+1.855.360.3282 Contact Us

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?

Read more Pharma Commercial Success Stories

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.

Efficient & Compliant Business with Trusted Reference Data Management (RDM)

Reference data, a subset of master data (lower in volume, variety and volatility), is generally uniform, enterprise-wide and often created by external standardization bodies. Let’s say your customer’s address is a part of a master data record, then the Zip Code and State fields are reference data. It is the kind of data you will find in dropdowns and lookups–restricted values that you can choose from within a field on a form.

The value of reliable reference data cannot be undermined. Due to the nature of IT application development and the reliance upon off-the-shelf application systems, reference data is all too often isolated in silos within many different systems. Inconsistent reference data across multiple systems can cause invalid transactions (state and zip code mismatches), revenue leakages (bad discount codes) and compliance risks (improper tax codes).

As a part of transactional records, reference data is grouped with associated master data and transactional data, and is needed for both operational and analytical master data management enterprise use cases to provide attributes, hierarchies and key performance indicators. Traditional mapping requires human judgment as well as manual synchronization and remediation of reference data. This is neither efficient nor reliable.

To ensure accurate reporting and analytics, proper governance and operational efficiencies, enterprises require a standardization system that makes it easier to define, map, manage and remediate reference data across the organization.

Reference data management is an integral part of Modern Data Management and needs to be a part of your data management strategy. Thinking about reference data in isolation or as an afterthought leads to expensive rework and compliance risks. Since Modern Data Management includes graph technology to establish relations across people, products and places, interesting capabilities result when combined with reference data. With the graph, reference data become pivoting attributes. For example, let’s say physician’s specialty is the reference data, as it needs to map to multiple systems and different physicians. Now speciality_code can be a pivoting attribute, which enables you to drill into a specialty to see the physicians across the organization, and other information relevant to the specialty. The graph makes such relationship management simple.


Today’s data management solutions need a user-friendly solution to define and manage reference data across multiple functional areas, industries and data domains. Whether customer, product or supplier data, Reltio Cloud RDM is a simple, business user-driven application that is adaptable to business needs across any use case required to preserve values and mappings between reference data sets–both in a domain and across domains.

Unlike other legacy MDM tools, that charge separately for basic RDM capabilities, Reltio Cloud Modern Data Management Platform as a Service includes core RDM functionality built-in. Being built-in makes it much simpler to ensure that there is consistent reference data for all downstream operational applications. By managing complex mappings among customer, partner, product and supplier data domains, and managing their interrelationships, enterprises will improve data quality and reduce compliance risk.


Governance of reference data is vital–manual or custom RDM often lacks change management, audit controls and granular security and permissions. Due to the complexity in managing and governing reference data, an RDM solution should include a seamless, intuitive user interface to manage lookups, and ensure data consistency across systems with version control, security and access controls. Reltio Cloud’s RDM facilitates remediation and improvement of reference data quality along with mapping to localized data, which helps with global harmonization. Built-in workflow capabilities, such reviews, approvals, history and audit trails help make structural changes to reference data with complete governance.


RDM data are often managed by business users who want to maintain, manage, standardize and remediate reference data at their fingertips. They need complete visibility into the “Crosswalks” for understanding data change impact. Collaborative curation of information through fine-grained workflow and governance allows cross-functional teams get the most accurate information real-time. Teams should be able to flexibly deliver information to downstream applications or provide access through embedded widgets within operational applications.


In many cases, organizations purchase or subscribe to third-party data sources for verified reference data. Lines of business want an easy way to connect to third-party reference data sources to enrich the existing data. Data as a Service within a modern data management platform lets you connect to such data sources, and merge the data with other master data for your data-driven applications.


A Modern Data Management platform lets you connect to existing MDM, operational applications and third-party data sources for real-time integration. User-friendly interfaces with import and export capability help map reference data sources quickly, and eliminate the burden of managing reference data sets. Reference data from multiple source systems require no transcoding, translation, custom code or IT involvement. Configuration, Lookup and Transcode REST APIs are available to manage reference data through integrations. A multi-tenant cloud platform ensures ease of provisioning and zero downtime upgrades. Deployed in the cloud, you will be delivering value faster than ever possible without the overhead of managing the infrastructure for this highly critical and available data.

Mona Rakibe is a Director of Platform Product Management at Reltio. She’s an expert in data management technologies with a specialty in content management and BPM, having worked for companies such as EMC, Oracle and BEA Systems.

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

Why did a Horizontal Modern Data Management Provider Invest in HITRUST CSF Certification?

Last month Reltio announced HITRUST CSF Certification in a press release. While this wasn’t exactly headline news it was significant for our customers and partners, present and future in the Healthcare and Life Sciences Industries (HCLS).

The foundation of all HITRUST programs and services is the HITRUST CSF, a certifiable framework that provides organizations with a comprehensive, flexible and efficient approach to regulatory compliance and risk management. In the same week John Houston, VP of security and privacy and associate counsel, at the University of Pittsburgh Medical Center (UPMC ) sounded an alarm in an article “UPMC Security Chief Sounds Warns Many Cloud Computing Vendors Lack Ability to Appropriately Secure Health Data” in which he calls upon cloud providers to be more transparent about their security offerings and to support standards such as HITRUST.

Developed in collaboration with healthcare and information security professionals, the HITRUST CSF rationalizes healthcare-relevant regulations and standards into a single overarching security framework. Because the HITRUST CSF is both risk- and compliance-based, organizations can tailor the security control baselines based on a variety of factors including organization type, size, systems, and regulatory requirements.

By continuing to improve and update the CSF, the HITRUST CSF has become the most widely-adopted security framework in the U.S. healthcare industry. This commitment and expertise demonstrated by HITRUST ensures that healthcare organizations leveraging the framework are prepared when new regulations and security risks are introduced.

Fundamental to HITRUST’s mission is the availability of the HITRUST CSF that provides the needed structure, clarity, functionality and cross-references to authoritative sources. The initial development of the CSF leveraged nationally and internationally accepted standards including ISO, NIST, PCI, HIPAA, and COBIT to ensure a comprehensive set of baseline security controls. The CSF normalizes these security requirements and provides clarity and consistency, reducing the burden of compliance with these requirements that apply to healthcare organizations.

Typically HITRUST has traditionally only been applied for, and awarded to Healthcare specific companies, whose sole focus is that industry and the handling of HIPAA and other patient-level compliant grade data. A search of HITRUST certification for legacy and cloud-based data management platforms yields no qualifying companies prior to Reltio.

Although Reltio is a horizontal Modern Data Management Platform as a Service, that is multi-tenant and industry agnostic, we have a significant number of HCLS companies who rely on us to manage and provide business facing application-level access to sensitive data. Over the last year, we have invested a tremendous amount in resources and cost to ensure that our platform compliance meets both industry and geographic-specific regulatory and compliance requirements. We anticipated the need for companies to want to use Reltio for data (e.g. Patient data) under HIPAA compliance, and were determined to go through the rigor and challenges to achieve full HITRUST CSF certification.

In conjunction we also appointed Peter Bierfeldt as Chief Information Security Officer (CISO), to lead customer security, privacy, validation and compliance efforts at Reltio. Peter has more than 20 years of industry experience, including leading complex, large enterprise IT programs and projects. He also has over 10 years of experience in the pharmaceutical industry, and has managed the global delivery of a multi-million-dollar IT program for a top 10 pharmaceutical organization.

With HITRUST CSF added to Reltio’s SOC type compliance, the growing roster of HCLS companies using Reltio Cloud can now confidently extend to sensitive data beyond what they were able to manage with other tools that are unable to provide this level of support.