The Pharmaceutical R&D Model is Broken. Here’s How to Fix It

3/5/10

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Cell Therapeutics, have both eliminated their new drug discovery programs while shifting efforts to develop candidates already in the late stages of development. Other local companies have laid off hundreds of researchers in recent years. Yes, if the good times return these companies will likely start hiring researchers again (provided they are not bought out first, a more likely outcome of success). However, the sad reality is that building a world-class research staff at a company that repeatedly cycles through layoffs and hirings is going to be quite difficult, if not impossible.

What did Sciele Pharma, Kowa Research, Gloucester Pharma, Dyax, Allos Therapeutics, and Vanda Pharma all have in common in 2009? Not sure? How about Merck, Genentech, Amgen, Abbott Laboratories, Bayer, and Pfizer? In the first group, all of these companies had a new drug approved by the US FDA in 2009. In the second group, none of the named powerhouse companies got a new drug over that goal line. What’s the lesson here? Small companies can succeed in getting their drugs approved by the FDA, and for a lot less than $2.7 billion. In this sense, size doesn’t matter.

These examples, while illustrative, are a bit misleading as they are only sampling a single year. Over a multi-year period, the drug approval numbers tilt much more heavily towards Big Pharma. However, the numbers don’t scale per employee. If a company with 500 employees can get one drug approved, this doesn’t mean that having 5,000 employees will net you 10 new drugs. Therefore, for their size, Big Pharma is relatively inefficient in developing new drugs. It’s also worth noting that some of the small companies that win drug approvals have Big Pharma partners helping them through the process.

To be fair, comparing drugs put into trials by Big Pharma vs. small biotechs is really an apples and oranges comparison. Why? Because the two groups have different expectations surrounding the returns generated by the drugs that they are developing. All companies want billion-dollar drugs, but these don’t come along so often. These businesses all have an internal benchmark number that they use for vetting drug candidates. Big Pharma might not send a drug to the clinic unless they are convinced it will produce hundreds of millions a year in revenue. In contrast, a $75 million/year drug can be a big winner for a company with only a couple of hundred employees. However, estimates of potential sales are just that, estimates, and these numbers often turn out to be wrong in both directions. Large companies are equally vulnerable to making bad decisions here as small ones. For example, in 2008 Amgen unloaded three drugs whose sales were so poor (combined sales of only $70 million in 2007) that they weren’t worth the sales and marketing expense.

Drug and biotech companies get started when entrepreneurs (usually a mix of business people and university profs) band together to license some discovery (and it’s concomitant intellectual property) from a university. This discovery then becomes the backbone upon which a company is incorporated and a drug is developed. How does this get paid for? It’s usually done with a combination of angel investors, small business grants, and the bigger dollars provided by VC firms.

VC money, however, comes with serious strings attached. VC firms are planning their divorces from the companies they fund before they even consummate their marriage. The investors will only make money if one of three things happens: the company is acquired, the company goes public, or the company successfully develops and profitably markets its drug. Estimates for the average time to fully develop a drug range from 8-12 years. Rightly or wrongly, most biotech investors are simply not willing to wait that long to get a return on their investment. If they had to wait until the drug was available … Next Page »

Stewart Lyman is Owner and Manager of Lyman BioPharma Consulting LLC in Seattle. He provides strategic advice to clients on their research programs, collaboration management issues, as well as preclinical data reviews. Follow @

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  • Ty

    Very good analysis on the problems, yet mere tax incentive is a kinda weak solution. What we need is a whole new biotech eco system. The long and single-threaded pipeline should be disected. Discovery companies should be focusing on validating novel disease/target concepts in animal and able to ‘sell’ the newly discovered target/lead. There should be a separate breed of companies with expertise in ‘lead optimization’ that turns the lead into a viable clinical candidate that can be ‘sold’. And development companies take over and proceed with clinical trials and registration. The first group sells the science. Second group compounds and the third drugs. It’s not too unlike Intel sells chips, MS sells Windows, and HP sells PCs. Why ROI is too long in pharma industry? Because we perceive ‘a drug’ as the only ‘product’. We need to change that perception.

  • Steve S

    If one of the problems of drug trial failure rates and wasted money is that small companies are pressured to move ideas to quickly into the clinic – how do you rate the so called new discipline of “translational medicine” where the whole idea is to get “drug candidates” into people with as little development as possible? (and I suspect is also a mechanism where Med Schools can gain access to a large previously untapped source of revenue!)

  • Simon

    Great analysis of the problem, but agree that tax incentives may not be enough. Although it is a good start. Bridging the “valley of death” or the period between proof of concept in animals and filing an IND is still the biggest problem for start-up biopharma. So-called “seed and early-satge funds” are now wanting phase 2 data. (Sorry VCs, but I’m going straight to big pharma with decent phase 2a data!)

  • http://robertmatthews.org Robert Matthews

    Great overview. Picking up on the point made by Ty, it seems to me that there are strong grounds for scepticism about current animal models. My own research (see http://tinyurl.com/ygm6dtc) suggests their false positive and false negative rates are so high that they contribute no predictive weight of evidence to subsequent performance in human RCTs. We really need these models either validated (which may well be very hard and expensive to do), or abandoned in favour of something better (eg microdosing, human tissue culture etc).

  • http://www.hustonassociates.net Mike

    Excellent overview and subsequent commentary. I have considerable experience with start ups as a consultant. The trends I have witnessed are CEO’s more focused filing an IND for whatever they can rather admitting that some drugs should never see the clinic. I also agree with Robert. Animal models (even for safety) are not very predictive. Translational medicine does have a chance to improve our “hit” rates, but most biomarkers are in the process of being validated and lag the availability of potential therapeutics. There will be convergence over the next 3-5 years.

  • Marc

    Insightful analysis. However missing some key points on the numbers.
    Yes one can pick 5 startups/pre-revenue companies who had a product approved in a given year. But the important stat is the denominator: how many comparable companies did not have a product advance, let alone file or get approved?
    Large pharmas are indeed advancing multiple compounds in multiple therapy areas, simultaneously. The startups do not have that luxury or capacity. The reported costs, $2.7 Billion per approved drug, reflect those allocated to failed and successful programs. Given the benchmarks of approx 10% success from IND to launch, that translates to roughly $270 Million / approved drug, which does not seem that far off the mark.
    Large pharma certainly does have its issues, and I’m not one to rush to its defense. But when stats are invoked to support a position, they need to be used carefully or they can detract from the inferences.

  • http://www.lymanbiopharma.com Stewart Lyman

    Thank you all for taking the time to share your thoughts. I agree that more reforms are needed besides the tax incentive for five-year minimum biotech investments, but that was the best idea that I could come up with that I could actually envision being put into practice relatively rapidly. I was hoping others would respond to my commentary with a variety of novel ideas as to how this R&D problem might be solved. In response to Ty’s comment, I heard a seminar just this week by Clive Stanway, CSO of Cancer Research Technology in the UK. His organization, in fact, represents the first third of what Ty is proposing: they do the preclinal research and then sell it off for a royalty to pharma companies to develop. Reconfiguring an entire industry, as Ty suggests doing, would be extremely difficult to accomplish (in the short term) given the inertia of the member companies. Look how long it took pharma to embrace biotechnology. As for Steve S’s comment, my sense of the term “translational medicine” is to imply adding resources directed at moving discoveries from the bench into the clinic. I do not associate this with “as little development as possible” although others may think of it that way. Translational medicine should benefit both the public and pharma/biotech by increasing the transfer rate of discoveries into potential medicines. Simon, any novel ideas how to bridge the “valley of death”? As to Robert’s comments, many people want to get rid of animal models because they are expensive (especially when you step up to primates), time consuming, and not always predictive. However, the industry is still waiting for an acceptable substitute that does better. If this were an easy problem to solve, someone would have already done so. I agree with Mike that useful biomarkers are still being validated, and while I think it is clear that many of these will be quite helpful in sorting patients with particular diseases (e.g. cancer) into different groups for dosing with distinct drugs, this approach may not work for many afflictions that result from a wide spectrum of molecular determinants. Finally, in response to Marc, the numbers I picked were not meant to be statistics. They were merely chosen to illustrate certain points. The “$2.7 billion dollars spent per new drug developed” number is clearly wrong; small companies never have anywhere near that kind of money, and the large ones clearly never spend anything close to that. Finding out true numbers in this area is exceedingly difficult. It is easy to determine the number of clinical trials being conducted in the US. However, many of these are not for new molecular entities, but instead are for new indications for old drugs, or new dosing modalities (different formulation, dose, route of administration, syringe design, etc.). Pharma, of course, counts all of this money spent as drug development R&D expense (which it is), but let’s be clear: this is not money spent on the discovery of new drugs. Small companies will, almost by definition, have a success rate of zero, fifty, or one hundred percent because they will only have one or two drugs in development.

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