single important drug. And it all fails because of one overriding factor which I and others have discussed before – our ignorance of basic biology and human disease. It seems that this is probably the preponderant feature of drug discovery that simply fails to make its way across to the public: almost every argument that the public makes against drugs, from their high cost to their side effects, boils down to the simple fact that we simply don’t know how to do it any better. I agree with the participants that if there’s one message that really needs to shine forth from any movie about drug discovery it needs to be this one about attrition, failure and ignorance. Not exactly an uplifting message, but essential for an accurate perception of drug research.

One of the panelists also raised the very relevant issue of how to accurately strike a balance between the sheer tedium of everyday research and the occasional breakthroughs that permeate the entire practice of science. If there’s one flaw in “The Billion Dollar Molecule” it’s that it seems to downplay the former aspect and really emphasize the latter. Yes, drug discovery is a high stakes enterprise and yes, the scientists who do drug discovery can have titanic-sized egos and can have their emotions running high and wild and yes, the science of drug design can sometimes seem as exciting as the ‘science’ in ‘Avatar’, but for every one of these facts the opposite is also true: drug discovery scientists are normal people with a spouse and kids and a mortgage, and 90% of the science of drug discovery is like 90% of science in general – incremental, unflashy and mundane; less Holmesian detective work and more 9 AM-5 PM office job. What the book did was compress all of this into a heady, heroic 350-page narrative, and one wonders if the movie should try to do the same. Another way to tackle the issue might be to make a documentary that’s more realistic, although admittedly it would then be harder to get Kevin Spacey to play Josh Boger (one of the more fanciful suggestions bandied about).

Curiously, the entire project that the book hinges on - the quest to find a breakthrough immunosuppressant - actually failed because they were looking at the wrong target (the curse of biological ignorance struck again), so communicating the reality of the fantastic failures that emerge from a fantastic effort should come naturally to the narrative in the movie. It's a testament to the vision and resilience of the company's BOD and management that they successfully pivoted away from this major failure. It also seems that the movie should heavily capitalize on the sequel to “The Billion-Dollar Molecule” (“The Antidote”): while that’s far less sensational, it deals with the two breakthrough projects at Vertex (hepatitis C and cystic fibrosis) that actually succeeded in a very big way.

Notwithstanding the challenges, I have to say I am game for any cinematic, literary or other endeavor that makes the science, art and business of drug discovery more comprehensible to the layman. There are few activities both more profoundly misunderstood and more fundamentally important to human society than the creation of new entities that save or improve the lives of millions, and any project whose express goal is to make the general public appreciate this reality – even at the expense of some glamorization – would be one I fully support. Good luck to the film-makers!

Big things come in little packages: How Willis Lamb's tiny measurement revolutionized 20th century physics

It's the end of World War 2. Scientists and especially physicists have spent the last four years working on military hardware, culminating in radar and the atomic bomb. Many of these talented men and women are eager to go back to their university campuses and resume normal civilian life; some of them are distraught at their role in engineering such horrific weapons and want to return to the carefree life of fundamental physics research which they knew before the war.

To reconnect the country's leading physicists with each other and with the great research problems which they left behind, the National Academy of Sciences decides to organize a series of conferences on the frontiers of physics. It's not hard to decide who should lead these conferences. Robert Oppenheimer has just led the wartime Los Alamos laboratory which produced the first nuclear weapons to high fame and glory. At Los Alamos and before at Berkeley, Oppenheimer has been widely acknowledged as the founder of the modern school of American theoretical physics and a man whose intellectual mastery of a wide array of disciplines is unmatched. It seems natural to have Oppenheimer be in charge of this post-war re-organization of physics in the country.

Oppenheimer and the National Academy of Sciences put together a list of the scientists they want to invite. Except for the famous Solvay Conferences organized in Europe during a more peaceful time, it's hard to think of another scientific gathering that attracted such an unprecedented constellation of talent. A dozen or more of the attendees have already won Nobel Prizes or would go on to win them; some for work which they would present during the conferences. The list of names is an all-star list in every respect: Hans Bethe, Enrico Fermi, Isidor Rabi, Robert Serber, Victor Weisskopf, Edward Teller, Abraham Pais, John Wheeler, Richard Feynman, Julian Schwinger and Hendrik Kramers. The meeting brings together both the new stars and the old guard (I mentioned Bohr and Dirac earlier, but as M Tucker points out in the comments section, they were present at a later conference: more on this equally interesting meeting in a future post).

Some of the participants at the Shelter Island conference:
Lamb (far left), Oppenheimer, (on arm rest) Feynman (seated
and writing) and Schwinger (second from right)

The first conference takes place in June 1947 at a tiny island called Shelter Island, situated in the jaws of the Long Island crocodile. The exclusive list of attendees gets escorted by a special police escort through major towns during their bus ride. Their selection as attendees, the cutting edge topics at the conference and Oppenheimer's leadership all make it clear that the center of physics has decidedly shifted from Europe to the United States. Shelter Island would go down in history as one of the most important conferences in the history of 20th century physics, but the participants don't quite know it yet.

One attendee in particular, a young protege of Oppenheimer's from Columbia University, is perhaps not as well known as the others: Willis Lamb. Lamb comes from a robust working class household and has obtained both his undergraduate and graduate degrees at Berkeley. Right before the war he got married to a German emigre, and as the story goes, for some time the authorities forbade him from walking on the beach and confiscated his shortwave radio for fear that he might be sympathetic with his wife's German compatriots and might try to communicate with German submarines. During the war he has worked on microwave radar with Rabi and others at Columbia. What is also perhaps not as well known is Lamb's versatility as a physicist. He is an experimental physicist now, but he got his PhD with Oppenheimer at Berkeley in the 1930s. This makes him one of the few scientists around to excel in both theoretical and experimental physics. Lamb's presence is already consequential since the participants at Shelter Island are pondering a discovery he made right after the war: a discovery important enough to be enshrined with his name - the Lamb Shift. The Lamb Shift will herald a new age in physics.

To understand the Lamb Shift, let's descend deep into the world of the atom with its electrons, protons and neutrons. Let's look at the simplest atom, hydrogen. As most of us have learnt in high school and college, electrons exist in energy levels defined by atomic orbitals. Each electron is defined by four so-called quantum numbers. In hydrogen, for the principal quantum number 2, the lone electron can exist in two orbitals defined by the secondary or angular quantum number: 2S and 2P. During the 1930s, in the heyday of quantum mechanics, the great English physicist Paul Dirac had worked out that the energy of the electron in these levels should be the same. Dirac's theory which also achieved the feat of marrying Einstein's special theory of relativity to the new quantum mechanics was the spectacular culmination of a decade of revolution in physics, a revolution led by men like Heisenberg, Bohr and Born, going back all the way to Einstein and Planck at the beginning of the century. The Dirac theory promises to be the icing on the cake of quantum mechanics, and its prediction of equivalent energies for the 2S and 2P orbitals of the hydrogen atom seems solid and indisputable.

But now, Willis Lamb has found that the two levels are different in energy by a tiny amount. It's an amount tiny enough to be undetectable except by the most sophisticated techniques and experimenters, but it causes shock waves in the world of physics and cries for an explanation. The Lamb Shift would be to quantum mechanics what the perihelion of Mercury was to astrophysics. Lamb with his background in both experimental and theoretical physics is in a unique position to measure this difference. He knows enough quantum mechanics to understand Dirac's theory of the electron. He knows enough atomic spectroscopy to understand the experimental underpinnings of the two energy levels. And, thanks to his work with microwave radar during the war, he knows enough microwave spectroscopy in particular to use microwaves to delicately probe the energies of the two levels. Microwave radiation may seem intense - it can sear your food to a crisp after all - but microwaves are actually pretty low in frequency compared to ultraviolet or visible light. By wielding them the way a surgeon wields a fine scalpel, Lamb and his graduate student Robert Retherford have probed the 2S and 2P levels of the hydrogen atom without injecting enough energetic radiation to cause other spectroscopic transitions and contaminate the experimental output. The number he gets is 1000 megahertz, a number which is a fraction of the kinds of frequencies emitted in spectroscopy and which could only have been determined by an experimenter of the first rank.

The Lamb Shift causes ripples in physics because it seems to point at physics beyond the Dirac equation. It's one of those rare, precious measurements in science which seem to inaugurate an entire field of study, a tiny, elusive number that points to great truths. In fact even during the 1930s some prescient physicists, Oppenheimer and Heisenberg among them, had suspected that the two energy levels might be different. But when they tried to calculate the actual number they started getting an absurd value for it: infinity. Nobody has bettered that result, partly because there was no experimental number to compare it with, but now at last, there is a solid reference number which the theoreticians can calibrate their calculations against. It's a rudder which they can finally use to guide the ship of their collective imagination.

The participants at the Shelter Island conference take the Lamb Shift to heart. The discussions continue into the twilight hours. Suggestions are thrown around without definite follow ups. One can sense the fomenting of a movement, but the destination is unclear. It's also clear from the conference that it's going to be the young breed of physicists who's going to crack the puzzle. First comes Julian Schwinger whose hours-long talk is like a prodigious performance by a violin virtuoso. His dazzling equations leave the attendees breathless. Then comes Richard Feynman, irreverent and colloquial with a wholly new way of looking at quantum mechanics, a language of wiggles and pictures which leaves the participants befuddled. It would take some time for his way of thinking to sink in. The proceedings of the conference are now legendary, with someone asking "What the hell should I calculate next?", Isidor Rabi asking "Who ordered that?" in response to the announcement of the muon, and Oppenheimer holding the gathering mesmerized with his splendid command over language, lightning fast mind and propensity to instantly summarize all agreements and disagreements into a concise package. And yet the Lamb Shift beckons.

It takes the resources of Hans Bethe with his unmatched ability to pound calculations into workable numbers to make the first great move; it's no wonder that years later after Bethe's death, his then promising protege Freeman Dyson called him "the supreme problem solver of the twentieth century". After the conference, Bethe astounds everyone by calculating the Lamb shift from scratch. One of his strokes of insight is to realize that even a non-relativistic calculation which ignores the effects of special relativity can give a number which is pretty damn close to the experimental value: 1040 megahertz. This requires a shift of a reference frame, so to speak, since everyone seems to have assumed that a non-relativistic calculation would be too inaccurate and unrealistic. And, as part of a Bethe story that has passed into lore, he does the calculation on the train ride home to upstate New York.

By his own account, Hans Bethe did the first calculation of
the Lamb Shift on a train ride to Schenectady in New York

Bethe's calculation energizes the physics community. It breathes life into a new technique called renormalization which gets rid of the ugly infinities plaguing pre-war calculations. It propels Feynman, Schwinger and Dyson along with Japanese physicist Sin-Itiro Tomonaga to put the finishing touches on their theory of quantum electrodynamics which is presented in the rest of the series of the conferences. Quantum electrodynamics reveals a magical world of so-called virtual particles such as photons that can flit in and out of existence in an eye-blink as the electron transitions between the 2S and 2P energy levels. These particles may seem to violate the conservation of energy because of their sudden appearance and disappearance, but Heisenberg's uncertainty principle as applied to energy and time ensures that one can have virtual particles existing for a definite amount of time as long as there is a finite uncertainty in the value of their energies. That uncertainty manifests itself as a difference in energy which is precisely equivalent in terms of frequency to the Lamb Shift.

The Lamb Shift achieves a flowering of theoretical physics that has not been seen since the heyday of quantum mechanics in the 1930s. Quantum electrodynamics becomes the most accurate theory of physics. It calculates the magnetic moment of the electron correctly to sixteen decimal places; later Richard Feynman famously compared this to measuring the distance between New York and New Orleans to within the width of a human hair. It uncovers a universe that is alive with virtual particles and fields; these particles even permeate an absolute vacuum and give rise to so-called vacuum energy. It gives voice to a new generation of American physicists whose descendants are still housed in the country's leading physics departments. These men and women not only develop quantum electrodynamics, but the techniques they pioneer - Feynman diagrams, renormalization, scattering matrices - are used in the development of all of particle physics in the future, culminating first in the Standard Model and finally in the discovery of the Higgs Boson seven decades later. Feynman, Schwinger and Sin-Itiro Tomonaga deservedly win Nobel Prizes. The Lamb Shift and its implications of a vacuum energy even helps Stephen Hawking postulate the presence of energetic radiation from black holes.

But none of this would have been possible without Willis Lamb, the perfect incarnation of theorist and experimentalist who was present at the right place at the right time. Lamb received the Nobel Prize in physics in 1955, and spent the rest of his career at Oxford, Yale and Arizona (where he moved so that his wife could find a faculty position). He mentored other successful students and developed another highly productive career in laser physics; ironically, one of his papers in this field is cited even more extensively than the one on the Lamb Shift. He lived a long and productive life and died in 2008. But it's the Lamb Shift that will go down in history as the opening shot which inaugurated a golden age of physics. As Freeman Dyson who was one of the prime participants in that saga complimented Lamb on his 65th birthday, 

"Those years, when the Lamb shift was the central theme of physics, were golden years for all the physicists of my generation. You were the first to see that this tiny shift, so elusive and hard to measure, would clarify our thinking about particles and fields."

And that's all we are, really, particles and fields. Happy 103rd birthday, Willis Lamb.

The linguistic adventures of Robert Burns Woodward

Photo credit: Jeff Seeman

Everyone knows about the supreme scientific achievements of Robert Burns Woodward, but few chemists from today's generation are perhaps acquainted with Woodward's love of the English language. This omission would be easy to remedy, however: anyone who reads Woodward's famous papers on the total synthesis of strychnine, or reserpine or chlorophyll would notice his unusually well-formed sentences, injection of Latin or historic references and allusions to synthetic chemistry as a heroic endeavor. Chemistry being a science whose products and protocols are especially palpable and vivid because of their colors, smells, textures and general visual displays, it was particularly amenable to Woodwardian linguistic flourishes. 

All these qualities are now presented in a delightful paper by my friend, the noted historian of chemistry Jeff Seeman, in Angewandte Chemie. Jeff describes how Woodward's English ancestry and Anglophilic affinities propelled him to develop his love of language and a very distinct style of writing that influenced his peers (in his autobiography, Jack Roberts of Caltech has also commented on some of Woodward's unusual English pronunciation: "mole-e-cule" instead of "mall-e-cule" for instance). Woodward of course considered and practiced organic synthesis as a mix of extreme performance sport and high art, so it's only appropriate that his language matched the elegance of his synthetic creations.

Foremost among his descriptions of compounds, reagents and reactions is what I consider to be the ultimate paean ever paid to a molecule: his tribute to a lowly isothiazole ring and his eloquent description of it as a travel companion to whom one needed to bid farewell after a fateful and adventurous journey. This was from his synthesis of colchicine:

"Our investigation now entered a phase which was tinged with melancholy. Our isothiazole ring had served admirably in every anticipated capacity, and some others as well. … It had enabled us to construct the entire colchicine skeleton, with almost all of the needed features properly in place, and throughout the process, it and its concealed nitrogen atom had withstood chemical operations, variegated in nature, and in some instances of no little severity. It had mobilized its special directive and reactive capacities dutifully, and had not once obtruded a willful and diverting reactivity of its own. Now, it must discharge but one more responsibility—to permit itself gracefully to be dismantled, not to be used again until someone might see another opportunity to adopt so useful a companion on another synthetic adventure. And perform this final act with grace it did.”

Then there's the famous synthesis of strychnine, in which the use of a simple exclamation mark in the first sentence places the project on a whole new level of scientific stardom. Albert Eschenmoser who worked with Woodward on his vitamin B12 synthesis offers an appropriate tribute:

Then there are the military metaphors. Today we might be used to descriptions of complex, multistep, multi-personnel and multiyear syntheses as being akin to climbing great mountains or fighting great battles; one of Woodward's successors, K C Nicolaou, has especially enshrined such comparisons in his reviews, but it was Woodward who was the first to memorialize them. As Jeff explains, Woodward was a serious history buff, and his knowledge of a reference to the Battle of Berezina in which the French under Napoleon achieved a costly victory against the Russians made its way into a review on strychnine. More martial references emerge in his description of efforts to decipher chlorophyll (as an aside, even today, I am struck by how much of the jargon of drug discovery is war-inspired: "targets", "hits" and "campaigns" are only a few examples).

1961: Fresh from his dramatic conquest of the blood pigment, [Hans] Fischer hurled his legions into the attack on chlorophyll, and during a period of approximately fifteen years, built a monumental corpus of fact. As this chemical record, almost unique in its scope and depth, was constructed, the molecule was transformed and rent asunder in innumerable directions, and the fascination and intricacy of the chemistry of chlorophyll and its congeners was fully revealed.”

Jeff considers dozens of other examples where Woodward's facility with language was on generous display: Strychnine possessed a "tangled skein of atoms" and another molecule contained a "felicitously placed carboxyl group and a double bond of good augury". Yet another compound is a "substance precariously balanced on a precipice", presumably by virtue of its instability. Finally, Woodward's love of Latin found its way into more than a few of his papers ("sui generis", "sub judice" and "pari passu").

All this achieves a goal which Woodward may or may not have consciously had in mind: to make synthesis look like high art, supremely arduous mountaineering and inspired military strategy all at once. A memorable paragraph of his on the fundamental motivation for organic synthesis brings together many of these themes and pays a glowing tribute to the the whys of the creation of new molecules:

“The structure known, but not yet accessible by synthesis, is to the chemist what the unclimbed mountain, the uncharted sea, the untilled field, the unreached planet, are to other men. The achievement of the objective in itself cannot but thrill all chemists, who even before they know the details of the journey can apprehend from their own experience the joys and elations, the disappointments and false hopes, the obstacles overcome, the frustrations subdued, which they experienced who traversed a road to the goal. The unique challenge which chemical synthesis provides for the creative imagination and the skilled hand ensures that it will endure as long as men write books, paint pictures, and fashion things which are beautiful, or practical, or both.”

Interestingly at the end of the article, Jeff also discusses the reactions of a few reviewers of Woodward's words who were not as taken by his linguistic playfullness, who thought that his undue emphasis on unusual language often obscured the clarity of the science. I am a bit sympathetic to this view myself. Personally I love reading Woodward's papers, but that's because I am someone who enjoys literature. Others who may not be as enamored of the felicities of language, who may have a no-nonsense approach to the writing of scientific papers and who might not want to wade through the icing before they get to the cake might not appreciate Woodward's language as much. This is not an entirely unfair point: The main purpose of scientific papers is to clarify, explain and enumerate, not to decorate, bedeck and garland. 

There's also another important aspect of scientific writing that especially needs to be considered in this age, one in which science is highly international: scientific papers have to be written for an international audience, and it's not unreasonable to think that the kind of language Woodward used might make his papers harder for those whose first language is not English to understand. In Woodward's time science was a smaller community, the Internet did not exist and the total synthesis of organic molecules was an endeavor whose leading practitioners were largely confined to Europe and the United States. One did not really worry about chemists in China appreciating the meaning of words like "adumbrate", "punctilio", "apposite" and "cavil", all of which were peppered across Woodward's writings. Today we do.

Nonetheless, in case of Woodward these stratospheric incarnations of the English language work, mostly because of the profound feats in science which they herald. The synthesis of strychnine or vitamin B12 is indeed an unprecedented achievement akin to high art, so it doesn't seem out of place for such performances to be described in language that is as novel as the achievements are groundbreaking. 

One can get away with a lot if one is Robert Burns Woodward.

On Patrick Blackett, the ideal experimental physicist, and what it takes to excel at interdisciplinary research

The grandly named Patrick Maynard Stuart Blackett was the Cambridge physicist on whose desk Robert Oppenheimer purportedly left a poisoned apple. The veracity of this yarn will likely never be determined, and it’s rather unfortunate that Blackett has been enshrined in the public's mind through this story, most notably by writer Malcolm Gladwell in his book “Outliers”.

This selective and sensationalized reporting is unfortunate because Blackett was the one of the most versatile and accomplished experimental physicists of the twentieth century. Not only was he an outstanding scientist who won the Nobel Prize for his research into cosmic rays and particle physics, but he was also a brave and decorated naval officer, a highly successful military scientist who pioneered operations research during World War 2, a vigorous campaigner for arms disarmament, and a writer of clear and engaging books advocating common sense thinking about weapons and warfare. This underappreciated scientist and government official deserves much more recognition than as the recipient of a possibly poisoned apple.

Athletic and handsome as a movie star with a finely sculpted face, Blackett saw raw action in the Battle of Jutland in World War 1. Between the war years he worked at the famed Cavendish Laboratory where he did much of his prizewinning work on cosmic rays. He and his colleague Giuseppe Occhialini discovered the positron (predicted by Paul Dirac) at the same time as American physicist Carl Anderson, but because the two wanted to confirm their discovery and were slow in publishing it, Anderson was the one who received the Nobel Prize for it (although Blackett was awarded his own prize for other work in 1948). The 'poisoned apple' incident emerges from this period. The story goes that Oppenheimer who was unsuccessfully trying his hand at experimental physics and suffering severe mental health problems as a result left the apple on Blackett's table out of sheer jealousy at Blackett's multifaceted personality and accomplishments. Even if the story is true it speaks to the kind of admiration Blackett could evoke.

During the war Blackett was one of the founders of the branch of mathematics and management science called operations research. He used this technique productively in trying to protect convoys against U-Boat attacks. After the war Blackett became an enthusiastic and sensible proponent of arms disarmament. As early as 1949 he wrote a book named “Fear, War and the Bomb” which argued against the efficacy of strategic bombing and the lure of nuclear weapons as instruments of warfare. In a time when the atomic bomb was seen as the linchpin of geopolitical strategy, this was a remarkably prescient and courageous position to adopt. Subsequent events have only vindicated Blackett's core thesis.

Blackett ended his career as a decorated scientist and public servant, having gathered many honors for his efforts and advice. Fortunately there are at least three books that vividly describe his life and times; volumes by Mary Jo Nye (2004), Peter Hore (2002) and most recently Stephen Budiansky (2013).

Blackett’s own writings on science and politics are worth reading, but here I want to highlight his views on what it takes to be an accomplished experimental physicist. It strikes me that Blackett’s take applies not just to experimental physicists but to any scientist who wants to straddle the boundary between two disciplines or modes of thinking. Here’s what he has to say (italics mine):

The experimental physicist is a jack-of-all-trades. A versatile, amateur craftsman he must blow glass and turn metal, carpenter, photograph, wire electric circuits and be a master of gadgets of all kinds. He may find invaluable his training as an engineer and can profit always by utilizing his gifts as a mathematician. In such activities will he be engaged for three quarters of his working day. During the rest he must be a physicist, that is he must cultivate an intimacy with the physical world, but in none of these activities taken alone need he be preeminent; certainly not as a craftsman, and not even in his knowledge of his own special field of physics need he, or indeed perhaps can he, surpass the knowledge of some theoretician… 

The experimental physicist must be enough of a theorist to know what experiments are worth doing, and enough of a craftsman to be able to do them. He is only preeminent in being able to do both. 

Blackett’s words are worth remembering for many reasons. First of all, he emphasizes the wide variety of tools that an experimental physicist needs to be proficient at. In fact Blackett says that good experimental physicists may end up spending most of their time not learning physics but building tools. Most notable among these are tools that are actually not experimental but theoretical. It’s not sufficient for an experimental physicist to be good at building magnetometers, wiring circuits or writing software; she also needs to understand the theory that her efforts are going to test, as well as the limitations of her efforts in validating essential features of the theory.

There are a handful of experimental physicists in the 20^th century who straddled this boundary with ease. Supreme among these was Enrico Fermi, whose achievements in both theory and experiment were unparalleled. The historian of science C P Snow paid Fermi the ultimate tribute when he remarked that, had Fermi been born twenty years earlier, he could have seen him first discovering Rutherford’s atomic nucleus and then inventing Bohr’s theory of the hydrogen atom. That’s as high as praise can get. However there were other physicists who were also quite accomplished in both domains. One example was Isidor Rabi who knew enough theory to interpret the results of his Nobel Prize winning magnetic beam experiments. Another was Willis Lamb, a student of Robert Oppenheimer whose precision experiments on the energy levels of electrons in hydrogen atoms led to observation of the so-called Lamb Shift. The Lamb Shift was the starting point for a revolution in physics that led to the theory of quantum electrodynamics.

In other sciences too it is important for practitioners to understand enough of other tools and ideas to have an impact. Chemistry being a more experimental science compared to physics, it’s especially important for chemists to remember Blackett’s motto. For instance a biochemist might be exceedingly accomplished in setting up assays to test the activity of a drug, but he might likely misinterpret results or not follow up on interesting ones if he is unaware of kinetics, thermodynamics and the principal features of intermolecular interactions. Similarly, a synthetic chemist setting up a reaction needs to be proficient in understanding molecular conformation and the determinants of molecular reactivity. Simply being able to set up low temperature reactions, handle flammable reagents and record NMR spectra won’t be enough.

Perhaps the most important message from Blackett’s musings is that one does not need to truly excel in one domain or another in order to excel in their combination. This principle applies to other fields too. For instance Oliver Sacks, while a very good neurologist, was not one of the top neurologists in the world. Similarly, although an excellent writer, he was perhaps not at the very top of the pantheon of prose stylists. But as Andrew Solomon says in his review of Sacks’s wonderful autobiography, what made him truly unique was the fact that he was a very good neurologist who was also a very good writer. It was this killer combination that made him world-class.

In this era of highly interdisciplinary research, Blackett’s message should be especially pertinent. With the constant river of diverse data flowing toward us at superhuman speed, it’s probably a bad strategy to try to excel in multiple fields all at once. Instead, just like Blackett’s ideal experimental physicist, it’s far better to aim for being pre-eminent in knowing those fields in the first place, and knowing enough of each to be useful and not dangerous.