India’s pharma segment is expected to grow to $120-130 billion by 2030. However, this growth assumes that progress grows at a stable pace. How do we ensure this?
Data analytics is the answer. The need of accessing large volumes of big data has now taken the front-seat in the pharma segment. With patents for drugs expiring, companies face huge losses which affect their balance sheet. In 2020, patent expirations were expected to cause a global loss of $17 billion. Coupled with this, the cost of bringing in new drugs with their clinical trials is on an everlasting hike.
Clinical Trial
Due to the rise in demand for personalized medication and orphan drugs, clinical trials remain a significant area within the pharma segment. Fueled by the coronavirus pandemic and prevalence of chronic diseases, clinical trial procedures have increased their focus on developing preventive measures and vaccines.
Clinical trials are costly, time-consuming and success is not guaranteed. Data analytics address these concerns by taking the variables of time, labor, and error out of the equation. Predictive analytics software is the most widely used data analytics tool, which allows pharma companies to assess trial operations, procedures, and their success rate. Data analytics also aids patient selection for clinical drug trials by assessing one’s biological and demographic factors to save costs. Possible negative effects of trial drugs can be eliminated without ever even having to administer them.
Marketing and Sales
India’s pharma segment’s market has been estimated to reach $52.61 billion by the end of 2028 – and a major contributor to this hike is attributed to data analytics. The more that a company is visible, the higher are its chances of stayed ahead of market competition.
Digitized marketing has taken over, and it ensures optimal market shares. In terms of productivity, data analytics yield precise and empirical information in the following areas:
To analyze sales rates depending on demographic data. Products can then be marketed according to customer preferences.- To uncover new sales opportunities.
- To plan customized strategies for the promotion of drugs, depending on the analysis of past statistics about the receptivity of customers. By identifying the needs of clients, consumer behavior can be predicted.
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Data analytics also enhances the efficiency of salespeople. The sales rates of different territories are measured, which provides insight into which sales team is the most productive. Based on their performance, pharma companies can develop training programs to address areas that need improvement.
R&D and Drug Discovery
Global expense on R&D in the pharma segment is expected to rise from $188 billion in 2020 to $233 billion in 2026. To keep this up, companies need to opt for cost-effective solutions in areas like drug development, marketing, and clinical trials. Especially with the increase in patent expirations, the industry must be able to quickly search through large volumes of data to cut costs in drug discovery.
Data analytics contribute to R&D by identifying different molecules and compounds, predicting their reactivity, etc. Similar trends are highlighted by sorting through hundreds of researches, without excess labor, time, and money that would have been invested without data analytics. Pharma giants such as AstraZeneca and Janssen Research and Development have entered a data-sharing scheme called Project Data Sphere. This is a global database that utilizes data analytics to provide companies with access to information to help R&D develop new strategies of management and prevention.
Compliance with Regulatory Bodies
Regulatory bodies have become stringent due to the health-safety prioritization of pharma customers. Restrictions on drug production, their transfer, and retail storage have hiked. While these are done to account for sustainable and safe operations, it makes the job of pharma companies a lot more difficult.
Data analytics makes compliance to such regulatory bodies much easier. It assesses potential risk factors and provides real-time updates – which allows companies to plan subsequent management strategies. By using business intelligence tools such as interactive dashboards, pharma companies facilitate faster communication between interdependent departments. Areas that are in danger of violating regulations can be managed via faster-decision. According to the Physician Payments Sunshine Act of 2010, penalties can go up to $15,000 for each payment that is not reported. To avoid such errors, data analytics need to be integrated into the framework of companies now.
Looking Ahead
By focusing on customized marketing, data consolidation, compliance, and clinical trial operations, data analytics successfully shapes the pharma segment. While the adoption of data analytics may have its own sets of challenges, pharmaceutical companies must understand its necessity in today’s competitive market. Data analytics is the only way to maintain pharma’s projected growth.