Express Pharma

Pharma’s path forward: From driving drug launches to improved patient outcomes

Subhro Mallik, SVP and Global Head Life Sciences, Infosys emphasises that an end-to-end ecosystem enabling data orchestration and meaningful is essential to drive true digital transformation across the life sciences value chain and enhance enterprise-wide performances

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The healthcare and life sciences ecosystem is rapidly evolving under the influence of various environmental factors. The commercial ecosystem for pharma companies is increasingly complex and interlaced with multiple dependencies influencing care management decisions. Therefore, decision-makers must consider complex data sets to make more precise and timely decisions.

Data proliferation in life sciences is happening faster than the time taken by the industry to consume the data and draw meaningful insights. Pharma companies have invested heavily in large data warehouses and building pipelines to ingest external data. Yet, they have managed to build disconnected data platforms at best. They must still rely on considerable manual intervention to interpret the data and put it to real use. The problem is exacerbated by the lack of a one-size-fits-all solution to address this challenge of managing commercial data.

Current challenges in commercial operations

When drug launches do not go as per plan, there is an impact on productivity. When a drug is introduced, pharma companies are hampered by lengthy onboarding processes and the need to buy data from multiple sources. They must also build point solutions and reporting engines for each brand. These investments force pharma companies to stretch their budgets often without achieving desired returns and satisfactory brand performance.

Drug launches can be long-winded. The company must navigate countless complexities of regulation, cost, and intense competition stemming from speciality therapeutics. As the patient population is typically small and spread out for pharma companies, they need an end-to-end insight platform that can handle these challenges while being flexible enough to repurpose existing investments of clients. Despite years of studying the drug, its potential market, and strategic planning, more than a third of newly launched drugs tend to underwhelm in terms of sales performance. This could be because of factors such as incorrect targeting of patient population or ineffectiveness in measuring field sales performance KPIs.

It makes sense for pharma companies to work on building an effective data marketplace and understanding end-user well ahead of a drug launch. Plus, they need the data discovery process to enter a self-service mode to speed up their insights and innovation capabilities. While several commercial insights solutions exist, they are isolated and limited to providing partial truths that result in costly investments without actually addressing the larger problem. The data they get is not the data they need.

Closing the data-to-insights gap for new drug success

While pharma companies have invested in various technology capabilities, an end-to-end ecosystem enabling data orchestration and meaningful insights eludes them. Such an ecosystem will help commercial teams do more with less while driving agility, innovation, and real-world data focus to improve patient outcomes. A single version of the truth is essential to drive true digital transformation across the life sciences value chain and enhance enterprise-wide performances so that they get insights that are faster and adaptable to their unique needs.

Such an ecosystem must be guided by:

  • Real-world data: Studies show that the more mature and effective the field force, the greater their contribution to sales performance. The right data can help drive patient outcomes, optimise commercial spend, and improve forecasting and effectiveness of the field force, which remains a vital promotional channel. Companies also recognise the need for better market segmentation and understanding of customer needs.
  • End-user-centricity: Data onboarding time can be shortened by identifying specific commercial personas that are targeted in the drug launch and understanding their needs. This will facilitate better collaboration and communication of patterns and other user insights between brand marketing, commercial operations, data scientists, and other partners involved.
  • The collective power of the ecosystem: Leveraging insights and capabilities from pharmacies, buyers, suppliers, and other ecosystem players can help build an effective commercial insights solution. This can help right from data discovery to democratisation to enhancing patient outcomes and boosting the drug’s commercial acceptance. Overall, this gives pharma organisations a greater chance of success.

Currently, life sciences companies are experiencing complex patient journeys, which call for tech interventions to deliver value along the continuum of care. End-users too increasingly prefer virtual communication channels that facilitate specialised disease conversations. Therefore, the uni-dimensional approach of driving business through field forces has morphed into a more segmented approach that leverages multiple channels to capture target users. Personalised and omnichannel engagements are required and therefore, data must be captured along all user touchpoints to stitch the narrative together.

A drug launch remains a pivotal event for pharma. Its success involves multiple factors such as market insights, access to patients, understanding of prevalent market forces, and competitor intelligence. All of these must align and contribute to the strategic planning of the roll-out. Robust tech capabilities backed by comprehensive advanced analytics capabilities can help address these evolving needs and enable the success of new drugs.

 

References

https://www.technologyreview.com/2022/02/15/1045405/streamlining-pharma-drug-launches-with-data-and-analytics/

https://img1.wsimg.com/blobby/go/1651eb46-a148-4180-836e-3cb99822cb3e/downloads/Mentor%20Group_WP_Field%20Sales%20Force%20Effectivenes.pdf?ver=1626130082785

 

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