Barriers and Enablers Affecting the Uptake of Biosimilar Medicines Viewed Through the Lens of Actor Network Theory: A Systematic Review

Abstract

Biosimilars represent an opportunity to realise savings against the costs of innovative medicines. Despite efforts made by stakeholders, there are numerous barriers to the uptake of biosimilars. To realise the promise of biosimilars reducing costs, barriers must be identified, understood, and overcome, and enablers magnified. The aim of this systematic review is to summarise the enablers and barriers affecting uptake of biosimilars through the application of a classification system to organise them into healthcare professional (HCP), patient, or systemic categories.
A systematic literature search was performed in PubMed, Scopus, CINAHL, eConlit, and Embase. Included were primary research studies published in English between Jan 2017 through June 2023 focused on enablers and barriers affecting uptake of biosimilars. Excluded studies comprised comparisons of biosimilar efficacy and safety versus the reference biologic. One reviewer extracted data that included classification of barriers or enablers, the sub-classification, and the identification of the degree of agency associated with the actor through their role and associations as a mediator within their network, through the application of Actor Network Theory. The data were validated by a second reviewer (PV).
Of the 94 studies included, 59 were cross-sectional, 20 were qualitative research, 12 were cohort studies, and three were economic evaluations. Within the review, 51 of the studies included HCP populations and 35 included patients. Policies and guidelines were the most cited group of enablers, overall. Systemic enablers were addressed in 29 studies. For patients, the most frequently cited enabler was positive framing of a biosimilar, while for HCPs, cost benefit was the most frequently noted enabler. The most frequently discussed systemic barrier to biosimilar acceptance was lack of effective policies or guidelines, followed by lack of financial incentives, while the most significant barriers for HCPs and patients, respectively, were their lack of general knowledge about biosimilars and concerns about safety and efficacy. Systemic actors and HCPs most frequently acted with broad degree of agency as mediators, while patient most frequently acted with a narrow degree of agency as mediators within their networks.
Barriers and enablers affecting uptake of biosimilars are interconnected within networks, and can be divided into systemic, HCP, and patient categories. Understanding the agency of actors within networks may allow for more comprehensive and effective approaches. Systemic enablers in the form of policies appear to be the most effective overall levers in affecting uptake of biosimilars, with policy makers advised to give careful consideration to appropriately educating HCPs and positively framing biosimilars for patients.

Full text

Vol.:(0123456789)
BioDrugs
https://doi.org/10.1007/s40259-024-00659-0
SYSTEMATIC REVIEW
Barriers andEnablers Affecting theUptake ofBiosimilar Medicines
Viewed Through theLens ofActor Network Theory: ASystematic
Review
ChadRieger1 · JudithA.Dean2· LisaHall2· PaolaVasquez3· GregoryMerlo2
Accepted: 26 March 2024
© The Author(s) 2024
Abstract
Background and Objective Biosimilars represent an opportunity to realise savings against the costs of innovative medicines.
Despite efforts made by stakeholders, there are numerous barriers to the uptake of biosimilars. To realise the promise of
biosimilars reducing costs, barriers must be identified, understood, and overcome, and enablers magnified. The aim of this
systematic reviewis to summarise the enablers and barriers affecting uptake of biosimilars through the application of a clas-
sification system to organise them into healthcare professional (HCP), patient, or systemic categories.
Methods A systematic literature search was performed in PubMed, Scopus, CINAHL, eConlit, and Embase. Included were
primary research studies published in English between Jan 2017 through June 2023 focused on enablers and barriers affecting
uptake of biosimilars. Excluded studies comprised comparisons of biosimilar efficacy and safety versus the reference biologic.
One reviewer extracted data that included classification of barriers or enablers, the sub-classification, and the identification
of the degree of agency associated with the actor through their role and associations as a mediator within their network,
through the application of Actor Network Theory. The data were validated by a second reviewer(PV).
Results Of the 94 studies included, 59 were cross-sectional, 20 were qualitative research, 12 were cohort studies, and three
were economic evaluations. Within the review, 51 of the studies included HCP populations and 35 included patients. Policies
and guidelines were the most cited group of enablers, overall. Systemic enablers were addressed in 29 studies. For patients,
the most frequently cited enabler was positive framing of a biosimilar, while for HCPs, cost benefit was the most frequently
noted enabler. The most frequently discussed systemic barrier to biosimilar acceptance was lack of effective policies or
guidelines, followed by lack of financial incentives, while the most significant barriers for HCPs and patients, respectively,
were their lack of general knowledge about biosimilars and concerns about safety and efficacy. Systemic actors and HCPs
most frequently acted with broad degree of agency as mediators, while patient most frequently acted with a narrow degree
of agency as mediators within their networks.
Conclusions Barriers and enablers affecting uptake of biosimilars are interconnected within networks, and can be divided
into systemic, HCP, and patient categories. Understanding the agency of actors within networks may allow for more com-
prehensive and effective approaches. Systemic enablers in the form of policies appear to be the most effective overall levers
in affecting uptake of biosimilars, with policy makers advised to give careful consideration to appropriately educating HCPs
and positively framing biosimilars for patients.
1 Introduction
Until recently, small molecule generic medicines served
the role of driving down costs in medicines budgets and
relieving substantial cost pressure within healthcare sys-
tems [1], but now biologic medicines occupy most of the
top spending positions in medicines budgets [2]. This has
resulted in a necessary shift of focus by third party payers
and governments towards anticipated cost savings repre-
sented by biosimilar medicines. Biosimilar medicines are
lower cost versions of their very expensive and widely used
biologic reference medicine precursors that become avail-
able in markets once patent periods run out for these refer-
ence biologic medicines [3]. Biosimilars are accepted to be
clinically equivalent to their reference biologic medicines in
terms of efficacy, safety, and immunogenicity [4]. Biosimi-
lars represent a key area of opportunity to realise savings
against the significant costs of innovative biologic medicines
Extended author information available on the last page of the article

C.Rieger et al.
Key Points
Factors affecting uptake of biosimilar medicines can be
classified as either enablers or barriers.
Barriers and enablers can be further divided into sys-
temic, healthcare provider (HCP), and patient categories.
Only four of the studies positioned the HCP as a media-
tor with narrow degree of agency within their role or
assemblage, or effectively a limited-decision maker within
the network, while in all others the HCP functioned as a
mediator with broad degree of agency in their assemblage.
In contrast, the patient or carer is most often positioned
as a mediator with a narrow degree of agency within their
network(s).
The factors or actors (both human and non-human)
affecting uptake of biosimilars each have agency and are
interconnected within their networks. Careful considera-
tion should be given to the interconnected nature of these
factors when applying changes to individual actors.
[5], allowing for expanded access to currently available med-
icines, and funding innovative medicines.
1.1 Pharmaceutical Market Outlook
andtheImportance ofBiosimilars
Biosimilars occupy 1% of the total biologic market in the
world [6]. Uptake or adoption of biosimilars has been most
successful in Europe, with 80% of biosimilar uptake being
attributed to Europe [6], however, despite efforts by gov-
ernment and industry, uptake of biosimilars in Australia is
lagging behind many other jurisdictions in the world [7], and
therein lays the concern; with more expensive life-saving
biologic medicines in development and entering the market,
payers may be faced with absorbing the increasing costs of
medicines, and particularly the costs of biologic medicines,
unless they are able to realise savings through increased
uptake of biosimilar medications.
Over the next 5–10 years, it is expected that the bio-
similar market will peak in Europe, with an expected €8
billion value [8]. Over this period, it is expected that the
most biologic losses of exclusivity (LOEs) will be in the
oncology space (29%), followed by blood and lymphatic
conditions (21%) [8]. It has been observed that drug devel-
opment is now focused in the biologic and targeted medi-
cines space. With this shift, drug budgets are escalating at
rates not seen in the past, in many cases to unsustainable
levels [9]. The future sustainability of medicines budgets
and overall healthcare budgets may become more dependent
upon the successful uptake of biosimilar medicines and the
consequential cost savings [10]. Medicine markets around
the world may need to consider making moves to drive up
acceptance and adoption of biosimilar medicines, such that
the biosimilar development pipeline remains viable, and to
realise the cost savings offered by biosimilar medicines [10].
This will allow markets and payers to budget for and realise
the advantages of newly developed medicines through rein-
vestment of these savings. Despite many of the efforts made
by manufacturers, governments, payers, and representative
organisations, uptake of biosimilars face numerous barriers
[11]. To realise the opportunity of biosimilars reducing costs
for healthcare systems and payers, barriers must be identi-
fied, understood, and overcome and enablers magnified.
Literature exists detailing the enablers and barriers affect-
ing biosimilar uptake, mostly focused on specific factors
such as healthcare professional (HCP) knowledge of and
confidence in biosimilars, patient knowledge and confidence
in biosimilars, and policies that limit uptake [12]. While this
may be useful on a micro level or in overcoming specific
jurisdictional concerns, there is a gap in the literature pro-
viding comprehensive views or applying useful models for
understanding the enablers and barriers affecting the uptake
of biosimilar medicines.
Additionally, there is inconsistency in how we classify
these barriers and enablers [11, 12]. Importantly, there is a
need to discuss how these barriers might be overcome, and/
or enablers be magnified through identifying the interac-
tions between actors within healthcare networks. Finally,
there is a lack of discussion around the interconnectedness
of actors within healthcare networks, affecting the uptake of
biosimilar medicines.
The aim of this systematic review is to explore and sum-
marise the enablers and barriers affecting uptake or use
of biosimilar medicines through the application of a basic
classification system, organising barriers and enablers into
HCP, patient, or systemic categories, allowing for a clearer
understanding, and how to potentially capitalise on or over-
come them, respectively. Further to this, the actors affect-
ing uptake of biosimilar medicines within their respective
healthcare networks will be examined through the lens of
the Actor Network Theory (ANT), allowing for a deeper
understanding of the interdependencies between actors, and
their roles and effects on each other.
Foundational to ANT is the concept of generalised sym-
metry, or the understanding that all actors, both human and
non-human, within a network are afforded agency [13].
This principle contributes to the success of ANT through its
extensibility and versatility [13]. Importantly, ANT removes
any level of allocated power, rather allocating agency to each
of the actors with nothing in between; “no aether in which
networks should be immersed” [14]. The aim of ANT is

Barriers and Enablers Affecting the Uptake of Biosimilar Medicines
not to “add social networks to social theory, but to rebuild
social theory out of networks” [15]. This clear allocation
of agency and removal of any additional social dynamic
allows for a clearer view of the role of actors and how they
interact with one another in a network to determine an out-
come. This interconnected dynamic web of actors may act
or be influenced by several other factors or actors within
the network, functioning as mediators, transforming, trans-
lating, distorting, and modifying meaning, whose potential
outcomes are effectively infinite or they may simply act as
channels through which information in the network is passed
in a binary way, functioning as intermediaries [15].
While not a foundational aspect of ANT, for our pur-
poses, agency can be conceived as existing on a continuum,
projecting from multiple sites within networks [16]. Our
discussion will seek to expand on this theory and the shifts
in agency resultant of the connections between or displace-
ments created by actors.
2 Methods
The management and reporting of this review is in accord-
ance with the Preferred Reporting Items for Systematic
Reviews and Meta-analyses (PRIMSA) [17].
2.1 Types ofStudies
We included primary research studies, inclusive of all
methodologies (qualitative, quantitative, and mixed meth-
ods) focused on enablers and barriers affecting the uptake
of biosimilar medicines after regulatory approval and payer
listing. Only studies written in English were included in this
review. We excluded studies that focused on comparisons of
biosimilar efficacy and safety versus the reference biologic,
pharmacovigilance, biosimilar overviews, review articles,
book chapters, books, book series, opinion articles, letters
to the editor, and conference proceedings (Table1).
2.2 Sources ofData
A determined, comprehensive search strategy was applied to
PubMed, Scopus, CINAHL, eConlit, and Embase from 2017
through June 2023. This period was selected based on the
relative scarcity of primary research articles available in this
space prior to 2017 in addition to the rapid advancements
occurring in this space over the past 7 years.
2.3 Search Strategy
The specific search terms applied are provided in the elec-
tronic supplementary material (ESM) [18].
2.4 Review Methods
Three review authors (CR; GM; PV) independently screened
all the titles and abstracts retrieved from the initial search
and excluded irrelevant studies. We retrieved full-text arti-
cles for all eligible studies, and the two reviewers (CR; PV)
independently selected studies for inclusion based on the
inclusion criteria. The primary reviewer (CR) extracted
data from the included studies utilising the standardised
data extraction table (Excel) and the second reviewer (PV)
validated the extracted data. The two reviewers (CR; PV)
resolved any disagreements by consulting with the third
reviewer (LH).
2.4.1 Analysis Framework andTheory
The following classification framework was applied through-
out this systematic review: barriers and enablers classified
as systemic, HCP, or patient. This model has been modified
based on the proposed grouping of barriers developed by
Cross etal. [12]. Further to this, both enablers and barriers
were sub-classified to uncover trends.
Enablers or barriers were classified as systemic where
said enablers or barriers were developed and/or imple-
mented by a system administrator, such as, but not limited
Table 1 Systematic review inclusion and exclusion criteria (Jan 2017–June 2023)
Inclusion criteria Exclusion criteria
Original primary studies Other than original primary studies, such as
reviews, book chapters, books, book series,
conference proceedings, commentaries and
letters to editors, consensus papers
English language Other than English language
Date range: Jan 2017–June 2023 Outside of date range 2017–June 2023
Studies focused on enablers and barriers affecting the uptake of biosimilar medicines after regu-
latory approval and payer listing
Studies that focused on comparisons of bio-
similar efficacy and safety vs the reference
biologic, pharmacovigilance, biosimilar
overviews

C.Rieger et al.
to, a hospital administrator or insurance provider. The out-
comes in studies involving systemic actors often focused on
enablers and barriers based on the workings of healthcare
systems in areas of policy, governance, guidelines, coordina-
tion, and capacity. Within these systemic enablers and barri-
ers categories, sub-categories were created. These categories
were discussed and agreed upon by all reviewers. The fol-
lowing sub-categories within systematic enablers and bar-
riers were agreed upon: (1) leadership and governance, (2)
policies and guidelines, (3) product demand or availability,
(4) service distribution and delivery, (5) costs of products,
(6) financial capacity, (7) human resources capacity, (8)
infrastructure and equipment capacity, (9) communication
and education capacity, (10) health system levels coordi-
nation and integration, (11) intersectoral coordination and
integration, and (12) others.
Studies involving HCP barriers and/or enablers had
study populations consisting of or including HCPs, such
as specialist clinicians, general practitioners, pharmacists,
or nurses. The outcomes of these studies were focused on
actions or reactions of HCPs. Studies involving patient bar-
riers and/or enablers had study populations consisting exclu-
sively of or including patients using or potentially eligible to
use biologic or biosimilar medicines. Sub-categories of HCP
and patient enablers and barriers were identified themati-
cally through the extraction process. These sub-categories
will be explored in further detail within the results section
of this review.
The actors (human and non-human) involved in each
of the included studies were analysed through the lens of
Actor Network Theory (ANT). ANT, the foundational the-
ory applied to this review, is a theoretical and methodologi-
cal approach to social theory where everything in the social
and natural worlds exists in constantly shifting networks
of relationships [19]. Within this systematic review, each
of the actors are viewed through their agency within their
healthcare networks, whether they act as mediators with
broad (effect on agency is broadened), narrow (agency is
narrowed), or mixed (mixed or varying effect on agency)
degrees of agency, resultant of their associations with other
actors within their networks. This designation is an impor-
tant representation of the role played by each individual
actor. ANT affords ‘agency’, or the ability to do things, with
an emphasis on either specific sites of action or aspects of
social interaction (but not to be confused with human inten-
tionality) [20]. Importantly, agency is attributed heterogene-
ously [21] to each of the actors that exist within a network,
including both the human and non-human actors [19]. As
an example, the clinician and the policy are both afforded
agency in a network determining if a patient will use a bio-
similar medicine.
Understanding the interconnectedness of the barriers and
enablers affecting the uptake of biosimilar medicines is an
important concept which can be further developed when
viewed through the lens of ANT, which positions actors dis-
tributed heterogeneously across their networks [19]. Media-
tors possess the ability within their network(s) to determine
a multitude of outcomes and possess agency [20], which for
our purposes exists on a spectrum within the network and
may be considered as broad, narrow, or mixed, while inter-
mediaries effectively act as gates through which decisions
or outcomes pass without being affected [20].
2.5 Data Extraction
Data was extracted according to the aforementioned classi-
fication framework on barriers and enablers affecting uptake
of biosimilar medicines, their sub-classifications, and posi-
tioning of said barriers and enablers and/or the position-
ing of the actors within ANT. The following key data were
extracted: (a) classification of barriers or enablers (systemic,
HCP, or patient), (b) the sub-classification of the barriers or
enablers described within each study, (c) the identification of
the actor enabler or barrier as a mediator with broad, narrow,
or mixed degree of agency within the context of the ANT, as
a result of their associations or connections with the other
actors within their assemblages or the entire network.
The following data were extracted using a purpose-built
Excel spreadsheet: title, year, and country of publication,
authors, Covidence unique identification code (code desig-
nated to each study by Covidence for data extraction pur-
poses), objectives of the study, methods used in the study,
inclusion and exclusion criteria applied, study instrument
used, and the type of study (see ESM [18]).
2.6 Quality Appraisal
The primary reviewer (CR) assessed the methodologi-
cal quality of each included study to determine the qual-
ity through the prospect of bias in its design, conduct, and
analysis. The second reviewer (PV) validated the quality
assessment completed by CR. The third reviewer (LH)
resolved any disagreements through discussion with the
two reviewers.
The Joanna Briggs Institute (JBI) Critical Appraisal
Tools were utilised as the quality assessment tools for each
of the included study types within this systematic review.
JBI provides a set of critical appraisal tools for evaluating
quantitative and qualitative study types. For this system-
atic review, the following JBI critical appraisal tools were
applied: (1) analytical cross-sectional studies, (2) cohort
studies, (3) economic evaluations, and (4) qualitative
research study (see ESM [18]).
Each of the JBI tools provide specific criteria for eval-
uating selected study types. These criteria are included
as Appendices to this systematic review (see ESM). The

Barriers and Enablers Affecting the Uptake of Biosimilar Medicines
criteria that exist within each of the appraisal tools require
Yes or No responses. The JBI Analytical Cross-Sectional
Studies appraisal tool includes eight individual items for
evaluation, the JBI Cohort Studies appraisal tool includes
11 individual items, the JBI Economic Evaluation appraisal
tool has 11 items, and the JBI Qualitative Research
appraisal tool includes ten items. The responses were tal-
lied, leading to a raw score for each study. The totals for
each study type have then been rolled up and averaged,
with an average also being provided for all included stud-
ies within the systematic review, as a percentage. In scor-
ing the included studies, one point was assigned for Yes,
with zero points being assigned for No responses. The fol-
lowing classification system was employed for Analytical
Cross-Sectional Studies: a score of ≥ 6/8 indicates ‘High’,
3/6–5/6 ‘Medium’, and < 3/6 indicates ‘Poor’ quality. The
following classification system was employed for both
Cohort Studies and Economic Evaluations: ≥ 8/11 ‘High’,
5/11–7/11 ‘Medium’, and < 5/11 as ‘Poor’ quality. The
following classification system was applied to Qualitative
Research studies included in this systematic review: ≥ 7/10
‘High’, 4/10–6/10 ‘Medium’, and < 4/10 ‘Poor’. No studies
were excluded based on quality.
3 Results
3.1 Identification ofStudies
The search of the five databases resulted in identifica-
tion of 11,541 studies, of which 1867 were duplicates.
This resulted in 9674 studies remaining. A further 9399
studies were removed based on the author’s judgement
of relevance of the title and abstract, and with 31 of the
275 remaining studies not available for retrieval, 244 arti-
cles were retrieved for full review. During the full review,
150 studies were excluded for the following reasons: (a)
duplicates: 2 studies, (b) wrong study outcomes: 15 stud-
ies, (c) wrong study design: 95 studies, (d) non-primary
research: 17 studies, (e) insufficient detail: 3 studies, (f)
not available in English: 1 study, (g) outdated study: 17
studies (publication prior to 2016). This resulted in 94
studies being included in the final review. A PRISMA
flowchart [22] is displayed in Fig.1 outlining the inclu-
sion and exclusion process for studies reviewed as part of
this systematic review.
3.2 Characteristics ofIncluded Studies
The characteristics of the 94 studies included in this sys-
tematic review are displayed in Supplementary Table1 (see
ESM). The included studies ranged in year of publication
from 2017 to June 2023. There were 12 studies included
from 2017 to 2018, while there were 58 studies included
from 2019 to 2021. Of the 94 studies included, 59 were
cross-sectional studies, 20 were qualitative research studies,
12 were cohort studies, and three were economic evalua-
tions. There was an even split of six retrospective studies and
six prospective studies within this category, with seven of
these studies involving patients, two considering the actions
or decisions of health professionals, while three examined
decisions or actions by decision makers or others (payers,
insurance providers) (Supplementary Table1). These were
either mixed methods or quantitative studies, with each of
them looking at either experts, decision makers, or patient
characteristics (Supplementary Table1, see ESM).
Of the 59 cross-sectional studies, 55 used surveys as their
primary research instrument, while three of these studies
employed interviews, and two used statistical analysis of
data. Of the 20 qualitative research studies, 16 of these stud-
ies using interviews as their primary study instrument. The
remaining four used focus groups. Of the 12 cohort studies,
six were prospective in nature, while the other six were ret-
rospective. The economic evaluations were each designed to
measure specific economic outcomes focused on biosimilar
uptake and/or generated savings.
Of the 94 studies included, 42 were published in Europe,
with 32 in North America, ten in Asia, four in Australia/
New Zealand, and two for each of South America, Africa,
and the Middle East. The country delivering the most pub-
lications was the United States of America (USA), with 31
of the included studies. The second largest contributor of
studies was Belgium with ten (see Supplementary Table2
in the ESM).
Within the systematic review, as detailed in Supplemen-
tary Table1, 13 of the included studies were qualitative
research, with 11 of these studies using interviews as their
primary study instrument. The remaining two used focus
groups. Most of the qualitative research involved multiple
stakeholders (patients, health professionals, carers, experts,
decision makers, or others), with seven of these studies
involving experts or decision makers, while eight involved
health professionals, six involved patients, two involved oth-
ers (payers etc), and one involved carers.
3.3 Quality Appraisal
Applying the JBI framework, 89 of the 94 studies were rated
as high according to the accepted scoring criteria. All 59
cross-sectional studies were rated as high with a scoring
range of 6/8 to 8/8, while 18 of 19 qualitative research stud-
ies were rated as high, with one study rating as medium. The
scoring range for qualitative research studies was 5/10 to
10/10, while nine of the 12 cohort studies rated as high, with
the remaining three rating as medium. The scoring range for

C.Rieger et al.
References from other sources (n =0)
0)
Grey literature (n =0)
Studies screened (n = 9674)
Studies sought for retrieval (n = 275)
Studies assessed for eligibility (n = 244)
References removed (n = 1867)
29)
1838)
0)
Other reasons (n =0)
Studies excluded (n = 9399)
Studies not retrieved (n =31)
Studies excluded (n = 150)
Duplicate(n = 2)
Outdated study(n = 17)
Wrong outcomes (n = 15)
Wrong study design (n = 95)
Non-Primary Research (n=17)
(n = 3)
Not available in English(n = 1)
Included
Studies included in review (n =94)
Included studies ongoing (n = 0)
(n =0)
Screening
Studies from databases/registers (n = 11541)
Embase (n = 5405)
PubMed (n = 5352)
Scopus (n = 784)
Fig. 1 Flow diagram of the study selection process

Barriers and Enablers Affecting the Uptake of Biosimilar Medicines
cohort studies was 5/11 to 11/11. All three of the included
economic evaluations rated as high, with a scoring range of
8/11 to 11/11.
Most studies set out clear criteria for inclusion and expo-
sure was measured in a valid way. However, where con-
founding factors were identified, there were often poor, or no
strategies stated to deal with these (57 of 60 cross-sectional
studies). Additionally, four of the 12 cohort studies did not
clearly identify strategies for dealing with confounding fac-
tors (Supplementary Table1, see ESM).
Notably, 13 of the 19 qualitative research studies did not
clearly identify the researcher culturally or theoretically
within the context of the research. Additionally, two of the
three economic evaluations included did not adjust costs and
outcomes for differential timing (Supplementary Table1,
see ESM).
3.4 Summary ofFindings
The findings of the 94 studies included in this systematic
review are included in Supplementary Table1 (see ESM).
This table includes details of the seven aspects considered
in this review, including (1) year of publication, (2) country
of publication, (3) approach (qualitative, quantitative, mixed
methods), (4) primary study instrument, (5) target popula-
tion, (6) type of study, and (7) raw quality assessment score.
3.4.1 Target Populations ofIncluded Studies
This systematic review found that most (46) studies (48.9%)
included were focused on HCP-centric barriers or enablers,
with systemic and patient-centric barriers and enablers hold-
ing a relatively equal share of the remainder at 28 studies
(29.7%) and 33 studies (35.1%), respectively (Supplemen-
tary Table1, see ESM). Within this systematic review, 51
of the studies included HCPs as targets of their studies, and
the second most frequent study population being patients
at 35 studies including patient populations (Supplementary
Table1, see ESM).
Of the 51 studies specifically examining HCP popula-
tions, 38 were cross-sectional studies and 11 were qualita-
tive research. Of the 51 studies that examined HCPs as a
target population, the literature points to specialist clinicians
being the primary focus of research on enablers and barri-
ers affecting biosimilars on health professionals, with 47
of these 51 studies focused on specialists, while 13 studies
included pharmacists, and six included nurses (Supplemen-
tary Table1, see ESM).
As outlined in Supplementary Table1, the second most
frequently studied population was patients and/or their
carers, with 35 of the 94 studies including patients and/or
carers within their study populations. The primary instru-
ments applied to studying these patient or carer populations
were surveys, with 17 of the 35 studies utilising surveys
and another 12 studies applying interviews (Supplementary
Table1, see ESM). The primary aims of studies of patients
were to examine their perceptions/attitudes and/or knowl-
edge and/or understanding of biosimilar medicines, with 13
of the included studies examining these areas, and another
ten studies examining patient perspectives about non-med-
ical or mandated switches to biosimilar medications (see
ESM [18]).
Importantly, the least frequently examined general popu-
lation was decision makers, with 15 of the studies including
decision makers within their target populations (Supplemen-
tary Table1, see ESM). Decision makers can be broadly
classified in this context as administrators and officials
within healthcare institutions, government officials, or pol-
icy makers. The most applied instrument studying decision
makers was interviews, with eight of the 15 studies utilis-
ing this method. Other instruments included surveys, cohort
studies, literature reviews, cross-sectional studies, and eco-
nomic analyses. Generally, the focus of these studies was to
understand what has transpired to affect biosimilar uptake,
and to understand what may be limiting, or what may drive
increased uptake of biosimilars.
3.4.2 Barrier andEnabler Classification Framework
In reviewing the literature, three categories of barriers
and enablers have emerged: barriers or enablers of patient
acceptance or uptake, barriers or enablers of HCP accept-
ance and usage, and systemic enablers or barriers, includ-
ing pricing, education, regulation, quotas, amongst others
[12]. This categorisation of enablers and barriers assists in
simplifying the view of the effect on uptake of biosimilars.
Importantly, in orienting us to these classifications, systemic
barriersand enablers can be viewed as foundational to both
HCP and patient barriers and enablers. We will further
explore the relationships between these classifications later
in this review. Both enablers and barriers will be examined
in detail, considering the most significant factors affecting
uptake of biosimilar medications in each of the patient, HCP,
and systemic categories. This examination will start with a
consideration of enablers.
Table2 provides a visual representation of the barrier and
enabler classifications, with the vertical columns displaying
the three classifications (systemic, HCP, and patient) and
each of barriers and enablers. The horizontal rows represent
the specific barriers or enablers detailed or discussed in the
included articles and the frequency of occurrence (number
of articles). Table3 provides a visual representation of the
roles played by the actors (HCPs, patients, systemic actors)
through the lens of ANT, specifically mediators, with broad,
narrow, or mixed degree of agency.

C.Rieger et al.
Table 2 Frequency of occurrence of roles played by actors (enablers or barriers to uptake of biosimilar medicines) within the included studies
Frequency of roles played by systemic, HCP, or patient actors within each study were classified as enablers or barriers to uptake of biosimilar
medicines. Roles of actors were further sub-classified into the specific types of actions within either enabler or barrier classes.
HCP healthcare provider
Type of enabler or barrier affecting uptake of biosimilar medi-
cines
Systemic
enablers
Sys-
temic
barriers
HCP enablers HCP barriers Patient enablers Patients
barriers
Number of studies 29 17 38 42 24 26
1. Leadership and governance 12 3
2. Policies and guidelines 25 11
3. Product demand or availability 3 1
4. Service distribution and delivery 1 0
5. Costs of products 13 6
6. Financial capacity 14 6
7. Human resources capacity 2 0
8. Infrastructure and equipment capacity 0 1
9. Communication and education capacity 13 3
10. Health system levels coordination and integration 7 3
11. Intersectoral coordination and integration 2 1
12. Others (institutional/hospital insurance system, real-world
data dissemination, insurance coverage, systemic results of
nocebo effect)
3 2
Biosimilar efficacy concerns 6 11 2 9
Biosimilar safety concerns 6 15 2 10
Cost concerns 12 2 1 2
Biosimilar or biologic medication education 5 7 3 1
Concerns about nocebo effect 0 1 1 1
Insurance restrictions 1 3 0 1
Positive framing—medical interview 1 0 6 0
Concern about pharmacy substitution 0 3 0 3
Limited knowledge of biosimilars 0 14 0 8
Increased knowledge 5 0 2 0
Non-medical switching 2 1
Table 3 Roles of actors (mediators) within studies (broad, narrow, or mixed degree of agency)
Frequency of effects on agency of systemic, HCP, or patient actors when biosimilar uptake enablers or barriers have been applied within a study
(broad, narrow, or mixed degree of agency)
HCP healthcare provider
Role of the target
actor in the article
(as enabler or bar-
rier to biosimilar
use)
Role of systemic
actor where
systemic enablers
applied
Role of systemic
actor when
systemic barriers
applied
Role of HCP actor
when HCP ena-
blers applied
Role of HCP actor
when HCP barri-
ers applied
Role of patient
actors when
patient enablers
applied
Role of patient
actor when patient
barriers applied
Mediator (broad
degree of
agency)
29 15 26 27 8 7
Mediator (mixed
effect on agency
of actor)
0 0 9 11 6 7
Mediator (nar-
row degree of
agency)
0 2 3 4 10 12

Barriers and Enablers Affecting the Uptake of Biosimilar Medicines
3.4.3 Enablers Facilitating Uptake ofBiosimilar Medicines
Within this review, 29 of the 94 articles addressed or
included systemic enablers. Of these 29 articles addressing
systemic enablers, the most frequently cited type of enabler
was policies and guidelines (25 articles). Further to this,
policies and guidelines are the most cited group of enablers.
However, as indicated earlier in this review, only 15 of the
articles focused specifically on decision makers as a tar-
get population, instead looking at these systemic enablers
through the lens of either the health care provider and/or the
patient. In reviewing specific types of policies addressed,
eight of the studies specifically considered mandatory or
non-medical switching, while six of the studies considered
incentives or gainshare arrangements (Table2).
Financial capacity and cost savings were the other sig-
nificant enablers in both the systemic and HCP categories,
but interestingly, not the patient category. Financial capacity
and cost savings were considered as systemic enablers in 14
studies, and HCP enablers in 12 studies (Table2). Moorkens
etal. [23] indicated that qualitative results of their study
demonstrate that the price difference between biosimilar
and originator products is an important factor in making it
worthwhile to switch the patient. Further to this, Moorkens
etal. [24] indicated in their 2019 study that relative dif-
ference in discounted price between the biosimilar and the
originator product is a key driver of biosimilar medicines.
The savings generated by utilising the lower cost biosimilar
can be distributed through gain share agreements with key
stakeholders.
In the patient category, the most frequently discussed ena-
bler is utilisation of amedical interview, or positive framing
of the switchto or start of a biosimilar medication, men-
tioned or discussed in six of the 24 studies involving patient
populations (Table2). Pouillon etal. [25] stated that the
patient–health care provider relationship is a key driver of
acceptance of biosimilars and limits risk of negative bias,
going on to say that education about biosimilars should be
tailored to the individual patient, taking into account nocebo
effect risk profile. Further to this effect, Gasteiger etal. [26]
indicated that positive framing by a clinician increased will-
ingness to switch from 46 to 67%, while positive framing
also increased perception of effectiveness of the biosimilar.
It has been observed through review of the literature
that there are strong linkages or dependencies between
the enablers. For instance, while a substitution policy may
drive uptake of biosimilars, patient outcomes are somewhat
dependent on patient–health care provider relationships [27].
Importantly, the confidence of the clinician or pharmacist in
sharing information with the patient is dependent on their
education and confidence in the efficacy and safety of the
biosimilar medicines [28].
3.4.4 Barriers Inhibiting Uptake ofBiosimilar Medicines
The perceived efficacy of biosimilar medicines is the most
frequently discussed barrier to biosimilar acceptance by both
HCPs and patients in the literature, with 22 articles discuss-
ing concerns about safety, efficacy, or limited knowledge of
biosimilars by HCPs, and ten articles discussing efficacy
or safety concerns by patients (Table2). Edgar etal. [29]
indicated in a 2021 study that one of the three hurdles to
biosimilar adoption was the lack of confidence in biosimilar
interchangeability and a need for education about biosimi-
lars. From the patient perspective, a study by Teeple etal.
[30] found that 85% of patients were concerned that biosimi-
lars wouldnot treat their disease as well.
Interestingly, a clear distinction has been observed in the
literature between starting new patients on biosimilars and
switching currently treated patients to a biosimilar. To high-
light this, four articles indicated a higher comfort level in
clinicians starting treatment-naïve patients on biosimilars,
relative to switching. In a 2022 study, Demirkan etal. [31]
found that nearly half (45%) of the paediatric rheumatolo-
gists surveyed preferred to prescribe biosimilars in the treat-
ment of biologic-naïve cases.
In examining the systemic barriers to biosimilar use or
acceptance, the most frequently discussed issue was lack of
effective policies or guidelines (11 studies), followed by lack
of financial or cost-saving incentives (six studies) (Table2).
Druedahl etal. [32], in a 2022 study of expert views, found
that almost all participants saw no need for additional sci-
entific data to support substitution, and urged greater policy
debate on biosimilar substitution, urging European and UK
policy makers and regulators to clarify their visions for bio-
similar substitution. To expand on this, there is a distinction
in the literature between demand- and supply-side policies.
A study by Kim etal. [33] found that demand-side policies
used in the UK and France have been more effective than the
supply-side price linking policy used alongside few demand-
side policies, where the volume of the originator brand of
infliximab actually increased. A study by Barcina Lacosta
etal. [34] lists the existence of policy frameworks that do
not necessarily support the initiation of switching protocols
as one of four key barriers to biosimilar uptake.
Several studies included in this review also mentioned
the issue of the originator being advantaged through rebates
or arrangements with insurance providers, limiting the use
of biosimilars (Table2). For instance, Herndon etal. [35]
found, in a 2021 study, that rebate increases of reference
biologics were rated as the highest (85%) barrier to health
system adoption of biosimilars. While there are several
types of barriers to the use of biosimilars, the literature has
clearly identified that the most significant barriers are HCP
and patient concerns about safety and efficacy, and their lack
of general knowledge about biosimilars. From a systemic

C.Rieger et al.
perspective, the most significant barriers are the lack of
effective policies and guidelines, such that there are con-
cerns about whether the promised cost savings of biosimilars
can be achieved (Table2).
3.4.5 Classification ofNetwork Actors Within theIncluded
Studies
Notably, only four of the studies (seven total scenarios) posi-
tioned the HCP as exclusively a mediator with a narrow
degree of agency, or effectively a limited-decision maker
within the network, while in all others the HCP functioned
as a mediator with broad degree of agency (Table3).
Interestingly, in each of these studies, the positioning of
the HCP as a mediator with narrow degree of agency was
the result of an insurance payer or institutional decision
requiring patients to use biosimilar medications, effectively
displacing the decision-making role from the clinician or
pharmacist assemblage with the patient and shifting the bal-
ance of agency across the spectrum to the policy actor. An
example of this was in Sullivan etal. [36], where patients
were required to switch to biosimilar medications but were
reluctant to accept biosimilar medications, highlighting the
importance of patient and physician communication.
In contrast to the positioning of the HCP as a media-
torwith broad degree of agency, the patient or carer actor
is most often positioned as a mediator with limited degree
of agency in their assemblages with such actors as HCPs,
insurance payers, and the medicines themselves within their
network(s). In 13 of the included studies (22 total scenarios),
the patient was positioned as an actor with narrow degree
of agency, whereas the patient is positioned exclusively as
a mediator with broad degree of agency in only eight of the
studies (15 total scenarios) (Table3).
4 Discussion
This systematic review summarises and explores the ena-
blers and barriers affecting uptake or use of biosimilar medi-
cines through the grouping of barriers and enablers into sys-
temic, HCP, and patient categories. It differs from a previous
systematic review of physicians’ perceptions of the uptake of
biosimilars [6] and the assessment of a need for pharmacist-
directed biosimilar education [37], by effectively scanning
and categorising enablers and barriers. This is an important
advancement in assessing how to improve uptake of bio-
similar medicines through the magnification of enablers and
overcoming of barriers. Additionally, this review considers
the interconnectedness and roles played by the actors within
networks affecting uptake of biosimilar medicines through
the lens of ANT. The present systematic review is the first
that we are aware of specifically considering all available
worldwide English publications and classifying them in
terms of types of enablers and barriers affecting uptake of
biosimilar medicines.
Consideration of the target populations of the studies
included in this systematic review is an important metric,
as it provides us with insights around the focus of research
in this space. This systematic review shows that the largest
proportion of studies position the HCP (clinician, nurse, or
pharmacist) as a mediator with broad degree of agency or
having the ability to affect the prescribing outcome (deter-
mining if a biosimilar medication will be used) (Table3).
Further to this, findings demonstrate that clinicians are the
most studied actors within networks affecting uptake of bio-
similar medicines. However, findings show that policies and
guidelines have the most significant effects inshifting the
uptake of biosimilar medicines worldwide, but relatively
few studies focus on key decision makers within healthcare
networks who have the ability to create and enact policy
changes.
Systemic actors, such as decision makers, guidelines, and
policies, by their very nature are most often positioned as
as mediators with broad degree of agency within their net-
works. When systemic actors, such as policies and guide-
lines, are positioned as mediators with broad degree of
agency, there is a consequential alteration of roles played
by other actors within the network(s), including HCPs and
patients. Where HCPs may have previously held broader
degrees of agency as mediators within the network, their
agency is often narrowed when a systemic actor, such as
a new policy enters the network. A clear example of this
change occurs when a non-medical switching policy is
adopted. Papautsky etal. [38] outlined experiences of cli-
nicians and breast cancer patients non-medically switched
to biosimilar trastuzumab when not initiated by the treat-
ing clinician, and found that there is a need for tailored and
effective patient communication, and oncologist informa-
tion and education on biosimilars, along with improved
healthcare communication regarding switching, as clini-
cians in this study were unaware of the switch being initi-
ated. Patients and clinicians in this study diverged on top-
ics such as patient opportunity to ask questions, patients
receiving adequate resources, and perception of the switch
being minor in nature. The discrepancy between patient- and
oncologist-reported experiences and perceptions highlights
a lack of adequate information exchange between clinicians
and patients. This demonstrates the importance of education
and HCP engagement when specific types of policies areput
in place with the intent of driving biosimilar use. While it
is evident that each actor plays a role within the network(s),
there is a critical interconnectedness which must be carefully
considered and accounted for when making changes to their
roles, such as in the case of non-medical switching.

Barriers and Enablers Affecting the Uptake of Biosimilar Medicines
Several of the studies referred to examples of non-medical
switching, where patients were required to switch to biosimi-
lar medicines by their payers (insurance payers). Chew etal.
[39] outlined the concerns of patients when faced with a
non-medical switch to a biosimilar, including cost concerns,
drug properties, adverse events, drug packaging, and loss
of disease control. A study by Petit etal. [27] indicated that
tailored communication with a nurse reduced occurrence of
the nocebo effect in non-medical switches. In this scenario,
the patient functions as a mediator with narrow agency, but
the patient still requires support to deliver the best possible
medical outcomes. This highlights the interconnectedness
or assemblages of actors and the importance of interactions
between these actors as their roles or agency shift.
Touching on another important consideration, a 2022
study by Rupert etal. [28] found that HCPparticipants
expressed reluctance to prescribe and dispense biosimilar
and interchangeable products without seeing detailed effi-
cacy and safety data; and physicians universally expressed
disapproval that pharmacists could substitute interchange-
able products for original products without prescriber con-
sent. This study positions the prescriber as a mediator with
broad degree of agency with the network, acting to evalu-
ate safety and efficacy data, and making all prescribing
and dispensing decisions. However, the interconnectedness
of actors must be carefully weighed, considering impacts
when their roles change.
Notably, within this review, patient populations were
examined much less frequently in the included studies
than HCPs (Supplementary Table1, see ESM). This is an
important observation, as patients are most often positioned
within biologic/biosimilar actor networks as end points,
whose understanding and acceptance of the medications is
important. However, it is interesting to note that patients
as actors most often played he role of mediator with less
agency, with less agency, while HCPs more often played the
role of mediator, taking on more agency as decision makers
within their networks (Table3). This dynamic could be an
important consideration in determining how information is
shared insituations such as non-medical switching.
The sharing of evidence-based information on the effi-
cacy and safety of biosimilars, leading to increased knowl-
edge of HCPs, was discussed as an enabler of biosimilar
usage in 14 studies, where HCPs were included in the study
populations. Peipert etal. [40], in a 2023 study of oncolo-
gists’ knowledge and perceptions of biosimilars, found that
information on safety and efficacy was an important factor
when considering the use of biosimilars. The confidence of
clinicians and their ability to clearly communicate this with
patients is evidently important in enabling patient accept-
ance. Building the confidence of the prescribing clinician
or pharmacist is an important first step leading to successful
patient interventions. This type of intervention could also
lead to increased agency held patients, contributing to bet-
ter outcomes. We can draw a reasonable deduction that the
patients in these studies were less responsible for making
their own decisions within their healthcare networks than
HCPs in determining the use of biosimilar medicines.
These observations are important in generating an under-
standing of the roles played by the actors within healthcare
networks, and how changes may be made to share agency
more equitably around decision making or, in some cases,
remove the decision-making roles of actors where this may
result in a higher frequency of intended outcomes.
This systematic review has several strengths, including
the application of a classification system for grouping ena-
blers and barriers affecting biosimilar uptake. This study
comprehensively reviewed available primary literature over
a broad date range, ensuring adequate coverage of publica-
tions. This review also considered the roles played by human
and non-human actors within healthcare networks and their
interconnectedness in determining outcomes.
A key limitation of this study is the progressive nature
of this space. Studies are being published at a rapid pace,
leaving open the possibility of missed literature. Addition-
ally, there is a level of subjectivity to rating articles through
the quality assessment tool applied (JBI) and the cross-cal-
culations between different study types. Finally, there is a
level of subjectivity applied to extracting and classifying
enablers, barriers, and the roles (mediators with broadened
or narrowed degrees of agency) played by the actors within
the articles, as these are not specifically identified within
the articles. While every effort was made through primary
and secondary reviews of the studies, and through quality
checks of the extracted data, risk of error exists. It is sug-
gested that further investigation be conducted around the
interconnectedness of actors within these networks and the
potential impacts of change in roles, particularly as new sys-
temic actors, such as policies, are enacted.
5 Conclusions
Barriers and enablers affecting uptake of biosimilar medicines
are interconnected within their networks, and can be divided
into systemic, HCP, and patient categories. Understanding the
agency of actors within networks may allow for more compre-
hensive and effective approaches. Systemic enablers and bar-
riers, including policies, governance, and cost structures, by
their nature function as mediators with broad degree of agency
within their networks. The main barriers affecting acceptance of
biosimilars for both HCPs and patients include general lack of
knowledge of biosimilars, in addition to concerns about safety
and efficacy. Enablers of uptake for HCPs often included struc-
tures creating cost savings. Systemic enablers in the form of
policies appear to be the most effective overall levers in affecting

C.Rieger et al.
uptake of biosimilars, with careful consideration given to appro-
priately educating HCPs and positively framing biosimilars for
patients.
Decision makers contemplating altering policies which
reposition the actors within networks, including HCPs and
patients, are advised to be mindful of the importance of edu-
cational strategies, which may function to alleviate the con-
cerns of HCPs around safety and efficacy of biosimilars, and
that will equip them with the ability to morepositively frame
startsof and switches to biosimilar medicines, which is the
most frequently named and successful enabler of biosimilar
uptake for patients in this systematic review.
Supplementary Information The online version contains supplemen-
tary material available at https:// doi. org/ 10. 1007/ s40259- 024- 00659-0.
Funding Open Access funding enabled and organized by CAUL and
its Member Institutions.
Declarations
Funding Not applicable. No funding was received in support of this
publication.
Conflicts of interest Author Chad Rieger is a PhD candidate in the Faculty
of Medicine at the University of Queensland in Brisbane, Australia. He is
also the Senior Medical Affairs Manager with Sandoz Pty Ltd, Australia
& New Zealand. Appropriate disclosures on his work with Sandoz Pty Ltd
have been made to ensure no interference with his academic work and spe-
cifically with this systematic review. No support or funding was provided
for this work by Sandoz Pty Ltd, nor from any other party.
Ethics approval Not applicable.
Patient consent to participate/publish Not applicable.
Availability of data and material Not applicable.
Code availability Not applicable.
Author contributions Chad Rieger: Primary author, completion of
search of databases and screening of titles and abstracts, full text
review, data extraction, preparation of final manuscript, editing and
final review of manuscript. Judith Dean: Secondary author, support of
preparation of final manuscript, editing and final review of manuscript.
Lisa Hall: Support of preparation of final manuscript, third reviewer on
title and abstract screening, third reviewer on data extraction, editing
and final review of manuscript. Paola Vasquez: Second reviewer on
the titleand abstract screening, full text review, and data extraction.
Editing and final review of manuscript. Gregory Merlo: Second review
on title and abstract screening, editing and final review of manuscript.
All authors read and approved the final manuscript.
Open Access This article is licensed under a Creative Commons Attri-
bution-NonCommercial 4.0 International License, which permits any
non-commercial use, sharing, adaptation, distribution and reproduction
in any medium or format, as long as you give appropriate credit to the
original author(s) and the source, provide a link to the Creative Com-
mons licence, and indicate if changes were made. The images or other
third party material in this article are included in the article’s Creative
Commons licence, unless indicated otherwise in a credit line to the
material. If material is not included in the article’s Creative Commons
licence and your intended use is not permitted by statutory regula-
tion or exceeds the permitted use, you will need to obtain permission
directly from the copyright holder. To view a copy of this licence, visit
http://creativecommons.org/licenses/by-nc/4.0/.
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Authors and Aliations
ChadRieger1 · JudithA.Dean2· LisaHall2· PaolaVasquez3· GregoryMerlo2
* Chad Rieger
c.rieger@uq.net.au
Judith A. Dean
j.dean4@uq.edu.au
Lisa Hall
l.hall3@uq.edu.au
Paola Vasquez
paola.vasquez@uq.edu.au
Gregory Merlo
gregory.merlo@health.qld.gov.au
1 Faculty ofMedicine, University ofQueensland, Brisbane,
Australia
2 Faculty ofMedicine, School ofPublic Health, University
ofQueensland, Brisbane, Australia
3 Centre forHealth Services Research, University
ofQueensland, Brisbane, Australia