About this Author
College chemistry, 1983
The 2002 Model
After 10 years of blogging. . .
Derek Lowe, an Arkansan by birth, got his BA from Hendrix College and his PhD in organic chemistry from Duke before spending time in Germany on a Humboldt Fellowship on his post-doc. He's worked for several major pharmaceutical companies since 1989 on drug discovery projects against schizophrenia, Alzheimer's, diabetes, osteoporosis and other diseases.
To contact Derek email him directly: email@example.com
August 28, 2014
Here's a short video history of the FDA, courtesy of BioCentury TV. The early days, especially Harvey Wiley and the "Poison Squad", are truly wild and alarming by today's standards. But then, the products that were on the market back then were pretty alarming, too. . .
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A reader has sent along the question: "Have any repurposed drugs actually been approved for their new indication?" And initially, I thought, confidently but rather blankly, "Well, certainly, there's. . . and. . .hmm", but then the biggest example hit me: thalidomide. It was, infamously, a sedative and remedy for morning sickness in its original tragic incarnation, but came back into use first for leprosy and then for multiple myeloma. The discovery of its efficacy in leprosy, specifically erythema nodosum laprosum, was a complete and total accident, it should be noted - the story is told in the book Dark Remedy. A physician gave a suffering leprosy patient the only sedative in the hospital's pharmacy that hadn't been tried, and it had a dramatic and unexpected effect on their condition.
That's an example of a total repurposing - a drug that had actually been approved and abandoned (and how) coming back to treat something else. At the other end of the spectrum, you have the normal sort of market expansion that many drugs undergo: kinase inhibitor Insolunib is approved for Cancer X, then later on for Cancer Y, then for Cancer Z. (As a side note, I would almost feel like working for free for a company that would actually propose "insolunib" as a generic name. My mortgage banker might not see things the same way, though). At any rate, that sort of thing doesn't really count as repurposing, in my book - you're using the same effect that the compound was developed for and finding closely related uses for it. When most people think of repurposing, they're thinking about cases where the drug's mechanism is the same, but turns out to be useful for something that no one realized, or those times where the drug has another mechanism that no one appreciated during its first approval.
Eflornithine, an ornithine decarboxylase inhibitor, is a good example - it was originally developed as a possible anticancer agent, but never came close to being submitted for approval. It turned out to be very effective for trypanosomiasis (sleeping sickness). Later, it was approved for slowing the growth of unwanted facial hair. This led, by the way, to an unfortunate and embarrassing period where the compound was available as a cream to improve appearance in several first-world countries, but not as a tablet to save lives in Africa. Aventis, as they were at the time, partnered with the WHO to produce the compound again and donated it to the agency and to Doctors Without Borders. (I should note that with a molecular weight of 182, that eflornithine just barely missed my no-larger-than-aspirin cutoff for the smallest drugs on the market).
Drugs that affect the immune system (cyclosporine, the interferons, anti-TNF antibodies etc.) are in their own category for repurposing, I'd say, They've had particularly broad therapeutic profiles, since that's such a nexus for infectious disease, cancer, inflammation and wound healing, and (naturally) autoimmune diseases of all sorts. Orencia (abatacept) is an example of this. It's approved for rheumatoid arthritis, but has been studied in several other conditions, and there's a report that it's extremely effective against a common kidney condition, focal segmental glomerulosclerosis. Drugs that affect the central or peripheral nervous system also have Swiss-army-knife aspects, since that's another powerful fuse box in a living system. The number of indications that a beta-blocker like propanolol has seen is enough evidence on its own!
C&E News did a drug repurposing story a couple of years ago, and included a table of examples. Some others can be found in this Nature Reviews Drug Discovery paper from 2004. I'm not aware of any new repurposing/repositioning approvals since then, but there's an awful lot of preclinical and clinical activity going on.
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August 27, 2014
Here is the updated version of the "smallest drugs" collection that I did the other day. Here are the criteria I used: the molecular weight cutoff was set, arbitrarily, at aspirin's 180. I excluded the inhaled anaesthetics, only allowing things that are oils or solids in their form of use. As a small-molecule organic chemist, I only allowed organic compounds - lithium and so on are for another category. And the hardest one was "Must be in current use across several countries". That's another arbitrary cutoff, but it excludes pemoline (176), for example, which has basically been removed from the market. It also gets rid of a lot of historical things like aminorex. That's not to say that there aren't some old drugs on the remaining list, but they're still in there pitching (even sulfanilamide, interestingly). I'm sure I've still missed a few.
What can be learned from this exercise? Well, take a look at those structures. There sure are a lot of carboxylic acids and phenols, and a lot more sulfur than we're used to seeing. And pretty much everything is polar, very polar, which makes sense: if you're down in this fragment-sized space, you've got to be making some strong interactions with biological targets. These are fragments that are also drugs, so fragment-based drug discovery people may find this interesting as the bedrock layer of the whole field.
Some of these are pretty specialized and obscure - you're only going to see pralidoxime if you have the misfortune to be exposed to nerve gas, for example. But there are some huge, huge compounds on the list, too, gigantic sellers that have changed their whole therapeutic areas and are still in constant use. Metformin alone is a constant rebuke to a lot of our med-chem prejudices: who among us, had we never heard of it, would not have crossed it off our lists of screening hits? So give these small things a chance, and keep an open mind. They're real, and they can really be drugs.
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August 26, 2014
There have been several analyses that have suggested that phenotypic drug discovery was unusually effective in delivering "first in class" drugs. Now comes a reworking of that question, and these authors (Jörg Eder, Richard Sedrani, and Christian Wiesmann of Novartis) find plenty of room to question that conclusion.
What they've done is to deliberately focus on the first-in-class drug approvals from 1999 to 2013, and take a detailed look at their origins. There have been 113 such drugs, and they find that 78 of them (45 small molecules and 33 biologics) come from target-based approaches, and 35 from "systems-based" approaches. They further divide the latter into "chemocentric" discovery, based around known pharmacophores, and so on, versus pure from-the-ground-up phenotypic screening, and the 33 systems compounds then split out 25 to 8.
As you might expect, a lot of these conclusions depend on what you classify as "phenotypic". The earlier paper stopped at the target-based/not target-based distinction, but this one is more strict: phenotypic screening is the evaluation of a large number of compounds (likely a random assortment) against a biological system, where you look for a desired phenotype without knowing what the target might be. And that's why this paper comes up with the term "chemocentric drug discovery", to encompass isolation of natural products, modification of known active structures, and so on.
Such conclusions also depend on knowing what approach was used in the original screening, and as everyone who's written about these things admits, this isn't always public information. The many readers of this site who've seen a drug project go from start to finish will appreciate how hard it is to find an accurate retelling of any given effort. Stuff gets left out, forgotten, is un- (or over-)appreciated, swept under the rug, etc. (And besides, an absolutely faithful retelling, with every single wrong turn left in, would be pretty difficult to sit through, wouldn't it?) At any rate, by the time a drug reaches FDA approval, many of the people who were present at the project's birth have probably scattered to other organizations entirely, have retired or been retired against their will, and so on.
But against all these obstacles, the authors seem to have done as thorough a job as anyone could possibly do. So looking further at their numbers, here are some more detailed breakdowns. Of those 45 first-in-class small molecules, 21 were from screening (18 of those high-throughput screening, 1 fragment-based, 1 in silico, and one low-throughput/directed screening). 18 came from chemocentric approaches, and 6 from modeling off of a known compound.
Of the 33 systems-based drugs, those 8 that were "pure phenotypic" feature one antibody (alemtuzumab) which was raised without knowledge of its target, and seven small molecules: sirolimus, fingolimod, eribulin, daptomycin, artemether–lumefantrine, bedaquiline and trametinib. The first three of those are natural products, or derived from natural products. Outside of fingolimod, all of them are anti-infectives or antiproliferatives, which I'd bet reflects the comparative ease of running pure phenotypic assays with those readouts.
Here are the authors on the discrepancies between their paper and the earlier one:
At first glance, the results of our analysis appear to significantly deviate from the numbers previously published for first-in-class drugs, which reported that of the 75 first-in-class drugs discovered between 1999 and 2008, 28 (37%) were discovered through phenotypic screening, 17 (23%) through target-based approaches, 25 (33%) were biologics and five (7%) came from other approaches. This discrepancy occurs for two reasons. First, we consider biologics to be target-based drugs, as there is little philosophical distinction in the hypothesis driven approach to drug discovery for small-molecule drugs versus biologics. Second, the past 5 years of our analysis time frame have seen a significant increase in the approval of first-in-class drugs, most of which were discovered in a target-based fashion.
Fair enough, and it may well be that many of us have been too optimistic about the evidence for the straight phenotypic approach. But the figure we don't have (and aren't going to get) is the overall success rate for both techniques. The number of target-based and phenotypic-based screening efforts that have been quietly abandoned - that's what we'd need to have to know which one has the better delivery percentage. If 78/113 drugs, 69% of the first-in-class approvals from the last 25 years, have come from target-based approaches how does that compare with the total number of first-in-class drug projects? My own suspicion is that target-based drug discovery has accounted for more than 70% of the industry's efforts over that span, which would mean that systems-based approaches have been relatively over-performing. But there's no way to know this for sure, and I may just be coming up with something that I want to hear.
That might especially be true when you consider that there are many therapeutic areas where phenotypic screening basically impossible (Alzheimer's, anyone?) But there's a flip side to that argument: it means that there's no special phenotypic sauce that you can spread around, either. The fact that so many of those pure-phenotypic drugs are in areas with such clear cellular readouts is suggestive. Even if phenotypic screeningwere to have some statistical advantage, you can't just go around telling people to be "more phenotypic" and expect increased success, especially outside anti-infectives or antiproliferatives.
The authors have another interesting point to make. As part of their analysis of these 113 first-in-class drugs, they've tried to see what the timeline is from the first efforts in the area to an approved drug. That's not easy, and there are some arbitrary decisions to be made. One example they give is anti-angiogenesis. The first report of tumors being able to stimulate blood vessel growth was in 1945. The presence of soluble tumor-derived growth factors was confirmed in 1968. VEGF, the outstanding example of these, was purified in 1983, and was cloned in 1989. So when did the starting pistol fire for drug discovery in this area? The authors choose 1983, which seems reasonable, but it's a judgment call.
So with all that in mind, they find that the average lead time (from discovery to drug) for a target-based project is 20 years, and for a systems-based drug it's been 25 years. They suggest that since target-based drug discovery has only been around since the late 1980s or so, that its impact is only recently beginning to show up in the figures, and that it's in much better shape than some would suppose.
The data also suggest that target-based drug discovery might have helped reduce the median time for drug discovery and development. Closer examination of the differences in median times between systems-based approaches and target-based approaches revealed that the 5-year median difference in overall approval time is largely due to statistically significant differences in the period from patent publication to FDA approval, where target-based approaches (taking 8 years) took only half the time as systems-based approaches (taking 16 years). . .
The pharmaceutical industry has often been criticized for not being sufficiently innovative. We think that our analysis indicates otherwise and perhaps even suggests that the best is yet to come as, owing to the length of time between project initiation and launch, new technologies such as high-throughput screening and the sequencing of the human genome may only be starting to have a major impact on drug approvals. . .
Now that's an optimistic point of view, I have to say. The genome certainly still has plenty of time to deliver, but you probably won't find too many other people saying in 2014 that HTS is only now starting to have an impact on drug approvals. My own take on this is that they're covering too wide a band of technologies with such statements, lumping together things that have come in at different times during this period and which would be expected to have differently-timed impacts on the rate of drug discovery. On the other hand, I would like this glass-half-full view to be correct, since it implies that things should be steadily improving in the business, and we could use it.
But the authors take pains to show, in the last part of their paper, that they're not putting down phenotypic drug discovery. In fact, they're calling for it to be strengthened as its own discipline, and not (as they put it) just as a falling back to the older "chemocentric" methods of the 1980s and before:
Perhaps we are in a phase today similar to the one in the mid-1980s, when systems-based chemocentric drug discovery was largely replaced by target-based approaches. This allowed the field to greatly expand beyond the relatively limited number of scaffolds that had been studied for decades and to gain access to many more pharmacologically active compound classes, providing a boost to innovation. Now, with an increased chemical space, the time might be right to further broaden the target space and open up new avenues. This could well be achieved by investing in phenotypic screening using the compound libraries that have been established in the context of target-based approaches. We therefore consider phenotypic screening not as a neoclassical approach that reverts to a supposedly more successful systems-based method of the past, but instead as a logical evolution of the current target-based activities in drug discovery. Moreover, phenotypic screening is not just dependent on the use of many tools that have been established for target-based approaches; it also requires further technological advancements.
That seems to me to be right on target: we probably are in a period just like the mid-to-late 1980s. In that case, though, a promising new technology was taking over because it seemed to offer so much more. Today, it's more driven by disillusionment with the current methods - but that means, even more, that we have to dig in and come up with some new ones and make them work.
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August 25, 2014
Mentioning such a small compound as pirfenidone prompts me to put up the graphic shown below: these are the smallest commonly used drugs that I can think of. (OK, there's cocaine as a nasal anaesthetic - no, really - but that's where I draw the line at "commonly used". Nominations for ones that I've missed are welcome, and I'll update the list as needed. Note: four more have been added since the initial post, with more to come. This sort of thing really makes a chemist think, though - some of these compounds are very good indeed at what they do, and have been wildly successful. We need to keep an open mind about small molecules, that's for sure, no matter how small they are.
Update: see this follow-up post for the latest version of the graphic.
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August 22, 2014
Science has an article by journalist Ken Garber on palbociclib, the Pfizer CDK4 compound that came up here the other day when we were discussing their oncology portfolio. You can read up on the details of how the compound was put in the fridge for several years, only to finally emerge as one of the company's better prospects. The roots of the project go back to about 1995 at Parke-Davis:
Because the many CDK family members are almost identical, “creating a truly selective CDK4 inhibitor was very difficult,” says former Parke-Davis biochemist Dave Fry, who co-chaired the project with chemist Peter Toogood. “A lot of pharmaceutical companies failed at it, and just accepted broad-spectrum CDK inhibitors as their lead compounds.” But after 6 years of work, the pair finally succeeded with the help of some clever screens that could quickly weed out nonspecific “dirty” compounds.
Their synthesis in 2001 of palbociclib, known internally as PD-0332991, was timely. By then, many dirty CDK inhibitors from other companies were already in clinical trials, but they worked poorly, if at all. Because they hit multiple CDK targets, these compounds caused too much collateral damage to normal cells. . .Eventually, most efforts to fight cancer by targeting the cell cycle ground to a halt. “Everything sort of got hung up, and I think people lost enthusiasm,” Slamon says.
PD-0332991 fell off the radar screen. Pfizer, which had acquired Warner-Lambert/Parke-Davis in 2000 mainly for the cholesterol drug Lipitor, did not consider the compound especially promising, Fry says, and moved it forward haltingly at best. “We had one of the most novel compounds ever produced,” Fry says, with a mixture of pride and frustration. “The only compound in its class.”
A major merger helped bury the PD-0332991 program. In 2003, Pfizer acquired Swedish-American drug giant Pharmacia, which flooded Pfizer's pipeline with multiple cancer drugs, all competing for limited clinical development resources. Organizational disarray followed, says cancer biologist Dick Leopold, who led cancer drug discovery at the Ann Arbor labs from 1989 to 2003. “Certainly there were some politics going on,” he says. “Also just some logistics with new management and reprioritization again and again.” In 2003, Pfizer shut down cancer research in Ann Arbor, which left PD-0332991 without scientists and managers who could demand it be given a chance, Toogood says. “All compounds in this business need an advocate.”
So there's no doubt that all the mergers and re-orgs at Pfizer slowed this compound down, and no doubt a long list of others, too. The problems didn't end there. The story goes on to show how the compound went into Phase I in 2004, but only got into Phase II in 2009. The problem is, well before that time it was clear that there were tumor types that should be more sensitive to CDK4 inhibition. See this paper from 2006, for example (and there were some before this as well).
It appears that Pfizer wasn't going to develop the compound at all (thus that long delay after Phase I). They made it available as a research tool to Selina Chen-Kiang at Weill Cornell, who saw promising results with mantle cell lymphoma, then Dennis Slamon and RIchard Finn at UCLA profiled the compound in breast cancer lines and took it into a small trial there, with even more impressive results. And at this point, Pfizer woke up.
Before indulging in a round of Pfizer-bashing, though, It's worth remembering that stories broadly similar to this are all too common. If you think that the course of true love never did run smooth, you should see the course of drug development. Warner-Lambert (for example) famously tried to kill Lipitor more than once during its path to the market, and it's a rare blockbuster indeed that hasn't passed through at least one near-death-experience along the way. It stands to reason: since the great majority of all drug projects die, the few that make it through are the ones that nearly died.
There are also uncounted stories of drugs that nearly lived. Everyone who's been around the industry for a while has, or has heard, tales of Project X for Target Y, which was going along fine and looked like a winner until Company Z dropped for Stupid Reason. . .uh, Aleph. (Ran out of letters there). And if only they'd realized this, that, and the other thing, that compound would have made it to market, but no, they didn't know what they had and walked away from it, etc. Some of these stories are probably correct: you know that there have to have been good projects dropped for the wrong reasons and never picked up again. But they can't all be right. Given the usual developmental success rates, most of these things would have eventually wiped out for some reason. There's an old saying among writers that the definition of a novel is a substantial length of narrative fiction that has something wrong with it. In the same way, every drug that's on the market has something wrong with it (usually several things), and all it takes is a bit more going wrong to keep it from succeeding at all.
So where I fault Pfizer in all this is in the way that this compound got lost in all the re-org shuffle. If it had developed more normally, its activity would have been discovered years earlier. Now, it's not like there are dozens of drugs that haven't made it to market because Pfizer dropped the ball on them - but given the statistics, I'll bet that there are several (two or three? five?) that could have made it through by now, if everyone hadn't been so preoccupied with merging, buying, moving, rearranging, and figuring out if they were getting laid off or not.
The good thing is that other companies stepped into the field on the basis of those earlier publications, and found CDK4/6 inhibitors of their own (notably Novartis and Lilly). This is why I think that huge mergers hurt the intellectual health of the drug industry. Take it to the reducio ad not all that absurdum of One Big Drug Company. If we had that, and only that, then whole projects and areas of research would inevitably get shelved, and there would be no one left to pick them up at all. (I'll also note, in passing, that should all of the CDK inhibitors make it to market, that there will be yahoos who decry the whole thing as nothing but a bunch of fast-follower me-too drugs, waste of time and money, profits before people, and so on. Watch for it.)
+ TrackBacks (0) | Category: Cancer | Drug Development | Drug Industry History
August 20, 2014
John LaMattina has a look at Pfizer's oncology portfolio, and what their relentless budget-cutting has been doing to it. The company is taking some criticism for having outlicensed two compounds (tremelimumab to AstraZeneca and neratinib to Puma) which seem to be performing very well after Pfizer ditched them. Here's LaMattina (a former Pfizer R&D head, for those who don't know):
Unfortunately, over 15 years of mergers and severe budget cuts, Pfizer has not been able to prosecute all of the compounds in its portfolio. Instead, it has had to make choices on which experimental medicines to keep and which to set aside. However, as I have stated before, these choices are filled with uncertainties as oftentimes the data in hand are far from complete. But in oncology, Pfizer seems to be especially snake-bit in the decisions it has made.
That goes for their internal compounds, too. As LaMattina goes one to say, palbociclib is supposed to be one of their better compounds, but it was shelved for several years due to more budget-cutting and the belief that the effort would be better spent elsewhere. It would be easy for an outside observer to whack away at the company and wonder how incompetent they could be to walk away from all these winners, but that really isn't fair. It's very hard in oncology to tell what's going to work out and what isn't - impossible, in fact, after compounds have progressed to a certain stage. The only way to be sure is to take these things on into the clinic and see, unfortunately (and there you have one of the reasons things are so expensive around here).
Pfizer brought up more interesting compounds than it later was able to develop. It's a good question to wonder what they could have done with these if they hadn't been pursuing their well-known merger strategy over these years, but we'll never know the answer to that one. The company got too big and spent too much money, and then tried to cure that by getting even bigger. Every one of those mergers was a big disruption, and you sometimes wonder how anyone kept their focus on developing anything. Some of its drug-development choices were disastrous and completely their fault (the Exubera inhaled-insulin fiasco, for example), but their decisions in their oncology portfolio, while retrospectively awful, were probably quite defensible at the time. But if they hadn't been occupied with all those upheavals over the last ten to fifteen years, they might have had a better chance on focusing on at least a few more of their own compounds.
Their last big merger was with Wyeth. If you take Pfizer's R&D budget and Wyeth's and add them, you don't get Pfizer's R&D post-merger. Not even close. Pfizer's R&D is smaller now than their budget was alone before the deal. Pyrrhus would have recognized the problem.
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July 30, 2014
It's not the most cheerful topic in the world, but NPR recently had an item on the decommissioned pharma research sites of New Jersey (of which there are many). Some of these are quite large, and correspondingly hard to unload onto anyone else. (This is, of course, a problem that is not unique to New Jersey, with plenty of ex-pharma sites around the US and the UK in particular falling into this category).
I got to see this in an earlier and less severe form when I worked at Schering-Plough: the company's old Bloomfield site proved difficult to deal with in the early 1990s once everyone had moved out of it. No other company (large or small) wanted it, and I was told that an attempt to more or less donate it to Rutgers University had fallen through as well. In the end, the buildings were demolished and the land was sold, with a Home Depot (and its parking lot) taking up a good part of the space.
That's always one option. Another is what happened to my next stop in pharma, the Bayer campus at West Haven. Yale picked that one up for what we heard was a good price, and turned it into the Yale West Research Campus. So that at least keeps the place doing research, which has to beat turning it into a hardware store. Breaking things up into an incubator for smaller companies is a good plan, too, when it can be done.
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July 25, 2014
Here's a business-section column at the New York Times on the problem of antibiotic drug discovery. To those of us following the industry, the problems of antibiotic drug discovery are big pieces of furniture that we've lived with all our lives; we hardly even notice if we bump into them again. You'd think that readers of the Times or other such outlets would have come across the topic a few times before, too, but there must always be a group for which it's new, no matter how many books and newspaper articles and magazine covers and TV segments are done on it. It's certainly important enough - there's no doubt that we really are going to be in big trouble if we don't keep up the arms race against the bacteria.
This piece takes the tack of "If drug discovery is actually doing OK, where are the new antibiotics?" Here's a key section:
Antibiotics face a daunting proposition. They are not only becoming more difficult to develop, but they are also not obviously profitable. Unlike, say, cancer drugs, which can be spectacularly expensive and may need to be taken for life, antibiotics do not command top dollar from hospitals. What’s more, they tend to be prescribed for only short periods of time.
Importantly, any new breakthrough antibiotic is likely to be jealously guarded by doctors and health officials for as long as possible, and used only as a drug of last resort to prevent bacteria from developing resistance. By the time it became a mass-market drug, companies fear, it could be already off patent and subject to competition from generics that would drive its price down.
Antibiotics are not the only drugs getting the cold shoulder, however. Research on treatments to combat H.I.V./AIDS is also drying up, according to the research at Yale, mostly because the cost and time required for development are increasing. Research into new cardiovascular therapies has mostly stuck to less risky “me too” drugs.
This mixes several different issues, unfortunately, and if a reader doesn't follow the drug industry (or medical research in general), then they may well not realize this. (And that's the most likely sort of reader for this article - people who do follow such things have heard all of this before). The reason that cardiovascular drug research seems to have waned is that we already have a pretty good arsenal of drugs for the most common cardiovascular conditions. There are a huge number of options for managing high blood pressure, for example, and they're mostly generic drugs by now. The same goes for lowering LDL: it's going to be hard to beat the statins, especially generic Lipitor. But there is a new class coming along targeting PCSK9 that is going to try to do just that. This is a very hot area of drug development (as the author of the Times column could have found without much effort), although the only reason it's so big is that PCSK9 is the only pathway known that could actually be more effective at lowering LDL than the statins. (How well it does that in the long term, and what the accompanying safety profile might be, are the subject of ongoing billion-dollar efforts). The point is, the barriers to entry in cardiovascular are, by now, rather high: a lot of good drugs are known that address a lot of the common problems. If you want to go after a new drug in the space, you need a new mechanism, like PCSK9 (and those are thin on the ground), or you need to find something that works against some of the unmet needs that people have already tried to fix and failed (such as stroke, a notorious swamp of drug development which has swallowed many large expeditions without a trace).
To be honest, HIV is a smaller-scale version of the same thing. The existing suite of therapies is large and diverse, and keeps the disease in check in huge numbers of patients. All sorts of other mechanisms have been tried as well, and found wanting in the development stage. If you want to find a new drug for HIV, you have a very high entry barrier again, because pretty most of the reasonable ways to attack the problem have already been tried. The focus now is on trying to "flush out" latent HIV from cells, which might actually lead to a cure. But no one knows yet if that's feasible, how well it will work when it's tried, or what the best way to do it might be. There were headlines on this just the other day.
The barriers to entry in the antibiotic field area similarly high, and that's what this article seems to have missed completely. All the known reasonable routes of antibiotic action have been thoroughly worked over by now. As mentioned here the other day, if you just start screening your million-compound libraries against bacteria to see what kills them, you will find a vast pile of stuff that will kill your own cells, too, which is not what you want, and once you've cleared those out, you will find a still-pretty-vast pile of compounds that work through mechanisms that we already have antibiotics targeting. Needles in haystacks have nothing on this.
In fact, a lot of not-so-reasonable routes have been worked over, too. I keep sending people to this article, which is now seven years old and talks about research efforts even older than that. It's the story of GlaxoSmithKline's exhaustive antibiotics research efforts, and it also tells you how many drugs they got out of it all in the end: zip. Not a thing. From what I can see, the folks who worked on this over the last fifteen or twenty years at AstraZeneca could easily write the same sort of article - they've published all kinds of things against a wide variety of bacterial targets, and I don't think any of it has led to an actual drug.
This brings up another thing mentioned in the Times column. Here's the quote:
This is particularly striking at a time when the pharmaceutical industry is unusually optimistic about the future of medical innovation. Dr. Mikael Dolsten, who oversees worldwide research and development at Pfizer, points out that if progress in the 15 years until 2010 or so looked sluggish, it was just because it takes time to figure out how to turn breakthroughs like the map of the human genome into new drugs.
Ah, but bacterial genomes were sequenced before the human one was (and they're more simple, at that). Keep in mind also that proof-of-concept for new targets can be easier to obtain in bacteria (if you manage to find any chemical matter, that is). I well recall talking with a bunch of people in 1997 who were poring over the sequence data for a human pathogen, fresh off the presses, and their optimism about all the targets that they were going to find in there, and the great new approaches they were going to be able to take. They tried it. None of it worked. Over and over, none of it worked. People had a head start in this area, genomically speaking, with an easier development path than many other therapeutic areas, and still nothing worked.
So while many large drug companies have exited antibiotic research over the years, not all of them did. But the ones that stayed have poured effort and money, over and over, down a large drain. Nothing has come out of the work. There are a number of smaller companies in the space as well, for whom even a small success would mean a lot, but they haven't been having an easy time of it, either.
Now, one thing the Times article gets right is that the financial incentives for new antibiotics are a different thing entirely than the rest of the drug discovery world. Getting one of these new approaches in LDL or HIV to work would at least be highly profitable - the PCSK9 competitors certainly are working on that basis. Alzheimer's is another good example of an area that has yielded no useful drugs whatsoever despite ferocious amounts of effort, but people keep at it because the first company to find a real Alzheimer's drug will be very well rewarded indeed. (The Times article says that this hasn't been researched enough, either, which makes me wonder what areas have been). But any great new antibiotic would be shelved for emergencies, and rightly so.
But that by itself is not enough to explain the shortage of those great new antibiotics. It's everything at once: the traditional approaches are played out and the genomic-revolution stuff has been tried, so the unpromising economics makes the search for yet another approach that much harder.
Note: be sure to see the comments for perspectives from others who've also done antibiotic research, including some who disagree. I don't think we'll find anyone who says it's easy, though, but you never know.
+ TrackBacks (0) | Category: Business and Markets | Drug Development | Drug Industry History | Infectious Diseases
July 15, 2014
K. C. Nicolaou has an article in the latest Angewandte Chemie on the future of drug discovery, which may seem a bit surprising, considering that he's usually thought of as Mister Total Synthesis, rather than Mister Drug Development Project. But I can report that it's relentlessly sensible. Maybe too sensible. It's such a dose of the common wisdom that I don't think it's going to be of much use or interest to people who are actually doing drug discovery - you've already had all these thoughts yourself, and more than once.
But for someone catching up from outside the field, it's not a bad survey at all. It gets across how much we don't know, and how much work there is to be done. And one thing that writing this blog has taught me is that most people outside of drug discovery don't have an appreciation of either of those things. Nicolaou's article isn't aimed at a lay audience, of course, which makes it a little more problematic, since many of the people who can appreciate everything he's saying will already know what he's going to say. But it does round pretty much everything up into one place.
+ TrackBacks (0) | Category: Drug Development | Drug Industry History
July 14, 2014
Here's an article from David Shayvitz at Forbes whose title says it all: "Should a Drug Discovery Team Ever Throw in the Towel?" The easy answer to that is "Sure". The hard part, naturally, is figuring out when.
You don’t have to be an expensive management consultant to realize that it would be helpful for the industry to kill doomed projects sooner (though all have said it).
There’s just the prickly little problem of figuring out how to do this. While it’s easy to point to expensive failures and criticize organizations for not pulling the plug sooner, it’s also true that just about every successful drug faced some legitimate existential crisis along the way — at some point during its development , there was a plausible reason to kill the program, and someone had to fight like hell to keep it going.
The question at the heart of the industry’s productivity struggles is the extent to which it’s even possible to pick the winners (or the losers), and figuring out better ways of managing this risk.
He goes on to contrast two approaches to this: one where you have a small company, focused on one thing, with the idea being that the experienced people involved will (A) be very motivated to find ways to get things to work, and (B) motivated to do something else if the writing ever does show up on the wall. The people doing the work should make the call. The other approach is to divide that up: you set things up with a project team whose mandate is to keep going, one way or another, dealing with all obstacles as best they can. Above them is a management team whose job it is to stay a bit distant from the trenches, and be ready to make the call of whether the project is still viable or not.
As Shayvitz goes on to say, quite correctly, both of these approaches can work, and both of them can run off the rails. In my view, the context of each drug discovery effort is so variable that it's probably impossible to say if one of these is truly better than the other. The people involved are a big part of that variability, too, and that makes generalizing very risky.
The big risk (in my experience) with having execution and decision-making in the same hands is that projects will run on for too long. You can always come up with more analogs to try, more experiments to run, more last-ditch efforts to take a crack it. Coming up with those things is, I think, better than not coming up with them, because (as Shayvitz mentions) it's hard to think of a successful drug that hasn't come close to dying at least once during its development. Give up too easily, and nothing will ever work at all.
But it's a painful fact that not every project can work, no matter how gritty and determined the team. We're heading out into the unknown with these drug candidates, and we find out things that we didn't know were there to be found out. Sometimes there really is no way to get the selectivity you need with the compound series you've chosen - heck, sometimes there's no way to get it with any compound series you could possibly choose, although that takes a long time to become obvious. Sometimes the whole idea behind the project is flawed from the start: blocking Kinase X will not, in fact, alter the course of Disease Y. It just won't. The hypothesis was wrong. An execute-at-all-costs team will shrug off these fatal problems, or attempt to shrug them off, for as long as you give them money.
But there's another danger waiting when you split off the executive decision-makers. If those folks get too removed from the project (or projects) then their ability to make good decisions is impaired. Just as you can have a warped perspective when you're right on top of the problems, you can have one when you're far away from them, too. It's tempting to thing that Distance = Clarity, but that's not a linear function, by any means. A little distance can certainly give you a lot of perspective, but if you keep moving out, things can start fuzzing back up again without anyone realizing what's going on.
That's true even if the managers are getting reasonably accurate reports, and we all know that that's not always the case in the real world. In many large organizations, there's a Big Monthly Meeting of some sort (or at some other regular time point) where projects are supposed to be reviewed by just those decision makers. These meetings are subject to terrible infections of Dog-And-Pony-itis. People get up to the front of the room and they tell everyone how great things are going. They minimize the flaws and paper over the mistakes. It's human nature. Anyone inclined to give a more accurate picture has a chance to see how that's going to look, when all the other projects are going Just Fine and everyone's Meeting Their Goals like it says on the form. Over time (and it may not take much time at all), the meeting floats away into its own bubble of altered reality. Managers who realize this can try to counteract it by going directly to the person running the project team in the labs, closing the office door, and asking for a verbal update on how things are really going, but sometimes people are so out of it that they mistake how things are going at the Big Monthly Meeting for what's really happening.
So yes indeed, you can (as is so often the case) screw things up in both directions. That's what makes it so hard to law down the law about how to run a drug discovery project: there are several ways to succeed, and the ways to mess them up are beyond counting. My own bias? I prefer the small-company back-to-the-wall approach, of being ready to swerve hard and try anything to make a project work. But I'd only recommend applying that to projects with a big potential payoff - it seems silly to do that sort of thing for anything less. And I'd recommend having a few people watching the process, but from as close as they can get without being quite of the project team themselves. Just enough to have some objectivity. Simple, eh? Getting this all balanced out is the hard part. Well, actually, the science is the hard part, but this is the hard part that we can actually do something about.
+ TrackBacks (0) | Category: Drug Development | Drug Industry History | Life in the Drug Labs
May 23, 2014
Matthew Herper has a really interesting story in Forbes on a new report that attempts to rank biopharma companies by their R&D abilities. Richard Evans of Sector and Sovereign Health (ex-Roche) has ranked companies not on their number of drugs, but on their early-stage innovation. He counts patents, for example, but not the later ones defending existing franchises, and he also looks to see how often these patents are cited by others. As for a company's portfolio, being early into a new therapeutic area counts for a lot more than following someone else, but at the same time, he's also trying to give points for companies that avoid "Not Invented Here" behavior (a tricky balance, I'd think). The full report can be purchased, but the parts that Herper have shared are intriguing.
Ranking the companies, he has (1) Bristol-Myers Squibb, (2) Celgene, (3) Vertex, (4) Gilead, and (5) Allergan. (Note that Allergan is currently being pursued by Valeant, who will, if they buy them, pursue their sworn vow to immediately gut the company's R&D). At the bottom of his table are (18) Novartis, (19) Regeneron, (20) Bayer, (21) Lilly, and (22) Alexion. (Note that Evans himself says that his analysis may be off for companies that have only launched one product in the ten years he's covering). I'm not sure what to make of this, to be honest, and I think what would give a better picture would be if the whole analysis were done again but only with the figures from about fifteen years ago to see if what's being measured really had an effect on the futures of the various companies. That would not be easy, but (as some of Herper's sources also say), without some kind of back-testing, it's hard to say if there's something valuable here.
You can tell that Evans himself almost certainly appreciates this issue from what he has to say about the current state of the industry and the methods used to evaluate it, so the lack of a retrospective analysis is interesting. Here's the sort of thing I mean:
Too often, Evans says, pharmaceutical executives instead use the industry’s low success rates as an argument that success is right around the corner. “A gambler that has lost everything he owned, just because he now has a strong hand doesn’t make him a good gambler,” Evans says. . .
True enough. Time and chance do indeed happeneth to them all, and many are the research organizations who've convinced themselves that they're good when they might just have been lucky. (Bad luck, on the other hand, while not everyone's favorite explanation, is still trotted out a lot more often. I suspect that AstraZeneca, during that bad period they've publicly analyzed, was sure that they were just having a bad run of the dice. After all, I'm sure that some of the higher-ups there thought that they were doing everything right, so what else could it be?)
But there's a particular chart from this report that I want to highlight. This one (in case that caption is too small) plots ten-year annualized net income returns against R&D spending, minus the cost of R&D capital. Everything has been adjusted for taxes and inflation. And that doesn't look too good, does it? These numbers would seem to line up with Bernard Munos' figures showing that industry productivity has been relatively constant, but only by constantly increased spending per successful drug. They also fit with this 2010 analysis from Morgan Stanley, where they warned that the returns on invested capital in pharma were way too high, considering the risks of failure.
So in case you thought, for some reason - food poisoning, concussion - that things had turned around, no such luck, apparently. That brings up this recent paper in Nature Reviews Drug Discovery, though, where several authors from Boston Consulting Group try to make the case that productivity is indeed improving. They're used peak sales as their measure of success, and they also believe that 2008 was the year when R&D spending started to get under control.
Before 2008, the combined effects of declining value outputs and ever-increasing R&D spending drove a rapid decline in R&D productivity, with many analysts questioning whether the industry as a whole would be able to return its cost of capital on R&D spending. . .we have analysed the productivity ratio of aggregate peak sales relative to R&D spending in the preceding 4 years. From a low of 0.12 in 2008, this has more than doubled to 0.29 in 2013. Through multiple engagements with major companies, we have observed that at a relatively steady state of R&D spending across the value chain, a productivity ratio of between 0.25 and 0.35 is required for a drug developer to meet its cost of capital of ~9%. Put simply, a company spending $1 billion annually on R&D needs to generate — on average — new drug approvals with $250–350 million in peak sales every year. . . So, although not approaching the productivity ratios of the late 1990s and early 2000s, the industry moved back towards an acceptable productivity ratio overall in 2013.
I would like to hope that this is correct, but I'm really not sure. This recent improvement doesn't look like much, graphically, compared to the way that things used to be. There's also a real disagreement between these two analyses, which is apparent even though the BCG chart only goes back to 1994. Its take on the mid-1990s looks a lot better than the Evans one, and this is surely due (at least partly) to the peak-sales method of evaluation. Is that a better metric, or not? You got me. One problem with it (as the authors of this paper also admit) is that you have to use peak-sale estimates to arrive at the recent figures. So with that level of fuzz in the numbers, I don't know if their chart shows recent improvement at all (as they claim), or how much.
But even the BCG method would say that the industry has not been meeting its cost-of-capital needs for the last ten years or so, which is clearly not how you want to run things. If they're right, and the crawl out of the swamp has begun, then good. But I don't know why we should have managed to do that since 2008; I don't think all that much has changed. My fear is that their numbers show an improvement because of R&D cuts, in which case, we're likely going to pay for those in a few years with a smaller number of approved drugs - because, again, I don't think anyone's found any new formula to spend the money more wisely. We shall see.
+ TrackBacks (0) | Category: Business and Markets | Drug Development | Drug Industry History
May 20, 2014
I occasionally talk about the ecosystem of the drug industry being harmed by all the disruptions of recent years, and this post by Bruce Booth is exactly the sort of thing that fits that category. He's talking about how much time it takes to get experience in this field, and what's been happening to the flow of people:
Two recent events sparked my interest in this topic of where young talent develops and emerges in our industry. A good friend and “greybeard” med chemist forwarded me a note from a chemistry professor who was trying to find a spot for his “best student”, a new PhD chemist. I said we tended to not hire new graduates into our portfolio, but was saddened to hear of this start pupil’s job challenge. Shortly after that, I had dinner with a senior chemist from Big Pharma. He said the shortest-tenured chemist on his 30+ person team was 15-year veteran. His group had shrunk in the past and had never rehired. Since hiring a “trainee” post-doc chemist “counted” as an FTE on their books, they haven’t even implemented the traditional fellowship programs that exist elsewhere. Stories like these abound.
There is indeed a steady stream of big-company veterans who depart for smaller biopharma, bringing with them their experience (and usually a desire not to spend all their time holding pre-meeting meetings and the like, fortunately). But Booth is worried about a general talent shortage that could well be coming:
The short version of the dilemma is this: biotech startups have no margin for error around very tight timelines so can’t really “train” folks in drug discovery, and because of that they rely on bigger companies as the principle source for talent; but, at the same time, bigger firms are cutting back on research hiring and training, in part while offshoring certain science roles to other geographies, and yet are looking “outside” their walls for innovation from biotechs.
While I’d argue this talent flux is fine and maybe a positive right now, it’s a classic “chicken and egg” problem for the future. Without training in bigger pharma, there’s less talent for biotech; without that talent, biotech won’t make good drugs; without good biotech drugs, there’s no innovation for pharma, and then the end is nigh.
So if Big Pharma is looking for people from the small companies while the smaller companies are looking for people from Big Pharma, it does make you wonder where the supply will eventually come from. I share some of these worries, but at the same time, I think that it's possible to learn on the job at a smaller company, in the lower-level positions, anyway. And not everyone who's working at a larger company is learning what they should be. I remember once at a previous job when we were bringing in a med-chem candidate from a big company, a guy with 8 or 9 years experience. We asked him how he got along with the people who did the assays for his projects, and he replied that well, he didn't see them much, because they were over in another building, and they weren't supposed to be hanging around there, anyway. OK, then, what about the tox or formulations people? Well, he didn't go to those meetings much, because that was something that his boss was supposed to be in charge of. And so on, and so on. What was happening was that the structure of his company was gradually crippling this guy's career. He should have known more than he did; he should have been more experienced than he really was, and the problem looked to be getting worse every year. There's plenty of blame to go around, though - not only was the structure of his research organization messing this guy up, but he himself didn't even seem to be noticing it, which was also not a good sign. This is what Booth is talking about here:
. . .the “unit of work” in drug R&D is the team, not the individual, and success is less about single expertise and more about how it gets integrated with others. In some ways, your value to the organization begins to correlate with more generalist, integrative skills rather than specialist, academic ones; with a strong R&D grounding, this “utility player” profile across drug discovery becomes increasingly valuable.
And its very hard to learn these hard and soft things, i.e., grow these noses, inside of a startup environment with always-urgent milestones to hit in order to get the next dollop of funding, and little margin of error in the plan to get there. This is true in both bricks-and-mortar startups and virtual ones.
With the former, these lab-based biotechs can spin their wheels inefficiently if they hire too heavily from academia – the “book smart” rather than “research-street smart” folks. It’s easy to keep churning out experiments to “explore” the science – but breaking the prevailing mindset of “writing the Nature paper” versus “making a drug” takes time, and this changes what experiments you do. . .
Bruce took a poll of the R&D folks associated with his own firm's roster of startups, and found that almost all of them were trained at larger companies, which certainly says something. I wonder, though, if this current form of the ecosystem is a bit of an artifact. Times have been so tough the last ten to fifteen years that there may well be a larger proportion of big-company veterans who have made the move to smaller firms, either by choice or out of necessity. (In a similar but even more dramatic example, the vast herds of buffalo and flocks of passenger pigeons described in the 19th century were partly (or maybe largely) due to the disruption of the hunting patterns of the American Indians, who had been displaced and quite literally decimated by disease - see the book 1491 for more on this).
The other side of all this, as mentioned above, is the lack of entry-level drug discovery positions in the bigger companies. Many readers here have mentioned this over the last few years, that the passing on of knowledge and experience from the older researchers to the younger ones has been getting thoroughly disrupted (as the older ones get laid off and the younger ones don't get hired). We don't want to find ourselves in the position of Casey Stengel, looking at his expansion-team Mets and asking "Don't anybody here know how to play this game?"
Booth's post has a few rays of hope near the end - read the whole thing to find them. I continue to think that drug discovery is a valuable enough activity that the incentives will keep it alive in one form or another, but I also realize that that's no guarantee, either. We (and everyone else with a stake in the matter) have to realize that we could indeed screw it up, and that we might be well along the way to doing it.
+ TrackBacks (0) | Category: Academia (vs. Industry) | Drug Development | Drug Industry History | How To Get a Pharma Job
May 19, 2014
While we're talking about AstraZeneca, here's a look at their recent drug development history from the inside. The company had undertaken a complete review of its portfolio and success rates (as well they might, given how things have been going overall).
In this article, we discuss the results of a comprehensive longitudinal review of AstraZeneca's small-molecule drug projects from 2005 to 2010. The analysis allowed us to establish a framework based on the five most important technical determinants of project success and pipeline quality, which we describe as the five 'R's: the right target, the right patient, the right tissue, the right safety and the right commercial potential. A sixth factor — the right culture — is also crucial in encouraging effective decision-making based on these technical determinants. AstraZeneca is currently applying this framework to guide its R&D teams, and although it is too early to demonstrate whether this has improved the company's R&D productivity, we present our data and analysis here in the hope that it may assist the industry overall in addressing this key challenge.
That already gets things off to a bad start, in my opinion, because I really hate those alliterative "Five Whatevers" and "Three Thingies" that companies like to proclaim. And that's not just because Chairman Mao liked that stuff, although that is reason enough to wonder a bit. I think that I suffer from Catchy Slogan Intolerance, a general disinclination to believe that reality can be usefully broken down into discrete actions and principles that just all happen to start with the same letter. I think these catchphrases quantify the unquantifiable and simplify what shouldn't be simplified. The shorter, snappier, and more poster-friendly the list of recommendations, the less chance I think they have of being any actual use. Other than setting people's teeth on edge, which probably isn't the goal.
That said, this article itself does a perfectly good job of laying out many of the things that have been going wrong in the big pharma organizations. See if any of this rings a bell for you:
. . .However, with the development of high-throughput and ultra-high-throughput screening and combinatorial chemistry approaches during the 1980s and 1990s, as well as the perception that a wealth of new targets would emerge from genomics, part of this productivity issue can also be attributed to a shift of R&D organizations towards the 'industrialization' of R&D. The aim was to drive efficiency while retaining quality, but in some organizations this led to the use of quantity-based metrics to drive productivity. The hypothesis was simple: if one drug was launched for every ten candidates entering clinical development, then doubling or tripling the number of candidates entering development should double or triple the number of drugs approved. However, this did not happen; consequently, R&D costs increased while output — as measured by launched drugs — remained static.
This volume-based approach damaged not only the quality and sustainability of R&D pipelines but, more importantly, also the health of the R&D organizations and their underlying scientific curiosity. This is because the focus of scientists and clinicians moved away from the more demanding goal of thoroughly understanding disease pathophysiology and the therapeutic opportunities, and instead moved towards meeting volume-based goals and identifying an unprecedented level of back-up and 'me too' drug candidates. In such an environment, 'truth-seeking' behaviours to understand disease biology may have been over-ridden by 'progression-driven' behaviours that rewarded scientists for meeting numerical volume-based goals.
Thought so. Pause to shiver a bit (that's what I did - it seemed to help). The AZ team looked at everything that had been active during the 2005-2010 period, from early preclinical up to the end of Phase II. What they found, compared to the best figures on industry averages, was that the company looked pretty normal in the preclinical area (as measured by number of projects and their rates of progression, anyway), and that they actually had a higher-than-usual pass rate through Phase I. Phase II, though, was nasty - they had a noticeably higher failure rate, suggesting that too many projects were being allowed to get that far. And although they weren't explicitly looking looking beyond Phase II, the authors do note that AZ's success rate at getting drugs all the way to market was significantly lower than rest of the industry's as well.
The biggest problem seemed to be safety and tox. This led to many outright failures, and to other cases where the human doses ended up limited to non-efficacious levels.
During preclinical testing, 75% of safety closures were compound-related (that is, they were due to 'off-target' or other properties of the compound other than its action at the primary pharmacological target) as opposed to being due to the primary pharmacology of the target. By contrast, the proportion of target-related safety closures rose substantially in the clinical phase and was responsible for almost half of the safety-related project closures. Such failures were often due to a collapse in the predicted margins between efficacious doses and safety outcomes, meaning it was not possible to achieve target engagement or patient benefit without incurring an unacceptable safety risk.
On top of this problem, an unacceptable number of compounds that made it through safety were failing in Phase II though lack of efficacy. There's a good analysis of how this seems to have happened, but a big underlying factor seems to have been the desire to keep progressing compounds to meet various targets. People kept pushing things ahead, because things had to be pushed ahead, and the projects kept being scooting along the ground until they rolled off into one ravine or another.
And I think that everyone with some experience in this business will know exactly what that feels like - this is not some mysterious ailment that infected AstraZeneca, although they seem to have had a more thorough case of it than usual. Taking the time to work out what a safety flag might be telling you, understand tricky details of target engagement, or figure out the right patient population or the right clinical endpoint - these things are not always popular. And to be fair, there are a near-infinite number of reasons to slow a project down (or stop it altogether), and you can't stop all of them. But AZ's experience shows, most painfully, that you can indeed stop too few of them. Here's a particularly alarming example of that:
In our analysis, another example of the impact of volume-based goals could be seen in the strategy used to select back-up drug candidates. Back-up molecules are often developed for important projects where biological confidence is high. They should be structurally diverse to mitigate the risk for the programme against compound-related issues in preclinical or early development, and/or they should confer some substantial advantage over the lead molecule. When used well, this strategy can save time and maintain the momentum of a project. However, with scientists being rewarded for the numbers of candidates coming out of the research organization, we observed multiple projects for which back-up molecules were not structurally diverse or a substantial improvement over the lead molecule. Although all back-up candidates met the chemical criteria for progression into clinical testing, and research teams were considered to have met their volume-based goals, these molecules did not contribute to the de-risking of a programme or increase project success rates. As a consequence, all back-up candidates from a 'compound family' could end up failing for the same reason as the lead compound and indeed had no higher probability of a successful outcome than the original lead molecule (Fig. 6). In one extreme case, we identified a project with seven back-up molecules in the family, all of which were regarded as a successful candidate delivery yet they all failed owing to the same preclinical toxicology finding. This overuse of back-up compounds resulted in a highly disproportionate number of back-up candidates in the portfolio. At the time of writing, approximately 50% of the AstraZeneca portfolio was composed of back-up molecules.
I'm glad this paper exists, since it can serve as a glowing, pulsing bad example to other organizations (which I'm sure was the intention of its author, actually). This is clearly not the way to do things, but it's also easy for a big R&D effort to slip into this sort of behavior, while all the time thinking that it's doing the right things for the right reasons. Stay alert! The lessons are the ones you'd expect:
An underlying theme that ran through the interviews with our project teams was how the need to maintain portfolio volume led to individual and team rewards being tied to project progression rather than 'truth-seeking' behaviour. The scientists and clinicians within the project teams need to believe that their personal success and careers are not intrinsically linked to project progression but to scientific quality, smart risk-taking and good decision-making.
But this is not the low energy state of a big organization. This sort of behavior has to be specifically encouraged and rewarded, or it will disappear, to be replaced by. . .well, you all know what it's replaced by. The sort of stuff detailed in the paper, and possibly even worse. What's frustrating is that none of these are new problems that AZ had to discover. I can bring up my own evidence from twelve years ago, and believe me, I was late to the party complaining about this sort of thing. Don't ever think that it can't happen some more.
+ TrackBacks (0) | Category: Clinical Trials | Drug Development | Drug Industry History
May 15, 2014
A reader sent along news of this interview on "The Daily Show" with Martin Blaser of NYU. He has a book out, Missing Microbes, on the overuse of antibiotics and the effects on various microbiomes. And I think he's got a lot of good points - we should only be exerting selection pressure where we have to, not (for example) slapping triclosan on every surface because it somehow makes consumers feel "germ-free". And there are (and always have been) too many antibiotics dispensed for what turn out to be viral infections, for which they will, naturally, do no good at all and probably some harm.
But Dr. Blaser, though an expert on bacteria, does not seem to be an expert on discovering drugs to kill bacteria. I've generated a transcript of part of the interview, starting around the five-minute mark, which went like this:
Stewart: Isn't there some way, that, the antibiotics can be used to kill the strep, but there can be some way of rejuvenating the microbiome that was doing all those other jobs?
Blaser: Well, that's what we need to do. We need to make narrow-spectrum antibiotics. We have broad-spectrum, that attack everything, but we have the science that we could develop narrow-spectrum antibiotics that will just target the one organism - maybe it's strep, maybe it's a different organism - but then we need the diagnostics, so that somebody going to the doctor, they say "You have a virus" "You have a bacteria", if you have a bacteria, which one is it?
Stewart: Now isn't this where the genome-type projects are going? Because finding the genetic makeup of these bacteria, won't that allow us to target these things more specifically?
Blaser Yeah. We have so much genomic information - we can harness that to make better medicine. . .
Stewart: Who would do the thing you're talking about, come up with the targeted - is it drug companies, could it, like, only be done through the CDC, who would do that. . .
Blaser: That's what we need taxes for. That's our tax dollars. Just like when we need taxes to build the road that everybody uses, we need to develop the drugs that our kids and our grandkids are going to use so that these epidemics could be stopped.
Stewart: Let's say, could there be a Manhattan Project, since that's the catch-all for these types of "We're going to put us on the moon" - let's say ten years, is that a realistic goal?
Blaser: I think it is. I think it is. We need both diagnostics, we need narrow-spectrum agents, and we have to change the economic base of how we assess illness in kids and how we treat kids and how we pay doctors. . .
First off, from a drug discovery perspective, a narrow-spectrum antibiotic, one that kills only (say) a particular genus of bacterium, has several big problems: it's even harder to discover than a broader-spectrum agent, its market is much smaller, it's much harder to prescribe usefully, and its lifetime as a drug is shorter. (Other than that, it's fine). The reasons for these are as follows:
Most antibiotic targets are enzyme systems peculiar to bacteria (as compared to eukaryotes like us), but such targets are shared across a lot of bacteria. They tend to be aimed at things like membrane synthesis and integrity (bacterial membranes are rather different than those of animals and plants), or target features of DNA handling that are found in different forms due to bacteria having no nuclei, and so on. Killing bacteria with mechanisms that are also found in human cells is possible, but it's a rough way to go: a drug of that kind would be similar to a classic chemotherapy agent, killing the fast-dividing bacteria (in theory) just before killing the patient.
So finding a Streoptococcus-only drug is a very tall order. You'd have to find some target-based difference between those bacteria and all their close relatives, and I can tell you that we don't know enough about bacterial biochemistry to sort things out quite that well. Stewart brings up genomic efforts, and points to him for it, because that's a completely reasonable suggestion. Unfortunately, it's a reasonable suggestion from about 1996. The first complete bacterial genomes became available in the late 1990s, and have singularly failed to produce any new targeted antibiotics whatsoever. The best reference I can send people to is the GSK "Drugs For Bad Bugs" paper, which shows just what happened (and not just at GSK) to the new frontier of new bacterial targets. Update: see also this excellent overview. A lot of companies tried this, and got nowhere. It did indeed seem possible that sequencing bacteria would give us all sorts of new ways to target them, but that's not how it's worked out in practice. Blaser's interview gives the impression that none of this has happened yet, but believe me, it has.
The market for a narrow-spectrum agent would necessarily be smaller, by design, but the cost of finding it would (as mentioned above) be greater, so the final drug would have to cost a great deal per dose - more than health insurance would want to pay, given the availability of broad-spectrum agents at far lower prices. It could not be prescribed without positively identifying the infectious agent - which adds to the cost of treatment, too. Without faster and more accurate ways to do this (which Blaser rightly notes as something we don't have), the barriers to developing such a drug are even higher.
And the development of resistance would surely take such a drug out of usefulness even faster, since the resistance plasmids would only have to spread between very closely related bacteria, who are swapping genes at great speed. I understand why Blaser (and others) would like to have more targeted agents, so as not to plow up the beneficial microbiome every time a patient is treated, but we'd need a lot of them, and we'd need new ones all the time. This in a world where we can't even seem to discover the standard type of antibiotic.
And not for lack of trying, either. There's a persistent explanation for the state of antibiotic therapy that blames drug companies for supposedly walking away from the field. This has the cause and effect turned around. It's true that some of them have given up working in the area (along with quite a few other areas), but they left because nothing was working. The companies that stayed the course have explored, in great detail and at great expense, the problem that nothing much is working. If there ever was a field of drug discovery where the low-hanging fruit has been picked clean, it is antibiotic research. You have to use binoculars to convince yourself that there's any more fruit up there at all. I wish that weren't so, very much. But it is. Bacteria are hard to kill.
So the talk later on in the interview of spending some tax dollars and getting a bunch of great new antibiotics in ten years is, unfortunately, a happy fantasy. For one thing, getting a single new drug onto the market in only ten years from the starting pistol is very close to impossible, in any therapeutic area. The drug industry would be in much better shape if that weren't so, but here we are. In that section, Jon Stewart actually brings to life one of the reasons I have this blog: he doesn't know where drugs come from, and that's no disgrace, because hardly anyone else knows, either.
+ TrackBacks (0) | Category: Drug Development | Drug Industry History | Infectious Diseases
April 16, 2014
Matthew Herper has a good piece in Forbes on Robert Duggan and Pharmacyclics. In the course of it, we learn this interesting (and perhaps disturbing) bit of information:
Second acts in the biotech business are hard: 56% of the drug firms that received an FDA approval between 1950 and 2011 did so only once.
And I hate to say it, but the article does not inspire confidence in Duggan's ability to break that trend. It's surely no coincidence that the profile mentions in its first paragraph that he's a major donor to the Church of Scientology, and maybe it's just my own prejudices, but when I hear that, I'm pretty much done with thinking that a person can make rational decisions.
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April 4, 2014
I really got a kick out of this picture that Wavefunction put up on Twitter last night. It's from a 1981 article in Fortune, and you'll just have to see the quality of the computer graphics to really appreciate it.
That sort of thing has hurt computer-aided drug design a vast amount over the years. It's safe to say that in 1981, Merck scientists did not (as the article asserts) "design drugs and check out their properties without leaving their consoles". It's 2014 and we can't do it like that yet. Whoever wrote that article, though, picked those ideas up from the people at Merck, with their fuzzy black-and-white monitor shots of DNA from three angles. (An old Evans and Sutherland terminal?) And who knows, some of the Merck folks may have even believed that they were close to doing it.
But computational power, for the most part, only helps you out when you already know how to calculate something. Then it does it for you faster. And when people are impressed (as they should be) with all that processing power can do for us now, from smart phones on up, they should still realize that these things are examples of fast, smooth, well-optimized versions of things that we know how to calculate. You could write down everything that's going on inside a smart phone with pencil and paper, and show exactly what it's working out when it display this pixel here, that pixel there, this call to that subroutine, which calculates the value for that parameter over there as the screen responds to the presence of your finger, and so on. It would be wildly tedious, but you could do it, given time. Someone, after all, had to program all that stuff, and programming steps can be written down.
The programs that drove those old DNA pictures could be written down, too, of course, and in a lot less space. But while the values for which pixels to light up on the CRT display were calculated exactly, the calculations behind those were (and are) a different matter. A very precise-looking picture can be drawn and animated of an animal that does not exist, and there are a lot of ways to draw animals that do not exist. The horse on your screen might look exact in every detail, except with a paisley hide and purple hooves (my daughter would gladly pay to ride one). Or it might have a platypus bill instead of a muzzle. Or look just like a horse from outside, but actually be filled with helium, because your program doesn't know how to handle horse innards. You get the idea.
The same for DNA, or a protein target. In 1981, figuring out exactly what happened as a transcription factor approached a section of DNA was not possible. Not to the degree that a drug designer would need. The changing conformation of the protein as it approaches the electrostatic field of the charged phosphate residues, what to do with the water molecules between the two as they come closer, the first binding event (what is it?) between the transcription factor and the double helix, leading to a cascade of tradeoffs between entropy and enthalpy as the two biomolecules adjust to each other in an intricate tandem dance down to a lower energy state. . .that stuff is hard. It's still hard. We don't know how to model some of those things well enough, and the (as yet unavoidable) errors and uncertainties in each step accumulate the further you go along. We're much better at it than we used to be, and getting better all the time, but there's a good way to go yet.
But while all that's true, I'm almost certainly reading too much into that old picture. The folks at Merck probably just put one of their more impressive-looking things up on the screen for the Fortune reporter, and hey, everyone's heard of DNA. I really don't think that anyone at Merck was targeting protein-DNA interactions 33 years ago (and if they were, they splintered their lance against that one, big-time). But the reporter came away with the impression that the age of computer-designed drugs was at hand, and in the years since, plenty of other people have seen progressively snazzier graphics and thought the same thing. And it's hurt the cause of modeling for them to think that, because the higher the expectations get, the harder it is to come back to reality.
Update: I had this originally as coming from a Forbes article; it was actually in Fortune.
+ TrackBacks (0) | Category: Drug Industry History | In Silico
March 31, 2014
Over at LifeSciVC, there's a useful look at how many drugs are coming into the larger companies via outside deals. As you might have guessed, the answer is "a lot". Looking at a Goldman Sachs list of "ten drugs that could transform the industry", Bruce Booth says:
By my quick review, it appears as though ~75% of these drugs originated at firms different from the company that owns them today (or owns most of the asset today) – either via in-licensing deal or via corporate acquisitions. Savvy business and corporate development strategies drove the bulk of the list. . .I suspect that in a review of the entire late stage industry pipeline, the imbalanced ratio of external:internal sourcing would largely be intact.
He has details on the ten drugs that Goldman is listing, and on the portfolios of several of the big outfits in the industry, and I think he's right. It would be very instructive to know what the failure rate, industry-wide, of inlicensed compounds like this might be. My guess is that it's still high, but not quite as high as the average for all programs. The inlicensed compounds have had, in theory, more than one set of eyes go over them, and someone had to reach into their wallet after seeing the data, so you'd think that they have to be in a little bit better shape. But a majority still surely fail, given that the industry's rate overall is close to 90% clinical failure (the math doesn't add up if you try to assume that the inlicensed failure rate is too low!)
Also of great interest is the "transformational" aspect. We can assume, I think, that most of the inlicensed compounds came from smaller companies - that's certainly how it looks on Bruce's list. This analysis suggested that smaller companies (and university-derived work) produced more innovative drugs than internal big-company programs, and these numbers might well be telling us the same thing.
This topic came up the last time I discussed a post from Bruce, and Bernard Munos suggested in 2009 that this might be the case as well. It's too simplistic to just say Small Companies Good, Big Companies Bad, because there are some real counterexamples to both of those assertions. But overall, averaged over the industry, there might be something to it.
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March 20, 2014
Over at LifeSciVC, guest blogger Jonathan Montagu talks about small molecules in drug discovery, and how we might move beyond them. Many of the themes he hits have come up around here, understandably - figuring why (and how) some huge molecules manage to have good PK properties, exploiting "natural-product-like" chemical space (again, if we can figure out a good way to do that), working with unusual mechanisms (allosteric sites, covalent inhibitors and probes), and so on. Well worth a read, even if he's more sanguine about structure-based drug discovery than I am. Most people are, come to think of it.
His take is very similar to what I've been telling people in my "state of drug discovery" presentations (at Illinois, most recently) - that we medicinal chemists need to stretch our definitions and move into biomolecule/small molecule hybrids and the like. These things need the techniques of organic chemistry, and we should be the people supplying them. Montagu goes even further than I do, saying that ". . .I believe that small molecule chemistry, as traditionally defined and practiced, has limited utility in today’s world." That may or may not be correct at the moment, but I'm willing to bet that it's going to become more and more correct in the future. We should plan accordingly.
+ TrackBacks (0) | Category: Chemical Biology | Chemical News | Drug Development | Drug Industry History