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Data Secrets to A Successful Drug Launch

Ankur Gupta, Sr. Product Marketing Manager, Reltio

Value from pharma should be measured in terms of clinical outcomes, patient satisfaction, and cost reduction. Using data, pharma companies can enhance value for patients along the entire lifecycle of a drug, from drug discovery to commercialization to end of exclusivity.

From the perspective of business strategy, value delivery can be seen as a three-step process as illustrated by David Ormesher, CEO of closerlook, in his PharmExec.com post.

  • Value Creation (discovery)

  • Value Capture (commercialization)

  • Value Extraction (end of exclusivity)

Discovery Phase: Value Creation via Data

It is important to capture unique customer insight to inform drug innovation. The drug should be relevant (to an urgent disease burden) as well as differentiated (relative to alternate therapies). These two factors will largely determine market access, provider endorsement and patient acceptance for a new drug. However, departmental silos between medical affairs and commercial side of the business, and lack of access to quality data lead to incomplete understanding of competition and the market.

A Self-Learning Data Platform goes beyond a traditional master data management (MDM) offering and brings together patient, provider, payer, and plan data from internal, third party, and public sources to cleanse, match, merge, un-merge, and relate in real time. Platform’s multi-domain data organization capability helps perform deeper analysis to better understand the needs of patients, providers, payers, and relationships among these players. A Self-Learning Data Platform breaks down silos among medical affairs, marketing, business intelligence and manufacturing, and helps develop a common understanding of customer data and market insight across all departments.

Research indicates that 81% of future drug sales performance is determined by actions taken during clinical development and early commercialization phase. It’s even more critical for a pre-commercial pharma which is planning to bring its first drug to the market. Early adoption of a Self-Learning Data Platform helps a pre-commercial pharma develop future-proof commercial infrastructure and put up business processes to launch their first drug with safety, efficacy, and desired formulary placement in place. Read the pre-commercial pharma success stories about how they successfully launched their first drug with the help of a Self-Learning Data Platform.

Commercialization Phase: Value Capture via Data

A new product’s commercial performance during the first six months after FDA approval is often considered a very important indicator for how the product will do over the course of its patent life. During Value Capture or commercialization phase, the purpose of data is to build trust and respect via data-driven personalization and engagement. However, pharma companies are unable to recognize prescribers and patients consistently across multiple channels and touchpoints. They often fail to increase content speed to market in their customers’ preferred channel. This leads to negative Net Promoter Score (NPS), increased defection to competitors, and loss of revenue and market share.

The more you know about your customers – the physicians who can write the product – and what they care about, the more you’re able to build an effective campaign around a new product. What you need – an out-of-the-box, data-driven affiliation management application, with built-in MDM, for managing all relationships within and across HCOs and HCPs to support commercial operations, identify the right key opinion leaders (KOLs), and understand their influence.

A Self-Learning Data Platform helps you organize launch as a micro-battle (See the Infographic “Make Your Drug Launch Truly Take Off”, Bain Insights, September, 2017), gather continuous front-line feedback from sales reps before, during and after the launch, and make rapid adjustments as needed to the launch strategy. It helps you make quick decisions on messaging, targeting and marketing investments. Such platform powers reliable advanced analytics by enabling master data profiles and graph relationships to be seamlessly combined with real-time interactions and analyzed in Spark. For example, when a new drug is launched, it helps track sales performance compared to projections so that you can adjust strategies whenever needed.

Read the success story of a French multinational pharmaceutical company that built Customer 360 on top of a Self-learning Data Platform to support their account-centric field operations and personalized engagement.

Loss of Exclusivity Phase: Value Extraction via Data

At the point when a drug loses its patent protection, its price typically drops quickly as generic competitors enter the market. During this phase, there is often enormous pricing pressure from competitive products and health insurers. In addition to these external pressures, there is also internal competition for attention and resources, usually from a promising new product.

The business strategy during Value Extraction is to increase efficiency via operational excellence. The main cost now is sales and marketing. This is where digital can play a very strategic role. Digital sales and marketing through non-personal promotion can become an effective substitute for sales rep promotion. By replacing expensive personnel costs with lower cost digital channels, we can reduce overhead costs but still maintain market share.

Read the success story of one of the oldest and largest global pharma that consolidated customer profile across all business functions to improve customer experience across all digital touchpoints, and better engage high-value customers.

Successful pharma companies use data as a competitive weapon to develop new sources of differentiation, focus on building superior customer experiences and treat drug launches as a micro-battle. How did your last launch perform vs. expectations, and what were the reasons for under-performance or over-performance? Which interactions matter most for your target physicians, and do you provide a superior customer experience? What are the three largest internal challenges your launch team faces, and what would it take to eliminate them?


Patient 360: Molecule to Market

Ankur Gupta, Sr. Product Marketing Manager, Reltio

The rise of the Chief Patient Officer and the “P–suite” emphasizes a commitment to a culture around patient-centricity across life sciences companies. Patients are becoming increasingly demanding and taking greater control of their own healthcare decisions. They expect all relevant parties like pharma, providers, and payers to collaborate and recommend the best treatment options.

It is essential for a pharma company to know their patient throughout the drug discovery, development, and commercialization process. Every department across a pharma company can contribute toward and benefit from complete patient understanding. Some of the use cases are:

1. Patient-centric Drug Discovery and Development

Recruiting and retaining the right patients, and capturing all interaction and transaction events during clinical trials are vital to continuously develop new diagnostics and treatments. Patient-centric clinical operations lead to improved clinical trial outcomes, reduced patient exposures to drug adverse events, and faster drug discovery.

Today, reliable data, relevant insights and recommended actions via machine learning can be combined into one, single cloud application, delivering analytical intelligence and operational execution. Such cloud based Patient 360 data-driven application helps pharma companies derive meaningful patterns from an ever-expanding volume of patient health data and incorporate those insights into the drug development processes. 


A Patient 360 application built upon a self-learning data platform delivers reliable, and up-to-date 360-degree views of patients, and their relationships with providers, healthcare organizations, caregivers, payers, plans, products and places, driving seamless omnichannel patient experience and improved health outcomes.


2. Personalized Corporate and Marketing Communications

Pharma companies are increasingly seeing more value in reaching out patients more personally and directly to improve patient loyalty and brand recognition. They want to execute direct-to consumer (DTC) drug advertising campaigns, deliver educational insights (such as medical information and pharmacovigilance) to inform patient decision-making and behaviours, and encourage patients to contribute their medical data to help advance medical knowledge.

A true Patient 360 data-driven application helps with prospect identification, capture, synchronization to CRM, and segmentation and targeting of existing customers and prospects in various life-stages. As part of the patient centric approach, brand-focused marketing is juxtaposed with the creation of content that supports a patient’s journey through disease progression. In addition, the Self-Learning Graph helps solve the problem of “householding” by grouping patients into family units by uncovering relationships. This patient-centric approach helps pharma companies to gain “profitable share” in competitive markets by informing their ‘pricing and contracting’ strategy and identifying treatable patients. 

3. Superior Patient Experience with Full Compliance in Place

Pharma companies can add far more value to patients by executing adherence programs such as tracking drug usage and benefits. Likewise, they can run affordability programs to help patients stay on therapy (e.g. by creating apps to educate patients or by reminding them about medications). However, to drive such initiatives, one needs to collect and use large amounts of sensitive health-related data of patients. A modern data organization platform helps you respect and protect patient HIPAA and data security concerns. In addition, it helps you be GDPR compliant and allows patients to provide granular consent for sharing their data.

The data forms a key part of the insight needed to create better products and services, better engagement, adherence, and relationships with patients. Changing business models, expectations of “patient of one” and newer regulations will accelerate the evolution of pharma and healthcare. The transition will not be easy, but building a reliable Patient 360 with ability to pivot around pharma, provider, and payer is the first step towards patient-centricity.

Get ‘IDMP Ready’ with Modern Data Management

There is no better time than now for pharma & medical device companies to modernize their product information management and comply with IDMP (Identification of Medicinal Products). Non-compliance might result not only in hefty penalties (as high as 5% of annual EU gross revenue) but also in poor operational efficiencies. Experts advise to kick-off the IDMP initiative now and reconfigure the data model later when the final guidelines are published by EMA (European Medicines Agency), FDA (Food & Drug Administration) or other similar regulatory body.

IDMP is a set of five ISO norms which has been developed in response to a world-wide demand for internationally harmonized specifications for medicinal products. Following a phased implementation process, pharma & medical device companies will be required to submit data on medicines and medical devices to EMA in accordance with these formats and terminologies. The implementation of the IDMP standards will help achieve operational savings for these companies as well as improve the health and safety of the human population.

Product information in pharma & medical device companies is distributed across several departments or lines of business in a myriad of different systems, authored in different formats, in multiple languages, and different terminologies. Harmonizing this data within a single organization itself is a big challenge, but doing so across the continents and coming up with common standards is a daunting task. It is for these reasons, the timelines for implementations of IDMP standards have been changed a few times. This valuable grace period should be utilized by these organizations in planning and preparing for this ambitious, enterprise-wide initiative.

As per the EMA, the underlying challenge of IDMP is fundamentally a Master Data one. EMA’s approach to implementing the ISO IDMP standards is based on the four domains of master data in pharmaceutical regulatory processes: substance, product, organization and referential (SPOR) data. Pharma & medical device companies that would be regulated as per the IDMP standards by the EMA, should be right now actively getting a handle around where is their product data scattered within their enterprise, and how they would manage it scientifically.

A Modern Data Management Platform allows you to create a strong underlying master data foundation for IDMP objects in the cloud as well as derive actionable insights from various data domains, their relationships, and the interactions among them by leveraging graph technology. It not only creates the reliable product data foundation but also offers flexible product hierarchies by markets, brands, segments and geographies that can be categorized, organized and analyzed from multiple perspectives.

It is extremely easy to write metadata based definitions of IDMP objects in an agile, real-time configurable data management platform. Not only can you start with the definitions of these objects as per the evolving IDMP standards, you can also extend these definitions over time based upon your varied business needs. You can create other objects over and above the IDMP objects, define relationships among themselves, and capture transactional data that will eventually provide valuable insights. Reference Data Management is yet another underlying capability of a Modern Data Management Platform that helps master reference data from multiple systems. In the world of IDMP, the reference data can be sourced from different systems. As an example, Global Substance Registration System (G-SRS) is one of the major source systems that implements and supports the ISO-11238 substance types and controlled vocabularies (CVs).

Last but not least, a cloud-based Modern Data Management Platform requires no on-premises installation, hardware or maintenance. Instead of buying servers, installing and patching software, and constantly wrestling with how to handle the relentless growth and diversity of data, your IT teams can focus on delivering relevant, operational intelligence to business users. Such platform is deployable in a fraction of the time and cost compared to the traditional MDM solutions, providing significantly faster time to value. Also, it provides fine-grained, attribute-level, visibility of who searched for, who looked at, and who modified what data, in logs that can be tracked and monitored for security and compliance.

Business leaders who can adopt a modern data management philosophy, program management teams that can help drive the project, and technology partners who can help implement specialty technologies, would need to come together to make full, organization-wide IDMP compliance a reality. Using a next generation data management platform for your IDMP implementation will not only reduce the time to compliance in a cost-effective manner, but it will empower your organization to create a futuristic data platform that will stay current. In addition, it will help you build new capabilities such as providing transparency to your consumers, facilitating acquisition of other products or companies, and identifying emerging product safety risks apart from meeting regulatory requirements and delivering cost savings.

If you enjoyed this post, please feel free to share the short video below

Data-driven Apps will Power the Next Generation of Pharma Marketing

This week, I was invited to present in front of a distinguished group of pharma marketing professionals at the recent Digital Pharma West conference held in San Francisco.

It’s clear that there continues to be significant interest by marketers to use data to help improve campaigns and outcomes. My presentation detailed how Pharma marketing is undergoing a tremendous change with new stakeholder and marketplace dynamics, with a more sophisticated consumer, and interconnected digital world.

Clearly the vast amount of information that marketers need to internalize to develop effective campaigns is simply daunting. Legacy IT systems set up to address repeatable processes are not able to scale to modern day demands, and contrary to popular opinion, standalone visualization and analytics isn’t a panacea either.  

In fact, a recent survey by Trailblazer research of marketing professionals highlighted the following reasons for their dissatisfaction of their existing marketing applications and processes:

  • Ease-of-use

  • Limitations surrounding customization capabilities

  • Lack of partner/vendor support

  • Lack of in-house expertise

  • Excessive costs

  • Difficulties surrounding implementation

It’s no wonder that marketers are crying out for linkedIn or Facebook-style enterprise data-driven applications equivalent to those that they themselves as consumers get to use on a daily basis.

In fact the survey further revealed some of the data management pain points preventing marketing teams from being agile and more targeted in their efforts, and their corresponding plans to address the issue:

Many of the 10 pain points can be addressed through a modern data management platform, that offers reliable data through master data management, big data, data-as-a-service, seamlessly fused with relevant insights with recommended actions through analytics and machine learning.

  1. Access customer data without IT or 3rd-party support

  2. Add new social or messaging channels quickly and with ease

  3. Analyze cross channel efforts to gain marketing insights

  4. Deliver consistent messages across all channels

  5. Deliver relevant, contextual messages to customers in order to create ongoing dialog

  6. Do A/B testing to improve email campaigns

  7. Integrate messages, data, and insights across siloed channels

  8. Turn unknown website visitors into identifiable prospect opportunities

  9. Use predictive analysis to improve marketing effort

  10. Use real-time data and insights to drive personalized next-best offers

During the session we also discussed what the future holds, including IoT and growing interest in data monetization

A lively panel following my presentation offered further insight from experienced pharma marketing executives appropriately titled “OK, So Pharma Is Now Successful at Data Aggregation, So What? How to Take an Applied Approach to Leverage Data in a Meaningful Way: Using Data to Meet Objectives.”

The panel was moderated by Nuvan Dassanaike , Vice President, Lead, Global Integrated Marketing at Mylan and included: 

  • Bill Keller , Vice President of Marketing , Acadia Pharmaceuticals

  • David DeJonghe , Worldwide Director of Marketing, Digital Solutions and New Product Development , Lifescan, a Johnson and Johnson com

  • John Vieira , Senior Director, Global Brand Strategy, Edoxaban , Daiichi Sankyo

Being data-driven may sometime be deemed an overused term, but for marketing professionals in pharma, it’s very much becoming the norm. If you would like a copy of my presentation or to exchange thoughts on how data is the new lifeblood of life sciences, please send me an email or leave a comment below.