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Munos On Big Companies and Small Ones

So that roughly linear production of new drugs by Pfizer, as shown in yesterday’s chart, is not an anomaly. As the Bernard Munos article I’ve been talking about says:

Surprisingly, nothing that companies have done in the past 60 years has affected their rates of new-drug production: whether large or small, focused on small molecules or biologics, operating in the twenty-first century or in the 1950s, companies have produced NMEs at steady rates, usually well below one per year. This characteristic raises questions about the sustainability of the industry’s R&D model, as costs per NME have soared into billions of dollars.

What he’s found, actually, is the NME generation at drug companies seems to follow a Poisson distribution, which makes sense. This behavior is found for systems (like nuclear decay in a radioactive sample) where there are a large number of possible events, but where individual ones are rare (and not dependent on the others). A Poisson process also implies that there’s some sort of underlying average rate, and that the process is stochastic – that is, not deterministic, but rather with a lot of underlying randomness. And that fits drug development pretty damned well, in my experience.
But that’s just the sort of thing, as I’ve pointed out, that the business-trained side of the industry doesn’t necessarily want to hear about. Modern management techniques are supposed to quantify and tame all that risky stuff, and give you a clear, rational path forward. Yeah, boy. The underlying business model of the drug industry, though, as with any fundamentally research-based industry, is much more like writing screenplays on spec or prospecting for gold. You can increase your chances of success, mostly by avoiding things that have been shown to actively decrease them, and you have to continually keep an eye out for new information that might help you out. But you most definitely need all the help you can get.
As that Pfizer chart helps make clear, Munos is particularly not a fan of the merge-your-way-to-success idea:

Another surprising finding is that companies that do essentially the same thing can have rates of NME output that differ widely. This suggests there are substantial differences in the ability of different companies to foster innovation. In this respect, the fact that the companies that have relied heavily on M&A tend to lag behind those that have not suggests that M&A are not an effective way to promote an innovation culture or remedy a deficit of innovation.

In fact, since the industry as a whole isn’t producing noticeably more in the way of new drugs, he suggests that one possibility is that nothing we’ve done over the last 50 years has helped much. There’s another explanation, though, that I’d like to throw out, and whether you think it’s a more cheerful one is up to you: perhaps the rate of drug discovery would actually have declined otherwise, and we’ve managed to keep it steady? I can argue this one semi-plausibly both ways: you could say, very believably, that the progress in finding and understanding disease targets and mechanisms has been an underlying driver that should have kept drug discovery moving along. On the other hand, our understanding of toxicology and our increased emphasis on drug safety have kept a lot of things from coming to the market that certainly would have been approved thirty years ago. Is it just that these two tendencies have fought each other to a draw, leaving us with the straight lines Munos is seeing?
Another important point the paper brings up is that the output of new drugs correlates with the number of companies, better than with pretty much anything else. This fits my own opinions well (therefore I think highly of it): I’ve long held that the pharmaceutical business benefits from as many different approaches to problems as can be brought to bear. Since we most certainly haven’t optimized our research and development processes, there are a lot of different ways to do things, and a lot of different ideas that might work. Twenty different competing companies are much more likely to explore this space than one company that’s twenty times the size. Much of my loathing for the bigger-bigger-bigger business model comes from this conviction.
In fact, the Munos paper notes that the share of NMEs from smaller companies has been growing, partly because the ratio of big companies to smaller ones has changed (what with all the mergers on the big end and all the startups on the small end). He advances several other possible reasons for this:

It is too early to tell whether the trends of the past 10 years are artefacts or evidence of a more fundamental transformation of the drug innovation dynamics that have prevailed since 1950. Hypotheses to explain these trends, which could be tested in the future, include: first, that the NME output of small companies has increased as they have become more enmeshed in innovation networks; second, that large companies are making more detailed investigations into fundamental science, which stretch research and regulatory timelines; and third, that the heightened safety concerns of regulators affect large and small companies differently, perhaps because a substantial number of small firms are developing orphan drugs and/or drugs that are likely to gain priority review from the FDA owing to unmet medical needs.

He makes the point that each individual small company has a lower chance of delivering a drug, but as a group, they do a better job for the money than the equivalent large ones. In other words, economies of scale really don’t seem to apply to the R&D part of the industry very well, despite what you might hear from people engaged in buying out other research organizations.
In other posts, I’ll look at his detailed analysis of what mergers do, his take on the (escalating) costs of research, and other topics. This paper manages to hit a great number of topics that I cover here; I highly recommend it.

41 comments on “Munos On Big Companies and Small Ones”

  1. clinicalpharmacologist says:

    So the drug discovery process is (scientifically speaking) magic and not susceptible to rational analysis?
    Sounds about right to me. Luck has always been the basis of the majority of the really game- changing breakthroughs and we’ve spent the last 20 years designing luck out of the system. Time to bring it back.

  2. Lucifer says:

    But MBAs do not like to hear that… you are removing the very reason for their existence.

  3. RB Woodweird says:

    Nah, it’s because you haven’t been properly trained in Six Sigma. And 5S, yeah, that’s it – 5S everything and those drugs will come billowing out the pipeline.

  4. Greg Hlatky says:

    Any day that you can remove an MBA’s reason for existence is a good day.

  5. anonymous says:

    #1, you are spot on! There is no way, repeat no way, to forecast blockbusters. Every penny spent towards that end is a penny wasted. And God only knows that the drug industry has huge staffs of PhDs dedicated to doing just that, not to mention the vendors. Art de Vany has written a wonderful book, Hollywood Economics, in which he works out the mathematics of blockbuster economics. Suffice to say that they follow a Bose-Einstein distribution to hint at the complexity. The short of it though, is forecasting their occurrence cannot be done. It’s a mathematical impossibility given their distribution. Try to explain that to a scientifically illiterate CEO.

  6. bamh1d says:

    Thanks for an excellent post, Derek. The picture projects the dis-integration of the big pharma companies and suggests two things to me: (1) if the trend continues we’re probably looking at a future that has only two or three global pharma companies that don’t discover or develop anything, but simply buy up promising clinical candidates and then manage the regulatory and marketing aspects of the business, and (2) as companies become bigger through M&A they close a lot of projects in order to arrive at a manageable number, which results in an ever more risk averse R&D environment. Painful as it may be, perhaps a lot of pharma R&D scientists will be happier working in smaller companies that are, by and large, more tolerant of innovative approaches. However, that happiness will be tempered by the fact that they share directly in the commercial risks of innovation.

  7. Anonymous says:

    I agree with #6. Big pharmas are at a real risk of losing drug discovery, and repositioning themselves, willy nilly, on drug development and regulatory. This is not happening as a result of vision, but as a result of risk aversion, and a compulsive addiction to process management. The big question is where is value created? I tend to think that it is created in discovery, while development and regulatory are (or will become) cost-plus operations. But perhaps I am wrong.

  8. emjeff says:

    Hi #1 ;
    “Chance favors the prepared mind”.
    In other words, you need to be smart BUT you need to be lucky too.

  9. Brian says:

    Nice post. One question from a non-industry person: does M&A here mean mergers and acquisitions, or are you talking about something specific to pharma?

  10. Guernseyman says:

    #7 I agree and I think there is an answer that could benefit all in this.
    Big pharma does regulatory, distribution and marketing driven by MBAs.
    However a certain percentage of budgets are directed to VC-like high risk diverse R & D efforts. The model of these efforts is to throw the money into as many possible different efforts as possible.

  11. CMCguy says:

    Is scary to imagine as I do not know if a rate decline might have occurred without some of the changes that have been introduced but has seen much oscillation caused by “new and approved” paradigms in how to discover drugs. Maybe we have so “overly prepared our minds and then missed out on serendipity”. I do like the concept of forces balancing out with better perceived understandings and tougher hurdles but I wonder how big factors such as targeting only “blockbusters” and sue-happy legal environment have impacted what could have been in terms of medicines available. Of course can’t forget how companies focus’ have changed from long term success to immediate return for shareholders.
    Although many Research people seem to think can divorce the Science/Discovery side from the Development/Business parts I am less convinced that in the end will be truly effective. To take something from an idea to a marketed drug product need inputs from many functions and the more different groups interact the smoother the process and better the result will be. I do think many Pharma companies have grow too big and the R&D often suffers from over-management that hinders progress. At the same time un- or misdirected efforts can detour a promising idea from being a success also, with many examples in Biotech. There should be possibilities for a balance in the middle that fosters great R&D and simultaneously executes well on the Marketing/Business side. Guess I can always dream although remember a time when several Pharmas were closer to that combination.

  12. David P says:

    Thanks again for bringing this article up. Sometimes you’ll hear about a study that makes concrete an intuition and this seems like one to me, though perhaps that the only thing related to the number of NMEs is number of companies is perhaps an even more extreme version of what I thought.
    Hmm, maybe big pharma can improve their pipelines by doing the opposite of M&A – they put money into start-up companies, then when a candidate makes it through they can acquire it and develop it (i.e. all the things that big pharma can do well and do benefit from economies of scale).
    It seems like a happy little dream though.

  13. Cellbio says:

    CMC guy, would like to pick up your theme:
    “Although many Research people seem to think can divorce the Science/Discovery side from the Development/Business parts I am less convinced that in the end will be truly effective.”
    Research needs to be in an environment not dominated by business and MBA types, but certainly not divorced from market insights, competitive intelligence etc.
    “To take something from an idea to a marketed drug product need inputs from many functions and the more different groups interact the smoother the process and better the result will be.”
    I agree in principle, but in practice, this is what does not scale, IMO. I have seen this work in small companies, and efficiently, with something as old fashioned as a conversation. In bigco’s, this is always placed into a context of metrics, analytics, defined portal criteria and all the other crap that McK and BCG use to create a false sense of controlling the risk, reducing variability and improving efficiency. In the end, bigco employees suffer. I also love this quote posted by Mutatis:
    “The leaders of major corporations including pharmaceuticals have incorrectly assumed that R&D was scalable, could be industrialized and could be driven by detailed metrics and automation. The grand result: a loss of personal accountability, transparency and the passion of scientists in discovery and development.”

  14. dearieme says:

    “Another surprising finding is that companies that do essentially the same thing can have rates of NME output that differ widely”: why is that surprising? For years the Oil Majors all explored for oil, but BP proved by far the most successful at finding the stuff.

  15. Hap says:

    At some point, though, don’t companies have to have some idea what the risk and reward for a given project is? There are lots of things we don’t know, and some of them are important, but some of them are not. Distinguishing them (and attmpting to do so quantitatively) seems like a good idea.
    If large companies have the infrastructure to attempt to measure and evaluate their research projects, why don’t they have the ability to admit to themselves that their metrics aren’t effective and to try new ones? If you can’t tell whether the outcomes of metric-based decisions are better or worse than those made based on a Magic 8-Ball or rat entrails, then that would be a legitimate issue (Why don’t you try something else? Why are you spending money for accountants who can’t account for anything? If you don’t know whether your research is better-performed or worse-performed based on your metrics, then are you just trying to fool yourselves or your stockholders?) Testable theories aren’t just for science after all, and nontestable ones aren’t terribly useful (particularly when measureable outcomes are the objectives).
    I don’t know that trying to evaluate risk quantitatively (or at least, as best you can) is a bad idea – the problem is the inability to see whether a theory works long before it’s too late to change it easily, and perhaps the inability to change metrics when they don’t work (or not to use them when you can’t actually tell if they work).

  16. srp says:

    Trying to get people to manage rationally is very, very difficult in high-uncertainty environments. For one thing, cause and effect is hard to establish between behavior and outcome. This leads to a lot of politics and impression management, as well as difficulty for any sincere effort to improve things. For another, psychological factors–fear, primarily–cause people to grasp for anything that gives them some feeling of control. Anyone who’s worked in the movie business can tell stories of “irrational” behavior and practices that would probably seem familiar to some of you in pharma-land.
    Chris Argyris at Harvard has a whole theory of what he calls “self-sealing discourse” in organizations–undiscussable subjects whose very undiscussability is undiscussable. I’m not a huge fan of his work, but there’s a grain of truth in there. (I sometimes feel, based on the threads here, that the use of animal screening to rule out human drugs, the employment of rational drug design despite evidence that even successful drugs work by other than their originally purported mechanisms, and the passive acceptance of a regulatory regime that would not approve aspirin are three subjects that fit this category.)
    Argyros proposes exactly what you suggest: Use more evidence-based reasoning as a solution to these problems. But he concedes that he’s not sure how to get from here to there in a currently messed-up organization.

  17. fungus says:

    Of course, some of this discussion assumes that the criteria for FDA approval have remained constant over time, which is probably not the case. Isn’t it possible that some of the drugs that passed 20 years ago would not obtain FDA approval today? What effect might this “raising of the bar” have on the drug discovery industry?

  18. Cellbio says:

    srp, enjoy your posts, always loved the pyschology of organizations, and it is a good “minor” to have when working in pharma.
    Hap, I have lived through several cycles of, to be a bit snarky, “we’re not going to do what those last guys did”. Problem of evaluating systems that assess the risk or merit of programs is compounded by the time scale. Latest example I know has the current crew (publicly derided the prior executive team) hoping the drug from the deposed regime makes it or they are all cooked. Meanwhile, their new manner of measuring, evaluating etc has become the business, not the tool to aid it.
    regarding a particular project, yes any good team or individual scientist will know the limitations of a project, and they always grow more limited with greater knowledge. Of course, this is not really changing the likelihood of positive outcome, but clarifying the true probability of success, which was set the day the compound was made. But how to productively use the information?
    To use the concept of self-sealing discourse, now try to be the sole team leader who stands up at your company portfolio review and accurately states the known limitations and see what happens to your project. Add a whiff of “fail fast” mentality to the organization and you end up with an strategy that rewards the unknown in that it keeps turning to promising new projects, precisely because not enough is known to speak clearly about the limitations. Takes special leadership to overcome this tendency and to allow researcher to develop depth and thorough understanding, and therefore the organizations true understanding of risk/reward for a given approach.

  19. Chris says:

    Many years ago, (more years than I care to remember) I was at a management meeting at Merck. As an exercise we were asked to suggest how Merck might be changed in the future. My colleague and I decided to be slightly provocative and suggested Merck should dedicate it two major sites in the US solely to drug development (there seemed to be efficiencies with size), all other sites should be made independent research labs that competed with the rest of the Pharma industry for slots in the Merck Development program. Needless to say it went down like a lead balloon….

  20. Mutatis Mutandis says:

    As an employee of dying company — no, not Wyeth, we had the “acquisition” part years ago and are only now dealing with the deadly “merger” — I find myself in firm agreement with the observation that there are “undiscussable subjects whose very undiscussability is undiscussable.”
    This is definitely how our management operates. We are being told, of course, that merging and relocating the research units will generate economies of infrastructure and scale, and make the company more competitive. As scientists we know pretty well that that definitely won’t be the case. However, we are denied any opportunity to challenge this belief, which is clearly beyond discussion. Instead, management merely continues to repeat it at on al almost daily basis, as if in the hope that they can somehow “reprogram” their researchers.
    Likewise, when we point out that the same management principles that are now being inflicted on us have already been tried in another internal group, and have resulted in chaotic inefficiency, laughable levels of productivity, and deep demoralization, people suddenly become deaf. When confronted with painful and undeniable evidence, managers will suggest that some minor tweaks in structures and a shuffle of a few seats will solve the problem.
    I’ve found that talking to pharma management is like dealing with creationists or flat-earthers. The only substantial difference that while the flat-earther starts from a point that is obviously invalid but rigidly adheres to it, management tends to start from a point that is valid but lacks relevance, and rigidly refuses to look further. The typical example is “Closing these sites will be a significant saving on our infrastructure budget, which is x% of our fixed expenditure. As for the people and the know-how at these sites, we will do out best to find a solution for them.”

  21. Cellbio says:

    Mutatis, nice characterization of the experience, been through it on many fronts.
    Regarding the inability to reach management, it is formally institutionalized. When I reached management levels, I was actually trained, or so they attempted, to “cascade” messages, as if a chorus of smiling executives would alter the truth. On the receiving front of this method, a favorite example is a “cascading meeting” where the message was the great advance made in rewarding our staff by adopting a method of calculating pay raise and bonus which split a normal distribution of performance score right down the middle of the peak, high performers to the right, poor performers to the left, nice and neat. All this a direct outcome of McKinsey’s war for talent garbage. You can imagine the blank stares as I talked about the folly of this approach, both from a statistics standpoint, independent reviewer issues, and impact on motivation when you tell have your staff they are poor performers.
    Also think the people (MBAs, management consultants) who institute these sorts of measures, and implement and run metrics based reviews make their judgments in very different ways than scientists. Rather than look at information to arrive at one’s best guess at the truth, the current crop of business leaders make decisions based more on social network models, or group think, and use bits of information to support the favored position, ignoring real data which is not supportive.
    A friend of mine is a script writer, when talking to him about this madness he told a Hollywood joke: Writer produces his best work, sends off to studio executive and follows up with a call. “How do you like the script”, pause, “I don’t know, I am the only one here right now.”
    Add greed as a personal motivator to keep one’s job, fat salary and nice big bonus…. cascade away baby!

  22. yshi8141 says:

    To #23 and #24:
    This reminds me of the way chinese institutions scale the achievement of their professors: Only the number of publications. I see no way you can judge a scientific discovery based on a number, right. I guess the pharma management people are trying the same thing to “simplify” things.

  23. CMCguy says:

    Cellbio #13 yes Research environments “dominated” by business/MBA (plus Marketing and legal) types is less productive (which unfortunately seems to be too common these days). But too often R&D types want to totally isolate themselves from other areas without realizing certain insights they are missing could be important in guiding those earlier efforts (again ideally without forcing incompatible criteria on decisions).
    As to the scalability of interactions I agree there as I see there is a point bigco will have more dead weight than solid contributors that wears on the later group (and whole suffer). However many smallco do not have the breadth of resources internally and these either bring in consultants who are not good at telling what is really needed (or smallco does not listen) or hire areas too late to impact properly.

  24. S Silverstein says:

    Derek wisely observes:
    “You can increase your chances of success, mostly by avoiding things that have been shown to actively decrease them, and you have to continually keep an eye out for new information that might help you out. But you most definitely need all the help you can get.”
    Or not.

  25. Bond says:

    Cellbio wrote:
    Also think the people (MBAs, management consultants) who institute these sorts of measures, and implement and run metrics based reviews make their judgments in very different ways than scientists. Rather than look at information to arrive at one’s best guess at the truth, the current crop of business leaders make decisions based more on social network models, or group think, and use bits of information to support the favored position, ignoring real data which is not supportive.
    One wonders if some of these folks are merely saboteurs, secretly working for the competition…

  26. cliffintokyo says:

    In a nutshell, the original post concludes that multiple approaches and more competition are good for pharma research productivity, (and less competition is of course good for big business profitability); as someone else mentioned, I believe, this provides direct evidence of what many of us feel we already knew by intuition, (and/or experience perhaps?)
    We seem to be agreed that MBAs should do their economies-of-scale, one-model-fits-all-businesses number-juggling in their mega pharma-dev service orgs; as for pharma research, who needs them?
    (This is the polite version)

  27. cliffintokyo says:

    PS #26
    Business-savvy insight about marketability, yes indeed, agreed, but this is not the kind of *advice* provided by MBAs!

  28. srp says:

    There is an interesting Harvard Business School teaching case about ALZA (when they were still an independent company). Their specialty, as you guys probably well know, was osmotic drug delivery systems (patches, time-release pills). The company was dominated by R&D people and the top management had ambitions of becoming a full-fledged pharma.
    One problem they had was that when they pursued new drugs on their own, their judgment was terrible. They got some things approved but there was no market for most of them and their sales efforts were pathetic. (Another problem was that their manufacturing capability was far below what their ambitious plans called for.)
    The case mentions (in passing) that one drawback to top management’s ambition to become a full-fledged pharma was that it would involve bringing in non-Ph.Ds to their idyllic R&D work environment. They would have to bring in engineers and business executives (some of whom might even have MBAs) and given them some power, and that would make the place less desirable as a work place for researchers.
    The bosses who wanted to build the big company model, by the way, were themselves scientists not MBAs. Some of their thinking about their expansion strategy reflected that, not always in a good way…

  29. Anonymous says:

    So Alza needed engineering, marketing and sales expertise, not MBAs to analyze their numbers (and tell them what they already knew?). There is a logical disconnection with your own previous comments which you surely don’t need me to point out?
    A couple of years ago at a business seminar I heard a first-class entrepreneur/ private company owner say that he would only consider inviting a MBA to join his senior management team if that person would be willing to invest a significant amount of his own money in the firm…i.e. only a rich MBA has a way of showing a commitment that might make him an asset to the company; all the rest are financial analyst grunts.
    I will swap you the name of the entrepeneur I met for a ref to the HBR article plus a consulting fee (seven figures would be reasonable in view of the low value of the dollar at present)

  30. cliffintokyo says:

    #29 PS
    Good scientists make a tremendous commitment to research from day #1 of their careers at pharma companies; people recruited directly into corp business admin functions do not understand this.
    From following the lit in their own time; to coordinating with analyt support and biol to get timely data on new compounds; to chatting with experts at conferences; MBAs would get business lunches and green fees out of most of these activities. The disconnect in value perceptions and understanding can be just as glaring as in the article linked to #24, when the *wrong* people are *in control*. Wow! (thanks, SS)

  31. simple_me says:

    I have a problem in the interpretation of the R&D numbers and the theories based on it. It is not clear if the money is invested on the R or the D side – which makes a huge difference. Maybe the only trend we see is: Clinical trials cost now a hell of a lot more than 60 years ago. Which could also explain the more companies – more NME trend, as the observation that merges etc didn’t improve the situation. I think it is unlikely that due to the merger the (R)&D budget will reach the amount of the sum of both companies (in the beginning: yes, but on the long run …). But I don’t know, maybe someone can comment on this …
    Best regards.

  32. Anonymous says:

    Good question.
    Pharma *Dev* swallows most (80%?) of the R&D budget, in particular when we include clinical trials, which are really part of *clinical development*, as you correctly assumed, although clinical investigators like to call themselves *researchers*.
    Anticipating your next question: this is not a pharma biz function budget that MBAs should be allowed to get their hands on, because their expertise is in sales, accounting, and investor management. Clearly there is even less of a case for letting MBAs near strategic research budgets.

  33. cliffintokyo says:

    #31 and #32
    *Plateauing* of combined R&D spending *might* be due to a decrease in the number of clinical trials?

  34. MBA2 says:

    I believe that there are always multiple views to an issue. I worked as commercial/maketing executive in one of the big five for over 20 years. Several years of my career were spent working with my R&D colleagues to help prioritize projects. My teams marketing knowledge together with my R&D colleagues scientific creativity helped us be a stonger player in my therapeutic areas. However, there have been cases where scientist have developed drugs all through phase II to find out that the mode of action had no value in the market place. We also had some short sighted commercial “experts” who would not see beyond their narrow sales experience and miss the chance for a creative blockbuster first in class.
    Both situations are sad and caused loss of revenue for the company

  35. cliffintokyo says:

    Happy to acknowledge that I am generally in harmony with your view (see my comment @ #27). As you say, sadly there are (probably many) instances of short-sightedness (bloody-mindedness?) from both sides, with a tendency to dictate in the face of lack of assertiveness and/or clear strategic thought.

  36. LWH says:

    I think you are right on to propose that the lack of growth of NME’s has been impacted by the difficulty of getting things approved by the FDA because of higher tox standards (for example). You can’t do the controlled experiment, so it’s hard to know exactly what the impact of this effect is, but I’m sure it’s considerable.
    And the tendency towards bean-counting, as opposed to sensible risk-taking, by upper management suits is sure to play a considerable role.
    But as researchers we also have to accept some blame for the problem. In the last several years I have seen the way that a number of research units (all medium to small sized) operate, and have noticed some common themes. Project teams often repeat the same mistakes over and over. For example, many focus on potency to the exclusion of all else, letting molecular weight and other liability-triggering properties get out of hand. No doubt this is at least partially driven by the urgency to present short-term favorable results at the expense of strategic development. And don’t forget the slow communication of internal data due to deficient informatics systems.
    Another problem, out of the hands of the project teams, is a tendency to have to do more with less (fewer counterscreens, less early animal testing, etc…). This has driven the tendency to more and more outsourcing which, while cheap, also slows the process down as the optimization cycle becomes longer.

  37. Sam Weller says:

    As a scientist on the periphery of this industry, I am reading the repeating comments grudging about those MBAs and those CEOs and VPs, and I am sure a lot of it is true. But I also have to wonder whether it is possible that our scientific understanding (or lack of) is the reason for the less than satisfactory performance. Maybe it’s just that our scientific perspective and tools are still too limited to produce a discovery and development process that is more rational and more deterministic than a roll of a dice. Maybe when it comes to pharmaceutical targets and diseases that are not “easy”, finding NME, is a matter of almost pure chance. Convolute this with probably less than optimal management, and you might explain the meager statistics.

  38. Mutatis Mutandis says:

    Sam Weller #37
    Yes, it is obvious we don’t have a deterministic discovery process with a guaranteed outcome. I guess that this is one of the causes of conflict between scientists and MBAs: People with managerial and financial training naturally focus on improving and streamlining the process, but the scientists have no reason to assume that this process is better than another one.
    But even in a game of chance there are ways to improve your gains. Generally speaking these come in two kinds: Ways to improve the odds of winning, and ways to increase your gains if you win.
    An example of the first kind was once offered by a team of scientists who analysed the behaviour of roulette wheels in Las Vegas and discovered that they were not perfectly random, but had enough bias to make a betting strategy work. This is the kind of improvement scientists tend to focus on: Finding methods that (slightly) increase the probability of finding promising compounds. Even minor improvements matter, and I am sure that serious progress is still possible in this area, but the going is hard. Nevertheless the track record of some drug discovery teams proves, in my opinion, that there are clearly good and bad ways of working.
    An example of the second kind is available in lotteries in which you can choose your own combination of numbers: All combinations are then equally likely to win, but with a bit of psychological insight you can reduce the risk of having to share the prize. For example by avoiding numbers below 12, because many people will enter dates of birth. This is the kind of statistical improvement MBAs and portfolio managers focus on: Trying to identify the most profitable future drugs.
    I think both strategies are worth pursuing. But what Munos’ paper seems to indicate is that the industry is failing in *both* strategies. The scientists didn’t find ways to make the discovery of NMEs more probably, and the financial people failed to identify potential blockbusters. Frankly most of the financial people strike me as the kind of people who *would* enter their date of birth as lottery combination, but perhaps the root cause is simply that many people in the industry are awful at statistics.

  39. Anonymous says:

    Thanks, Scot #24. As if I wasn’t depressed enough for the holidays.
    I get the impression that even I could run a company better than those doofuses. I only have one serious handicap: I know full well that I can’t.

    Layoffs still continue, which compound the problem of unhappiness and insecurity, especially for middle-aged individuals with a wealth of scientific and corporate knowledge – and mortgages and kids in college

    I’m glad that I at least won’t have that ball chained to my ankle.

  40. Sili says:

    Oops – That was me @39

  41. Doug says:

    Very interesting discussion. I thought I’d let you in the pharma world know you’re not alone. I’ve been part of the medical device universe going on 30+ years now and everything you say about M&A and the disconnect between discovery and product realization is just the same for us. I’ve seen many an innovative company swallowed up by the next biggest python in the jungle for ‘synergy’ and ‘strategic alliance’ reasons to then be divested 5 years later due to poor performance. Innovation is hard and happens infrequently. Most of what I see being created today is functionally identical to systems in place 30 years ago, just smaller.
    Hmmph…and I still don’t have my flying car either…

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