Preliminary site survey data for biopharmaceutical manufacturing regulatory economics

Working Paper for Industry Studies Association 2011 Annual Conference

Pittsburgh, PA, USA

WORKING PAPER:

Preliminary Site Survey Data for Biopharmaceutical Manufacturing Regulatory Economics

CURRENT AUTHORS:

Domike, R.D.1,2; Macher, J.T.1,3; Pande, R.1; Barone, P.W.1; Springs, S.L.1
1: M.I.T. Center for Biomedical Innovation, M.I.T., USA
2: School of Business, University of Prince Edward Island, Canada
3: McDonough School of Business, Georgetown University, USA

ABSTRACT:

Efforts to understand and quantify trade-offs and economics relevant to the regulation of

biopharmaceutical manufacturing sites from the perspective of the US FDA are underway.

Preliminary results from a site survey that includes fifteen sites and thirty-one products

manufactured in North America, Europe, and Asia are presented. These preliminary results

suggest that sites expect more types of drivers or influencers regarding their quality

activities, with particularly increased expectations of the role of new technology, cost

reduction, and the pursuit of new markets. Also reported are the site perceptions of the

presence of variation between inspections completed at their facilities. With the product-

specific data, logistic regression suggests that the presence of a self-reported quality

deviation is statistically related to whether the product was previously produced elsewhere at

similar scale, use of advanced analytical approaches, regular manufacturing, use of

mammalian cell culture, and whether the site considers the process relatively complex.

Ongoing efforts and research objectives of the full project are described, with particular

focus on incorporating US FDA inspection data.

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WORKING PAPER: Preliminary Survey Data for Biopharmaceutical Manufacturing Regulatory Economics

1 Project Background and Preliminary Work Completed to Date

1.1 Background
The use of biopharmaceutical products has increased dramatically over the past twenty years and is expected to
continue to increase in volume and importance in years to come. Current worldwide market is approximately $100
billion and expected to double by 2020.  Compared to small molecule pharmaceuticals, biopharmaceuticals represent
approximately 7.5% of marketed products, but 32% of pipeline research programs.  Biopharmaceuticals are currently in
use or development to help humans fight diseases such as cancer, viral infections, diabetes, hepatitis and multiple
sclerosis. Biopharmaceuticals are common in high importance situations: in cases of life‐saving or end‐stage
applications, biopharmaceuticals are administered with nearly twice the frequency of small molecule pharmaceuticals.

Biopharmaceuticals are pharmaceuticals manufactured by biotechnology methods, involving live organisms or
their active components.  Types of biopharmaceuticals include recombinant proteins, (monoclonal) antibodies, vaccines,
and blood/plasma‐derived products. The biological nature and criticality of the products result in complex
manufacturing, quality assurance, and supply chain management.

The U.S. Food and Drug Administration (FDA) is tasked with ensuring public safety and health in the production
of biopharmaceuticals consumed within the United States. Federal statutes mandate that firms manufacturing
biopharmaceutical products for human administration operate under standards termed “current Good Manufacturing
Practices” (cGMPs), which require that all drug products and drug components be in conformance with guidelines
related to safety and have the identity, strength, quality and purity that they purport or are represented to possess.
Beyond manufacturing establishment inspection, the FDA is also tasked with the responsibility of recalling defective or
potentially harmful FDA‐regulated products, which can entail either removing them from the market or correcting the
underlying problems. The responsibility of these activities falls under the Center for Drug Evaluation and Research
(CDER) of the FDA. CDER faces a significant challenge in fulfilling their regulatory mission, given the increasing
complexity of biopharmaceutical manufacturing and the increasingly global nature of biopharmaceutical production.

CDER is faced with the difficult tasks of inspecting all manufacturing establishments that produce
biopharmaceutical products for U.S. consumption at least once every two years, as well as monitoring and alerting the
public of any product‐related problems that exist. While some effort is made in focusing investigational resources on
those establishments that are considered most critical to public health, CDER must make inspection decisions across a
range of establishments—from raw materials to intermediate products, fill and finish services, and final products.

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The scope of these myriad activities is against a backdrop of an increasingly complex regulatory environment.
Over the past decade, the sheer number and unique geographic locations of biopharmaceutical manufacturing facilities
requiring inspection have increased substantially. Many new biopharmaceutical manufacturing sites have been
established—many in China and India. New sites in China and India represent greater than 40% of FDA‐registered
foreign pharmaceutical locations—making inspection and oversight increasingly costly and cumbersome (Woo,
Wolfgang and Batista 2008). The net effect of these two factors has increased the complexity with which CDER
structures its cGMP inspection and recall programs, given the limited resources (in both dollars and people) available.

1.2 Full Project Intent
The full intent of this research project seeks to examine the effect of globalization on regulatory compliance for
biopharmaceutical product manufacturing, the behavior of manufacturing firms in this environment, and the impact of
FDA policy on biopharmaceutical manufacturing regulatory performance.

A central motivation for this research is the increasing complexity and globalization of biopharmaceutical
manufacturing. This combination has increased the policy challenges for effective safety regulation by the FDA, and
enhanced the potential for manufacturers to locate in environments where regulation may be less onerous. While the
research will be largely empirical, it is grounded in theoretical work on optimal regulation, and will have implications for
improving regulation and policy.

Most prior economic analyses of the regulatory process are based on principal‐agent models that incorporate
asymmetric information assumptions between the regulator and the firm, whereby the regulator attempts to optimize
its use of limited resources to provide oversight of the firms. This central tenant of asymmetric information has led to
research on the design of optimal regulatory mechanisms in an attempt to better align regulator incentives with those
of firms they regulate (e.g., Armstrong and Sappington, 2007; Baron, 1989; and Laffont and Martimort, 2002).

Additional research in the modeling of regulation examines whether regulators act rationally toward or are
influenced by various interest groups. This general theory of “regulatory capture” treats the regulator as a single,
monolithic and homogenous entity (Beard, Kaserman and Mayo, 2003; Becker, 1983; Laffont and Tirole 1991; Olson,
1995; Spiller, 1990; Weingart and Moran, 1983). While the existing literature on regulatory design and modeling has
advanced understanding of the regulatory process, the actual implementation of suggested schemes is rare (e.g., Blank
and Mayo, 2007). Some proposed reasons for this outcome include the costs associated with making changes in an
existing regulatory interaction; assumptions that information asymmetry is static (however in practice, regulators may

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undertake activities to close the information gap); the lack of “real” data in regulatory modeling; and assumptions that
the regulator acts as a homogenous entity (e.g., Macher, Mayo and Nickerson, 2009).

The FDA is aware of the existing challenges and trade‐offs associated with monitoring the safety of drug
products consumed within the U.S. Towards framing a coordinated solution to these challenges and trade‐offs, the
agency has actively pursued a risk‐based approach to manufacturing establishment inspection (U.S. FDA, 2004), and an
active reporting and monitoring system for recalls. Explicit inputs to the FDA risk‐based facility inspection selection
include the types of products manufactured (e.g., prescription (Rx) versus over‐the‐counter (OTC) drug products,
therapeutic classes, approved versus unapproved drug products); the control and/or contamination potential of the
manufacturing environment (e.g., facility size, facility type, number of drug products, sterility requirements, etc.); and
cost (e.g. domestic versus international locations). More practical outcomes of the risk‐based approach include which
manufacturing establishments to inspect and when, as well as how much time and how many resources to dedicate to
each inspection.

Additionally, the FDA has recently allowed a comprehensive review of their inspection patterns and outcomes
on pharmaceutical manufacturing facilities worldwide (Macher, Mayo and Nickerson, 2009). The compiled data covers
in excess of 10,000 inspections at 2,400 manufacturing facilities from 1990‐2003. These data provide insight into the
determinants of inspection frequency and inspection outcomes. The empirical analyses uncover several interesting
findings in FDA inspection patterns and outcomes. For instance, substantial regulator heterogeneity exists in the
propensity of FDA investigators to find manufacturing establishments in violation of regulatory standards which, in part,
are found to depend on the amount and type of training investigators receive and the frequency with which
investigators participate in inspections. Another finding examines inspection patterns at international facilities.
Moreover, foreign manufacturing establishments, in comparison to domestic (U.S.‐based) manufacturing
establishments experience: 1) lower frequencies of inspection; 2) greater rates of citations of mild noncompliance; and
3) comparable rates of citations of significant noncompliance.

This full research project’s intent is to build on the learning from pharmaceutical manufacturing and focus on
the regulatory economics of biopharmaceutical manufacturing.  Data will be collected from FDA databases on
inspections and product non‐compliance.  Additionally, a survey of biopharmaceutical manufacturing sites will be
completed to understand the perceptions and activities of the firms.  Results will hopefully have the potential to aid
CDER and FDA in better designing and refining regulatory approaches toward foreign manufacturing establishments is
seen as beneficial. Moreover, with calls for increased harmonization between and among different drug agencies (e.g.,

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EU’s EMEA, Japan, Brazil, etc.), leadership by the FDA in this area will also likely have positive impact on health
regulators worldwide (Vogel, 2002). Finally, biopharmaceutical manufacturing may represent a special (and important)
case for consideration, given the complexity, limited analytical tools for ensuring quality, and risk associated with
manufacturing globally.

1.3 Preliminary Work Completed to Date
To date, a comprehensive survey on topics related to site characteristics, quality approaches, quality activities, perception of
relative consistency of regulators, product‐level process details, and product‐level compliance performance has been
developed, tested, and deployed.  The firm survey is being administered as a secure web‐based questionnaire and full
deployment was initiated in March, 2011. The individuals selected for inclusion as survey respondents have been
manufacturing plant managers or their representatives and, once the required information is readily available, requires
30‐60 minutes to complete. In the first six weeks of the survey being deployed, fifteen (15) sites representing thirty‐one
(31) commercially manufactured products have completed the survey and it is the data from these preliminary results
that are presented and discussed in this working paper.

2 Preliminary Results and Discussion

2.1 Site‐Level Results
The following characteristics summarize the fifteen (15) biopharmaceutical manufacturing sites that are including in this
preliminary results and discussion:

 Geographic location: Five each are from Asia, Europe, North America
 Market(s) served: The market(s) served as a function of manufacturing site location are presented in Table 1 and of
the five Asian biopharmaceutical manufacturing sites surveyed to date, only one provides product outside of Asia
 Age of site: Five sites are ten years of age or less and the sample average age is twelve years
 Contract manufacturing: Six sites do less than 20% of their production volume for others and five do greater than 80%
of their production volume for others as contract manufacturers
 Batch capacity: Four sites have less than 1,000 liters of batch capacity and seven have between 1,000 and 5,000 liters
 Perfusion capacity:  Six sites have no perfusion capacity and six have 100 to 1,000 liters of perfusion capacity

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Table 1: Market(s) served with biopharmaceutical product based on physical location of manufacturing site

Manufacturing Site Location
North Europe Asia (n=5)
America (n=5) (n=5)
USA 100% 80% 20%
Market(s) Served

Europe 80% 100% 20%
Canada 60% 60% 0%
Japan 60% 60% 20%
Asia 60% 40% 80%
Middle East 60% 40% 0%
South America 40% 40% 0%

Three site‐level intentions of the survey of biopharmaceutical manufacturing sites that can be discussed with the preliminary
survey data include:

 What, in practice, drives quality efforts at the sites both experienced in the past and expected in the future?
 To what extent are the sites undertaking common quality activities to increase the effectiveness of their quality
assurance and control?
 What perspectives do the sites have of the regulators in terms of relative consistency between inspections?

Preliminary answers to these three questions are described in the following sub‐sections using the data available to date from
the survey of biopharmaceutical manufacturing sites.  A number of other questions related to site location will be considered
once more survey data and FDA inspection data is collected – these are discussed in a later section of this working paper and
described as ongoing efforts.

2.1.1 Quality Drivers and Activities

2.1.1.1 Quality drivers past and anticipated future
As part of the survey of biopharmaceutical manufacturing sites, each site was asked to identify significant sources, or drivers,
for changes in quality efforts and activities at their site.  The respondents indicated whether the quality drivers had been
experienced by the site in the past, are anticipated drivers for the site in the future, both, or neither past nor future.  The
preliminary results from the survey of the sites are presented in Figure 1 ordered from left to right in descending order of
fraction of sites identifying the type of driver as one that has historically been experienced.  Of particular note, albeit based
on preliminary data, are the following:

Page 6 of 16


 Changes around quality approach and activities driven by the regulator, although not necessarily due to site non‐
compliance, was the most frequently experienced driver
 Drivers potentially directly related to profitability of the product (cost reduction and pursuit of new markets) have
been very infrequently experienced
 A number of drivers of quality approach and activities are expected to be experienced by more than twice the
number of sites that have experienced them to date, specifically the introduction of new technology, cost reduction,
and pursuit of new markets – perhaps based on a hope for more efficient and profitable future or based on current
economic climate
 The number of types of quality drivers expected to be experienced per site is significantly higher than the number of
types of quality drivers historically experienced per site, increasing from an average of 39% to 62% (excluding the
“Other” category) suggesting that, in the future, sites will have more drivers of change in quality approach and
activities – these different drivers could have different outcome priorities (e.g. cost reduction and anticipated
regulatory change) and therefore involve trade‐off decisions for the sites

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90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Non‐compliance
Equipment
Change from Regulator

New Technology

Other
Raw Material

Management Objective
Scale‐up
Production Process

Cost Reduction

Pursuit of New Markets
Past Drivers Experienced Expected Future Drivers

Figure 1: Experienced and expected drivers of quality activities and resources (preliminary data: number of respondents
ranges within 7 and 11)

2.1.1.2 Site‐Level Quality Activities
Three quality efforts and activities about which the biopharmaceutical manufacturing sites were surveyed are presented in
Table 2 for each of the sites that provided sufficient detail for analysis in this area of the survey. The three metrics associated
with quality effort and activity shown are:

 Fraction of total technical personnel at the site that are part of the quality control (QC) and quality assurance (QA)
divisions of the site – this quantity was calculated from number of personnel in each division and is color‐coded from
red (0%) to green (100%)
 Site‐reported extent of using multi‐disciplinary (including engineering, technical support, etc.) internal quality teams
with color‐coding from red (1 = low use) to green (5 = high use)
 Number of third party inspections (as practice for inspections from regulators) conducted in the past five years with
color‐coding from red (0) to green (10)

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These three metrics are presented alongside a relevant quality performance outcome of reported deviation at the
commercial scale for any of the products produced at the site (where reported) within the past five years with color‐coding of
red for deviation reported and green for reporting that no deviations were encountered.  The one site that ranks high in
quality activity intensity for both internal and external efforts is also the one site reporting that no deviations were
encountered.  Sites having strong focus on either internal or external activities, but not both, were amongst those reporting
deviations.  Conclusions beyond these observations may be possible in the ongoing work as details of regulatory performance
will be collected and a larger data set from the survey will be available.

Table 2: Intensity of quality activities and associated presence of reported deviation in commercial product with color‐
coding from red (low intensity, negative outcome) to green (high intensity, positive outcome)

2.1.2 Perception of Interaction with Regulatory Bodies
As noted previously, recent quantitative analysis of FDA inspection data of the manufacture of small molecule
pharmaceuticals identified the presence of statistically significant differences in inspection outcomes for different FDA
inspectors (Macher, Mayo and Nickerson, 2009).  A similar analysis for biopharmaceutical manufacture using FDA inspection
data is intended to be completed as part of the ongoing work of this research project.  As part of the preliminary
biopharmaceutical manufacturing site survey results, a histogram of site‐reported perception of significant variation between
inspections completed by the FDA compared to the EMA as well as significant variation between inspections by the same
agency is presented in Figure 2.  Only sites familiar with inspections by both agencies provided responses.  In this preliminary
data, respondents were more likely to perceive variation within a given agency than between the FDA and EMA.  The logic for
this may be that the responses are framed relative to expectations, such that variation from a single agency appears more
obvious than variation between agencies and is therefore more likely to be recalled.

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6

5

4

3

2

1

0
Strongly Somewhat Neither Agree Somewhat Agree Strongly Agree
Disagree Disagree Nor Disagree
FDA ‐ EMA Within FDA Within EMA

Figure 2: Site perceptions of whether significant variation exists across inspections based on experience

2.2 Product‐Specific Results
The following characteristics summarize the thirty‐one (31) biopharmaceutical products that are including in this preliminary
results and discussion:

 Geographic location: Fifteen of the products are produced at sites in North America, ten in Europe, and six in Asia
 Processing: Twenty two of the products were produced by mammalian cell culture, nine by microbial fermentation
 Prior production: Three of the products were reported as being produced previously elsewhere at a similar scale
 Complexity: Fourteen of the products were site‐reported as significantly complex
 Role of Quality by Design (QbD) and continuous improvement (CI) initiatives: Four of the products were site‐reported
as being significantly impacted by one or both of these initiatives
 Advanced analysis: Eight of the products were site‐reported as being significantly impacted by novel process
analytical technology, management information systems, and/or multivariate data analysis
 Regularly manufactured: Eighteen of the products were site‐reported as being regularly produced at that site

Correlations of significance between these characteristics for the products in the preliminary survey data are presented in
Table 3. Positive correlation values between two variables indicate a likelihood of both having the same binomial direction.

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For example, based on the preliminary site‐reported survey data, products manufactured at the sites in Asia are most likely to
be characterized as not mammalian cell culture processes (therefore microbial fermentation), experienced significant input
from QbD and/or CI initiatives, utilized advanced analysis, and reported critical issues in commercial‐scale manufacturing
within the past five years.

Table 3: Correlation matrix for site‐reported product‐level quality compliance outcomes (shown in gray boxes) and product
characteristics.  Correlations significant at a 0.05 level are bold and correlations found to be significant at a 0.10 level are
italicized.

Critical Advanced
Quality Quality Quality Mammalian Process Prior Major Analysis Regularly Produced
Issue(s) in Issue(s) in Issue(s) in Cell Culture Described Role of QbD Used Manufactured Elsewhere Produced in
Development Commercial Commercial Process as Complex or CI Previously at this Site Previously Asia
Quality Issue(s) 1 0.33 0.43
in Development
Quality Issue(s) 0.33 1 0.51
in Commercial
Critical Quality 0.51 1 0.35 0.54
Issue(s) in
Commercial
Mammalian Cell 0.43 1 -0.41
Culture Process
Process 1
Described as
Complex
Prior Major Role 0.35 1 0.79
of QbD or CI
Advanced 1 0.46
Analysis Used
Previously
Regularly 1
Manufactured at
Produced 1
Elsewhere
Produced in Asia 0.54 -0.41 0.79 0.46 1

2.2.1 Preliminary results from logistic regression
Direct logistic regression was performed using PASW Statistics Version 18 software to assess the impact of a number of
factors on the likelihood that a product has had a reported quality defect at commercial scale within the past five years.  Five
independent variables were found to be significant at the 0.10 level and the resulting model was statistically significant at the
0.019 level  with χ2 (5, N=31) = 13.572.  The model as a whole explained between 35.5% (Cox and Snell R squared) and 47.3%
(Nagelkerke R squared) of the variance in reported quality defect of a given product, and correctly classified 74.2% of cases.
The strongest predictor of a reported quality defect was whether the product had been produced previously at a similar scale
at another site, recording an odds ratio of 0.016 as shown in the “Exp(B)” column of Table 4, indicating that products with a
reported quality defect were 0.016 times as likely to report previous production elsewhere at a similar scale than products

Page 11 of 16


without a reported quality defect, controlling for all other factors in the model.  The variables shown in Table 3 that are not
shown in Table 4 were included in the logistic regression analysis but were not found to be statistically significant.

Table 4: Logistic regression model independent variables of significance level of at least 0.10.  Row highlighting is shown to
improve readability of the table, but has no further meaning.

95% C.I.for EXP(B)
Variables in the Equation B S.E. Wald df Sig. Exp(B)
Lower Upper
Produced Elsewhere Previously at Similar Scale -4.127 2.055 4.036 1 .045 .016 .000 .904
Advanced Analysis Used Previously 2.986 1.492 4.006 1 .045 19.810 1.064 368.886
Regularly Manufactured at this Site -1.930 1.044 3.416 1 .065 .145 .019 1.124
Mammalian Cell Culture Process 1.614 .913 3.123 1 .077 5.021 .839 30.065
Process Described as Complex 1.760 1.002 3.085 1 .079 5.813 .816 41.440

The logic of relation between presence of a reported commercial scale defect within the past five years for a product and the
independent variables used in the logistic regression could take on multiple descriptions, as summarized in Table 5.  It is
hopeful that ongoing work in this research project will provide further detail into the potential logics.

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Table 5: Potential logics of independent variables as being a cause or an effect of quality defect(s)

Independent Variable Direction of Relationship with Potential Logic of Quality Defect Potential Logic of Quality Defect
Presence of Quality Defect Depending on Independent Variable Causing Independent Variable

Produced Elsewhere Occurrence of independent Products produced elsewhere More robust products more likely to
Previously at Similar variable correlated with previously more likely to have more be considered for transfer between
Scale decrease in likelihood of total lots produced, therefore greater sites
reported defect process understanding, thereby
reducing likelihood of defects

Advanced Analysis Occurrence of independent Use of advanced analysis techniques Process(es) that have had quality
Technique(s) Used variable correlated with increase involves greater level and frequency defects may be more likely
in likelihood of reported defect of inspection, thereby increasing the candidates for further and advanced
likelihood of detecting defect(s) analysis technique(s)

Regularly Occurrence of independent Regularly manufactured products Process(es) that have had quality
Manufactured at this variable correlated with may have well established quality defects may have to be
Site decrease in likelihood of analytical techniques that increase manufactured more regularly to
reported defect the likelihood of detecting defect(s) compensate for rejected lots

Mammalian Cell Occurrence of independent The mammalian cell culture process More complex products may be
Culture Process variable correlated with increase is generally considered to be more more likely candidates for cell
in likelihood of reported defect complex than microbial fermentation culture than microbial fermentation
(Molowa and Mazanet, 2003)

Manufacturing Occurrence of independent Complex process(es) more likely to Process(es) that have had quality
Process(es) Reported variable correlated with increase be difficult to operate, monitor, and defects are apparently less well
as Complex in likelihood of reported defect control, thereby increasing likelihood understood than others and
of defects therefore considered more complex

3 Ongoing Efforts
As noted previously, the intent of this research is to incorporate data from both the FDA and biomanufacturing firms.
Ongoing efforts are being made on both of these fronts to obtain the data and connect the data on site‐specific and
product‐specific bases between the sources. The FDA databases contain very detailed information on a variety of
dimensions. For instance, the Registration and Listing (R&L) database contains detailed manufacturing establishment
information, including the number and types of registered and listed drug products; establishment function(s), location,
and ownership characteristics; drug product therapeutic area, dosage form, and release profile characteristics. The
Inspections database provides detailed data on cGMP inspection outcomes, including the date and length of
inspections; manufacturing facility characteristics; FDA characteristics (e.g., district involved, investigator(s) involved,

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etc); and inspection outcomes. The Recalls database provides detailed data on product recalls, including date and length
of recall; root causes related to recalls, products involved in recalls, and manufacturing establishments/firms
responsible for recalls.

By bringing together these data sources, the research is focused on questions along the following lines of inquiry:

 How do biopharmaceutical manufacturing facility characteristics (e.g. location, experience), FDA
inspection policy (e.g. frequency, extent), and the increasing role of globalization impact U.S. public
health and safety as measured by regulatory outcomes?
o Does manufacturing firm experience with a given country or internationally have any effect on
regulatory compliance? Frequency and/or intensity of inspection by the FDA? Product recall
frequencies?
o Do country economic characteristics and country institutional‐level factors affect inspection
and/or product recall performance?
 How do timing of FDA inspections and outcomes of prior inspections impact firm behavior around the
importance of product quality and manufacturing innovation?
o Do shifts in regulatory policy approaches change inspection and/or recall performance of
biopharmaceutical firms?
o Are establishments that are in poor standing with the FDA in terms of compliance less likely to
pursue manufacturing innovations?
 At a summary level, how do the FDA strategies for ensuring biopharmaceutical product safety compare
in design and performance to those of other countries?
o To what extent is the FDA or other regulators intelligently employing their limited inspection
resources (e.g. use of stratified sampling and/or multi‐objective optimization)?
o Do demonstrated best practices in biopharmaceutical inspections exist and to what extent are
these practices relevant to the FDA?
In this way, this research will attempt to specifically address how the FDA can best achieve required compliance
by biopharmaceutical suppliers and manufacturers given the known resource and information limitations associated
with inspections. This involves defining and evaluating options to structure inspection and recall programs that minimize
safety risks to U.S. consumers. Comparison of these options and strategies practiced by regulators in other countries to
the US FDA will provide insight into potential strategic improvement opportunities that would reduce the likelihood of
biopharmaceutical product quality problems.

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4 References
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Organization, by M Armstrong and R. Porter. Elsevier, 2007.

Baron, D. "Design of Regulatory Mechanisms and Institutions." In Handbook of Industrial Organization, Vol. II, by R.
Schmalensee and R. Willig. North Holland, 1989.

Beard, T., D. Kaserman, and J. Mayo. "A Graphical Exposition of the Economic Theory of Regulation." Economic Inquiry 41
(October 2003): 592‐606.

Becker, G. "A Theory of Competition among Pressure Groups for Political Influence." Quarterly Journal of Economics 98
(August 1983): 371‐400.

Blank, L., and J. Mayo. "Endogeneous Regulatory Constraints and the Emergence of Hybrid Regulation." Georgetown
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Feinstein, J. "Detection Controlled Estimation." Journal of Law and Economics 33, no. 1 (April 1990): 233‐276.

Feinstein, J. "The Safety Regulation of U.S. Nuclear Power Plants: Violations, Inspections, and Abnormal Occurences." The
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Fremeth, A. and G.L.F. Holburn. “Information Asymmetries and Regulatory Decision Costs: An Analysis of Electric Utility Rate
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Laffont, J., and D. Martimort. The Theory of Incentives: The Principal‐Agent Model. Princeton, NJ: Princeton University Press,
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Laffont, J., and J. Tirole. "The Politics of Government Decision‐making: A Theory of Regulatory Capture." Quarterly Journal of
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Macher, J., J. Mayo, and J. Nickerson. "Exploring the Information Asymmetry Gap: Evidence from FDA Regulation." Journal of
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Olson, M. "Regulatory Agency Discretion among Competing Industries: Inside the FDA." Journal of Law, Economics and
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Spiller, P. "Politicians, Interest Groups and Regulators: A Multiple‐Principals Agency Theory of Regulation, or ‘Let Them be
Bribed'." Journal of Law and Economics 33 (April 1990): 65‐102.

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U.S. FDA. About the Center for Drug Evaluation and Research.
http://www.fda.gov/AboutFDA/CentersOffices/CDER/default.htm.

U.S. FDA. Risk‐Based Method for Prioritizing CGMP Inspections of Pharmaceutical Manufacturing Sites—A Pilot Risk Ranking
Model. FDA Mimeo, 2004, 1‐18.

Vogel, D. "The Globalization of Pharmaceutical Regulation." Governance 11, no. 1 (2002): 1‐22.

Weingart, B., and M. Moran. "Bureaucratic Discretion or Congressional Control? Regulatory Policymaking by the Federal
Trade Commission." Journal of Political Economy 91, no. 5 (October 1983): 765‐800.

Woo, J., S. Wolfgang, and H. Batista. "The Effect of Globalization of Drug Manufacturing, Production, and Sourcing and
Challenges for American Drug Safety." Clinical Pharmacology & Therapeutics 83, no. 3 (2008): 494–497.

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