In many health data analytics companies, Biomarkers are playing increasingly critical roles in the development of new drugs in early-phase trials. This blog is meant to introduce clinical investigators to the fundamentals of choosing a biomarker test for use in an early phase trial. Some steps to consider are briefly outlined including defining the role of the biomarker in the early phase trial are: Errors in Measurement, Bigotry, Astounding, Price and Acceptability. Continue Reading: http://bit.ly/38TbC2H Contact us: UK: +44-1143520021 US/Canada: +1-972-502-9262 India: +91-9884350006 Email id: sales.cro@pepgra.com Website: www.pepgra.com

1. Copyright © 2020 pepgra. All rights reserved 1
Practical Guidance for Biomarkers into Early Phase Clinical Research
Purposes
Dr. Nancy Agnes, Head,
Technical Operations, Pepgra
Sales.cro@pepgra.com
In-Brief
Healthcare data analytics solutions provide
a powerful approach to understand the
spectrum of disease with applications in
observational and analytic epidemiology,
screening and diagnosis randomized
clinical trials, and prognosis in the clinical
research organization. Causes of
measurement errors of
biomarkershttps://www.pepgra.com/what-
we-do/clinical-biostatistics-statistical-
programming/ differ with the individual to
the laboratory. Discussing problems that
affect the biomarker analysis along with
recommendations on how to concern with
bias and confounding. This Pepgra blog
review describes the concerns before using
biomarkers in clinical investigation.
Keywords:
Healthcare Analytics Services, Healthcare
data analytics services, healthcare data
analysis, healthcare analytics, healthcare
data analytics, Healthcare Analytics
Solutions, healthcare data analytics
solutions
I. INTRODUCTION
Biological markers are “cellular,
biochemical alterations that are accountable
in biological media such as human tissues,
or fluids.” the definition broadens as an
indicator of normal biological processes, or
pharmacological responses, pathogenic
processes to a therapeutic
intervention. Biomarkers include tools that
can aid in understanding the prediction,
diagnosis, progression, cause, regression, or
outcome of therapeutics of disease. In the
nervous system, there is a wide range of
techniques that gain information about the
brain in a healthy and diseased state.
Healthcare Analytics Services may involve
measurements directly on biological media
or sizes such as brain imaging which do not
include a direct sampling of physical media
using Clinical trial Monitoring Services.
Generations of physicians, epidemiologists,
have used biomarkers, and scientists to
study and treat human disease. The benefits
of biomarkers in the diagnosis and
management of cardiovascular disease,
immunological and genetic disorders,
infections, and cancer are well known. The
neuroscientists have relied on biomarkers to
assist in the diagnosis and therapeutics of
nervous system disorders and to investigate
their cause. The rapid growth of cellular
biology and laboratory has expanded using
the application of technically advance
biomarkers. Molecular biomarkers will be
in clinical investigators, provide a dynamic
and powerful approach to understanding the
spectrum of neurological disease with
obvious applications in analytic
epidemiology, diagnosis, and disease
management, clinical trials and disease
prevention.

2. Copyright © 2020 pepgra. All rights reserved 2
II. PRACTICAL CONSIDERATIONS
BEFORE USING BIOMARKERS
 Errors in Measurement
Improper measurement of the biomarker
would naturally lead to low validity of the
relation to the disease. There are many types
of errors other than those errors that occur in
the cellular laboratory. Problems for
transporting the specimens to the laboratory
can alter the measurement of the biomarker.
Storing samples improperly or changes in
storage surroundings can also disturb the
size of biomarkers. Technicians handle most
of the specimens, and so appropriate training
of personnel is there. Finally, receipt and
control errors such as in the transcription of
identification numbers if done by hand can
always be a source of error. A well-
organized procedures manual outlining the
details for documentation, storage,
monitoring of specimens and maintaining
records, can alleviate many of these issues.
The laboratories in an institute, the quality
assurance and quality-control program
conduction to reduce measurement errors
with Clinical Biostatistics services.
 Bigotry
Healthcare data analytics services evade the
bias that occurs in any study, with the help
of biomarkers. When biases arise without
regard to the outcome, so-called
nondifferential bias, the effects on the
survey are less severe but favour the null
hypothesis of no association. Problems
occur when the availability of the biomarker
is differentially related to either the disease
or exposure of the specimen acquisition,
storage, measurement, or specific
procedures differ with the disease compared
to those without the disease. Differential
biases tend to favour an association in either
direction; the real relationship has a high
response rate from all cases and controls
have maintenance. The investigators should
have an objective review board review and
monitor the conduct of the study, observing
possible biases in subject participation or
specimen ascertainment to reduce such
biases for pharmaceutical regulatory
consulting services.
 Astounding
Astounding is the failure to identify factors
that may change the measurement of the
biomarker. It can be internal, the weight of
the subject, or external, a batch of laboratory
kits used. Individual properties of
biomarkers should influence the choice and
interpretation for its inclusion in any
investigation. The effects of confounders
like age, gender, diet, and other metabolic
factors must have examinations before
initiating the study. Biologic stability is
critical mainly if the biomarker storage for
any length of time. Banked serum or plasma
is of great value in any review unless it
affects the pharmacologic properties of the
biomarker in the healthcare data analytics
services.
For example, some nutrients such as
vitamins do not store well because they are
light-sensitive. Storage of all tissues,
including lymphocytes and extracted DNA,

3. Copyright © 2020 pepgra. All rights reserved 2
can be expensive, and the evaluating
stability of the biomarker if storage needed
for extended intervals. These are often
overlooked in the analyses and can seriously
affect the outcome. One should use data on
potential confounders when designing the
study and collect relevant internal and
external information that might affect the
measurement of clinical study design,
including the analysis of the relation
between the biomarker and the outcome of
interest.
 Price
The choice of the biomarker for research
should be guided by the scientific question
and by the financial resources. Cost is
always a concern. In a small clinical trial,
this may be important; if an epidemiologic
study includes thousands of subjects, the
price can be quite high unless the laboratory
procedure is automated and relatively
simple. In fact, for some investigations,
larger sample sizes can bring down the cost
per subject. It generally implies that the
biomarker is readily available, and its
inclusion in the study is feasible. For
example, automated procedures have made
the inclusion of lipid profiles in clinical
studies of stroke quite possible. Methods
have improved to the point that a “finger-
stick” can provide the necessary amount of
blood. Healthcare data analytics works
depends on the type of investigation,
researchers should have an idea of the false-
positive or false-negative profile of the
biomarker.
As might be expected “false positives”
create extra work regardless of whether it is
a biomarker of exposure, susceptibility, or
disease. “False negatives” increase the
overall cost of the study. Tolerance for this
problem depends on the funding available
even in therapeutics of clinical research.
 Acceptability
Healthcare data analysis service provides
data from biomarkers of human tissues or
body fluids, the choice of biomarkers are not
trivial. Biomarkers possess some degree of
risk. In Healthcare Analytics Solutions the
clinical trials, that is less a concern because
the patient will possibly benefit from the
“new treatment.” In quasi-experimental
studies, the source of the biomarker may be
critical. Body fluids, such as blood and
urine, are usually well tolerated.
However, biopsy and collection of
cerebrospinal fluid is more complicated and
associated with slight risks. Risk-benefit will
be an issue for the investigator to resolve.
Pilot studies are always beneficial for
convincing institutional review boards that
your research is safe and that the risk-benefit
ratio favours a benefit for biomedical
research.
III. CONCLUSION
Many studies using biomarkers never
achieve their full potential because of the
failure to adhere to the same rules that
would apply for the use of variables that are
not biological. The development of any
biomarker should precede or go in parallel
with the standard design of any
epidemiological project or healthcare
analytics protocol and the formal
investigations listed in this Pepgra blog.
REFERENCES
1. Dobbin, K. K., Cesano, A., Alvarez, J., Hawtin, R.,
Janetzki, S., Kirsch, I., ... & Zhang, J. (2016).
Validation of biomarkers to predict response to
immunotherapy in cancer: Volume II—clinical
validation and regulatory considerations. Journal for
immunotherapy of cancer, 4(1), 77.
2. Gazerani, P. (2019). Current evidence on potential
uses of MicroRNA biomarkers for migraine: from
diagnosis to treatment. Molecular Diagnosis &
Therapy, 23(6), 681-694.
3. Mayeux, R. (2004). Biomarkers: potential uses and
limitations. NeuroRx, 1(2), 182-188.