Budget control, shaping priorities, attitudes towards clinical trials and data utilization are four areas in which governments can take actions to improve spending efficiency of medicine reimbursement, while remaining budget neutral. Unfortunately, those opportunities are rarely seized. Therefore, there is space for pharmaceutical companies to support public bodies.

1. White Paper
RESPONSE TO LIMITED
REIMBURSEMENT FUNDING
A CEE perspective
MIROSŁAW PAWEŁKO, PhD, General Manager, South East European Cluster, IQVIA

2. TABLE OF CONTENTS
Four opportunities 3
Budget control 4
Shaping priorities 5
Attitude towards clinical trials 7
Data utilization 8
Conclusion 10
Appendix 11
References 12
About the author 13
Acknowledgement 13
About IQVIA 14

3. iqvia.com | 3
FOUR OPPORTUNITIES
Budget control, shaping priorities, attitude towards clinical trials and data
utilization are four areas in which governments can take actions to improve
efficiency of medicine reimbursement, while remaining budget neutral.
Unfortunately, existing opportunities are rarely seized. This creates an
opportunity for pharmaceutical companies to support public bodies.
In 2018 15 CEE countries1
spent 11.3 bn EUR2
(ca. 50 bn
PLN) of public money on reimbursement of medicines,
which constituted ca. 64% of total spending on
medicines. It was an increase of 1.6 bn EUR compared
to 2014 (17% growth), however still many innovative
products remained unreimbursed in our region. In fact,
only between 10-33% of new drugs approved between
years 2013-16 by the European Drug Agency were
reimbursed in the CEE countries in 2018.
Admittedly, the total spending on medicine (reimbursed
and out of pocket), which comprises between 13-25% of
the total spending on health care is not the only challenge
faced by the healthcare systems in our region. While
specialists’ accessibility, their average age and their low
remuneration (often leading to the, so called, brain drain)
is often seen as more crucial, drug accessibility remain
among the top hindrances to the system.
Public spending on medicine may never cover all
needs. We are still lagging behind countries offering
better access to innovative medicines. For example,
Germany spends 3 times more per capita on medicines
then an average CEE country. On the horizon we also
have new, initially costly, therapies (e.g. for dementia)
and in some cases (e.g. CAR-T, RNAi gene editing) they
may shift the paradigm of pharmaceutical therapies.
Chimeric antigen receptor T-cell therapy today still
costs over 0.4m EUR per patient. At the same time,
we are experiencing changes on the demand side,
Exhibit 1. Four opportunities for public decision makers
BUDGET CONTROL
• Gaining real control
on public spending
ATTITUDE TOWARDS
CLINICAL TRIALS
• Creating context for better patients’
access to innovative medicines
in Phase 3 trials
SHAPING PRIORITIES
DATA UTILIZATION
• Deciding proactively about share
of public spending per therapy
area and patient groups as well
as about copayment share
• Understanding spending structure
• Utilizing real world evidence to
take beter decisions
FOUR
OPPORTUNITIES
Source: IQVIA analysis

4. 4 | Response to limited reimbursement funding. A CEE perspective.
with ageing population as one of the most important
drivers. Today, out of the total 119m living in CEE,
there are 20.5 m people age >65. In 5 years this will
increase to ca. 23.0 m. There are also other trends
leading to higher demand, e.g. rise in chronic disease,
and other conditions related to unhealthy lifestyles or
environmental pollution.
Having said that, the preoccupation with limited
resources restrains actions. We need to accept scarcity
of resources, just as we do in the case of our family
budgets. Therefore, the key question should not
be how to define new sources of funding – but how
we want to make the best out of the available ones.
Apart from price pressure on manufacturers and
restricting access to drugs, there are at least four more
constructive actions governments can take to focus on
efficiency. Unfortunately, they are often not sufficiently
addressed, a case in point being the Drug Policy
adopted in December 2018 by the Polish government.
BUDGET CONTROL
When discussing the allocation efficiency of public
funds in healthcare, the first step should be the
verification if supervisory bodies have a real ability to
execute expenditure frameworks and thereby remain
within budget constraints.
Three out of top four CEE countries, by the
pharmaceutical market size (Poland, Romania and
Czechia), appear to have strong tools to control
spending and in 2017 and in 2018 (based on preliminary
estimations) recorded no deficit. Officially, only
Hungary exceeded the budget by 5.7% in 2017.
However, there is a difference in the way payback is
approached – in Poland and Hungary it is not added
to the reimbursement budget, while in Romania and
Czechia it is. Further, it needs to be mentioned that
Czechia, which has 7 private payers (not a single public
one like the others), has a different budget structure.
The surplus in the reimbursement budget in Poland
was the result of a new reimbursement law in force
since January 2012. Until 2014, the final spending had
never exceeded initial budget (there were budget
updates, but finally they only served as an extra buffer).
From 2015 onwards, after elimination of constraints for
oncology treatment, updates were needed to remain
within the budget. The resulting initial surplus was
successively decreasing and in 2018 it finally resulted
in an estimated 0.5% deficit (based on a recent press
statement by the Minister of Health, the Health Fund
reported preliminary 2.5% surplus).
The deficit partially depends on the quality of planning
and strength of budget forecast assumptions that
build on previous periods. None of the CEE countries
goes beyond simple tools when predicting the demand
for the coming year. Instead countries use a relatively
simple top down approach – health funds define how
much money they will have the following year based on
macroeconomic assumptions. The process does not take
into consideration outcomes of the health technology
assessment (HTA), an analysis that is submitted for the
reimbursement approvals, which calculates budgetary
impact by looking at the population of patients and the
expected use of the drugs.
Whatever the way the total budget is defined, there
are several tools that help governments control the
spending. They may negotiate low price, set clear
reimbursement level, strictly control prescribing or
dispensing, require higher patients’ contribution (out
of pocket) or set payback mechanism. Countries in our
region choose different sets of tools and they define
the logic of those tools in different ways. Thus, the
system may either create context for allowing demand
to generate deficit or not.
Most diverse interpretation relates to payback (or
clawback)3
mechanism. The baseline is shared – the
mechanism obliges companies which have their drugs
reimbursed, to give some part of it back based on
defined criteria. The devil is in the criteria.
In Poland regulations see payback in two forms – as
an excess reimbursement in comparison to budget by
therapy area and as a potential outcome of risk sharing

5. iqvia.com | 5
agreements (RSAs). The former one was not yet used as
the budget has not been exceeded since the regulation
was implemented in 2012. The latter one in 2017
generated an amount of 4.26% of total reimbursement
spending (351m PLN, or 81.6m EUR). As RSAs are
applied for innovative therapies, the scheme affected
the new, patent protected products which increased
their sales.
In Romania the situation is different as the payback
is calculated versus the total budget and is equal for
all companies. In 2018 on average it reached 23.6%
of the reimbursement. This way players, both those
which increased their sales and those which faced sales
decrease, are equally affected.
The Hungarian scheme also affects revenue of each
company but is a bit more complex as there are three
elements of the payback. First, there is a 20% tax on
all reimbursed revenues. Then there is an extra 10%
applied to branded drugs that have been reimbursed
for at least 6 years, without any generic equivalent
and priced at 3.1 EUR or more. Finally, there might be
budget excess payments – however since 2010 that has
not been enforced. Finally, some analysts consider the
tax on representative (31k EUR fee per an employed
sales rep) as the fourth form of payback.
In Czechia payback is applied only based on individual
risk sharing agreements and no value has been
reported publicly.
The clawback schemes also give some advantages to
pharma producers, especially when they are applied
under special agreements (managed entry/ risk sharing
agreements). For example, they allow for hiding of the
applied discount, which matters for the International
Reference Pricing. That is the model that requires
pharma companies to present list prices in different
countries so that the local payer may monitor if it gets
the best price.
SHAPING PRIORITIES
Once we know if we can control the budget, we can
discuss the structure of the spending. Within just the
spending on medicines we can notice considerable
differences between CEE countries. Oncology
medicines represented between 11 and 27%, while
Exhibit 2. 2017 deficit, payback and other spending control tools (Top 4 CEE countries)
*TA=Therapy Area; **MAH=Marketing Authorization Holder
Source: IQVIA analysis, local Health Funds
POL ROM HUN CZE
Reimbursement budget deficit as share
of the total budget [%]
– – 5.7% –
Payback
Share of total
reimbursement value [%]
4.26% 23.6% 20% <1%
Logic • From risk sharing
• Excess vs budget
per TA*
Equal for all MAHs** • 20% on all
• Extra 10% if
criteria met
• Budget excess
Based on individual
agreements
Strength of other spending control tool (relative assessment: 1-weak, 5-strong)
PRICE CONTROL
PRESCRIBING CONTROL
DISPENSE CONTROL
PATIENTS CONTRIBUTION

6. 6 | Response to limited reimbursement funding. A CEE perspective.
alimentary diseases took 8-18% of total public
spending. We may assume that prevalence is similar
among CEE countries, therefore the indicated ranges
show the room for maneuvering for the payers. It
is indeed a political decision to define therapy area
priorities, to define co-payment requirements, to
negotiate prices, to drive therapeutic guidelines and
to enroll innovative drug onto the reimbursement lists
and shape the basket of products used.
The structure of spending does not corelate with the
structure of patients. Out of the total population there
are 1.0-2.0% people affected by oncological diseases
and immunological disorders, while spending for
those therapies takes on average 16% of total budgets.
In alimentary field, there are 6-10% of population
who received ca. 14% of the total public spending. On
average an oncology patient pay from their pockets
0-5%, while alimentary patients pay up to 29% of drugs
value. Conclusions from such comparisons should be
made by politicians. While they will have impact on
performance of pharmaceutical companies – the main
criterion should be the impact on patients. We should
bear in mind, that there is a moral challenge decision
makers face. Some lifesaving one off therapies for one
person might cost as much as lifelong therapies for
multiple other patients. With 119m people living in the
CEE, such reckonings are infinite.
In the era of health economics, we may look also at
the quality adjusted life year (QALY) benefit, which
is a measure of disease burden, including both the
quality and the length of life. In most CEE countries
there are HTA agencies established to assess the
value for money for drugs before decision about
their reimbursement is made. However, in none
of the countries one can see analysis of multiple
drugs used by one patient or comparisons between
investments in different therapies. An example of
a good practice in this area is the recent analysis of
Exhibit 3. Shares in public spending of ATC L and A, Out of Pocket (OOP) and patient population;
Top 4 CEE countries
17.1% 15.3%
27.8%
21.3%
5.0%
Share in
total public
spending
Share in
total public
spending
Oncology
and
Immunology
(ATC1
L)
Alimentary
(ATC1
A)
Share of
OOP* in
the class
Share of
OOP* in
the class
5.0% 0.4% 0.0%
23.0% 29.0% 25.0% 2.4%
POL ROM HUN CZE POL ROM HUN CZE
8.2%
17.1%
12.5% 12.8%
1.3%
1.0%
1.8% 1.9%
6.4%
9.8%
7.4 %
8.5%
Share in spending and of out of pocket
[%] 2018
Share of patients in total population**
[%]
*Out Of Pocket; **By WHO: for Oncology: 5y prevalence| for Alimentary: Diabetes cases (18-99 years)
Source: IQVIA analysis, Health Funds report

7. iqvia.com | 7
the latest submissions to the UK HTA agency (NICE),
which indicated that QALY benefit from 1 EUR spent
on diabetic therapy might be 27 time higher than on
oncology therapy.
In our region one can hear arguments that drugs
should prevent from death more often rather then
that they should improve life quality – therefore as the
argumentation for the structure of spending we can
see mortality and cause of deaths structures, not QALY.
In Poland this way goals were set for the health care
policies and the statistic was presented in the recent
governmental Drug Policy. Data4
shows that in top 4 CEE
countries 46-50% of deaths are caused by diseases of
the circulatory system, 23-26% by cancer and 5-7% by
respiratory system issues. Those proportions are not
reflected in the structure of spending (e.g. Cardiovascular
drugs comprised 9-20% of reimbursement). At the same
time, it is indicated that ca. 28%5
of deaths might have
been reported using garbage codes, which do not allow
for precise definition of the cause.
Biosimilars’ use is a good example of policies impacting
structure of spending. As there are some concerns
about bioequivalence, there are different approaches
between countries about how the biosimilars should
be treated. Openness for their reimbursement and
treating them almost as generics (vs their originator
biologic) reduces costs per patient and allows for an
increase of the total number of patients treated. For
example (see Exhibit 4) entry of biosimilar infliximab in
Poland increased spending efficiency.
ATTITUDE TOWARDS CLINICAL
TRIALS
Countries in our region offer different conditions
for clinical trials and as a consequence there are
differences in volumes, which are unrelated to their
total populations. See Exhibit 5.
Romania and Poland show substantially lower levels of
participation in clinical trials than Czechia or Hungary.
Romania could have 4 times more patients and Poland
twice as many as they do currently, if they reached
Czechia’s rates. Apart from the population of patients,
volume of trials depends on the time to market,
costs and quality of specialists and of the medical
equipment. Duration of preparatory works and
trials themselves depend on regulatory framework,
administrative procedures with hospital and timely
responses of public bodies in the approval process.
All those elements might be impacted by Ministries
Exhibit 4. Infliximab case in Poland.
Source: IQVIA analysis
2015 2016 2017 2018 2019
1.32 1.22 1.19 1.17
1.02
-22.4%
Average price/ unit [PLN] Reimbursement value [m PLN] Reimbursement volume [k Units]
2015 2016 2017
Originator Biosimilars
2018 2019
16.0 15.8
19.1
33.4
38.6
+142%
21.0 19.2
22.8
39.0 39.4
2015 2016 2017 2018 2019
+88%

8. 8 | Response to limited reimbursement funding. A CEE perspective.
of Health. In the near future legal framework for the
remote trials will also be required.
As Exhibit 5 shows, it takes almost twice as long in
Poland and three time longer in Romania then in
Hungary to initiate clinical trial. Thus, even if Romania
is cost wise and population wise competitive, it does
not attract as many studies as Hungary.
There are numerous advantages of bringing more
clinical trials to the country. They help patients get
access to innovative treatments for free and give them
opportunities for additional screening and checks. They
stimulate training of specialists, who take the role of
researchers and allow for knowledge and technology
transfers. They provide extra money flow to the
healthcare system – not only to specialists or teams
leading trials, but might also cover expensive diagnostic
tests for a broader population or infrastructural
investment for hospitals. Finally, they generate extra
money for public budgets in the form of taxes and fees.
DATA UTILIZATION
Better data utilization might also lead to efficiency in
reimbursement spending and there are two aspects
related to this point. One is about analyzing the
spending structure, the other about utilizing real world
evidence to make better decisions.
As in any big data analysis, it starts with collection of
data. Poland, Hungary and Czechia have developed
transparent tracking system of reimbursement
expenses. They register reimbursed sales by pack and
patient and offer decision makers access to aggregated
and detailed information. Currently, they only miss
inclusion non-reimbursed sales (which might change
soon in Poland). Romania is the only country that lags
behind the group, with only some data collected and
without full transparency.
However, what matters more, is the utilization of
data collected for analyses. Hungary stands out from
Exhibit 5. Clinical trials benchmarking, 2017, Top 4 CEE countries
POL
ROM
HUN
CZE
932
402
1,364
1,698
1,379
559
1,027
1,019
24
36
14
19
49
40
44
46
# of patient in trial/
1m of population
Active studies −
2017
Average initiation
timeline for clinical
studies [weeks]
Cost of CT
(US=100)
Source: IQVIA analysis, LongTaal

9. iqvia.com | 9
the group – it produces regular reports analyzing
expense dynamic and patient level statistics. They
offer paid access to detailed set of information for
external parties on request basis and from time to
time they do use analyses’ outcomes in the decision-
making process.
In Poland the quantitative information, while
collected, remains underutilized. The governmental
Drug Policy of Poland, for example, included no
analysis based on payer’s data. Therefore, there
exists a clear room for improvement, as leveraging
statistical analysis in overviews and forecasts would
undoubtedly enhance their value. In Romania and
Czechia the situation is worse, as there are only
some, ad hoc analyses of the general and patient
level spending.
What could we learn from extra reviews? For
example, the spending structure by patient gives
information on who really uses the system. Based
on IQVIA Longitudinal Prescription Data in Poland
we can see that 21% of retail reimbursement spending
goes to 1% of patients, and first 10% of patients get 64%
of the budget. It helps to ask the question of efficiency
and usefulness of the system – clear majority of
population does not participate in the reimbursement.
The second aspect is the use of real treatment
outcomes to assess reimbursement decisions. Hungary
seems to be a clear leader in the field, as there are
drugs reimbursed based on positive treatment
outcomes, they use data to run efficacy analysis and
conclusion of the analysis are used in the negotiations
of reimbursement. There are cases where NEAK
(Hungarian payer) analyzed data and claimed that the
drug was not as efficacious as in the clinical trials, so
they should have got higher discounts. Or it can also
work reversely – company may use the payer data, so
they can go to the payer and negotiate against higher
discounts as their drug works best according to the
data. Still the challenge is too few patient registries.
In Czechia and Romania there are some drugs
reimbursed only based on the positive outcomes of
therapy (e.g. Hepatitis C) and some individual analysis
use of real-world data for selected drugs. Poland seems
to present the least advanced status – though the
recently established Medical Research Agency took the
first attempts to run such reviews.
To use real world evidence, patient registries are
needed. The simple reimbursement data is not enough,
as we need to aggregate treatment outcomes. That
sets another challenge for Health Funds as it calls for
technological platforms to process data, systems to
secure privacy issues and statistical algorithms to
define patterns. It requires contribution from multiple
stakeholders – doctors, payer, manufacturers and
technology providers. Still this could be the trigger
not to perceive data collection as an administrative
burden of the hospitals, but as the starting point of
real health care data science. That could also reposition
the perception of the jobs assigned with those tasks in
health care organizations.
Exhibit 6. Data utilization in reimbursement – country
advancement ranking*, Top 4 CEE countries
Expense analysis Rate
Expense data collection Rate
RWE
analysis
Rate
0,0
0,2
0,4
0,6
0,8
1,0
0,0 0,2 0,4 0,6 0,8 1,0
CZE
POL
ROM
HUN
* Relative assessment: 0-weak, 1-strong
Source: IQVIA analysis

10. 10 | Response to limited reimbursement funding. A CEE perspective.
CONCLUSIONS
In general, the cross-country review review shows
that there is a space for more active approach by both
payers and pharmaceutical companies to drive a better
use of reimbursement budgets. Application of even
simple analytical tools or sharing data access might
lead to better decisions. We are lagging with more
advanced data science solutions, but they are within
the reach of our governments – and together with new
technologies, they might change our thinking about
reimbursement in general.
Some specific suggestions for Ministries and
pharmaceutical companies are listed on Exhibit 7.
Exhibit 7. Suggested action for Ministries of Health and pharmaceutical companies
BUDGET
CONTROL
By public bodies
Improve regulatory
context for clinical
trials
Improve transparency
of reimbursement
prioritization policies
Enhance spending
data collection and
prepare regular reports,
incl. per TA and patient
Build patient registries
to analyze efficiency of
spending using real
world outcomes
Tighten budget control
Consider outcome
based agreements
By pharmaceutical player
ATTITUDE
TOWARDS
CLINICAL TRIALS
SHAPING
PRIORITIES
DATA
UTILIZATION
1
2
3
4
5
6
Stimulate jointly
funding increase but
individually spending
priorities
Run and promote
comparative studies
to enhance public
discussion about
priorities
Calculate advantages
of clinical trial
Promote own
investment in local
clinical trial
Push for data access
1
2
3
4
5
Source: IQVIA analysis

11. APPENDIX
iqvia.com | 11
DATA UTILIZATION – RATING DETAILS
Exhibit 8. Backup to Exhibit 6
WEIGHT POL ROM HUN CZE
TOTAL RATING 32% 30% 70% 46%
EXPENSE DATA COLLECTION RATE – TRACKING OF REIMBURSEMENT EXPENSES 30% 60% 40% 80% 60%
Rx Data collected of high quality (e.g. sales, all elements from prescription) and
available for decision makers
20% yes yes yes yes
Rx Data shared publicly on aggregated level 20% yes no yes yes
Rx Data shared publicly on detailed level – incl. hospital/ regions 20% no no yes no
Patient level data collected for reimbursed Rx 20% yes yes yes yes
Patient level data collected for non-reimbursed Rx 10% no no no no
Hospital consumption tracked (apart from national drug programs) on pack level and
on patient level
10% no no no no
EXPENSE ANALYSIS RATE – USE OF COLLECTED DATA FOR ANALYSES 35% 35% 25% 75% 35%
Some ad hoc analysis 20% yes yes yes yes
Regular reports analysing expenses dynamic (e.g. descriptive analytics) 10% yes no yes no
Regular reports covering more advanced analytics (e.g. diagnostic and prescriptive
analytics)
25% no no no no
Regular report on patient level 10% no no yes no
Internal basic use of patient level data for analysis (e.g. only to control excess
spending/prescribing)
5% yes yes yes yes
Internal advanced use of patient level data for analysis 5% no no yes no
Option of external access detailed patient level data for own analysis 15% no no yes no
Use of data in decision making/ public discussions 10% no no yes yes
RWE ANALYSIS RATE – USE OF RWE (APART FROM THE FIRST LINE, THIS IS
NOT ABOUT HTA) IN REIMBURSEMENT DECISIONS
35% 5% 25% 55% 45%
HTA used for reimbursement decisions 5% yes yes yes yes
<5 drugs refunded based on positive outcomes 5% no yes yes yes
>5 drugs refunded based on positive outcomes 10% no no no no
Examples of RWE efficacy analysis of a drug to review contunuation of the
reimbursement
10% no no yes no
Use of local RWE in reimbursement decision process about some drugs (individual cases) 15% no yes yes yes
Patient registries (with RWE) available for some therapies 20% no no yes yes
Patient registries (with RWE) available for most therapies 20% no no no no
Regular use of RWE to analyze most drugs, and compare between ATC 15% no no no no
Source: IQVIA analysis, assessment simplification was applied for the clarity of review

12. REFERENCES
1. From the North to the South: Estonia, Latvia, Lithuania, Poland, Czechia, Slovakia, Hungary, Romania,
Slovenia, Croatia, Serbia, Bosnia, Bulgaria, Albania, Macedonia
2. All data are calculations and estimations by IQVIA as in some cases no detailed public data available
3. For the purpose of this paper we treat those names as equivalent
4. OECD Health at Glance, 2017
5. Polish Statistical Office
12 | Response to limited reimbursement funding. A CEE perspective.

13. ABOUT THE AUTHOR
iqvia.com | 13
Mirosław is General Manager at IQVIA, responsible
for 9 countries: Romania, Bulgaria, Croatia,
Serbia, Slovenia, Bosnia, Albania, Macedonia and
Montenegro. He has over 15 years of experience in
strategic and operational advisory, with CEE focus.
He has been supporting leading innovative, generic
and OTC players in setting their development
and efficiency improvement plans. He has been
developing thought leadership papers incl. CEE
pharmaceutical markets comparison.
Earlier he worked at Roland Berger Strategy
Consultants.
He graduated from the Warsaw School of Economics
and in 2009 he received a PhD in economics in the
aspect of management.
He can be reached at miroslaw.pawelko@iqvia.com
MIROSŁAW PAWEŁKO, PHD
General Manager
South East European Cluster
IQVIA
Thank you to the following people for their contribution to this report:
• Timea Fejes | Hungary
• Alice Havlovicová | Czechia
• Piotr Jakubczak | Poland
• Michał Lubas | Poland
• Zsófia Ludányi | Hungary
• Marta Koncka | Poland
• Cristian Radulescu | Romania
• Martin Slegl | Czechia
ACKNOWLEDGEMENTS

14. ABOUT IQVIA
14 | Response to limited reimbursement funding. A CEE perspective.
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