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Reference Pricing or Price Cap Regulation of Pharmaceuticals?
Kurt R. Brekke∗, Astrid L. Grasdal,†Tor Helge Holmås‡
We study the relative performance of generic reference pricing (GRP) and price cap
regulation using a unique policy experiment from Norway. In 2003 Norway introduced a
GRP system called ‘index pricing’ for a subsample of oﬀ-patent pharmaceuticals, replacing a
price cap system based on international price comparisons. Unlike most other GRP systems,
the pharmacies were exposed to all incentives; not only did they keep the savings from selling
a (generic) drug with a price below the reimbursement level, but they also had to bear the
cost of selling a (brand-name) drug with a price above the reimbursement level. We use a
product level panel dataset covering the drugs exposed to index pricing and comparison group
consisting of therapeutic substitutes and unrelated drugs still under price cap regulation,
before and after the policy experiment. We find that the GRP system significantly reduced
both brand-name and generic prices within the reference group, but also had a price reducing
eﬀect on the non-included therapeutic substitutes.
Keywords: Pharmaceuticals; Price Regulation; Generic competition
∗Norwegian School of Economics and Business Administration, Department of Economics, HEB.
†University of Bergen, Department of Economics, HEB. email@example.com‡Institute for Research in Economics and Business Administration, HEB. firstname.lastname@example.org
Pharmaceutical markets are characterised by price inelastic demand, mainly due to extensive
medical insurance, and supply-side market power associated with the patent system protecting
new chemical entities from being copied within a given period. This combination has lead
most countries to exert various means to curb the pharmaceutical firms’ market power and to
control the growth in medical expenditures.1 We can distinguish between two diﬀerent price
control mechanisms: (i) regulation of drug prices by enforcing price caps; and (ii) regulation
of the reimbursement level, frequently referred to as reference pricing. While price caps limit
pharmaceutical firms’ ability to exploit market power by charging high prices, reference pricing
systems aim at stimulating competition by making demand more price elastic.
The price cap on pharmaceuticals is determined in many ways. Ideally, the price cap level
of a particular drug should reflect the therapeutic benefit, the R&D and production costs, and,
potentially, the costs of public funds. Instead, many countries, including Norway, apply the
increasingly popular scheme called international reference pricing. This scheme makes use of
international price comparisons, where the price cap of a particular drug is determined by the
lower prices of this drug in a set of ”comparable” countries.
Under reference pricing, however, the pharmaceutical firms are free to set their prices at
any level. Instead the reimbursement level is regulated. Drugs are classified into clusters based
on therapeutic eﬀect. The clusters may be narrowly or widely defined. A narrow definition is
to cluster drugs with the same active chemical ingredients only, called generic reference pricing
(GRP). A wider definition includes products with diﬀerent chemical ingredients but comparable
therapeutic eﬀects (therapeutic substitutes), called therapeutic reference pricing (TRP). The
reference price, which is the maximum reimbursement for all products in the cluster, is typically
based on a relatively low-priced drug in the cluster. Thus, (brand-name) drugs with prices above
the reference price, are subject to surcharges, which in most reference price systems are imposed
Price regulation of pharmaceuticals is a widely debated issue. However, little is known about
1 Danzon (1997) provides an excellent overview and discussion of various regulatory mechanisms and their
purposes in the pharmaceutical industry.
the performance of the diﬀerent systems.2 This paper exploits a unique policy experiment from
Norway. In 2003 the government introduced a GRP system, called ‘index pricing’, to a subsample
of the oﬀ-patent pharmaceuticals, replacing a price cap system based on international reference
pricing. We make use of a product-level panel dataset over a four-year period, covering the years
2001-2004, which means that we have information on drug prices before and after the policy
experiment. Moreover, the dataset includes not only the drugs exposed to index pricing, but
also a significant set of drugs still subject to price cap regulation. This latter group consists of
therapeutic substitutes and drugs that are unrelated in consumption, which may or may not
be under patent protection. The comparison group enables us to identify potential cross-price
eﬀects between the drugs subject to the GRP system and their therapeutic substitutes.
We find that the index price system had a strong price reducing eﬀect on both the brand-name
drugs and the generic drugs subject to this regime. Depending on the choice of comparison group
(and time specification), the GRP system induced a price reduction on the brand-names between
24 to 31 percent, and on generics between 13 to 19 percent. This result demonstrates that the
GRP system induced fierce price competition between branded and generic drugs exposed to
the system. It also indicates that GRP systems are more eﬀective than price cap systems in
reducing public and private medical expenditures.
We also identify a negative cross-price eﬀect of the index price system on the therapeutic
substitutes still under price cap regulation. In contrast to the drugs exposed to GRP, the price
reduction is more pronounced for generics than for brand-name drugs. The GRP system induced
a price reduction on generics in the therapeutic substitute group of 12.5 percent, while the same
figure for the brand-name substitutes is 5.9 percent. The weaker eﬀect on brand-names is most
The literature on performance of price regulation regimes are limited and mainly descriptive,
and there is a pronounced lack of theoretical and empirical studies of potential eﬀects of the
2 According to the extensive literature survey by Lopez-Casasnovas and Puig-Junoy (2001), the bulk of the RP
literature is mainly descriptive. See also Danzon (2001).
diﬀerent studies.3 Our paper is a contribution in that respect. There are, however, some notable
exceptions. Below we relate our paper to these.
Our paper is primarily concerned with price eﬀects of generic reference pricing compared
with a price cap regime. Danzon and Lui (1996) argues that all (the brand-name and generic)
prices within the reference cluster will converge towards the reference price, implying a price
decrease on the high-price (brand-name) drugs and a price increase on the low-priced (generic)
drugs. The reason is that in most GRP systems, the patients have to pay the surcharges when
demanding an expensive (brand-name) drug, but do not obtain any benefits from demanding
cheaper (generic) drugs. In this case, the demand curve is elastic above the reference price,
kinked at the reference price, and perfectly inelastic below the reference price.
Our results do not support the price convergence hypothesis. We find that both the brand-
name and the generic drug prices are substantially reduced following the introduction of the
index price system. In the Norwegian system, the patients were not exposed to any surcharges.
Instead all incentives were put on the pharmacies, which not only kept the margin from selling
a drug at price below the reference price, but also had to bear the full cost of selling a drug
priced above the reference price. If we, for the sake of exposition, include the pharmacies on
the demand-side, as we do with physicians, the demand curve associated with the index price
system is continuous (or smooth), and not kinked as suggested by Danzon and Liu (1996).
A related empirical study by Pavcnik (2002) derives a similar result to ours. Analysing
the policy change in Germany from "free pricing" towards a therapeutic reference pricing, she
identifies a strong price decrease for both brand-name and generic drugs, with the price decrease
being more pronounced for the former group. While we apply a somewhat similar approach to
identify the eﬀects of the Norwegian GRP system, the studies diﬀer quite significantly. In
particular, Pavcnik (2002) considers the eﬀect of the change on the patients’ out-of-pocket
expenses on the pharmaceutical firms price setting. The Norwegian GRP system did not change
the patients’ out-of-pocket expenses, and the benchmark is not "free pricing", as in Germany.
Our paper is instead concerned with the price eﬀects of a GRP system — exposing the pharmacies
to all incentives — compared with price cap regulation.
3 See Danzon (1997) for a general overview of the literature on price regulation of pharmaceuticals. On the
reference price systems, in particular, the extensive literature survey by Lopez-Casasnovas and Puig-Junoy (2000)explicitly states this concern. See also Danzon (2001).
There exists a recent paper by Dalen et al. (2005) analysing the Norwegian index pricing
system. They estimate a structural model to analyse the impact of the reform on both demand
and market power, showing that the index price system increased the market shares of the
generic drugs and triggered price competition. However, they only have data on the six chemical
substances subject to the GRP system, and for a limited (22) number of pharmacies. Our dataset
includes, besides the six chemical substances, a wide set of drugs — both therapeutic substitutes
and drugs that are unrelated in consumption — which enables us to clearly identify the net price
eﬀects of the index pricing system, and assess the relative performance of the GRP system and
the price cap system. In addition, we provide evidence on a negative cross-price eﬀect of the
GRP system on the therapeutic substitutes still under price cap regulation, which indicates that
the study by Dalen et al. (2005) focusing only on the drugs exposed to the GRP system tend
to under-estimate the total price, and thus cost-saving, eﬀect of this system.
GRP is considered to be uncontroversial (in contrast to TRP) for two reasons (see e.g., Lopez-
Casasnovas and Puig-Junoy, 2000). First, since it only applies to drugs with the same active
chemical substances, the health risks to patients associated generic substitution are considered
to be very limited. Second, since GRP applies by definition to oﬀ-patent drugs only, it is
perceived to not aﬀect the patent protection, and thus market entry and innovation decisions.
A theoretical paper by Brekke et al. (2005) show that this is not necessarily true. Using a
model combining generic and therapeutic competition, they find that GRP exposes patients
to higher health risks than TRP (and free pricing) since it results in the largest diﬀerences in
out-of-pocket payments. Moreover, they show that GRP not only triggers lower prices for the
chemically equivalent drugs, but also has a price decreasing eﬀect on the therapeutic substitutes,
with the magnitude depending on the degree of substitutability.
Our paper is not able to test the eﬀect of GRP on neither the patients’ health risk nor
the market entry and innovation incentives of the firms.4 However, we provide evidence on a
negative cross-price eﬀect of the GRP system on therapeutic substitutes not subject to this
system. This confirms the concern with GRP systems, raised by Brekke et al. (2005), that it
may influence the patent protection. The cross-price eﬀect is, however, much weaker than the
4 A paper by Danzon and Ketchham (2004) analyses the eﬀect of reference pricing on the availability of drugs
in Germany, the Netherlands and New Zealand, providing results that indicates that the strictness of the RPsystems tend to lower the number of drugs available in a country.
direct price eﬀect on the drugs subject to index pricing, which is consistent with Ellison et al.
The Norwegian pharmaceutical market is extensively regulated, as most other countries. The
regulatory body is the Norwegian Ministry of Health and Care Services and its agency called the
Norwegian Medicines Agency. Norway has adopted the European patent law system to a large
extent, such that all new chemical entities are subject to patent protection for a given period.
However, the pharmaceutical firms still need government approval to launch a new product in
Norway. In addition, they must submit an application providing suﬃcient evidence of benefits
compared with costs from the drug therapy in order to get the drug listed in the reimbursement
system (the blue list). Once this is obtained, the prices are subject to price control.
The current system is a price cap scheme based on international reference pricing. This
system was introduced in 2001, and covers all prescription drugs, both on-patent and oﬀ-patent,
except for those included in the index pricing system.5 The price cap is defined as the weighted
sum of the three lowest prices of a specific drug in a basket of countries that is "comparable"
to Norway.6 The price cap is imposed at the wholesale level, leaving the producer prices un-
regulated. The government then defines a maximum product-specific mark-up, which in turn
determines the price cap on the retail price of each product.
The index pricing scheme was introduced in March 2003 for a subsample of oﬀ-patent phar-
maceuticals facing generic competition. Initially, the index price system covered six chemical
substances: Citalopram (depression), Omeprazol (antiulcer), Cetirizin (allergy), Loratadin (al-
lergy), Enalapril (high blood pressure), Lisinopril (high blood pressure). In June 2004 Simavas-
tatin (high cholesterol) was included. The government decided to terminate the system by the
end of 2004, arguing that the expected cost savings did not materialise. Thus, in total the
5 Over-the-counter (OTC) drugs are not subject to any price regulation, so the pharmaceutical firms can freely
set the prices on these group of drugs.
6 The following countries are included in the Norwegian basket: Austria, Belgium, Danmark, Finland, Germany,
Irland, the Netherlands, Sweden and the UK. Thus, Southern and Eastern Europian countries, as well as, Franceand Swiss, are excluded. If there are no prices yet in these countries, the price is determined by negotiationsbased on the provided evidence on benefit and costs of the medical treatment in question.
The index price was calculated as follows. First, the drugs were classified into clusters
based on chemical substance. Then within each cluster, the drugs were classified into subgroups
depending on the package size and dosage in order to adjust for cost variation. Second, the
index price was calculated as the sales weighted sum of producer prices of the drugs included
in each subgroup. For the six chemical substances initially included, there were 16 index prices
in total. This exercise were repeated every three months, resulting in a revised index price for
every quarterly. Formally, the index price for a given period t, denoted by It, can be defined as:
where pt−1 is the producer price of product i in the previous period, i.e., t
sold of product i in the previous period, measured in tablets or defined daily doses (DDD), and,
thus, M t−1 is the market share of product i in the previous period. Since each period t lasts for
three months, all variables are average values. The index price was the maximum reimbursement
for every drug in the reference group. We see that the index price is reduced if lower-priced
(generic) drugs increase their market share, and/or if there is a price decrease of the higher-priced
(brand-name) drugs and/or the lower-priced (generic) drugs generic in the cluster.
A special feature of the index price system relative to other reference price systems is that
the pharmacies were exposed to all incentives. Not only did they keep the margin of selling
a (generic) drug with a price lower than the index price, but they also had to bear the full
cost of selling the a (brand-name) drug with a price higher than the index price. Importantly,
generic substitution was allowed in 2001, so the pharmacies could suggest a cheaper (generic)
drug, although the physician had written a brand-name drug on the prescription (which they
frequently tend to do). If the patient refused to accept a generic substitution, the patient had
to pay the surcharge associated with the diﬀerence between the high-priced (brand-name) drug
and the index price. On the other hand, the physicians could blockade generic substitution by
actively writing an argument on the prescription of why this particular patient is better oﬀ with
In Norway there is a statutory public health insurance, covering the whole population. Close
to 70 percent of the total drug expenses are covered by this insurance scheme. For prescription
drugs on the reimbursement list (the blue list), patients pay a fixed share (36 percent) of the
drug price, constrained by a maximum amount per prescription (400 NOK) and per year (1.350
NOK). Notably, the patients’ copayments are not aﬀected by the index price system — as all
incentives are imposed on the pharmacies — except for the case when the patient refuses to
accept a cheaper (generic) substitute. Then the patient must pay the diﬀerence between the
reference price and the actual price of the drug, as common in reference price system. In addition,
the physicians can blockade generic substitution by actively claim on the prescription that the
patient is better-oﬀ with the expensive (brand-name) drug, but an argument is needed.
In the empirical analysis we use data from Farmastat.7 Their database includes information
on value and volume for each package of drugs sold at the Norwegian pharmaceutical market.
Values are in pharmacy purchase prices and volumes in defined daily doses (DDD) for the
active substance (ATC-code). The database also provides information about product name,
manufacturer, launch date, price cap, whether the product is a brand-name or a generic drug,
From this database we have data on all prescription drugs within the 30 largest (in terms of
volume) ATC-groups over a four year period from 2001 to 2004. Table 1 lists ATC-code, brand-
name, and manufacturer of these pharmaceuticals. The table also gives information about
whether the drugs within each ATC-code are subject to reference pricing or not, whether the
branded drug faces generic competition or not, and whether or not it is classified as a therapeutic
competitor to a drug in the reference price group. This last classification is based on therapeutic
categories. For example, Losec with ATC-code A02BC01 is included in the index price system,
and therefore all pharmaceuticals with A02 as the first three characters in the ATC-code are
classified as therapeutic competitors to Losec.
7 Farmastat is a company specialised in provision of pharmaceutical statistics. The company is owned by the
Norwegian Association of Pharmaceutical Manufacturers.
In our analysis, we define a product as all presentations of a given drug produced by a
given manufacturer. For example, the brand-name Zantac together with five generic products
give a total of six products in ATC-group A02BA02. For each product, prices are calculated
as total sales values divided by the total volume sold (in DDD). All prices therefore refer to
average prices per defined daily dose of the active ingredient; a price measure that enables
comparison across diﬀerent formulations (tablets, capsules, etc.) within each product, and also
across diﬀerent active ingredients. Time is divided into two-month periods, and the average
price of each product in each time-period constitutes an observation provided that the product
is present in our data. The number of observations within each ATC-group is given in the last
column in Table 1. The total number of observations in our analysis is 1415.
A natural starting point for the descriptive analysis is to look at how average prices have de-
veloped over time. In Figure 1, we plot average prices for brand-names and generics for the
following three groups of pharmaceuticals: (i) the pharmaceuticals subject to generic reference
pricing, (ii) the drugs that are therapeutic substitutes still under price cap regulation, and (iii)
the others, which are independent in consumption and exposed to price cap regulation.
With time measured in two month periods, the reference price regulation was introduced in
period 13 in the figure. Average prices of pharmaceuticals subject to reference pricing display
a pronounced decrease after the implementation of the reform. In Table 2, we have calculated
the average price in the periods before and after the implementation of the index price system.
We find that average prices in the pre-regulation period is about 4.7 NOK, while average prices
during reference pricing is about 3.3 NOK. This implies a price reduction of more than 29
percent. Turning to the therapeutic competitor group, we find a somewhat similar price pattern
as in the group of pharmaceutical subject to GRP prior to the reform, but the decrease in
average prices after the regulation is much smaller, about 12 percent. The average prices in
the “others” group show a quite diﬀerent price pattern; a large decline in the first part of the
reference price period is followed by an increase in the second part of this period.
To get a better understanding of the price patterns depicted in Figure 1, we plot the average
prices of brand-names and generics together with the average price cap for the three groups. In
Figure 2, we see that the average price of the brand-name drugs has been steadily decreasing
after the implementation of the reference price regulation. Interestingly, in the pre-regulation
period, average prices of generic drugs follow almost the same price pattern as brand-name
From Figure 3 and 4, we see that average prices of brand-names in the therapeutic competitor
group and the “others” group follow the maximum price over the entire period. This indicates
that the generic reference price regulation had a small, if any eﬀect on the price setting of brand-
name drugs in the group of pharmaceuticals not directly aﬀected by the regulation. However,
average prices of generic drugs in the therapeutic competitor group follow the same pattern as
prices for generics in the reference pricing group. This indicates that much of the price reduction
in the therapeutic competitor group is explained by a reduction in prices on generic drugs.
We estimate the eﬀect of introducing index pricing on product level prices by comparing inter-
temporal variation in (log) prices before and after imposition of the reform. Identification relies
not only on before-after comparison, but also on comparison of price variation for drugs subject
to the reform with price variation for comparable drugs not subject to the reform.
Ideally, in order to estimate the eﬀect on prices of introducing index pricing on the products
aﬀected by the reform, we would like to know what the prices on these products would have been
had the reform not been imposed on them. Since we only can observe prices for these products
with the imposed reform, we let the prices for a set of other comparable products represent the
counterfactual. For this specific reform comparable products are first and foremost products
within other therapeutic substances with a broad spectre of presentations and their generic
substitutes. However, since we also are interested in whether or not the reform has an impact
on therapeutic substitutes, branded as well as generic, we also include such among the products
We employ the following semi-logarithmic specification:
tDt + β1GRPit + β2GRPit ∗ Bi + β3GRP Pit ∗ T Si
+β4GRP Pit ∗ Bi ∗ T Si + β5Hit + β6NGit + β7P CAPit + ai + εit,
where the D‘s are period indicators. GRP is an indicator of whether product i is subject to the
GRP-system at time t. For products in six of the seven chemical substances included in the index
price system the variable equals zero for t = 1, ., 13, and one for t = 14, ., 24. For products
in the seventh substance that was included in September 2004, the variable equals zero up to
period 22 and one thereafter. GRP is equal to zero in all time periods for all other products.
GRP ∗ B is an interaction between GRP and an indicator of whether or not the product is a
brand-name product. Furthermore, we define a variable GRP P equal to zero for all time periods
before the GRP system was introduced, and one thereafter. In the regression, this variable is
interacted with a variable T S, indicating whether or not a product is a therapeutic substitute
to the products exposed to the GRP system. We also include the interaction GRP P ∗ B ∗ T S in
order to capture the diﬀerence in eﬀect on branded versus generic therapeutic substitutes. We
augment equation (1) with the variable H, which is the Herfindahl index, measuring the degree
of market concentration within a chemical substance group, the variable N G, which measures
the number of generic products, and P CAP , which is the average price cap. Note that i for
these three variables refer to the chemical substance group, and not the particular product i.
Finally, ai is a product fixed eﬀect, and εit represent measurement errors in prices or unobserved
We employ the fixed eﬀect estimator, and compute robust standard errors adjusted for
clustering on product level.8 The standard errors are robust to the presence of general forms of
8 Note that one base time period had to be excluded in the models estimated with time periods.
heteroscedasticity and also accounts for potential serial correlation within products over time.
We start out by estimating fixed eﬀects based on a more simple version of equation (1), where
we only include GRP , GRP ∗ B, and alternative time-specifications, i.e. time periods, year-
dummies or a time-trend variable. The three diﬀerent models are estimated when including
all products not exposed to GRP in the comparison group, when including only therapeutic
competitors and when excluding therapeutic competitors.
Results reported in Table 3 show that the introduction of GRP significantly (1%-level) re-
duces prices on generics, as well as branded products included in the system. Depending on
the choice of time specification and comparison group the eﬀect on prices on generic substitutes
vary between −13.1 percent and −19.3 percent, whereas the reduction in prices for the branded
products is even stronger (the sum of β1 and β2) varying between −24.1 percent (column 4) and
−30.9 percent (column 8).9 We see that the estimated eﬀects of introducing GRP are smaller
when only including therapeutic substitutes among the comparison group members. This may
indicate that prices on therapeutic substitutes too are aﬀected by the introduction of the GRP
We now estimate the full model when using time period dummies, and including all other
products among the comparison group members. Fixed eﬀect estimates are reported in Table
4 when including one additional variable at a time. The estimates of the eﬀects of the reform
are robust to the inclusion of other variables and remain statistically significant at the 1%-level.
In column 5 in the table, results are reported for the full model. We see that when controlling
for over time changes in the price cap, and changes in market structure and competition, the
reform on average has resulted in a 20.1 percent decrease in prices on generic substitutes, and
a 30 percent decrease in prices on branded products. In addition, these results show that, on
average, prices on therapeutic substitutes not included in the reform have responded to the
reform as well. The eﬀect is strongest for therapeutic generic substitutes, for which prices on
average are reduced by 12.5 percent. For branded therapeutic competitors, prices are on average
9 We also estimated the models when including only therapeutic substances with a broad spectre of presentations
and their generic substitutes in the comparison group. The results did not diﬀer substantially from those reportedin Table 3.
reduces by 5.9 percent. These eﬀects too, are statistically significant at the 1% level.
 Brekke, K.R., Königbauer, I., Straume, O.R., 2005. Reference pricing of pharmaceuticals.
Discussion Paper SAM 25, Norwegian School of Economics and Business Administration.
 Dalen, D.M., Strøm, S., Haabeth, T., 2005. Price regulation and generic competition in the
pharmaceutical market. University of Oslo, Mimeo.
 Danzon, P.M., Lui, H., 1996. RP and physician drug budgets: the German experience in
controlling pharmaceutical expenditures. Working paper, The Wharton School.
 Danzon, P.M., 1997. Pharmaceutical Price Regulation: National Policies versus Global In-
terests. American Enterprise Institute Press, Washington.
 Danzon, P.M., 2001. Reference Pricing:
Casasnovas, G., Jönsson, B., (eds.): Reference Pricing and Pharmaceutical Policy: Per-
spectives on Economics and Innovation. Springer, Barcelona.
 Danzon, P.M., Ketcham, J.D, 2004. Reference pricing of pharmaceuticals for Medicare: Ev-
idence from Germany, The Netherlands and New Zealand. Frontiers in Health Policy Re-
search, vol. 7, Cutler, D.M, Garber A.M., (eds.) National Bureau of Economic Research and
 Ellison, S.F., Cockburn, I., Griliches, A., Hausman, J., 1997. Characteristics of demand for
pharmaceutical products: an examination of four cephalosporins. RAND Journal of Eco-
 Lopez-Casasnovas, G., Puig-Junoy, J., 2000. Review of the Literature on Reference Pricing,
 Pavcnik, N., 2002. Do pharmaceutical prices respond to potential patient out-of-pocket ex-
penses? RAND Journal of Economics 33(3), 469-487.
Appendix A: Tables and Figures
Table 1: Sample characteristics
Table 2: Average prices before and after generic reference pricing.
Table 3: Price effects of generic reference pricing. Fixed effect results with robust
*: significant at the 5% level. **: significant at the 1% level. Table 4: Price effects of generic reference pricing when controlling for competition and
price cap regulation. Fixed effect results with robust standard errors.
*: significant at the 5% level. **: significant at the 1% level.
LIST OF BIOANALYTICAL METHODS NEWLY DEVELOPED OR RECENTLY UPDATED METHODS Bioanalytical Compound Calibration Range Bioanalytical matrix Carbidopa ; Levodopa LC/MS/MS 2-75 ng/mL ; 10-750 ng/mL Human EDTA Plasma Carbidopa ; Levodopa LC/MS/MS 5-250 ng/mL ; 10-2500 ng/mL Human EDTA Plasma Budesonide LC/MS/MS 5-1000 pg/mL Human EDTA
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