Benefits of bringing Data Analytics:
By
bringing data analytics to the pharmaceutical industry, we are basically
putting to use the tons of data already accumulated with years of research in
the process of developing a new drug. Apart from putting the huge amounts of
data to use, data analytics can also solve some major shortcomings of the
industry.
· By
sequencing the already available data, the diagnosis of any disease can be done
much faster and accurately. Also, based on the failures faced in the previous
experiment, the same errors can be avoided while experimenting with a new drug
hence saving time and funds.
· By
knowing the market scenario for a drug like ‘Place of highest demand’, ‘Age
group of highest demand’, and ‘Economical status of people needing the drug’, the
production and distribution of the drug can be better regulated hence avoiding
its shortage or excess in any place.
· By
understanding the customers and market well, risk management becomes easy. The
predictability of success of failure of a particular drug can also be
accurately calculated thus ultimately saving funds spent in hit and trial.
· Various
models can be designed on the basis of different data available. These models
can be used to predict shortages or other failures that might occur in supply
chain.
Ground breaking change:
One
of the biggest bottlenecks faced by the pharmaceutical industry is the difference in response by different
human bodies to the same drug. A drug designed for treating cancer must be
effective on almost every cancer patient. The major amount of fund allotted for
research of a drug is spent on finding out the compound that works on major
percentage of the patients suffering from that ailment. Using the analysis of
data from various different researches, the probability of success of a
particular drug will certainly go up. The trick here is not only analysing data
from research facilities but also from various public and private hospitals as
well as clinics where the exact response of a patient to a particular drug is
minutely monitored. These changes will lead to:
1. Increased
collaboration
2. Predictive
analysis
3. Most
effective drug trials
4. Targeted
marketing and sales
Future Enhancement:
· Clinical
Trials – Patients could be specially identified
for clinical trials. The identification of a patient would not only be done on
the basis of their medical history but also their social media profile and
other places. Using data from places that would speak more about the lifestyle
of the person rather than only their medical profile.
· Integration
of data – Starting from the developmental stage
of a drug to its real world use, everything can be documented electronically on
a single platform. This is a huge step with regard to the pharmaceutical
industry because this will eliminate the possibility of error to a great
extent.
· Auto
generated reports – If integration of data
on a large scale is made possible, many softwares can then be designed to
generate reports in seconds that currently take years to be prepared. These reports
will reduce the time taken for a compound to become a certified drug and hence
increase its value.
· Collaboration
of internal and external teams – Because of the
risk inherent in the development of a drug, the research and development in
pharmaceutical companies is done with utmost secrecy. This leads to very little
or no communication between the R and D team and the marketing team. With the
arrival of data analytics, the R and D team can now work with the data compiled
on the basis of market surveys which will thus help them in conducting their
research better.
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Wouldn't it be a good idea to create a course?
