In today’s dynamic and quickly changing competitive battleground, pharma companies are scrambling to emerge on top and boost their performance without adding to their total cost of operations. The rise in innovative technologies such as artificial intelligence, robotic process automation, and big data analytics in the pharmaceutical industry requires pharma companies to innovate rapidly in order to gain a competitive edge and harness the opportunities in the market landscape.
The design and manufacturing of drugs generally take several years, lengthy clinical processes & huge costs. However, the industry has been snowballing recently.
The global pharmaceutical industry is projected to have a market worth $1170 bn by 2021, growing yearly at 5.8% since 2017. Americans alone spent 329 bn $ on prescription drugs in 2016 and are expected to have a market worth 25% of the global pharma market.
The Asia Pacific is showing strong growth trajectories with pharma sales in the Asia Pacific will grow by 8.4% in 2021 with India & China expected to grow by 10%.
Pharma data analytics and its supporting infrastructures- advancements in cloud computing, machine learning, etc. promise several cutting-edge innovations to deliver insights into pharma to formulate a fact-based strategy in the global market using big data analytics for the pharma industry.
Pharma data analytics offers several benefits to the pharmaceutical firms such as the ability to perform in-depth competitor analysis and monitoring and to improve the in-house processes with data-backed insights.
According to McKinsey, operating efficiencies attainable from scaling the impact of advanced analytics in the pharma industry range as high as 15 to 30 percent of EBITDA over five years, accelerating to 45 to 70 percent over a decade giving the potential impact of predictive modeling in discovering and optimizing new blockbuster therapies.
Drugs Market Top Sub-segment
Big Data Analytics In Pharma: Key Challenges
For pharma data analytics to become successful, pharma businesses need to be innovators and adopt technology early to utilize the benefits. There are significant challenges that need to be addressed before pharma businesses can begin to realize advantages with pharmaceutical data analytics.
Breaking down process silos & integrating siloed data to derive cross-functional insights.
Setting up the infrastructure to turn big data into smart data.
Capturing & utilizing unstructured clinical & medicine distribution data.
Deriving insights on the clinical trials data to create projections and report as per the investor requirements for funding.
Defining data privacy and engagement rules on customers' data.
# Proving the ROI on the initiatives is turning out to be a considerable challenge for many enterprises. Many pharma organizations are struggling to see the impact and ROI of their business intelligence initiatives.
Everyone is on board with the idea, its scope, and the benefits of pharma business intelligence. But not everyone is on board with a clear plan about how to get there.
#1. Accelerate Drug Discovery And Development
The cost to introduce a new drug into the market is skyrocketing and with the patents for blockbuster drugs expiring, the pharmaceutical industry is looking to accelerate this process of bringing a drug to market.
By sifting through vast datasets of scientific publications, academic research papers, control group data, and by running predictive algorithms through these immense swathes of data, pharmaceutical analytics can help firms make more intelligent decisions to accelerate the process of data discovery. Innovation in drug discovery is going to be a key strategy in leading to improved financial performance.
#2. Increase The Efficacy Of Clinical Trials
Big data analytics in pharma can help pharmaceutical businesses to reduce the cost and speed up clinical trials by identifying and analyzing various data points: such as the participants’ demographic and historical data, remote patient monitoring data, and by examining past clinical trial events data.
By optimizing this whole process & identifying test sites with high patient availability, pharma firms can use pharmaceutical analytics to speed up disease diagnosis and design more efficient control groups and clinical trials.
#3. Personalize & Create Targeted Medications
Every individual has a unique genomic makeup, and ideally, medicine should be personalized to everyone. However, it is challenging to use current biology and technology to handle complex data to make effective decisions.
Big data analytics in the pharmaceutical industry can solve this problem by combing through data of genomic sequencing, patient’s medical sensor data (the device that can be worn to track physical changes in an individual during treatment) and electronic medical records.
By effectively utilizing big data technologies to sift through unstructured genomic data, pharma companies can spot patterns to help create a more effective and personalized medication for their patients.
#4. Reduce Cost And Increase Drug Utilization
With increasing pressure on the pharmacy's operating margins, it becomes essential to increase the efficiency of the whole process. Granular analysis of key metrics such as average ingredient cost per prescription, rebate as a percentage of total drug spending, drug utilization review savings per member per year, will help pharmaceutical businesses make smarter decisions to increase revenue and reduce costs by using pharmaceutical analytics.
#5. Social & Search Engine Listening To Capture Data Of Interest
By scraping through internet data, pharma companies can tap into what conversations people are having online around, for instance, their product launch & similarly around their competitors.
This will help them understand how their product is being received. By capturing additional data that may include safety-related information from conversations on the internet, the information can be quickly sent to the concerned team to address in time so that the company’s reputation does not take a hit.
#6. Drive Effective Sales & Marketing Operations
By capturing key data points, pharma business intelligence can help new markets can be identified, and the efficiency of the different marketing channels can be analyzed to prioritize efforts and gain a competitive edge. It will help to understand the performance of sales reps; helping to make better & faster decisions.
This will help you to make effective capital and resource allocation decisions. By analyzing patient trends to identify new markets, adopting innovative technology, and big data analytics in the pharmaceutical industry, pharmaceutical businesses are witnessing increased effectiveness of their sales & marketing strategies.
#7. Streamline Compliance
With stringent government regulations increasing by the day, failing to adhere to the rules can open up civil & criminal lawsuits which can not only harm the drug maker’s reputation but can also result in making huge payouts to settle the charges.
With a complex & dynamic environment in which drugmakers operate in multiple geographies and complex legal environments, big data analytics in pharma can help quickly uncover insights to streamline governance decisions and highlight the gaps in the safety of current drugs.
Digital operations assistance on the floor can support human workers to manage their daily tasks and raise alerts, if any, to reduce the risk of compliance failures.
#8. Improving Operations & Employee Training
Pharma companies can significantly reduce their costs by improving their existing operations & processes with pharmaceutical analytics and data insights. By using advanced analytics, pharmaceutical businesses can understand how machine settings, operator training levels, or raw material inputs are going to affect the output quality.
It will inform pharma firms to make decisions to optimize and improve the whole process. By utilizing predictive analytics and big data analytics in pharma, external indicators, pharma businesses can predict risks such as quality issues, machine failures, or substantial changes in demand.
TODAY, WITH THE USE OF BIG DATA, MEDICAL ANALYSIS TO PREDICT CANCER RECURRENCE, PROGRESSION, AND RESPONSE TO THERAPY IS NO LONGER A TOUGH TASK.
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How Can Pharma Companies Ensure Success With Data Analytics?
To derive optimum benefits, a company-wide strategy to mobilize analytics is needed. Advanced analytics presents a significant & real advantage for pharma companies to gather data & build models for turning insights into impact at scale. But first, they must identify and prioritize how to invest their time, money & efforts.
There is a vast scope that remains unfulfilled today. This is for pharma businesses to adopt and make winning strategies with data. The scope of pharmaceutical analytics exists in every single function.
Break down data & process silos which can be the death knell for pharma business intelligence and big data analytics in pharma. Implementing agile use-case sprints with streamlined governance and implementing change management initiatives will be the key to success. Having the action is driven by the leadership that will help to effectively break down biases & prejudiced notions about the scope and role of analytics and tackle the naysayers
Find the right use cases, start small and onboard believers in your process. Get an executive to back your project. Show your ROI in the early stages by choosing wisely the right use case to target in the beginning. You will find that it will then become more comfortable over time to gather more supporters for your initiative and turn doubters into believers.
Polestar Solutions can help you to implement the right solutions in order to set up success with analytics. Our experts understand the typical problems faced by pharma companies and have deployed suitable analytics systems that help you derive impact from your data and deliver success on pharma data analytics use cases. Feel free to leave a comment below, we will get in touch soon.
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