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Study of Herbal-Drug Interactions (HDIs) Using in
Silico Methods – Mission (Im)Possible
Opinion
Studying herb-drug interactions (HDIs) is extremely
important for the clinical practice, as many patients with chronic
diseases taking a number of conventional medicines, also take
phytomedicines, decoyed by advertising, without realizing that
these herbal products in some cases can be harmful instead
of beneficial. Herbal extracts contain a very large range of
substances (more than 200 sometimes) that can affect both the
pharmacokinetic and the pharmacodynamic characteristics of the
conventional therapy. However, can these interactions be evaluated
by in vitro and in silico methods in order to be highly informative
without major clinical trial costs? What are the difficulties that
must be taken into account in order to overcome the trade-offs
that are being made? This mini-review aims to address briefly
these issues and and the difficulty of building the models and
the simulations with herbal drugs. More patients suffering from
chronic diseases are taking herbal medicines, claiming them to
be effective agents with little or negligible undesirable effects.
Many of them, however, could lead to important clinical herb-drug
interactions (HDIs) [1-3]. Herbal extracts contain many biologically
active substances, with specific pharmacological characteristics,
which in some cases may act in different directions. The most
common form of interaction is the inhibition of the activity of the
cytochrome enzymes and, therefore, this mechanism will be largely
considered [4]. Evaluation of possible drug interactions is most
commonly evaluated in vitro, using isolated liver microsomes or
recombinant forms of cytochrome enzymes [5,6]. The mechanism
of the inhibition can be – reversible competitive, and irreversible,
mechanism-based. The values of inhibitory concentration 50 (IC
50
)
are calculated, which subsequently, after clarifying the mechanism
of action, recalculate the inhibition constants (K
i
– for reversible, K
I
and k
inact
– for irreversible inhibition). So far, the processes are not
complicated to perform. According to the guidelines for studying
drug interactions, basic static models are used to evaluate the
potential of the new drug to cause drug-drug interactions (DDIs).
However, in addition to the inhibitory constant, it is necessary to
know the plasma concentration of the drug, in the case of plant
extracts and fractions, because of the many substances in them,
which is a problem. Alternatively, each plant extract exhibiting
inhibitory potential on CYP3A4 can be tentatively calculated for the
potential for herb-drug interactions with substrates of enterocytic
CYP3A4 isoenzymes, using the basic static equations, where plasma
concentrations are exchanged with concentrations in GIT, namely:
[ ]
1
g
i o
o i i
I
AUC CL
AUC CL K
= = +
where AUC
i
and AUC
o
are the values of the areas under the
curves with inhibitor and no inhibitor respectively, CL
i
and CL
o
are
the values of clearance with inhibitor and no inhibitor respectively,
[I
g
] is the concentration of inhibitor, in this case the plant extract in
the gastrointestinal tract, and K
i
is the enzyme inhibition constant
by reversible competitive inhibition. The inhibitor concentration
in the intestinal lumen, [I
g
], was calculated as follows: [I
g
] = Taken
dose of the plan extract/250 ml. 250 ml is assumed to be the
volume in which the entire dose is dissolved, and this dissolution
is immediate. In addition, it is suggested that the full dose becomes
available for intestinal enzymes. Consequently, it provides a high
result for [I
g
]. In other words, worst case scenarios are considered.
However, how can we evaluate the risk of HDIs which have
affected hepatocyte cytochrome enzymes, without resorting
to in vivo studies? Using in silico techniques, could we simulate
pharmacokinetic behavior in the body and determine the potential
for herbal extract-drug interactions? This is the right way, in the
case of pure substances. Next steps involve using mechanistic static
models or more comprehensive dynamic PBPK (Physiology-based
ISSN: 2641-2020 DOI: 10.33552/APPR.2019.02.000540
Archives of
Pharmacy & Pharmacology Research
Opinion Copyright © All rights are reserved by Kaloyan Georgiev
*Corresponding author: Kaloyan Georgiev, Department of Pharmaceutical
technologies, Faculty of Pharmacy, Medical University “Prof. Dr. Paraskev
Stoyanov”, Varna, Bulgaria.
Received Date: November 06, 2019
Published Date: November 21, 2019
Kaloyan D Georgiev*
Department of Pharmaceutical technologies, Medical University, Bulgaria
This work is licensed under Creative Commons Attribution 4.0 License APPR.MS.ID.000540.