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Methods to Detect, Predict,
and Prevent Adverse Drug
Reactions in Pharmacovigilance
and Clinical Practice
JereyPradeepRaj, NithyaJ.Gogtay,
andSuparnaChatterjee
16
Abstract
The fundamental principle in any drug approval
process is that the drug’s perceived benets outweigh the risks at the population level. However,
post-marketing authorization, adverse drug
reactions (ADRs) abound in clinical practice as
individual-level factors vary. Further, the number of subjects on whom a drug is tested during
the process of drug development is relatively
small and thus continuous monitoring is warranted. This is undertaken through the process
of pharmacovigilance, which is dened by the
World Health Organization as the science and
activities related to detecting, assessing, understanding, and preventing adverse effects and
J. P. Raj (*)
Division of Clinical Pharmacology,
Department of Pharmacology, Kasturba Medical
College, Manipal, Karnataka, India
Manipal Academy of Higher Education,
Manipal, Karnataka, India
e-mail: jpraj.m07@gmail.com
N. J. Gogtay
Department of Clinical Pharmacology, Seth GS
Medical College and King Edward Memorial
Hospital, Mumbai, India
S. Chatterjee
Department of Pharmacology, Institute of
Postgraduate Medical Education & Research,
Kolkata, India
other medicine/vaccine-related problems. This
chapter outlines the various study designs of
post-authorization safety studies used to identify ADRs andthe various challenges in detecting ADRs. This chapter also summarizes the
various strategies to predict and prevent ADRs
in clinical practice andby other meanssuch as
pharmacogenetics, use of omics, and in silico
approaches including articial intelligence.
Keywords
Adverse drug reactions · Post-authorization
safety studies · Pharmacovigilance study
methods · Risk factors · Pharmacogenetics ·
Omics · Articial intelligence ·
Preventability · Predictability
Learning Objectives
• To understand the various methods used in
pharmacovigilance for detecting adverse drug
reactions (ADRs)/pharmacovigilance study
methods.
• To list the challenges in identifying/diagnos-
ing ADRs.
• To describe various methods and strategies to
predict, prevent, and manage ADRs.
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
J. Jose et al. (eds.), Principles and Practice of Pharmacovigilance and Drug Safety,
https://doi.org/10.1007/978-3-031-51089-2_16
369
370
Key Points
• ADR is any response that is noxious,
unintended, and which occurs at doses
normally used in humans for prophylaxis,
diagnosis, or therapy of disease or for the
modication of a physiological function.
• Before the drug is approved, it is
exposed only to a few patients in a controlled research setting and a drug is
approved based on its perceived benets
over the risks at a population level rather
than at an individual level. On the other
hand, ADRs abound in routine clinical
practice and post-authorization safety
studies help identify ADRs in real-world
setting.
• The strategies for the prediction and
prevention of ADRs include genomics, metabolomics, proteomics, transcriptomics, epigenomics, and in
silico approaches including articial
intelligence.
• Management of ADRs includes early
detection, symptomatic and/or specic
management, documentation, followup, and monitoring.
1 Introduction
Benets and risks are two sides of the same coin,
and there really is no medication that can be
claimed to be devoid of adverse effects. The fundamental principle in a drug approval process is
that the drug’s perceived benets outweigh the
risks at the population level, and this permits the
marketing of the drug. However, in clinical practice, routine monitoring for adverse effects at an
individual level is warranted as safety data generated in pre-approval phases are insufcient and
need to be constantly updated with real-world
safety data for estimating risks associated with
drug usage. The process of continuous monitoring of a drug for its safety is called pharmacovigilance which is derived from the words pharmakon
J. P. Raj et al.
(Greek word for drug) and vigiliare (Latin word
to keep watch) [1].
Monitoring of adverse drug reactions (ADRs)
has become more important than ever before,
given the rapidly growing complexity of therapeutics (biologics, biosimilars, and novel vaccines to name a few), an aging population, and the
presence of comorbidities leading to polypharmacy. What once started off as a branch of science
that deals with the safety of a small number of
drugs has now widened its scope to include herbals, traditional and complementary medicines,
biologics, vaccines, and even medical devices [2,
3]. Of late, specialized branches of pharmacovigi-
lance programs such as hemovigilance that deals
with the surveillance of blood and blood products
[4] and materiovigilance that deals with medical
devices have gained importance globally [5].
ADRs abound in routine clinical practice and
can be something as simple as nausea, vomiting,
or gastritis associated with antimalarials that can
be easily treated to something more sinister such
as warfarin-induced bleeding leading to intracranial hemorrhage and even death. While mortality
and morbidity can be appreciated by the patient
and prescriber alike, there are signicant nancial costs associated with ADRs that impact the
patient, hospital, insurer, or society and also
impact the physician–patient relationship [6]. A
successful pharmacovigilance program is one
that can predict, minimize, and mitigate mortality
and morbidity. The withdrawal of drugs such as
pergolide (for Parkinson’s disease) due to
increased risk of cardiac valvulopathy and pemoline (for attention-decit hyperactivity disease)
due to hepatotoxicity are some examples of a
successful pharmacovigilance program. Had it
not been for the continued monitoring for safety
after its marketing, these important adverse
events may not have been picked up [7].
Hence, this chapter aims to outline the various
study designs of post-authorization safety studies
(PASS) used to identify ADRs and the various
challenges in diagnosing ADRs. This chapter
also aims to summarize the various strategies to
predict and prevent ADRs such as pharmacogenetics, use of omics, and in silico approaches
including articial intelligence (AI).
16 Methods to Detect, Predict, and Prevent Adverse Drug Reactions in Pharmacovigilance and Clinical…
371
2 Detecting Adverse Drug
Reactions/
Pharmacovigilance Study
Methods
ADRs can be detected at various levels. Since
most of the adverse reactions are likely to be
detected after the drug is marketed, PASS
becomes very important and forms a signicant
part of a drug’s pharmacovigilance life cycle.
These can be dened as “any study relating to an
authorized medicinal product conducted with the
aim of identifying, characterizing, or quantifying a safety hazard, conrming the safety prole
of the medicinal product, or of measuring the
effectiveness of risk management measures”.
These are noninterventional with the primary
objective of collecting safety information beyond
clinical trials and can also be used to assess drug
utilization [8].
The following are the various pharmacovigilance methods employed to evaluate drug safety
[9, 10]:
1. Passive surveillance
(a) Spontaneous reports/spontaneous reporting
The International Council for Harmonisation of Technical Requirements
for Pharmaceuticals for Human Use
(ICH) has dened spontaneous reporting
as “an unsolicited communication by a
healthcare professional or consumer to a
company, regulatory authority, or other
organization (e.g., a national pharmacovigilance center) that describes one or
more adverse drug reactions in a patient
who was given one or more medicinal
products and that does not derive from
a study or any organized data collection
scheme” [11]. This form of reporting
to detect ADRs forms the cornerstone
of many national pharmacovigilance
systems worldwide and can be both
paper-based or electronic. Though the
modality is passive, it is a low-maintenance, cost-effective approach that has
picked up several ADRs of consequence.
Reports from individual patients are
called as Individual Case Safety Reports
(ICSRs) and help identify early warning
signals, especially to newly introduced
medicinal products [12]. An example
of a well-known spontaneous reporting
system is the “Yellow Card” reporting
system from the UK regulator that collects information not just about medicinal products but also about devices. This
is available in both paper and electronic
versions including a Yellow Card app.
The system was established in 1964, and
patients are also able to report ADRs
effective from2005 [13]. Cough induced
by the angiotensin inhibitors captopril
and enalapril is an example of an adverse
event picked up through analysis of
spontaneous reports [14].
(b) Case series
It is a series of case reports reporting
the same event spontaneously in at least
two or more patients. They are useful in
generating hypotheses rather than for
testing association or causation of the
event with the medicinal agent.
2. Stimulated reporting/targeted spontaneous
reporting
This system of stimulated reporting is
identical to the spontaneous reporting system
except this is drug-specic or with a focus on
drugs for a certain disease condition (e.g.,
antiretroviral therapy) and is also at times
called targeted spontaneous reporting [15].
Targeted spontaneous reporting was introduced by the World Health Organization
(WHO) in 2010 and uses the same principles
and methodology as spontaneous reporting
except the specic focus of the former.
Although this method increases the rate of
ADR reporting, it is not devoid of the usual
drawbacks of passive surveillance such as
underreporting and incomplete information.
An example of this method is the identication of nephrotoxicity in patients receiving
antiretroviral therapy, specically tenofovir in
Uganda [16]. This methodology led to both a
vefold increase in overall reporting of ADRs
372
J. P. Raj et al.
for all antiretrovirals and identication of one
suspected case of nephrotoxicity per 200
patients treated with tenofovir.
3. Active surveillance
In an active surveillancesystem, a continu-
ous pre-organized process is established as
an attempt to ascertain the total number of
adverse events. For instance, patients prescribed a specic drug may be followed up
using a risk management program wherein
they may be asked to complete a brief survey
and sought permission to be contacted at a
later time as well. For instance, brexanolone
(Zulresso) has a risk evaluation and mitigation
strategy program as this drug when given as
per its approved mode of administration of
continuous IV infusion over 60h for postpartum depression can cause some people to faint
or even lose consciousness. The regulators
too, many a times, recommend the innovators
to propose a risk management plan (RMP)
detailing the commitments of post- marketing
pharmacovigilance with an aim to identify
safety signals that continue to emerge early in
the post-approval phase [17]—e.g., bedaquiline (antituberculosis drug) RMP.
(a) Sentinel sites/sentinel surveillance
Here, a sample of sentinel sites are
selected, and active surveillance is
achieved by thoroughly interviewing
patients and/or pharmacists/physicians or
by reviewing medical records in order to
ensure accurate and complete reporting of
ADRs. The advantages are that the data
from specic patient subgroup may be
collected and information on the use of
certain medicinal products with a potential for abuse could also be targeted.
However, the disadvantages are the small
number of patients, selection bias, and
increased cost. Therefore, this type of
active surveillance with sentinel sites
works efciently in an institutional setup
where certain drug products are used in
higher frequency, for example, drugs used
in ICU such as colistin.
(b) Cohort event monitoring and prescription
event monitoring [9, 18]
Cohort event monitoring (CEM)is a
system of pharmacovigilance which is
often used following the approval of a
new drug or vaccine to identify signals
or adverse events not picked up during
the clinical trials due to a limited sample size. Essentially, CEM studies select
a dened group of individuals (e.g.,
those who have received a COVID-19
vaccine) or a drug and prospectively
monitor them after dening a specied
time interval for follow-up. The initial
visit captures demographic data and relevant medical information—for example, medication history, comorbidities,
past history of drug allergy, and the
like. The studies are observational
(noninterventional) and form safety
assessments in the early period after
marketing. Participants in these studies
are followed up at predened intervals.
Adverse events that occur are collated
regardless of causality. The method is
based on prescriptionevent monitoring
(PEM) that originated in the 1970s, but
the only difference between the two is
that the enrollment into the CEM is
done by the physician directly, whereas
in the PEM it is through the prescription details provided by the pharmacists/pharmacies. Here, patients are
identied via electronic prescriptions or
health insurance claims. A predened
questionnaire is sent to patients and/or
the prescribing physicians at prespecied
time intervals to obtain outcome information such as clinical events, reason for
discontinuation, ADRs, and likewise.
The disadvantages are the unfocussed
nature of data collection that can obscure
important signals, difculty in maintaining patient condentiality, and poor
response rates to the questionnaires sent.
However, the main advantage is that
more detailed information on adverse
events may be collected from a large
number of patients and physicians. The
methodology is also used by the WHO
for safety monitoring for drugs used in
16 Methods to Detect, Predict, and Prevent Adverse Drug Reactions in Pharmacovigilance and Clinical…
373
public health programs. The WHO has
published handbooks for the conduct of
these studies in the elds of HIV/AIDS,
malaria, tuberculosis, and even for
COVID-19 vaccines. Studies of this
nature have the advantage of both a
numerator and a denominator and thus
give us incidence rates of adverse
events. Multiple adverse events can also
be picked up during the course of the
monitoring. However, these studies can
become difcult if the drug of interest
is an orphan drug, as an adequate sample may be difcult to come by.
Similarly, rare outcomes may still be
missed if the cohort is not sufciently
large.
(c) Specialist cohort event monitoring stud-
ies [19]
Specialist cohort event monitoring
(SCEM) studies involves a cohort of
patients from the hospital and secondary
care settings who have been prescribed a
particular medicinal agent to be monitored for ADRs. It also allows concurrent
monitoring of a comparator cohort of
patients on standard of care or another
counterfactual comparator group depending on the research question. These studies are proposed with a preamble that the
study population is usually under the care
of specialists due to their complex health
situation in terms of comorbidities,
underlying disease severity, and concurrent medications when compared to a
general population that gets treated in primary care. An example of an SCEM study
is the ROSE study—Rivaroxaban
Observational Safety Evaluation, where
specialist healthcare professionals from
the Cardiovascular Specialty Group,
Non- Malignant Haematology Speciality
Group, and Stroke Research Network
were invited to participate.
(d) Registries [10]
There are two types of registries that
collect data on patients; product registries
that focus on a specic product or drug and
disease registries that focus on a specic
disease—for example, aplastic anemia or
glomerulonephritis. Both these registries
are extremely useful sources for drug
safety for the simple reason that the population enrolled is far more heterogenous
than the homogenous population that is
enrolled in regular clinical trials.
Information in product-specic registries
should record the maximum amount of
variables for suitable inferences to be
made. These could be apart from dose,
duration, and start and stop date information on whether a branded or generic product was used or the nature of the excipient
which would make it product- specic. For
example, the adjuvants of interest in
COVID-19 vaccines are polyethylene glycol (PEG found in mRNA vaccines) and
polysorbate 80 (present in the AstraZeneca
COVID-19 vaccine). This will give an
indication of the diversity of adverse
events with the two vaccines and also help
make comparisons. If details of unvaccinated patients who are similar in characteristics are available in such registries or
other nation-wide large databases, then it
would help by giving an indication of the
baseline/background risk of a certain condition, for example, Guillain–Barre syndrome [20]. This also enables the
calculations of the “odds” of these specic
adverse events. These registries thus provide real-world data on a wider population
by keeping the selection criteria broad and
inclusive. Registries can similarly be
established for biologics, biosimilars, and
devices. The variables of interest here
would be different, for example, production batch, device identier, the company
making the biosimilar, and so forth.
Proportions of both total adverse events
and specic adverse events seen would
help sample size calculation for future epidemiological studies as well as for similar
products.
4. Comparative observational studies [10]
These are the traditional epidemiological
study designs centered around the time of
exposure and occurrence of the outcome/event,
374
J. P. Raj et al.
namely, cross-sectional, case–control, and
cohort studies, which are discussed in detail in
Chap.9.
5. Targeted clinical investigations
At times, after the marketing approval has
been obtained, further clinical studies may be
planned to delineate the mechanism of action
of an ADR, especially when signicant risks
are identied in the pre-approval clinical trials. These studies may include pharmacokinetic, pharmacodynamic, or pharmacogenetic
studies. With the growing emphasis on personalized medicine and dose individualization, these clinical investigations are gaining
importance and are utilized in modeling studies such as the population pharmacokinetics
or physiology-based pharmacokinetics studies with the main goal of maximizing therapeutic benet and at the same time minimizing
safety concerns. These studies are more useful in establishing potential risks or unforeseen benets in special populations such as
children, the elderly, or those with renal or
hepatic impairment who usually get excluded
from the traditional clinical trials. This category of studies also includes the drug–drug
interaction studies as well as the food–drug
interaction studies that are also conducted
with an aim to minimize ADRs due to concomitant drugs or specic food intake.
6. Descriptive studies
These studies are used to estimate the
background rate of ADRs that occur in a specied population that uses a specic drug.
(a) Natural history of disease
This includes the study of the natural
course of the disease such as the distribution of the disease in the said population,
characteristics of a diseased patient, treatments used, and the adverse events or
favorable outcomes encountered. For
example, a natural history of disease
study could be conducted in a certain disease registry in a specic sub-population
of patients such as those with comorbid
illnesses like cardiovascular diseases and
estimate the background incidence rate of
ADRs. Similarly, in the pharmacovigi-
lance of vaccines, knowing the background rates allows to perform observed
(adverse events reported) versus expected
analysis, as a method to continuous and
proactive surveillance [20].
(b) Drug utilization studies
The WHO denes drug utilization
studies (DUS) as “studying the market-
ing, distribution, prescription, and use of
medicinal products in a society, with special emphasis on the resulting medical
and socioeconomic consequences” [19].
Thus, DUS can be used to determine if a
medicinal product is being used in a specic sub-population or a special population and, if used, what are the ADRs
encountered in that population.
3 Identifying Adverse Drug
Reactions inClinical Practice
Many a times, patients themselves can pick up
early warning signs of ADRs and report them to
their treating physicians, provided the physicians
adequately communicate with their patients on
what to expect and bring it to their attention. In
addition, any new complaint that the patient
reports must be considered as a potential
ADR. Practical methods of identication of
ADRs in clinical practice to facilitate their early
identication are to identify and monitor patients
at high risk of ADRs, monitor for clinical signs
and laboratory parameters, keep a high level of
suspicion, and consider ADRs as a differential
diagnosis. This would be aided by a thorough
review of the patients’ medical and medication
history, ordering necessary laboratory investigations and, wherever appropriate, subjecting the
patients to drug dechallenge and/or rechallenge.
However, the responsibility of identifying an
ADR is not merely conned to the treating physician and the patient, but to thewider care team
including pharmacists, staff nurses, and caregivers.
With advances in science and technology, the identication of ADRs also includes various advanced
methods such as the use of trigger tools, tracer
drugs, and coding of diseases/events that ag
potential ADRs [21, 22].
16 Methods to Detect, Predict, and Prevent Adverse Drug Reactions in Pharmacovigilance and Clinical…
375
4 Challenges inDiagnosing
Adverse Drug Reactions
In clinical practice, prescribers tend to remain better informed about the perceived benets of prescribed drugs rather than their risks, especially if
such ADRs are rare and not likely to beserious.
ADRs are classically described as “Type A” reactions called augmented reactions and can be predicted based on the drug’s pharmacology. These
can be prevented or at the least mitigated by identifying a susceptible cohort of individuals (e.g.,
patients at extremes of age) and tailoring an appropriate treatment plan along with effective communication. The “Type B” or the bizarre reactions are
the ones like anaphylaxis that are unpredictable
and potentially cannot be prevented [23]. Type A
ADRs are akin to the pharmacological effects of
the drug and may pose diagnostic difculties when
they resemble the disease for which it is indicated
[23]. For example, arrhythmias occurring in
patients on digoxin may be either drug-induced or
due to the underlying disease, i.e., heart failure for
which digoxin was prescribed. Similarly, many a
times, patients do not report the common, mild, or
nonserious ADRs to their prescribing physicians
[24]. This is more so with Type A ADRs which are
merely an extension of the pharmacological activity of the drug prescribed, for example, constipation following opioid use and dry mouth following
the use of anticholinergics.
On the contrary, for Type B reactions, which
are bizarre or unpredictable reactions, a strong
clinical suspicion is the basic tenet in the detection of ADR, for instance, the recent identication
of adenovirus vector-based COVID-19 vaccineinduced thrombosis with thrombocytopenia syndrome [25]. Furthermore, the diagnoses of
immunological ADRs like acute exanthematous
generalized pustulosis which is reported to occur
rarely with some antimicrobial drugs like betalactam antibiotics and macrolides are often indistinguishable from the indication for their use [26].
Similarly, some neurological adverse effects seen
with high doses of antiseizure medications like
phenytoin may be indistinguishable from the disease for which it is being prescribed [27]. Thus, a
thorough knowledge of the safety prole of drugs
is important for all the stakeholders involved in
patient care, especially in the diagnosis of idio-
syncratic and immune-mediated ADRs. With the
advent of several biologics and small molecules
with complex therapeutics, establishing a causal
association needs consideration of several additional issues.
Though infrequent, we also encounter situations where multiple drugs can cause similar
ADRs. A common example is when a patient on
antituberculosis drugs develops hepatotoxicity.
The suspect drugs can be isoniazid, rifampicin,
and pyrazinamide singly or in combination. It is
well known that theoretically all these drugs can
cause liver injury, but all of them may not be the
suspect drug(s) in a given patient [28]. Establishing
causality in such scenarios is often challenging
mainly because withholding drugs which may not
be causally related is indeed undesirable.
Similarly, diagnosis of ADRs in special populations and settings also needs careful consideration. For example, it is often difcult to diagnose
ADR in neonates and infants or critically ill
patients with altered consciousness. Such patients
(neonates and unconscious patients) are unable to
communicate, and it is likely that diagnosis of an
ADR may be delayed or missed unless there is a
strong clinical suspicion. This is because most
ADRs detected in such settings need to manifest
as abnormalities in investigational parameters or
present as overt clinical signs.
5 Predicting andPreventing
Adverse Drug Reactions
It is estimated in several studies that the median proportion of preventable ADRs-related admissions to
hospital was 3.7% (range 1.4–15.4). The drugs commonly implicated in these hospital admissions
include diuretics, nonsteroidal anti- inammatory
drugs, antiplatelets, and anticoagulants. These four
groups of drugs account for a little more than 50%
of all the drug groups that are associated with preventable drug-related hospital admissions [29].
The nature, frequency, and severity of ADRs
can be diverse, ranging from innocuous, frequently occurring ones like skin rash, nausea, and
vomiting to life-threatening or fatal rare events
like ventricular arrhythmias or Stevens–Johnson
syndrome. Since any organ or biological system
can be the target of adverse effects of drugs, the
376
J. P. Raj et al.
act of identifying and predicting such risks is one
of the most challenging tasks. Though complex,
efforts to identify ADR and its predictors are initiated in the early phases of drug development and
continue well beyond approval stage. The strategies to identify predictive factors include invitro
and invivo nonclinical studies such as computational tools of simulation and modeling, AI-based
approach in the early stages of new drug development [30], and active and passive safety surveillance in the post-marketing phase. Complex
predictive models and algorithms are often formulated, but often their clinical applicability becomes
limited as the extent of contribution of a predictive
factor for a drug of interest is not uniform and may
demonstrate signicant interindividual variability.
Additionally, assessment of any risk associated
with drugs entails identication as well as quantication of risk compared to the background rates
of such events. Unless comprehensive information is available about background rates, quantifying the risk attributable to a drug is not feasible
or scientically sound. A thorough understanding
and consideration of risk factors for ADRs is very
essential in preventing ADRs to the best way possible. The same should be considered while prescribing medications, dispensing, administering,
patient education, and monitoring of patients. A
detailed discussion on predisposing factors for
ADRs is included in Chap. 3.
5.1 Methods to Predict Adverse
Drug Reactions
1. Pharmacogenomics to predict ADRs.
2. Omics approaches to predict ADRs in drug
development practice.
(a) Metabolomics
(b) Proteomics
(c) Transcriptomics
(d) Epigenomics
3. In silico approaches and use of articial intel-
ligence to predict ADRs in silico techniques in
drug safety assessments are as follows:
(a) Structure-related data
(b) Drug target and pathways
(c) Drug-induced gene expression proles
(d) Phenotypic features from primary cell
cultures
1. Pharmacogenomics to predict and prevent
ADRs
Several ADRs that occur in clinical practice can be anticipated and prevented or at
least their impact mitigated. The role of pharmacogenetics/pharmacogenomics in predicting drug response has transformed from being
a mere research tool to one that guides and
shapes clinical practice. Pharmacogenetics is
the study of how individual genetic variations
impact the drug response whereas pharmacogenomics deals with how the genome as a
whole with simultaneous multiple mutations
may determine a patient’s response to drug
therapy [54]. Despite the restricted availability of such testing in resource-limited settings,
their utility in predicting some ADR risks has
been well documented. In countries where
such screening facilities are readily available, the Clinical Pharmacogenetics
Implementation Consortium (CPIC) guidelines-based prescribing has reduced the occurrence of these ADRs [55].
Specic examples of the use of pharmacogenetics to predict and therefore prevent
ADRs are discussed as part of Chap. 23.
2. Omics approaches to predict ADRs in drug
development
Omics refers to the study of the sum of specic constituents in the cell. These constituents
could be proteins, metabolites, or genetic material. It is a scientic discipline that aims to
understand biological systems at a molecular
level [31]. Omics technologies provide a comprehensive view of the biological effects of
drugs on different biological systems and
therefore have the potential to signicantly
improve our understanding of drug safety both
in the drug development stage and in the postmarketing phase [31]. Although these omics
technologies offer a great potential to understand drug safety, they are not yet extensively
applied in routine clinical practice. Some
important types of omics are described below.
(a) Metabolomics
It is the study of small molecules called
metabolites such as the carbohydrates,
amino acids, fatty acids, or other by- products
of metabolic function found within the cells,
biouids, tissues, or organisms [32].
16 Methods to Detect, Predict, and Prevent Adverse Drug Reactions in Pharmacovigilance and Clinical…
377
Metabolomics helps to investigate toxicities
due to drugs and xenobiotics. As a result of
drug metabolism, three types of metabolites,
namely, active, inactive, and reactive metabolites, are produced. These reactive metabolites can bind to normal cellular
macromolecules such as the DNA or cellular proteins and disrupt the homeostasis.
These reactive metabolites are also unstable,
unpredictable, and thus are sometimes difcult to be detected using regular technology
if not for metabolomics [33]. Thus, metabolomics can be used to predict ADRs in the
early phases of drug development as well as
to predict etiopathogenesis of ADRs of old
drugs and their likelihood to cause the
ADR in a patient. One such example is
the use of liquid chromatography and
mass spectrometry-based metabolomics
approach in screening the bioactivation
pathways of ritonavir, a protease inhibitor
used in the management of HIV infection.
Ritonavir frequently causes hepatoxicity
and metabolomics helped to identify 26
metabolites of which 5 were reactive [33].
(b) Proteomics
It refers to the large-scale study of
genome- wide proteomes. Proteome is a
complete set of proteins produced by the
organism post-translation based on the
genetic makeup [32]. The subspecialty of
proteomics that deals with toxicity due to
drugs and xenobiotics is called as toxicoproteomics. The principle is that a specic
group of xenobiotic will bring about a specic pattern of protein expression that
would aid in predicting the ADR/toxicity
[34]. An example of the successful utiliza-
tion of proteomics in ADR prediction was
that of a novel lipid-lowering agent, torcetrapib, a cholesteryl-ester transfer protein
inhibitor used in the ILLUMINATE trial
conducted among 15,000 patients at high
risk for coronary heart disease. The study
was abruptly stopped after a median followup of 550days due to reports of an increased
cardiovascular event in the intervention
arm. A subsequent retrospective study by
Williams etal. analyzed paired plasma samples (baseline and 3-month post-
intervention) using aptamer-based arrays
and identied a signicant increase within
group, in nearly 200 proteins, including
proteins functioning in the aldosterone
pathways, inammation, and immunity
pathways post-intervention in the torcetrapib group when compared to the control
group. Thus, the authors were able to identify the likely deleterious plasma proteins
that were responsible for torcetrapib-associated increased cardiovascular events [35].
(c) Transcriptomics
A transcriptome is a complete set of
RNA transcripts that are produced by a
genome. As per the central dogma of biology, the process of transcription produces
the RNA from the DNA followed by the
process of translation which produces the
required proteins necessary for biological
action from the RNA. Thus, transcriptomics is the study of transcriptome both
qualitatively (the types of RNA present,
RNA editing sites, identication of novel
splicing sites, etc.) and quantitatively (the
number of each transcript that is present)
using high throughput methods [32].
ADRs are often related to immunological
features, as many drugs or metabolites can
interact with major histocompatibility
molecules, and these associations have
been detected in the early genome-wide
association studies of ADRs. An example
of the use of transcriptomics in pharmacovigilance was in the understanding of the
mechanism of peroxisome proliferators
clobrate and gembrozil causing hepatotoxicity in rat liver cells in comparison
with an enzyme- inducer phenobarbital,
and there were striking differences in the
RNA transcripts suggesting novel mechanisms of hepatotoxicity [31, 36].
(d) Epigenomics
It is the study of the genome-wide epigenetic modications found on the genetic
material of the cell. These are reversible
modications of the DNA or the DNAassociated proteins such as histone acetylation, histone deacetylation, DNA
methylation, DNA demethylation, and
likewise [35]. Although currently there is
378
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much evidence that suggests differential
response of certain diseases to drug therapies based on epigenetic changes, none
have yet obtained a regulatory approval to
be incorporated in routine practice. Some
examples include hypomethylation of the
CYP2E1 gene promoter in the CNS being
associated with Parkinson’s disease, prostate cancer with methylation levels at
CYP1A1 and CYP1B1, and colon cancer
with CYP2W1 [37]. It is further hypothesized that some iatrogenic ADRs such as
drug-induced lupus and tardive dyskinesia
are epigenetic in nature [38]. For instance,
hydralazine is known to inhibit DNA
methylation which is believed to cause the
drug- induced lupus-like syndrome [39].
3. In silico approaches and use of AI to predict
ADRs [40–42]
Traditional clinical trials cannot identify
all serious ADRs because of genetic factors,
nongenetic factors, and ethnic diversity of
patients who are enrolled in clinical trials. In
contrast to traditional toxicological studies,
the in silico method is an innovative and
highly efcient technique to evaluate the toxicity and hazards of drugs. In silico modeling
is an organ-on-a- chip technology that
employs applied computer, omics, and mathematical biology, which can provide complementary knowledge of specic biological
interactions and pathway analysis of the
potential response of an organism to a chemical stressor [42]. In silico approaches have
become a part of the drug discovery pathway
that includes target protein identication,
chemical library screening, and toxicity
assessments using machine learning
approaches. The in silico technique and computational pharmacology can be used to
repurpose existing drugs to understand their
pharmacological effect. They may be useful
in improving clinical use and preventing
potential ADRs[42].
In silico approaches often use principles of
AI wherein a machine simulates human intelligence processes like learning, reasoning,
and decision-making. Some commonly used
types of AI in predicting ADRs are machine
learning and deep learning. Machine learning
is the science and study of algorithms that
depict mathematical models derived from
available sample data to make predictions or
decisions, but the machine itself is not programmed to perform that task directly. Deep
learning is a subset of machine learning where
there is a neural network across multiple layers of transformed data to extract higher-level
information/features from raw data. Deep
learning simulates the function of the human
brain [43].
Some approaches and applications of in
silico techniques in drug safety assessments
are as follows:
(a) Structure-related data
In-silico technique is an overriding
approach involved in the assessment of
drug toxicity based on their quantitative
structure–activity relationships [44]. In
silico modeling can be used in predicting
severe cutaneous adverse reactions
(SCARs) by deep learning. It is considered a useful technique to assess the association between the chemical substances
and SCARs [45].
(b) Drug target and pathways
The technique includes the identication of ADR-related proteins that are used
to predict ADRs based on existing literature on known drugs and their ADR prole. The known information regarding
ADR- related proteins is compiled in databases such as the Drug-Induced Toxicity
Related Protein Database (DITOP) and
the Drug Adverse Reaction Target
Database (DART) which are in the public
domain. In silico drug target search
approach (INVDOCK) was a helpful
technique for predicting ADRs of 11 marketed anti-HIV drug interactions with
related proteins. INVDOCK- predicted
ADRs of these drugs were consistent with
the literature-reported ADRs. This
method proved that 86–89% of all predicted ADRs were consistent with known
anti-HIV drug ADRs.
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