Predictors of tacrolimus pharmacokinetic variability: current evidences and future perspectives

Abstract

Introduction
In kidney transplantation, tacrolimus (TAC) is at the cornerstone of current immunosuppressive strategies. Though because of its narrow therapeutic index, it is critical to ensure that TAC levels are maintained within this sharp window through reactive adjustments. This would allow maximizing efficiency while limiting drug-associated toxicity. However, TAC high intra- and inter-patient pharmacokinetic (PK) variability makes it more laborious to accurately predict the appropriate dosage required for a given patient.

Areas covered
This review summarizes the state-of-the-art knowledge regarding drug interactions, demographic and pharmacogenetics factors as predictors of TAC PK. We provide a scoring index for each association to grade its relevance and we present practical recommendations, when possible for clinical practice.

Expert opinion
The management of TAC concentration in transplanted kidney patients is as critical as it is challenging. Recommendations based on rigorous scientific evidences are lacking as knowledge of potential predictors remains limited outside of DDIs. Awareness of these limitations should pave the way for studies looking at demographic and pharmacogenetic factors as well as gut microbiota composition in order to promote tailored treatment plans. Therapeutic approaches considering patients’ clinical singularities may help allowing to maintain appropriate concentration of TAC.

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Predictors of tacrolimus pharmacokinetic
variability: current evidences and future
perspectives
Alexandra L Degraeve , Serge Moudio , Vincent Haufroid , Djamila Chaib
Eddour , Michel Mourad , Laure B Bindels & Laure Elens
To cite this article: Alexandra L Degraeve , Serge Moudio , Vincent Haufroid , Djamila Chaib
Eddour , Michel Mourad , Laure B Bindels & Laure Elens (2020): Predictors of tacrolimus
pharmacokinetic variability: current evidences and future perspectives, Expert Opinion on Drug
Metabolism & Toxicology, DOI: 10.1080/17425255.2020.1803277
To link to this article: https://doi.org/10.1080/17425255.2020.1803277
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REVIEW
Predictors of tacrolimus pharmacokinetic variability: current evidences and future
perspectives
Alexandra L Degraeve
a,b
,†
, Serge Moudio
a,c
,†
, Vincent Haufroid
c,d
, Djamila Chaib Eddour
e
, Michel Mourad
e
,
Laure B Bindels
b
and Laure Elens
a,c
a
Integrated Pharmacometrics, Pharmacogenomics and Pharmacokinetics (PMGK), Louvain Drug Research Institute (LDRI), Université Catholique De
Louvain, Brussels, Belgium;
b
Metabolism and Nutrition Research Group (Mnut), Louvain Drug Research Institute (LDRI), Université Catholique De
Louvain, Brussels, Belgium;
c
Louvain Centre for Toxicology and Applied Pharmacology (LTAP), Institut De Recherche Expérimentale Et Clinique
(IREC), Université Catholique De Louvain, Brussels, Belgium;
d
Department of Clinical Chemistry, Cliniques Universitaires Saint-Luc, Brussels,
Belgium;
e
Kidney and Pancreas Transplantation Unit, Cliniques Universitaires Saint-Luc, Brussels, Belgium
ABSTRACT
Introduction: In kidney transplantation, tacrolimus (TAC) is at the cornerstone of current immunosup-
pressive strategies. Though because of its narrow therapeutic index, it is critical to ensure that TAC
levels are maintained within this sharp window through reactive adjustments. This would allow
maximizing efficiency while limiting drug-associated toxicity. However, TAC high intra- and inter-
patient pharmacokinetic (PK) variability makes it more laborious to accurately predict the appropriate
dosage required for a given patient.
Areas covered: This review summarizes the state-of-the-art knowledge regarding drug interactions,
demographic and pharmacogenetics factors as predictors of TAC PK. We provide a scoring index for
each association to grade its relevance and we present practical recommendations, when possible for
clinical practice.
Expert opinion: The management of TAC concentration in transplanted kidney patients is as critical as
it is challenging. Recommendations based on rigorous scientific evidences are lacking as knowledge of
potential predictors remains limited outside of DDIs. Awareness of these limitations should pave the
way for studies looking at demographic and pharmacogenetic factors as well as gut microbiota
composition in order to promote tailored treatment plans. Therapeutic approaches considering
patients’ clinical singularities may help allowing to maintain appropriate concentration of TAC.
ARTICLE HISTORY
Received 5 May 2020
Accepted 27 July 2020
KEYWORDS
Tacrolimus; kidney
transplantation;
pharmacokinetics;
pharmacogenetics;
demographic factors; drug
interactions
1. Introduction
Solid-organ transplantation is the treatment of choice for
patients suffering from end-stage organ disease. In 2018,
more than 140,000 organ transplantations were recorded
worldwide, of which 65% were kidney grafts [1]. Post-surgical
treatment includes the implementation of a lifelong immuno-
suppressive (IS) therapy to prevent organ rejection. In kidney
transplantation, the most commonly used combination for
maintenance IS therapy is composed of one calcineurin inhi-
bitor (CNIs), most often tacrolimus (TAC), one anti-metabolite,
mycophenolate mofetil (MMF), and glucocorticoids [2,3].
Among these IS agents, TAC has become a central part of IS
protocols in organ transplantation due to its ability to inhibit
T-cell activation. By forming a complex with FK binding pro-
tein-12, TAC blocks the serine-threonine phosphatase activity
of calcineurin, thus preventing T-cell and antibody-mediated
rejection after organ transplantation [4].
TAC is characterized by a narrow therapeutic index with
drug overexposure linked to nephrotoxicity, neurotoxicity, and
diabetes mellitus [5], while underexposure might result in
graft rejection [6]. Considerable intra- and inter-individual
variability has been reported in TAC pharmacokinetics (PK),
highlighting the need for precise therapeutic drug monitoring
(TDM). Thus, drug levels are to be constantly maintained
within the sharp therapeutic window through reactive adjust-
ments, in order to limit drug-associated toxicity while max-
imizing efficacy [2,7].
Oral bioavailability of TAC is highly variable among
patients, ranging from as low as 4% to 89% [8]. With the
prolonged-release tablet formulation (Advagraf®) given once
daily, TAC has the capacity to be released and absorbed
throughout the gastrointestinal tract until the distal gut
[9,10]. There is extensive and highly variable pre-systemic
metabolism in the gut wall and the liver, mainly driven by
cytochromes P450 (CYP) 3A isoenzymes [11], with CYP3A5
being a better catalyst than CYP3A4 [12]. TAC is also subjected
to active transport, directed by efflux proteins, chiefly ABCB1
(P-glycoprotein, P-gp) [13] which modulates gastrointestinal
absorption and cellular distribution [14]. After absorption, the
remaining fraction is extensively bound to erythrocytes, and in
the plasma, 90% of TAC is fixed to proteins [8]. CYP450-
mediated metabolism gives rise to at least 15 metabolites,
CONTACT Laure Elens laure.elens@uclouvain.be Université Catholique De Louvain (UC Louvain). Louvain Drug Research Institute (LDRI), Integrated
Pharmacometrics, Pharmacogenomics and Pharmacokinetics (PMGK). , 1200 Bruxelles Belgium
†
Both authors contributed equally to this work.
EXPERT OPINION ON DRUG METABOLISM & TOXICOLOGY
https://doi.org/10.1080/17425255.2020.1803277
© 2020 Informa UK Limited, trading as Taylor & Francis Group

resulting from O-demethylation, hydroxylation, and/or oxida-
tive metabolic reactions [8]. Among these, 13-O-desmethyl-
TAC is the major metabolite with an IS activity reduced to
merely one-tenth compared to TAC itself. By contrast, 31-
O-desmethyl-TAC is the only metabolite as active as TAC but
is quantitatively negligible. Thenceforth the contribution of
TAC metabolites to it IS efficacy is likely insignificant [8].
Eventually, these metabolites are excreted in the bile [8].
Besides this phase, I metabolic process, TAC glucuronidation
by UGT1A4 was shown, but little is known about the physio-
logical abundance of these glucuronides’ derivatives [15–17].
Furthermore, it was evidenced in vitro that gut bacteria can
also metabolize TAC with the production of a distinct TAC
metabolite through a C-9 keto-reduction [18]. All in all, the
intrinsic PK properties of TAC, including erratic absorption,
variable first-pass effect, and microbial metabolism, are
responsible for its large PK intra- and inter-patient variability.
Clinically significant variability within individual patients can
be defined as an alternation between episodes of over- and
under-exposure within a timeframe in which the dosage itself
remains constant [19]. In renal transplantation, intra-patient
variability in TAC drug exposure is now recognized as
a predictor of poor clinical outcome [20,21]. Indeed, persistent
variability might be associated to alloimmune activation during
low exposure [22], and toxicity, and/or low immunity during
overexposure. This inconsistent situation is commonly observed
early after the engraftment and leads to suboptimal outcomes.
Several factors have been proposed as contributing to TAC
intra- and/or inter-patient variability, including concomitant intake
of food or drugs [7], genetic polymorphisms [23,24], demographic
variables (gender [25,26], age [27], ethnicity [28]), gastrointestinal
disturbances [29], low serum protein [30], hematocrit [31], time-
post transplantation [32], non-adherence [33], circadian rhythm
[34], drug–disease interactions [35], and possibly change in gut
microbiota composition [36].
To advance the understanding of the factors able to influence
TAC PK, in the present review, we summarize studies investigat-
ing drug interactions with TAC, as well as demographic and
pharmacogenetic predictors of TAC PK. Our aim is to identify
clinical and genetic covariates able to explain the variability, and
to provide dosing recommendations safeguarding appropriate
drug exposure in kidney transplant recipients.
To help the reader in the identification of relevant associations,
for each section, we have defined an ordinal scoring index reflect-
ing the strength of reported associations between the different
covariates and TAC PK. The clusters were scaled in four groups
according to their relative relevance: either none, weak, moderate
or strong effect. This classification aims to pool different aspects
evaluating the strength and magnitude of the observations pre-
viously reported in the literature, including the consistency and
repeatability, the quality as well as the size of the studies, and if
there is in vitro/mechanistic-based data supporting the associa-
tion. To consider these factors in clinical practice, recommenda-
tions are proposed in some sections, where appropriate. As it
reflects our judgment, this proposed scoring should be inter-
preted carefully and ideally adapted to each individual situation.
2. Drug-drug interactions
Drug–drug interactions occur (DDI) when the PK of
a medication is altered by the concomitant administration of
another medication [37], the likelihood of DDI thus increases
with the number of medications a patient is taking. For trans-
plant patients, in order to achieve adequate immunosuppres-
sion while limiting side effects, the current guidelines involve
combining medications from different classes. The use of poly-
pharmacy is thus unavoidable; therefore, it is important to
study the impact it might have on TAC PK and vice-versa.
As we previously established, monitoring TAC concentra-
tion is essential. Amongst some of the factors interfering with
its PK, it was reported that DDI, by their impact on absorption,
distribution, metabolism, and excretion (ADME), might directly
affect blood levels, with TAC also able to affect the PK of other
drugs [38]. To date, more than 707 drugs interacting to some
extend with TAC have been reported, in addition to several
alcohol/food interactions and diseases interactions [39]. The
majority of food–drug interactions are only moderate to minor
[7], still food is a factor to consider when studying TAC PK. In
Table 1, we present the main interactions relevant to
a transplanted patient’s regimen.
TAC is extensively metabolized by the CYP3A isoenzymes,
with CYP3A5 being the main protagonist [12]. Therefore, DDI
associated with TAC are mostly mediated by these enzymes.
An inhibition of CYP3A activity leads to increased TAC blood
levels, caused by decreased clearance through competitive
inhibition, potentially causing significant overdosing. Such
elevation of blood concentration has been reported with cal-
cium channels blockers (diltiazem [40], verapamil [41], nicardi-
pine [42], amlodipine [43]), which are potent inhibitors of
CYP3A enzymes [44,45]. Similar effects have been reported
for antibiotics erythromycin and clarithromycin [46,47], and
suggested for some food products such as grapefruit [48,49]
and pomegranate [50,51] including several cases of severe
interactions. On the contrary, drugs inducing CYP3A enzymes
such as anticonvulsants phenytoin [52–54], carbamazepine
[55], and phenobarbital [56] reduce TAC blood levels, thus
Article highlights
●TAC concentrations can be affected by several factors such as genet-
ics, demographics, drug–drug interactions or microbiota composition.
●Taking this information into account might allow individualized treat-
ments with increased efficiency and reduced toxicity.
●We provide a scoring index for known associations between these
factors and TAC PK to grade the relevance of these associations.
●For drug–drug interactions, we present clear guidelines to clinicians
allowing for a better control of TAC PK.
●For demographics, ageing and ethnicity appear to be of relevance for
explaining part of the TAC PK disparities.
●For Pharmacogenetics, several lines of evidences pinpoint the poten-
tial benefit of CYP3A5 pre-emptive genotyping strategy for TAC
dosage individualization.
●More recently, some clues have been highlighted for a possible
involvement of microbiota in TAC PK.
●In the Expert opinion section, we recap the current state of knowl-
edge and provide perspectives for future research into TAC PK inter-
and intra-individual variability.
This box summarizes key points contained in the article.
2A. DEGRAEVE ET AL.

decreasing its bioavailability and possibly causing under dos-
ing, increasing the risk of graft failure.
Though, TAC is also a substrate for ABCB1 expressed by
different epithelial and endothelial cells including enterocytes,
hepatocytes, lymphocytes, site of therapeutic action, and kid-
ney, where its toxicity is exerted. Further to effects mediated
by CYP3A enzymes, as emphasized above, TAC bioavailability
is also highly influenced by this efflux transport [57]. Hence,
drugs acting as ABCB1 inducers and inhibitors can interact
with TAC PK leading to changes in TAC absorption and bioa-
vailability, with a direct impact on blood exposure [7,39]. It
was described that in combination with corticosteroids inhi-
biting TAC metabolism while also acting on ABCB1 induction,
the bioavailability of TAC is initially reduced and a higher
dosage is required to achieve target trough levels [58–60].
However, this effect is only observed in the short term as the
impact of induction gradually decreases after several days, due
to compensatory mechanisms [7]. Likewise, the toxicity of
colchicine, also an ABCB1 substrate, was reported to increase
at therapeutic doses in combination with TAC [61,62].
Of even higher importance are the several drugs able to act
on both CYP3A and ABCB1 activities. Their use, combined to
administration of TAC, can lead to dangerous changes in
blood levels with subsequent adverse effects. This is particu-
larly true for anti-viral medications such as anti-HIV protease
inhibitors, where TAC levels can be increased up to 140-fold
together with an important decrease in clearance [63–66].
Furthermore, in co-medication with the anti-arrhythmic amio-
darone, an ABCB1 inhibitor, TAC levels have been reported to
increase significantly [67,68]. When taken together, drugs of
azole antifungal family and TAC would maximize their effects
resulting in increased blood concentrations [69–71].
Meanwhile, rifampicin, an antibiotic and anti-tuberculosis
agent causing ABCB1 induction, is reducing TAC levels when
given concomitantly [72,73]. In these cases, and whenever
possible, drug substitution is strongly recommended to main-
tain TAC at optimal levels.
Both these metabolic pathways are critically involved in the
PK of a wide range of commonly used drugs. CYP3A are
important in the metabolism of drugs, while intestinal ABCB1
appears to influence the peak concentration of orally adminis-
tered drugs in the systemic circulation. Therefore, it is essential
to evaluate and consider the PK and potential DDI profiles of
drugs used in IS protocols to avoid significant detrimental
clinical effects. A better consideration of principles underlying
TAC DDI in clinic will heavily contribute to more efficient and
more adapted therapies for transplant patients.
Beside these conventional DDI, drug-mediated alterations
of gut microbiota composition are other underexplored likely
sources of DDI. Indeed, microbiota composition is very sensi-
tive to any shift in environmental factors, including pharma-
ceutical regimen. This intestinal microbial community
influences the PK processes of xenobiotics (including drugs)
in the human body through direct or indirect mechanisms
Table 1. Drug–drug interactions affecting tacrolimus pharmacokinetics and associated recommendations.
CLASS DRUGS PK IMPACT STRENGTH RECOMMENDATIONS
Antibacterials Clarithromycin,
erythromycin
[45,46]
↑ concentration
(up to 6-fold)
Strong Consider substitution for a drug less likely to interact with
CYP3A4/5 (e.g. azithromycin, spiramycin).
Rifampicin
[70,71]
↓ concentration
(2 to 4-fold)
Strong Consider substitution for a drug less likely to interact with
CYP3A4 (e.g. isoniazide) or increase TAC dosage with
blood concentration monitoring.
Calcium Channel
Blockers
Diltiazem
[39]
, verapamil
[40]
,
nicardipine
[41]
, amlodipine
[42]
↑ concentration
(up to 4-fold)
Strong Monitor TAC blood concentration (especially if CYP3A5 non-
expressers).
Antiretrovirals Protease inhibitors
[61–64]
(e.g. lopinavir/darunavir + booster
(ritonavir, cobicistat))
Extended ↑
concentration
(˃10-fold)
Strong Strong dosage reduction (0.5–1 mg once a week) with
Protease Inhibitors. Monitor TAC blood concentration.
Efavirenz
[62]
↓ concentration Moderate Monitor TAC blood concentration.
Antifungals Fluconazole, voriconazole,
posaconazole, itraconazole
[67–69]
↑ concentration
(up to 3-fold)
Strong Consider dose adjustments (reduce by 2/3, except
itraconazole monitoring only). Monitor TAC blood
concentration, and Long QT prolongation.
Anti-convulsants Phenobarbital
[55]
, carbamazepine
[54]
,
phenytoin
[51–53]
↓ concentration
(up to 2-fold)
Strong Consider progressive substitution for non-CYP3A4-inducer
drug (e.g. gabapentine, pregabaline, but not primidone)
or increase TAC dosage, both with blood concentration
monitoring. Avoid extended release TAC with phenytoin.
Anti-inflammatory Colchicine
[60]
↑ colchicine
concentration
Strong Monitor closely for colchicine toxicity. Consider colchicine
dose reduction.
Corticosteroids
[58,59]
↓ concentration Strong Monitor TAC blood concentration, when changing doses.
Anti-arrhythmics Amiodarone
[65,66]
Quinidine
[193]
↑ concentration
(≥4-fold)
/
Strong Consider substitution for drugs not acting on CYP3A4 (e.g.
flecainide, propafenone). Monitor TAC blood
concentration, and potential QT interval prolongation.
Hormones Danazol
[194]
, testosterone
[195]
↑ concentration Moderate Monitor TAC serum concentration, and toxicity.
Gastro-intestinals Lansoprazole
[196]
, omeprazole,
esomeprazole
[197]
↑ concentration
(Up 2 to 3-fold)
Moderate Monitor TAC blood concentration. Consider substitution
(e.g. pantoprazole, rabeprazole).
Antacids
[198]
(Al(OH)3 – MgO – NaHCO₃)
↓ absorption Moderate Consider 2 hours interval between TAC and antacids
administration.
Anticoagulants Rivaroxaban, apixaban
[199,200]
↑ concentration
(Up to 1.3-fold)
Moderate Consider substitution (e.g. dabigatran). Monitor
anticoagulation. Avoid in patients with renal
insufficiencies.
Antimalarials Mefloquine
[201]
↑ concentration Moderate Monitor TAC blood concentration and potential QT interval
prolongation.
TAC = tacrolimus, ↑ = increased, ↓ = decreased.
EXPERT OPINION ON DRUG METABOLISM & TOXICOLOGY 3

[74]. We can expect that drugs, and particularly antibiotics,
also alter indirectly TAC PK through changes in microbiota-
influenced PK processes.
In summary, co-administration with a drug known to inter-
act with ABCB1 and/or CYP3A, can cause alterations in TAC
bioavailability and metabolism [39], thus leading to danger-
ously high IS levels with subsequent toxicity, or to inade-
quately low levels and increased probabilities of organ
rejection [75]. In consequence, additionally to anticipated
dosage modifications, TDM is of primary importance in clinical
practice for transplant patients, even more in cases were
adjustments to patient’s regimen are required.
3. Demographic predictors
Apart from medication and potential interactions, patient’s
demographic parameters are another major factor to consider
in TAC dosage adjustment. Recently several studies have high-
lighted a relation between demographic characteristics such as
race, gender, or age to TAC PK [76,77]. Therefore, analyses aimed
at determining if demographic predictors could improve the
understanding of tolerability and safety profiles within key sub-
populations. In Table 2, we summarize the main demographic
factors relevant to a transplanted patient’s regimen.
Biological aging is a complex multifactorial process character-
ized by structural and functional changes affecting most molecu-
lar, cellular, and organ systems, resulting in an overall reduced
homeostatic capacity and a decreased physiological reserve in
response to stress [78]. Aging induces significant changes in
body composition, hepatic, and renal function [79]. This has
a direct impact on the pharmacodynamic (PD) and PK, resulting
notably in an increased bioavailability for some drugs, including
for TAC [80]. In the elderly population, understanding alterations
in PK are particularly important since age-related impairments
have been reported to have a critical impact on TAC metabolism
and excretion, leading to a prolongation of half-life [81]. Despite
a lower dose-to-bodyweight, increased TAC exposure (up to 50%)
was observed in older transplant patients (≥65 years) compared to
younger adults, possibly due to reduced clearance capacities [27].
Alongside the impact on PK, higher prevalence of TAC-mediated
toxicity was reported after 60 years of age and associated with
higher rate of TAC withdrawal [82]. Moreover, because of genetic
and environmental modulators, patients at the same age will
show different trajectories of age-related decline [83]. Taken
together, these observations partly explain the increasing inter-
individual variability observed in TAC PK as people get older, but
also give hints to explain the intra-variability observed for patients
over time [81,84]. We recommend to increase vigilance and rein-
force TDM for older patients as they are also more vulnerable.
Research has shown that sex differences may contribute to
variations observed between women and men in PK. It was pre-
viously suggested that sex could affect drug ADME leading to
differences in drug response [85]. These PK differences can mostly
be explained by body composition and weight since the majority
of drugs are currently administered at fixed doses for adult
patients rather than on an mg/kg basis [86]. Still, using fixed
doses might lead to higher exposure in women compared to
men, resulting in potential adverse effects [87]. However, for
TAC, initial doses are prescribed on an mg/kg basis.
Consequently, a part of the impact of gender on TAC exposure is
indirectly considered. This could also explain why, in most studies,
the gender has not been identified as a covariate of TAC exposure
[25,26]. Yet, recent literature suggests that, even with weight
adjustment, sex differences might persist based on additional
indirect and concomitant factors such as hormonal distribution,
age, polypharmacy, genetic specificities or polymorphisms, and
disease state [88].
Despite the high prevalence of TAC as an IS in transplanta-
tion and the aforementioned issues of intra- and inter-
variability, surprisingly, few studies have attempted to clarify
the impact of ethnic disparities on TAC exposure. It has, how-
ever, been established that ethnic factors might affect the
bioavailability, distribution, metabolism, and elimination of
drugs [89]. Recent studies have provided evidence that
African American transplant recipients require higher doses of
TAC in order to achieve therapeutic drug concentrations and to
decrease the risk of acute rejection. Although these doses
would also significantly increase the risk of TAC-induced
nephrotoxicity [90]. Indeed, African Americans were described
as having a greater risk of renal failure than the general popula-
tion [91]. On the other hand, it was demonstrated that Asian
populations display greater TAC bioavailability compared to
other ethnic groups, suggesting that these patients may require
lower TAC doses [92]. The differential prevalence of CYP3A5
polymorphisms in these populations is the main explanation
for these differences. We consider that with regards to the
current knowledge on the effect of specific SNPs on drug
metabolism, it is pharmacogenetics and not ethnicity per se
that need to be considered as the central variable.
4. Pharmacogenetic predictors
Proteins implicated in TAC ADME pathways are highly poly-
morphic, providing alternative explanations to the observation
that some patients have relatively low drug exposure with
Table 2. Demographic factors affecting tacrolimus pharmacokinetics and associated recommendations.
FACTOR PK IMPACT STRENGTH RECOMMENDATIONS
Age (˃ 65 years)
[27,80]
↑ concentration (up to 50%)
normalized to dose ↓ Cl/F
Strong Consider dose reduction in elderly, based on regular TAC monitoring. Consider follow-up
of TAC-induced neurotoxicity and nephrotoxicity.
Gender
[25,26]
/ Weak Consider dosage adjustment on an mg/kg basis sufficient to limit gender variability.
Ethnicity
[87–90]
Lower TAC concentration in Afro-
American population
Higher TAC bioavailability in Asian
population
Strong Ethnic factors highly correlate to genetic polymorphisms, (see pharmacogenetic section).
TAC = tacrolimus, ↑ = increased, ↓ = decreased, Cl/F = apparent clearance.
4A. DEGRAEVE ET AL.

possibly fast drug clearance, while others display a higher
drug exposure and slower drug elimination rate.
Pharmacogenetic studies have provided interesting clues to
clarify the reasons behind TAC PK variability (Table 3). With the
exception of a single nucleotide polymorphism (SNP) in
CYP3A5 that correlates with significant changes in TAC PK,
most of the associations are still controversial. Confidently,
for CYP3A5, some findings have been validated and repeated
across multiple studies. Nevertheless, the systematic applica-
tion of pharmacogenetic testing strategies in daily clinical
practice is not as universally accepted as it can be for DDI,
and still requires stronger guidelines before clinical
implementation.
As exposed above, after oral administration, TAC is metabolized
by intestinal and hepatic CYP3A isoenzymes, with CYP3A5 being
a better catalyst than CYP3A4 [12]. The expression of CYP3A5 is
largely determined by genetic polymorphisms with only 15% of
Caucasians expressing a functional enzyme at a detectable level
[93,94]. The CYP3A5*3 allele (rs776746) is an intronic SNP that
creates a cryptic splice site causing the addition of an extra exon
(exon 3B) in the mRNA [93]. This splicing defect leads to the
introduction of a premature stop codon, ending up with the
translation of an inactive-truncated protein. As a consequence,
carriers of two loss-of-function (LOF) alleles do not express
a functional CYP3A5, and are therefore classified as CYP3A5 non-
expressers, whereas carriership of at least one functional allele
(CYP3A5*1) is associated with a significant CYP3A5 effective expres-
sion (CYP3A5 expressers). CYP3A5*3 is the main genetic predictor
of TAC PK and it was shown that CYP3A expressers require
a double dose when compared to carriers of two LOF alleles
[24,25,95–104]. The consistency of this association was confirmed
by meta-analyses, regardless of the time post-transplantation or
the ethnicity of the patient [105–107]. The dominance of the
explicative value of CYP3A5 allelic status was illustrated by the
fact that, in a population of 446 kidney transplant recipients,
among a panel of more than 2000 SNPs in PK genes, no variant
other than CYP3A5*3 was significantly correlated with concentra-
tion-to-dose ratio and, by itself, the CYP3A5*3 SNP explained up to
39% of the variability in dose requirement [108]. Additionally,
multiple population PK models describing the PK effect of
CYP3A5*3 have been developed so far in distinct types of trans-
plant populations. They revealed that introducing the CYP3A5*3
genetic status of the patient in the model explained on average
30% of the total variability in the TAC clearance [26,31,103,109–
119]. Subsequent to these convincing observations, it was
expected that pharmacogenetics-based TAC dosage would
decrease the time needed to achieve target concentration range.
This hypothesis was investigated in three independent rando-
mized clinical trials (RCT) [120–122]. In all three of these trials, the
patients were assigned to receive either a standard, body-weight-
based, or a CYP3A5 genotype-based TAC starting dose, with
CYP3A5 expressers receiving a higher TAC dose when compared
to CYP3A5 non-expressers. In the first RCT [120], it was observed
that, in the group receiving the CYP3A5-adapted dose, a higher
proportion of patients had values within the targeted through
concentration (C
0
) range at day 3 after TAC initiation. They also
required fewer dose modifications, and the targeted C
0
was
achieved sooner by 75% of these patients. However, the benefit
of reaching therapeutic TAC concentrations earlier did not trans-
late into better clinical outcomes. In the second RCT [121], it was
shown by Min et al. that a preemptive CYP3A5 genotyping strategy
allows shortening the time to reach target concentrations in pedia-
tric transplant recipients. By contrast, in the third trial [122], at day
3, no difference in the proportion of patients having a TAC expo-
sure within the target range was observed between the standard-
dose and genotype-based groups despite CYP3A5 expressers still
Table 3. Pharmacogenetic factors affecting tacrolimus pharmacokinetics and associated recommendations.
ALLELIC
FREQUENCIES
[202]
GENE SNP rs# PK IMPACT ADDITIONNAL REMARKS Cau As Afr His STRENGTH REFERENCES
ABCB1 1199 G > A rs2229109 ↑ TAC cellular
concentrations
No effect on blood concentrations 0.03 0.00 0.00 0.03 Moderate [160,161,165,167]
3435 C > T
(1236 C > T,
2677 G > T/A)
rs1045642
(rs1128503,
rs1045642)
↑ TAC cellular
concentrations
No clear effect on blood
concentrations
0.48 0.60 0.85 0.54 Moderate [103,159–167]
CYP3A4 CYP3A4*1B rs2740574 ↑ TAC clearance
↓ TAC exposure
In strong linkage disequilibrium with
CYP3A5*1
0.03 0.00 0.77 0.03 None [98,99,102]
CYP3A4*18B rs28371759 ↑ TAC clearance
↓ TAC exposure
Only relevant in Asians 0.00 0.01 0.00 0.00 Weak [151–153]
CYP3A4*20 rs67666821 ↓ TAC clearance
↑ TAC exposure
Only relevant in Latinos 0.00 0.00 0.00 0.01 Weak [154]
CYP3A4*22 rs35599367 ↓ TAC clearance
↑TAC exposure
Only relevant in Caucasians 0.05 0.00 0.00 0.04 Strong [101,109,116,126–
140]
CYP3A5 CYP3A5*3 rs776746 ↓ TAC clearance
↑ TAC exposure
Preemptive genotyping tested in 3
independent RCT, CPIC guidelines
available
0.06 0.29 0.82 0.07 Strong [24–26,31,93–
120]
NR1I2 c.938–17 C > T rs2776707 ↑ risk of DGF for
TT (kidney
genotype)
Not repeated 0.16 0.17 0.02 0.22 None [170,171]
c.-1135 C > T rs3814055 ↓ TAC clearance
↑ TAC exposure
↓ PXR activity and expression 0.37 0.22 0.31 0.40 Moderate [172–174]
POR POR*28 rs1057868 ↑ TAC clearance
↓ TAC exposure
Effect observed in CYP3A5
expressers only
0.30 0.37 0.17 0.28 Weak [144–147]
PPARα c.1055–17 C > G rs2276707 None ↓ CYP3A4 activity, ↑ risk of
Tac-associated NODAT
0.17 0.47 0.42 0.18 Weak [149,150]
TAC = tacrolimus, ↑ = increased, ↓ = decreased. Cau = Caucasians, As = Asians, Afr = Africans, His = Hispanics.
EXPERT OPINION ON DRUG METABOLISM & TOXICOLOGY 5

required a higher Tac dose to achieve target concentrations com-
pared with CYP3A5 nonexpressers. Given the implication of
CYP3A5 in TAC PK, these negative results are quite surprising and
might possibly be attributed to variances in study design. In this
third RCT, like in others, the incidence of acute rejection was
comparable between both groups. All together, these results indi-
cate that despite the fact that CYP3A5 genotype has the power to
explain a substantial part of TAC PK variabilities, it is not sufficient
by itself to improve the clinical outcome. Although it has been
prospectively shown in a pilot study that a genotype-based
approach was safe and allowed deferring TDM interventions
[123], it was recently reported that genotype-guided initial doses
and achieving target therapeutic TAC levels at day 3 do not
decrease the cost associated with TDM after transplantation
[124]. However, the authors have also shown that CYP3A5 expres-
sers generate higher additional hospitalization cost for kidney
transplants when compared to CYP3A5 non-expressers [124].
This last observation suggests that genotyping is a cost-
conscious tool that can assist the clinicians and somewhat support
the Clinical Pharmacogenetics Implementation Consortium (CPIC)
recommendations that endorse increasing the TAC starting dose
1.5–2 times for CYP3A5 expressers [125].
In addition to CYP3A5 genotype, other SNPs might explain the
residual TAC PK variability, especially in CYP3A5 non-expressers
where CYP3A4 seems to compensate the loss of CYP3A5 activity.
The activity of CYP3A4 is extremely variable and depends on
multiple demographic, physiologic but also genetic factors. It
was suggested that up to 90% of CYP3A4 activity variability
would have a genetic basis [126]. Among the different SNPs
that have been tested for association with TAC PK, the
CYP3A4*1B SNP, which is defined by an A to G transition at
position −392 in the promoter region of CYP3A4, was associated
with an increased CYP3A4 activity [127]. It was shown that the
dose requirement (i.e. the through concentration-to-dose ratio)
was increased among carriers of the G variant allele [100,104].
However, it is suspected that this association is mostly due to the
strong linkage disequilibrium with the CYP3A5*1 functional allele
and not from a substantial change in CYP3A4-mediated meta-
bolism [101]. By contrast, the CYP3A4*22 allele which is defined
by the presence of the rs35599367C>T SNP in intron 6 was
associated with reduced CYP3A4 hepatic expression and activity
leading to a decreased TAC clearance for CYP3A4*22 carriers
[128–131]. Kidney transplant recipients who carry the
CYP3A4*22 variant allele require significantly lower TAC doses
compared to non-carriers [132–136]. Additionally, CYP3A5 non-
expressers who carry a CYP3A4*22 allele have a higher risk of TAC
overshoot during the first 3 days after kidney transplantation
[134,137,138]. This suggests that TAC dosage adjustment based
on CYP3A4*22–CYP3A5*3 combined allelic status might be more
informative than an algorithm considering the CYP3A5 genotype
exclusively [139,140]. These findings were further corroborated
through statistical investigation and discrimination analysis,
showing that CYP3A clustering according to both CYP3A4*22
and CYP3A5*3 better fits with TAC PK reality when compared to
regrouping according to CYP3A5*3 genotype solely and refining
of the CPIC recommendations has been proposed accordingly
[141]. This observation is also supported by the fact that popula-
tion PK (popPK) models including CYP3A4*22 are more accurate
than those not including this SNP [103,111,118,142]. However,
this specific SNP seems to be relevant in whites not expressing
CYP3A5 only because CYP3A4*22 alone does not significantly
improve the performance of TAC popPK models. It is thus possi-
ble that in population where CYP3A5*1 is more frequent, other
SNPs might have a predictive value for explaining differences in
TAC PK. In that way, it was proposed that CYP3A5 activity is
affected by SNPs in the P450 oxidoreductase (POR) gene, which
codes for a protein essential for CYP450 activity [143–145].
POR*28 is the most common nonsynonymous SNP reported for
POR and was associated with increased TAC dose requirement in
CYP3A5 expressers [146–149]. Likewise, the rs4253728 SNP in
PPAR-alpha was linked with decreased CYP3A4 activity [150]
and further associated with the development of new-onset dia-
betes (NODAT) in kidney transplant recipients treated with TAC
[151,152]. In Asians, it seems that an additional predictive value
can be credited to the CYP3A4*18B allele to explain TAC inter-
individual variability [153–155] as it is the case for CYP3A4*20 in
the Spanish population [156].
Apart from the oxidative metabolism, TAC is a known sub-
strate for ABCB1, formerly known as the P-gp [157]. ABCB1 is an
efflux pump belonging to the ATP-binding cassette (ABC) super-
family and is responsible for the active transport of substrates
across cell membranes from the intra- to the extra-cellular envir-
onment. ABCB1 expression is quite ubiquitous and plays a key
role in absorption, distribution, and excretion of drugs [158]. By
its expression in enterocytes, ABCB1 limits TAC bioavailability. It
is also expressed in lymphocytes where it might limit the access
of TAC to its therapeutic target. Finally, it is expressed in excre-
tory organs like the kidney, where TAC (or its metabolites) toxi-
city occurs, and the liver, where metabolites are excreted. SNPs in
ABCB1 have been widely considered for association with TAC PK
[98,104]. The most common SNPs in ABCB1 are 1236 C > T,
2677 G > T/A, and 3435 C > T and are in strong linkage disequili-
brium and, like CYP3A SNPs, their allelic frequencies vary among
ethnic groups. Much attention has been focused on the synon-
ymous coding 3435 C > T SNP which variant allele 3435 T was
associated with reduced mRNA expression and stability but also
differential substrate affinity [159,160]. Meta-analyses have
attempted to unravel the different controversial observations
on the influence of ABCB1 SNPs on TAC PK in renal transplanta-
tion [105,161]. The results suggest a limited impact of the
3435 C > T as well as 1236 C > T and 2677 G > T/A SNPs on
TAC blood concentrations. It was hypothesized that changes in
ABCB1 activity could be more relevant to explain differences in
TAC drug tissue distribution than differences in TAC blood con-
centration. Indeed, it seems that ABCB1 SNPs have a greater
influence on TAC local cellular concentration and compartmen-
talization than on systemic drug exposure, as it was shown that
both 1199 G > A and 3435 C > T SNPs are significantly associated
with increased TAC cellular concentrations in hepatocytes and in
lymphocytes [162–166]. These observations were further con-
firmed in vitro either in recombinant cellular models or in cul-
tured cells obtained from renal tissue [13,167]. Interestingly, the
ABCB1 SNPs have been more consistently linked with TAC PD
outcomes, suggesting that TAC local exposure is more closely
related to the drug activity than the blood concentrations
[168–170].
6A. DEGRAEVE ET AL.

Other genetic factors might potentially explain differences in
metabolism. For instance, the pregnane X receptor (PXR), encoded
by NR1I2, is a key nuclear receptor controlling the expression of
multiple CYP and transporter proteins [171]. In a mixed cohort of
kidney transplant patients treated with either TAC or cyclosporin,
the rs2276707C>T NR1I2 SNP in donors has been associated with
an increased expression of PXR in the kidney [172]. This gain of
function in the engrafted kidney carrying the TT variant genotype
was shown to be related to an increased risk of delayed graft
function [172]. It was hypothesized by the authors that renal
induction of CYP3A5 and ABCB1 expression by activation of PXR
may be more pronounced in recipients of kidneys from TT-
carrying donors and lead to an increased risk for the development
of delayed graft function. However, to our knowledge, these
results have not been repeated so far and still await confirmation
[173]. In vitro, it was shown that the rs3814055C>T SNP in NR1I2 is
associated with a down regulation of PXR expression and activity
either when assessed in liver samples or through luciferase assay
in recombinant models [174,175]. In this later study, the authors
also investigated the effect of this SNP on the TAC PK in 42 healthy
volunteers. They showed that the greater the number of T alleles
at rs3814055 in the NR1I2 gene, the greater the mean exposure to
TAC was and that the effect was independent from CYP3A5*3.
Quantitatively, they observed that the area under the concentra-
tion–time curve to the last quantifiable time point (AUClast) was
3.42 times greater in CYP3A5 non-expressers with the variant TT
genotype for rs3814055 when compared to wild-type individuals.
Supporting this observation, a clinical trial in 32 kidney transplant
patients showed that TAC clearance decreased gradually with the
number of variant alleles for the rs3814055C>T SNP in NR1I2 [176].
Other genetic associations have been reported, for instance
in ABCC2 or CYP2C8, but the sense of these findings is not
clear. These associations have not been repeated despite the
high number of studies published in the field, indicating
possibly their poor clinical relevance [98,104,177].
5. Recent perspectives in PK variability research
Although the different factors developed here above have the
potential to advance the understanding of PK variabilities, it is
clear that the current body of knowledge is not sufficient to
explain inter- and intra-individual variabilities. This appears as
particularly important for intra-individual PK variability, as it
has been related to the risk of treatment failure [20,21].
Of old, researchers have perceived that microbiota, and
especially gut microbiota, must take part in the becoming of
drugs, and thus in individual susceptibilities [178,179].
A decade ago, pharmacomicrobiomics has been defined as
a new branch of pharmacology that focuses on variations in
responses to drug disposition, action, and toxicity in which the
variable is the combined genetic makeup of the human-
associated microbes (microbiome) and their metabolic poten-
tial [180]. The role played by gut microbiota in drug efficiency
and safety has attracted more and more attention over the last
years. This field has also benefited from pioneering examples
of gut microbiota interacting with drugs such as digoxin and
irinotecan [181,182].
Given its mode of administration, its low intestinal absorption,
and its biliary excretion after metabolization [8], TAC is in close
contact with the gut microbiota, which substantiates the like-
lihood of direct interactions with microorganisms in vivo [74].
Several clues support the hypothesis of an interplay between
TAC and the gut microbiota. For instance, post-transplant diar-
rhea and enterocolitis might be associated with gut dysbiosis
and have been repeatedly associated with altered drug levels,
caused by a paradoxical increased bioavailability, possibly result-
ing in additional toxicity and the need of dose reduction [183–
185]. Furthermore, co-administration of antibiotics was linked to
variations in TAC levels [186–188]. In addition, TAC dose escala-
tion during chronic therapy in kidney transplant patients was
correlated with Faecalibacterium prausnitzii (F. prausnitzii) abun-
dance in the first week after kidney transplantation and was also
positively correlated with future TAC dosing at 1 month after
engraftment [36]. However, given the small number of partici-
pants enrolled (n = 5 patients in ‘dose escalation group’, n = 14
patients in ‘stable group’) and the relatively minor correlation
observed (Rho = 0.57, p = 0.01), the results reported in this clinical
study must be interpreted with caution. Following up on this
study, F. prausnitzii, but also several other Clostridiales, were
proposed as being able to metabolize TAC in vitro into a much
less potent immunosuppressive metabolite, the C-9 keto-
reduction product. This newly discovered metabolite is specific
to bacterial metabolization since it was shown that hepatic
microsomes were not able to produce it [18]. However, the
physiological relevance of this bacterial metabolite is still unclear.
On the other hand, microbial metabolites can also indir-
ectly affect the PK processes of drugs through interactions
with host pathways [74]. In the case of TAC, we believe that
microbial alterations could cause a change in CYP3A-mediated
metabolization and/or ABCB1 efflux, resulting in variable TAC
exposure. Indeed, it was demonstrated that, in germ-free mice,
the hepatic mRNA expression and activity of cyp3a11 (mice
orthologous of CYP3A4) is decreased [189]. The same trend is
observed after antibiotics-mediated microbial depletion [190].
However, current knowledge is insufficient to predict how
a change in intestinal microbiota can result in alterations of
TAC exposure, through modification of these host metabolic
pathways.
Thanks to their β-glucuronidase, some intestinal bacteria pos-
sess the metabolizing capacity to deconjugate glucuronide meta-
bolites [191]. Then, the restored parent compound can be
reabsorbed in the intestine through enterohepatic circulation
[74]. Such a process is responsible for the intestinal toxicity of
the chemotherapeutic agent irinotecan [182]. For MMF, enterohe-
patic circulation contributes for almost 40% of drug exposure in
humans [192]. Considering TAC, in a clinical study on liver trans-
plantation, Tron et al. observed a second peak in TAC profile in
15% of patients, that might indicate the existence of an entero-
hepatic circulation of the drug [17]. While optimizing TAC quanti-
fication by HPLC-MS/MS in human bile sample, they observed
a co-eluted peak using the same MS/MS m/z transition than TAC
[193]. This co-eluted peak disappeared when samples were pre-
treated with β-glucuronidases before extraction, resulting in
increased TAC total peak area. This result suggests that TAC
glucuronide metabolites were back converted into TAC by β-
glucuronidases treatment. Similar observations were previously
described by Firdaous et al. in 1997 [15]. Therefore, biliary excre-
tion of TAC glucuronide derivatives could participate to such
EXPERT OPINION ON DRUG METABOLISM & TOXICOLOGY 7

enterohepatic circulation. Alteration of microbiota composition
could affect this re-absorption process, and consequently be
a source of microbial-mediated TAC PK variability.
It is now accepted that the composition of the intestinal
microbiota impacts on uremic toxins generation [194].
However, in patients with chronic kidney disease, the problem
is bidirectional as the uremic status in turn affects the compo-
sition of gut microbiota and, consequently, the inflammation
status. An inflammatory environment is known to lead to the
phenoconversion of drug-metabolizing enzymes, meaning
that the presence of some pro-inflammatory cytokines (e.g.
IL-6, TNFα, IL-1 …) reduces their expression and/or activity
[195]. More particularly, IL-6 represses the expression of the
nuclear receptors PXR and CAR (constitutive androstane recep-
tor) and their target genes, including CYP3A4/5 [196]. This
phenoconversion process could explain unexpected overdoses
of tacrolimus reported in two clinical cases where patients
suffered from acute inflammatory episodes [197]. Indeed,
a very recent study highlighted that the median daily weight-
based TAC dose requirement was associated with inflamma-
tion and oxidative stress markers [35]. In this context, the
contribution of the gut microbiota to an inflammatory envir-
onment, possibly still present after the transplantation, could
contribute to the PK variability of TAC.
Hopefully, improving the knowledge about gut micro-
biota, including as a regulating factor of TAC PK will fuel
the state-of-the-art in regard to TAC therapy optimization
and provide new insights for precision pharmacotherapy. In
contrast to genetics, microbial composition and metabolic
function evolve all life long, and therefore, could also
explain TAC intra-patient variability. So, we trust this is
a promising track that should be explored further for TAC
management therapy.
6. Conclusion
Immunosuppression is a critical part of current transplantation
protocols, with TAC being increasingly more prevalent which
is not expected to decrease in the decade to come. However,
because TAC is also characterized by a narrow therapeutic
index, it is essential that optimal dosage is achieved immedi-
ately after transplantation and at all time to ensure immuno-
suppression efficiency. Furthermore, despite its popularity,
high incidence of intra- and inter-individual variability is still
being reported, and still leads to devastating outcomes in
some cases. In this review, we provide a state-of-the-art
update on the potential influence of demographics, genetic
polymorphisms and drug interactions on TAC PK and variabil-
ity. In addition, we discuss in this paper how the gut micro-
biota might constitute a promising avenue to address this
issue in the future. Further prospective studies are essential
to determine optimal dosing strategies for TAC based on
patients’ specific characteristics, including demographics and
pharmacogenetics. We believe that a better knowledge of all
of these interfering parameters collectively will advance the
understanding of inter-individual response differences. Thus,
enabling better predictions of dosage requirements leading to
an improvement in TAC management in transplant patients.
7. Expert opinion
Several criteria are necessary before implementing this type of
recommendations into practice. First, the strength of the asso-
ciation must be validated, widely established, and ideally,
mechanistically explained. Second, recommendations must
be clear and clinicians who makes use of them should be
deeply briefed about all aspects of the issue to ensure ade-
quate compliance from patients. Given the data we summarize
in the present paper, and although some recent progresses
have been achieved, one can easily appreciate that lots of
hurdles are to be cleared before we can convert theoretical
knowledge about TAC PK into clear enforceable messages that
can be implemented in practice, in order to address
variabilities.
In the present review some suggestions and solutions are
offered depending on the current knowledge to simplify the
situation and to help the reader detangle valuable associations
from insignificant observations. For some of the stronger find-
ings regarding drug interactions, we have sketched their possible
integration into practice by giving advice for dosage adjustment
anticipations. Nowadays, the expansion of screening software
provides an important tool to assist clinicians in the detection
and management of DDIs, including for TAC. Yet, for pharmaco-
genetic and demographic factors, and even for strongly substan-
tiated associations, translation into clinical recommendations is
still marginal in clinical practice (e.g. CYP3A5*3).
Therapeutic drug monitoring currently remains the tool of
choice to master TAC PK variabilities but more factors might
be considered as additional means to help refining these
recommendations. These will have to include genetic poly-
morphisms and study of demographic predictors. Particular
enthusiasm is also set on gut microbiota with the emergence
of pharmacomicrobiomics, a field that is yet to be fully
explored in the case of TAC. Once validated, all recommenda-
tions will have to demonstrate their benefits through prospec-
tive trials. From there, a robust and ideally cost-effective
framework will have to be implemented to ensure proper
clinical application. The road to clinics is still long, but we
expect that the advances summarized here will raise aware-
ness in the clinical community to better understand and man-
age the issue of TAC PK variabilities.
Funding
This work was supported by the Fonds de la Recherche Scientifique –
FNRS under Grant No F450919F. A. Degraeve is a research fellow of the
Fonds de la Recherche Scientifique - FNRS (FC-37471). This work was also
completed with the financial support of the French community of Belgium
(WBI program) through FSR action (UCLouvain).
Reviewer disclosures
Peer reviewers on this manuscript have no relevant financial or other
relationships to disclose.
Declaration of interest
No potential conflict of interest was reported by the authors.
8A. DEGRAEVE ET AL.

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