Data Analytics in the Pharmaceutical Industry

The hope of the world is pinned on the pharmaceutical industry probably more than ever before in the COVID pandemic times. With new viruses surfacing every year, data plays a crucial role in drug and vaccine development. The data collected from COVID-19 hit countries like the recovery rates, intensive care requirement, number of deaths, and the total number of cases generate valuable insight into spread, recovery, affected demographic, and aided in administration.

There are multiple ways in which data can contribute to the healthcare and pharmaceutical industry; hence it becomes essential for every individual to understand its importance. Some of the prominent examples are discussed below.

Use of data in clinical trials

It has been observed that the healthcare industry doesn’t work on size fits all. During the clinical trials of medicine, data collected can be processed to generate insights on its outcome on individuals as per medical history, gender, age, and others. The medical practitioners need to look at the existing ailments and history of the patient before recommending any drug.

Having a system in place to track actual and existent ailments, and earlier prescribed drugs can generate a method to differentiate on individual treatment. Using big data analytics, the pharma companies can advise the physicians how a particular medicine would fit within an individual’s treatment plan.

Use of Data Across Pharma value chain

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Accelerate drug discovery and development

Companies and institutions, namely AstraZeneca, Celgene, Bayer, Janssen Research and development, Sanofi, and Memorial Sloan Kettering Cancer Center, started a data sharing under the name Project Data Sphere to share historical research on cancer to help researchers in finding better treatments against the disease.

Importance of data in COVID-19 treatment

With vaccines still in development phases, the shared knowledge and existing research on similar types of protein jacketed viruses proved to be instrumental in treating COVID-19 patients. The knowledge generated from processing the data on a series of related viruses like SARS, MERS, etc. helped in finding the medicine remdesivir, which saved the lives of thousands of chronic patients of COVID-19.

Other evolving treatments like plasma therapy helped in severe cases of the virus. The data collected on daily bases for active cases and death rates helped gauge India’s administrative response against the spread of the virus. The pro-active response in some states by collecting information on every incoming citizen and their immediate contacts kept the number of deaths incredibly low than other states.

Data became a useful tool to identify hotspot zones, most affected communities, aiding in narrowing down to check the spread of the deadly virus.

Location analytics proved to be one of the best tools; the government urged citizens to use an app to collect data of positive and unhealthy citizens and put a check in the spread of the virus, especially in countries like South Korea.

The government collected the data on the mobility of quarantined patients and found the virus’s primary source of spread. The app developed by the Indian government lets the user conduct a symptom-based check and make them aware of the active cases in their radius up to 2 km.

About the upGrad Program

The program is targeted at closing the skill gap in your enterprise and ensure a data-driven culture. The 6-week (48 hrs) blended program, designed for professionals from any background, will help your enterprise gain the necessary skills and knowledge to make data your lingua franca or second language. The program is also curated for different industries and helps in:

  • Building a Data Culture.
  • It enables them to seek the right information and collaborate.
  • Empowers your employees with tools, models, and techniques to make informed decisions.
  • Generate more value by increasing productivity, efficiency, and ultimately the profitability.

Industry leaders will deliver the program via live sessions, recorded sessions, self-learning lessons, and assessments explained with Illustrations. The program can be split into five key areas:

  • Program Orientation

Covers the overview of the program, platform walkthrough, and objectives of the program.

  • Data Science, Machine Learning, Artificial Intelligence: Genesis, Value and Future – Live

The industry leaders take the course beneficiaries on a journey towards data culture. They will briefly explain the existing technologies like Machine learning and AI. This will help your employees get an overview of the data lifecycle, data strategy, and design thinking with data.

  • Data Science and the Industry: e-Learning

In this, your workforce will understand the application and scope of data related technologies in your industry, be it BFSI, ITES, Manufacturing, Telecommunication, Oil, and Gas, and so on.

  • Data Analytics- Hands-on: e-Learning and Live

The most extended module of the course enriches the learning with tools and techniques by covering – Data analysis in Excel, Statistics and Hypothesis Testing, Exploratory Data Analysis, and Data Visualization.

  • Data-Driven Decision Making: Live Workshop

The capstone to the program is application based. Using a case-based approach, specific to the industry, the beneficiaries will be part of problem-solving in a real-world scenario.

Trials, patents, manufacturing, precision medicine, containing the spread, and many more- data collected throughout the pharma industry’s value chain can generate valuable insights and improve efficiency, time to market and prove to be lifesaving.  

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