The price of innovation: new estimates of drug development costs

TL;DR: The research and development costs of 68 randomly selected new drugs were obtained from a survey of 10 pharmaceutical firms and used to estimate the average pre-tax cost of new drug development.

About: This article is published in Journal of Health Economics.The article was published on 2003-03-01 and is currently open access. It has received 4135 citations till now. The article focuses on the topics: Fixed cost & Total cost.

Summary

1. Introduction

• Innovations in the health sciences have resulted in dramatic changes in the ability to treat disease and improve the quality of life.
• Finally, the cost of R&D has become an important issue in its own right in the recent policy deliberations involving regulatory requirements and the economic performance of the pharmaceutical industry”.
• Viewed as an investment project, it is necessary to know both the amount of expenditures and the timing of these expenditures, since funds committed to R&D in advance of any returns from sales have both a direct and an opportunity cost.

1.1. Previous studies of the cost of pharmaceutical innovation

• A summary of early studies of the cost of drug development can be found in the authors’ previous study (DiMasi et al., 1991) and inOTA (1993).
• In contrast, the study byHansen (1979) and the current authors’ previous study (DiMasi et al., 1991) estimated development cost based on data supplied by firms for a representative sample of drug development efforts.
• Measured in constant dollars, this value is more than double that obtained by Hansen for an earlier sample.
• Based on an analysis by Myers and Shyam-Sunder performed for the OTA, theOTA (1993)report noted that the cost-of-capital for the industry was roughly 10% in the early 1980s.
• The OTA presented both pre- and post-tax cost estimates.

1.2. Aggregate data analyses

• There have been no recent comprehensive studies of the cost of developing new pharmaceuticals from synthesis to marketing approval based on actual project-level data.
• Reports on specific components of the R&D process, such as the number of subjects in clinical trials (OTA, 1993; The Boston Consulting Group [BCG], 1993), also suggest an increase in the real cost of pharmaceutical innovation.
• Given the much faster rate of growth of R&D expenditures, data such as these suggest that R&D costs have increased over time.
• On that account the data would tend to underestimate costs.
• Section 8contains data and analyses that corroborate their results.

2. The new drug development process

• New drug development can proceed along varied pathways for different compounds, but a development paradigm has been articulated that has long served well as a general model.
• In outline form, the paradigm portrays new drug discovery and development as proceeding in a sequence of (possibly overlapping) phases.
• It was not possible to disaggregate their data into discovery and preclinical development testing costs,3 so for the purposes of this study discovery and preclinical development costs are grouped and referred to as preclinical costs.
• Clinical testing typically proceeds through three successive phases.
• In the United States, manufacturers submit a new drug application (NDA) or a biological license application (BLA) to the FDA for review and approval.

3. Data

• Ten multinational pharmaceutical firms, including both foreign and US-owned firms, provided data through a confidential survey of their new drug R&D costs.
• In addition, the authors used a Tufts CSDD database supplemented by commercial databases to determine that of the 284 new drugs approved in the United States from 1990 to 1999,12 93.3% originated from industrial sources (either from the sponsoring firm or from another firm from which the compound was licensed or otherwise acquired).
• The firms that did not participate in the survey cited a number of reasons for not doing so.
• The population is composed of all investigational compounds in the Tufts CSDD investigational drug database that met study criteria: the compounds were self-originated and first tested in humans anywhere in the world from 1983 to 1994, and the authors had the information necessary to classify them according their strata.
• For these drugs it is possible that there will be some future costs for the drug’s most recent phase.

4. Methodology for estimating new drug development costs

• The approach that the authors use to estimate development costs is similar to that described in their earlier work (DiMasi et al., 1991).
• The authors will outline here the general methodology for developing an overall cost estimate.
• Results from previous analyses suggested that the variability of drug costs tends to increase with the development phase or the amount of time that a drug spends in testing (Hansen, 1979; DiMasi et al., 1991).
• The reported sample values were then weighted, where the weights were determined so that the sample perfectly reflects the population in terms of the four strata.

4.1. Expected costs in the clinical period

• Since new drug development is a risky process, with many compounds failing for every one that succeeds, it is necessary to analyze costs in expected value terms.
• The total clinical period cost for an individual drug can be viewed as the realization of a random variable,c.
• Specifically,µI|e, µII |e, µIII |e, andµA|e are the population mean costs for drugs that enter phases I–III, and clinical period long-term animal testing, respectively.
• Weighted mean phase costs derived from the cost survey data were used to estimate the conditional expectations.
• A description of how the probabilities were estimated is presented in the next section.

4.2. Clinical success and phase attrition rates

• An overall clinical approval success rate is the probability that a compound that enters the clinical testing pipeline will eventually be approved for marketing.
• A phase transition probability is the likelihood that an investigational drug will proceed in testing from one phase to the next.
• The data used here consist of the investigational drugs in the Tufts CSDD database that were first tested in humans anywhere in the world from 1983 to 1994, with information on their status (approval or research abandonment) obtained through early 2001.
• Dividing this estimate by the overall clinical success rate yields their estimate of out-of-pocket cost per approved drug.

4.3. Out-of-pocket discovery and preclinical development costs

• Many costs incurred prior to clinical testing cannot be attributed to specific compounds.
• Thus, aggregate level data at the firm level were used to impute costs per drug for R&D incurred prior to human testing.
• Specifically, time series data for each surveyed firm on spending on pre-human R&D and on human testing for 1980–1999 were obtained, and a ratio of pre-human R&D expenditures to human testing expenditures was determined based on an appropriate lag structure (on average, pre-human R&D expenditures should occur years prior to the associated human testing costs).
• This ratio was then multiplied by an estimate of out-of-pocket clinical cost per drug, which is based on the project-level data, to yield an estimate of the pre-human R&D cost per new drug.18.

4.4. Capitalized costs: development times and the cost-of-capital

• Given that drug development is a very lengthy process, the full cost of drug development should depend significantly on the timing of investment and returns.
• The timeline is constructed from information on average phase lengths and the average gaps and overlaps between successive phases in a Tufts CSDD database of approved new drugs and in their cost survey.
• DiMasi (2001a)found very high approval rates for NDA submissions, with an increasing trend.
• This leads to lower cost estimates than would be the case if the same procedure for determining failure that was used for compounds still in testing had been used instead.
• Dividing by the overall clinical success rate results in their estimate of the total capitalized cost per approved new drug.

5.1. Out-of-pocket clinical cost per investigational drug

• Given the method of weighting reported costs as described inSection 4, weighted means, medians, and standard deviations were calculated and are presented inTable 1.20 Mean 19.
• Thus, the authors estimate clinical phase lengths and approval phase times for new chemical entities and biopharmaceuticals separately and compute a weighted average of the mean phase lengths, where the weights are the shares of self-originated investigational compounds in the Tufts CSDD database for each of these compound types.
• Cost per investigational drug entering a phase increases substantially by clinical phase, particularly for phase III, which is typically characterized by large-scale trials.
• Similarly, the ratio of mean phase II to phase I cost was 1.9 for the earlier study, but was 1.5 for this study.
• Lower probabilities of entering a phase will, other things being equal, result in lower expected costs.

5.2. Cost-of-capital estimates

• In their earlier paper (DiMasi et al., 1991), the authors employed a 9% real cost-of-capital based on a capital asset pricing model (CAPM) analysis for a representative group of pharmaceutical firms during the 1970s and early 1980s.
• Hence a relevant time period for their cost-of-capital measure is 1985–2000.

5.3. Capitalized clinical cost per investigational drug

• To calculate opportunity cost for clinical period expenditures the authors estimated average phase lengths and average gaps or overlaps between successive clinical phases.
• Mean phase lengths and mean times between successive phases are shown inTable 3.
• In addition, as noted in footnote 4, many firms appear to use higher costs of capital in their R&D investment decisions than what emerges from this CAPM analysis.
• While the approval phase averaged 30.3 months for the earlier paper’s study period, that phase averaged only 18.2 months for drugs covered by the current study.
• Other things being equal, the observed shorter times from clinical testing to approval yield lower capitalized costs relative to out-of-pocket costs.

5.4. Clinical cost per approved new drug

• The authors are mainly interested in developing estimates of cost per approved new drug.
• The authors statistical analysis of compounds in the Tufts CSDD database of investigational drugs that met study criteria yielded a predicted final clinical success rate of 21.5%.
• Applying this success rate to their estimates of out-of-pocket and capitalized costs per investigational drug results in estimates of cost per approved new drug that link the cost of drug failures to the successes.
• These costs are more than four-fold higher than those the authors found in their previous study.
• The ratios of capitalized to out-of-pocket cost for the earlier study were 1.9, 1.7, 1.4, and 1.6 for phases I–III, and animal testing, respectively.

5.5. Preclinical out-of-pocket and capitalized costs per approved drug

• The preclinical period, as defined here, includes discovery research as well as preclinical development.
• As noted above, not all costs during this period can be allocated to specific compounds.
• The authors gathered data on aggregate expenditures for these periods from survey firms for 1980–1999.
• Both times series tended to increase over time in real terms.

5.6. Total capitalized cost per approved drug

• The authors full cost estimate is the sum of their preclinical and clinical period cost estimates.
• Real total capitalized cost per approved new drug for the current study is 2.5 times higher than for the previous study.
• An alternative is to determine an average approval date for drugs in each study’s sample and use the differences in these dates to define the time differences between the studies.
• Thus, the authors used 13 years as the relevant time span between the studies and calculated compound annual rates of growth between the two studies accordingly.
• The growth in total costs, however, masks substantial differences in growth rates for the preclinical and clinical periods.

6.1. Effects of parameter changes

• The authors undertook sensitivity analyses for several of the key parameters that underlie the cost estimates.
• At their base case discount rate, total capitalized cost for a success rate of 23.5% is US$ 734 million, or 8.5% lower than their base case result.
• If the clinical success rate is 23.0% and phase attrition rates are altered accordingly, total capitalized cost is 5.6% lower (5.1% lower if account is also taken of estimated differences in phase costs between the failures and successes in the sample [see the following section]).
• 28 The simulation was conducted assuming statistical independence for the parameters.
• The coefficient of variation when only development times vary, when only the discount rate varies, when only success and attrition rates vary, and when only out-of-pocket phase costs vary were 0.015, 0.035, 0.044, and 0.065, respectively.

6.2. Variable discount rates

• Myers and others (Myers and Shyam-Sunder, 1996; Myers and Howe, 1997) have argued that the cost-of-capital for R&D should decline over the development process as a step function.
• A more levered position amplifies risk and is associated with a higher cost-of-capital for investors.
• Under certain assumptions, theMyers and Hothe authors (1997)two-discount rate method yields the same results as the more complex compound options valuation.
• For purposes of comparison, the authors did compute drug R&D costs with theMy rs and Hothey (1997)two-discount rate method.
• The total capitalized cost estimate is US$ 955 million when a 10% discount rate is used for rNR and a 5% discount rate is used forrFC.

7. Extensions to the base case

• The base case results on overall pre-approval drug development costs can be extended in several interesting ways.
• The authors base case results link the costs of the failures to the successes.
• The authors can provide estimates of the clinical period cost of taking a successful drug all the way to approval by examining the data for the approved drugs in the sample.
• This also allows us to obtain some evidence on costs for the more medically significant products (according to what is known at the time of approval) by using an FDA prioritization ranking for approved drugs.
• Finally, the authors can examine what impact tax policies and procedures have had on the effective cost of pharmaceutical R&D for pharmaceutical firms.

7.1. Development costs for successes

• As their results indicate, development costs vary across drugs.
• For comparative purposes, the results for the full sample are also shown.
• Since the authors are not linking failures to successes here and since they have full phase cost data for the 24 approved drugs, they can add phase costs for each drug to determine a total clinical period cost for each drug and use those data to find confidence intervals for mean out-of-pocket and capitalized clinical period cost for approved drugs.
• New drugs are rated as either priority (P) or standard (S).31 Kaitin and Healy (2000), Kaitin and DiMasi (2000), Reichert (2000), andDiMasi (2001a)contain numerous analyses of development and approval times by FDA therapeutic rating.
• The authors found higher mean clinical phase costs for more highly rated drugs.

7.3. Tax analysis

• The cost estimates that are presented here are pre-tax.
• Hence, a straightforward calculation can be made to use their R&D cost estimates as inputs in after-tax analyses of R&D rates of return (OTA, 1993; Grabowski and Vernon, 1994).
• The R&E tax credit was not relevant to a significant degree to the study period for their previous analysis (DiMasi et al., 1991).
• Optimal administration of the tax would involve depreciating all forms of intangible capital at economically appropriate rates.
• 35 Analysis of data provided in a Congressional Research Service (CRS) report indicates that orphan drug tax credits amount to a fraction of a percent of pharmaceutical industry R&D expenditures (Guenther, 1999).36 33.

8. Validation

• In their 1993 report, the OTA reviewed the literature on pharmaceutical R&D costs.
• In addition to critiquing the methodologies used in these studies, the review addressed evidence on the reasonableness of the studies, particularly theDiMasi et al. (1991)study.
• The OTA concluded that, “the estimates by DiMasi and colleagues of the cash outlays required to bring a new drug to market and the time profile of those costs provide a reasonably accurate picture of the mean R&D cash outlays for NCEs first tested in humans between 1970 and 1982” (OTA, 1993, p. 66).
• The OTA provided varied data and analyses to corroborate the results in DiMasi et al. (1991).
• The authors pay particular attention to data that corroborate the growth in costs between the previous study and the current one.

8.1. Internal validation

• The Tufts CSDD database of investigational compounds, from which their sample was selected, contains data on the vast majority of new drugs developed in the United States (DiMasi, 2001a).
• The authors examined the data for eight specific therapeutic classes and one miscellaneous class for drugs in the database that met study inclusion criteria.
• The largest difference in share for a specific class between all firms in the database and the cost survey firms was 1.5%.37.
• Using a chi-squared goodness-of-fit test comparing the therapeutic class distributions for the cost survey firms and the other firms in the database, the authors found no statistically significant difference for the class shares (χ2 = 5.01, d.f . = 9).38.
• The annual growth rate in real pharmaceutical R&D expenditures for the survey firms39 from 1995 to 2000 is 11.3%, compared to 11.0% for PhRMA member firms over the same period.

8.2. External validation

• Publicly available data that were collected independently can be examined to determine the extent to which they are consistent with their results in terms of levels or rates of change.
• Specifically, the authors examined independent information on clinical trial sizes, measures of clinical trial complexity, and published trade association data on R&D employment and expenditures.

8.2.1. Clinical trial sizes and complexity

• These separate estimations need not be in perfect agreement because their clinical cost figures include costs not directly related to the number of clinical trial subjects (infrastructure costs, fixed costs related to production of clinical trial supplies, animal testing during the clinical period, etc.).
• 42 These groupings were chosen so that the mean approval years were 1984 and 1997 (the average approval years for theDiMasi et al. (1991)and the current cost samples).
• Applying this growth rate to the growth rate of 5.4% for all pharmaceutical industry R&D personnel yields an increase of 6.7% per year in labor costs.
• The ratio of total lagged self-originated R&D expenditures to the total number of self-originated approvals yields an estimate of the out-of-pocket cost of new drug 48 PhRMA also publishes a breakdown of annual R&D expenditures of its member firms by function (PhRMA, 2001).

9. Conclusions

• The cost of developing new drugs is a topic that has long engendered considerable interest.
• The rate of increase for the preclinical period was less than one-third that for the first two studies, while the growth rate for clinical costs was nearly twice as high for the two most recent studies.
• A number of technical factors can work to alter the growth pattern for future R&D costs.
• Results from their prior studies have in fact been used in analyses of the rate of return to pharmaceutical R&D (Grabowski and Vernon, 1990; OTA, 1993; Grabowski and Vernon, 1994).
• The reason is that the tax essentially enters symmetrically in the analysis (applied to revenues as well as costs), and so the impact on the internal rate of return is minimal.

Figures

Table 3 Average phase times and clinical period capitalized costs for investigational compounds (in millions of 2000 dollars)a

Table 5 Out-of-pocket clinical period phase costs for approved compounds (in millions of 2000 dollars)a

Table 2 Nominal and real cost-of-capital (COC) for the pharmaceutical industry, 1985–2000

Table 4 Compound annual growth rates in out-of-pocket and capitalized inflation-adjusted costs per approved new druga

Fig. 3. Capitalized preclinical, clinical, and total costs per approved new drug by discount rate.

Fig. 4. Out-of-pocket and capitalized total cost per approved new drug for new drugs and for improvements to existing drugs.

Fig. 1. Inflation-adjusted industry R&D expenditures (2000 dollars) and US new chemical entity (NCE) approvals from 1963 to 2000. Source of data:PhRMA (2001)and Tufts CSDD Approved NCE Database.

Fig. 2. Trends in capitalized preclinical, clinical and total cost per approved new drug.

Table 1 Average out-of-pocket clinical period costs for investigational compounds (in millions of 2000 dollars)a

Frequently asked questions

Q1. What have the authors contributed in "The price of innovation: new estimates of drug development costs" ?

For example, DiMasi et al. this paper found that the average out-of-pocket cost per new drug is US $ 403 million ( 2000 dollars ). 

Q2. What are the future works mentioned in the paper "The price of innovation: new estimates of drug development costs" ?

Can further improve their performance in terminating research early for compounds that will not make it to approval, then this will help lower out-of-pocket and capitalized costs. The growth rate for gross margins for recent years was also substantially lower than the growth rate for R & D outlays, leading to the suggestion that R & D growth rates could lessen in the future. The authors will examine costs by therapeutic category in future research. The R & D cost data for this study can be used in further analyses of R & D productivity at the firm level in future research. 

Q3. What categories would each have to be decomposed into shares for pre-human, pre-?

The categories “Toxicology and Safety Testing (4.5%),” Pharmaceutical Dosage Formulation and Stability Testing (7.3%),” “Regulatory: IND and NDA (4.1%),” “Bioavailability (1.8%),” and “Other (9.0%)” would each have to be decomposed into shares for pre-human R&D, pre-approval clinical period R&D, and post-approval R&D. 

Q4. What are the main factors that have intensified the interest in the performance of the pharmaceutical industry?

In addition, the congressional debates on Medicare prescription drug coverage and various new state initiatives to fill gaps in coverage for the elderly and the uninsured have intensified the interest in the performance of the pharmaceutical industry. 

Q5. What is the growth rate in total cost of preclinical research?

The growth rate in capitalized costs, however, is driven more by the fact that preclinical costs have a lower share of total out-of-pocket costs in the current study than in the previous studies, and time costs are necessarily proportionately more important for preclinical than for clinical expenditures. 

Q6. What is the common way drug developers submit their results to regulatory authorities?

Once drug developers believe that they have enough evidence of safety and efficacy, they will compile the results of their testing in an application to regulatory authorities for marketing approval. 

Q7. What are the common types of pharmaceutical firms that have received orphan drug designations?

In addition, the vast majority of the manufacturers with products that have received orphan drug designations are biotech firms or small niche pharmaceutical firms (see http://www.fda.gov/orphan/designat/list.htm). 

Q8. What percentage of pharmaceutical R&D expenditures are currently accounted for by outsourcing?

By all accounts, pharmaceutical firms have contracted out drug development activities at a rapidly growing rate over their study period, and the share of pharmaceutical R&D expenditures currently accounted for by outsourcing is substantial.