Lynn C. Klotz, Ph.D. Bridging BioScience & BioBusiness
The historical graph that tells many stories.
This article is aimed at those interested in learning about the drug discovery and development (DD&D) business, who include science Ph.D.s and business people new to the business. The article is written with this audience in mind. Old pros in drug development might find this graphical visual approach to be a good teaching or presentation tool.
At first glance, the graph below seems way out of date, but it tells the story of the pharmaceutical industry’s issues and strategy both then and now. The graph is from a 1993 report “Pharmaceutical R&D: Costs, Risks, and Rewards” by the now-defunct government agency, the Office of Technology Assessment. In this graph, the base year for discounting costs and income is year 0, the year of FDA approval just prior to market launch. The discount rate for cost of capital was about 14%.
The first thing to notice is that the OTA report was written in 1993, so all the data in the graph must be from years before 1993. The time period covers 32 years (from -10 to +20 years), so the data goes back as far as 1961, clearly light years away from today in DD&D technical advances. Over that period, drug discovery has evolved and expanded from a chemistry focus to a molecular biology, biotechnology, and still chemistry focus. Recombinant DNA, the key technology of modern molecular biology, was not invented until the 1970s.
The data points below the horizontal straight line show DD&D cost. The data points above the straight line show income, after the drug is marketed. In visual terms, the graph area enclosed by the straight line and the income data measures total income, and the area enclosed by the straight line and the cost data measures total cost. The area reflecting total income is bigger than the area reflecting total cost, so the 20 drugs were profitable to the industry. If the income area were smaller than the cost area, the industry would have lost money. So the strategic task for the industry is to find ways to make the income area bigger by increasing it vertically or horizontally, and make the cost area smaller by decreasing it vertically or horizontally.
Decreasing DD&D Cost
Reducing clinical trial time and expense
The dollar cost values on the vertical axis are very small compared to today. As shown in the Table, DD&D costs have risen steeply. In an earlier article, it is calculated that the actual out-of-pocket outlay for DD&D for a small company may be less than $242 million today, despite the $1,778 billion in the Table. The numbers in the Table are more appropriate for big companies as they are inflated by accounting for the cost of failed drugs and the cost of capital, legitimate costs for big drug companies.
The industry organization BIO argues that the FDA should allow “new trial designs, especially for drugs for fatal, rare diseases where it doesn’t make sense to give some patients a placebo.” Another BIO proposal is to allow “the FDA to initially approve drugs for a specific subset of patients for whom the benefits clearly outweigh the risks, and then monitor those patients to collect data for a wider approval.” In effect, this proposal would do away with some Phase III clinical trials, which are the longest and most expensive of the three clinical trial phases. If adopted, the proposal would decrease both cost and time to market.
Improving clinical trial success rate
From the graph, the clinical trial success rate, the percent of drugs that entered clinical trials and reached the marketplace, was 20/100 or 20%. It may come as a surprise to you that clinical trial success rate today has dropped to just above 10%. With the profound influence of molecular biology and biotechnology on drug discovery and development, how can this be?
The reasons are many: poor choice of drug candidates put into trials, more complex FDA requirements increasing trial cost and length, aging population with patients on many drugs creating unfavorable drug interactions in trials, more competition causing management to pull drug candidates from trials for business reasons, and so on.
Most surprisingly, molecular biology-based, isolated-target screening to choose the tightest binding candidates for clinical trials turns out to be less valuable at predicting trial success than the old pre-molecular biology phenotypic screens that tested drug candidates in living cells. In a study of all 75 drugs with new molecular mechanisms of action approved by the FDA between 1999 and 2008, 37% employed phenotypic screening and 22% employed target binding assays in their discovery, which seems to indicate that phenotypic screens may be better at predicting clinical trial success. A key conclusion is that the widely adopted screens, using targets reproduced by recombinant DNA, may have set us back a step.
The drug industry is addressing all these issues, including starting new phenotypic screening programs, in an attempt to increase clinical trial success rates, which will lower costs from failed drugs.
The dollar income numbers on the vertical axis are very small compared to today as well. Sales, income (averaging roughly 20% to 25% of sales), and individual drug prices have skyrocketed.
The obvious ways to increase the graph’s income area vertically are to increase numbers of customers or increase price. Expansion into emerging markets in China, India, and other developing nations is one way industry is finding new customers. And at present, the industry appears also to be hiking prices significantly.
Moreover, increasing clinical trial success rates should result in more drugs on the market creating greater sales and income, along with lowering cost.
Warding off generics
From the graph, income from sales declines rapidly due to competition from generics once patents expire. The allowed 20-year patent term usually does not provide anywhere near 20 years of market protection. Many drug patents are applied for in the discovery stage, before clinical trials begin. Since clinical trials and FDA approval can take eight years or longer, the average small molecule drug has 13.5 years of market protection.
Drug companies have several strategies to increase the number of years of high sales. These include follow-on patents (e.g., new drug formulations) and even paying generic drug companies to delay putting their competitive drug on the market. Developers of biologic drugs have lucked out in this regard, since biosimilar drugs are just now beginning to reach the market. Biologic drugs are still experiencing high sales after their patents expired.
This article sets the stage for a second article, which will update the graph to the present. One goal is to analyze what dollar sales big drug companies need to make a profit. Not surprisingly, profit or loss depends on the discount rate used to calculate cost of capital. At high capital costs, it may require blockbuster drugs, ones with $1 billion or more yearly sales, to turn a profit on new drugs.
One interesting new industry strategy to produce blockbusters is orphan drugs, a strategy that both reduces development cost from special FDA considerations and can provide blockbuster sales through high pricing. This second article will look closely at orphan disease statistics that reveal limitations of the industry’s orphan drug blockbuster strategy. It will suggest a path forward to avoid the pharmacoeconomic problems that high pricing creates.
Lynn C. Klotz, Ph.D. (firstname.lastname@example.org), is co-managing director of Bridging BioScience & BioBusiness. The material in this article comes from the Topic Books on Bridging BioScience & BioBusiness' website.