By Jignesh Desai, WW Migration Solutions Architect – AWS
By Balaji Ramanujam, Head, Industry Architecture – Infosys
For a specialty pharmaceutical company, the launch of a new drug is of great importance for their commercial success.
Monitoring commercial operations is therefore a data-driven approach needing accurate and timely insights. Pharma companies depend upon data from third-party vendors and internal systems like enterprise resource planning (ERP) and customer relationship management (CRM) to get holistic insights.
During a product launch, data coming from multiple or new sources needs to be integrated quickly to understand things like sales trends, marketing costs, managed markets performance, financial metrics, competitor product performance through real-world evidence, health care professional (HCP) segmentation, and so on.
As COVID-19 continues to evolve at unprecedented speed and scale, the life sciences industry is at the epicenter of developing tests and treatments and getting them to the masses. Drug researchers around the world are scrambling to develop vaccines and other treatments in an attempt to slow the spread of the disease.
Thanks to artificial intelligence (AI) capabilities to crunch massive amounts of data in a short period of time, drug development pipelines that would normally take over a decade are being compressed into a matter of months.
The platform provides “one version of truth” that generates faster insights, can be rapidly customized for clients’ needs, and is scalable across new markets and business units across a pharma enterprise. It enables commercial teams with precision metrics, and provides the ability to deploy strategies to increase revenue at reduced cost.
This advanced data and analytics platform accelerates digital transformation across life science commercial operations, while helping to reduce the data onboarding cycle and deliver valuable insights using advanced analytical services.
In this post, we will explain the approach Infosys and AWS followed to develop the Infosys Life Science Insights Platform and its key components. Infosys is an AWS Premier Tier Consulting Partner and Managed Cloud Service Provider (MSP) that enables clients to outperform competition and stay ahead of the innovation curve.
Why the Platform is Beneficial
A report by Market Research Future (MRFR) expects the healthcare analytics market size to be worth $51.5 billion by 2027 at 23% CAGR. New-age analytic platforms allow templatization of data, reduce data lifecycle, and enable different analysis on the same set of data.
It’s normal to have corporate strategies that explicitly mention information as a critical enterprise asset and analytics as an essential competency. Enterprises need the capabilities to make analytics available not only to smaller groups of data scientists but also to data analysts who can perform their own analysis in a self-service fashion.
Varity in Data Sources
Data is the glue to pharma companies’ commercial ecosystem. Pharma companies are purchasing data more than ever, and this contributes to insights across all business functions. Brand teams and data scientists needs access to real-world evidences overlaid with existing sales data to make brand-specific plans.
Variety of Data Type
Commercial data processing involves different patterns of data, and it’s important to create a data processing template that can be reused across brands, business units, and commercial markets.
This platform is based entirely on self-service and configuration approach, which eliminates the need for custom-developed insights for each new drug launches.
Key Features of the Platform
Infosys and AWS decided to address these needs by building an end-to-end, cloud-native commercial analytics platform. It’s available as a fully managed services solution to help pharma customers navigate the complexity of persona-based KPIs and cost of ownership. The core platform provides a flexible subscription-based pricing model.
The Infosys Life Science Commercial Insights Platform enables agile, template-based data onboarding. It reduces overall onboarding time, uses artificial intelligence-based data quality rules for standardization, subject area-based models for data harmonization, machine learning-based alerts, and has a mix of standard and custom analytics to drive actionable insights along with a variety of consumption options.
All of these features enable multiple personas in commercial organizations to increase revenue and effectively calculate performance of different territories.
The platform provides various new-age consumption patterns (like KPI library) to generate actionable insights and measure field sales performance on various KPIs. Advanced analytics can be used to provide visibility on patient outcomes for rare oncology disease drugs, for example.
The use of AI/ML also accelerates innovation and opens up new frontiers such as disease detection and right interventions. Analytics for brand-specific roles can help in brand optimization, resulting in reduced time to actionable insights. Business users can query the data in natural language and use Amazon Alexa to monitor KPIs on the go.
The platform is built using AWS-native services such as Amazon Simple Storage Service (Amazon S3), AWS Lambda, Amazon EMR, Amazon QuickSight, Amazon Redshift, Amazon DocumentDB, AWS Step Functions, and Amazon Elastic Compute Cloud (Amazon EC2).
Encrypted channel of communication is used to access resources on the AWS Cloud with proper authentication and network access control.
Authentication and authorization are ensured using AWS Identity and Access Management (IAM), and network access permissions are granted by the native access control while accessing Hypervisor management console or other admin consoles by administrators.
The platform also ensures confidentiality and data privacy of clinical data (GCP) or patient safety data (PV), and leverages TLS/SSL protocols to ensure secure transfer post authentication.
Value Adds Across Commercial
Some of the value adds from the Infosys Life Science Commercial Insights Platform are:
- Drive richer real-world patient outcomes.
- Enhance commercial spend optimization.
- Improve patient and customer experience.
- Enhance forecasting.
- Real-time field force effectiveness.
- Optimize gross to net.
- Increase specialty drug sales.
- Reduce data onboarding time.
- Increase market share.
- Increase visibility into patients, hospitals, practitioners, and rare diseases while building a stronger, cost-effective pipeline for new drug releases.
The platform architecture is modular and guided by the following architecture components:
- All cloud-native services.
- Microservice-driven architecture.
- Intelligent data pipelines and ML-driven entity resolution.
- Metadata-driven data processing framework with prefabricated design templates.
- Unified platform for both structured and unstructured data analytics.
Figure 1 – Platform architecture.
The various architecture components are explained below:
- Capture and ingestion flow for template-specific data ingestion. Data from various industry-standard sources like Veeva CRM, SAP, MDM, IQVIA, Prometric, and Symphony Health will be received in raw zone in batch mode using AWS Glue, or in real time using Amazon Kinesis. This data will be moved to a landing zone using metadata-driven ingestion framework.
- Refine flow for UI-driven data standardization, curation, validation, and transformation. The platform has a rule-based as well as AI-based data quality check which will be applied to data. Only good quality data that passes stringent DQ rules will be moved to the curated layer. A number of aggregation rules will be applied to the curated data to make it consumption-ready. Not only the aggregated data but pass-through data direct from sources will be available in the semantic layer and to make consumption-ready.
- Semantic services consume KPIs directly from source or raw layer and frequently-used persistent KPIs. Recipe of data and KPI libraries for data transformations and KPI derivations will be available in the semantic layer, which can be customized and reused by users in self-service mode. Semantic services will have the aggregated data, but only the pass-through data directly from the source will be available for customization
- API services provide API-based consumption from the curated data store based on KPI metadata. New-age consumption patterns like natural language queries, API-based consumption, and analytical dashboards in Amazon QuickSight will enable users to consume data in various ways.
- Common microservices for audit capture, exception, asset catalogue, and workflow. The platform’s microservice-based architecture and common services like audit capture and exception handling and logging are available across all of the modules.
- Metadata and governance services capture various metadata and data lineage. The platform provides various services around data governance, data lineage, data security, and data encryption. It also captures metadata related to different modules in NoSQL database like Amazon DocumentDB.
- Data science toolsets for data scientists are available on AWS and allow data scientists to analyze and use raw and curated data for analytics use cases.
What makes the Life Science Insights Platform different from others?
- Cloud native: All of the platform components use AWS-native services.
- Persona-based advanced analytics: The platform has a mix of standard and custom analytics to drive actionable insights and value for various brand personas.
- Easily customizable: The platform can be customized for clients’ needs. All of the modules in the platform are loosely coupled, allowing clients to pick from a range of options. This includes the ability to get the whole platform, all the way to picking modular options per business needs and infrastructure compatibility.
- Open source: The platform is a combination of AWS-native services and open-source software. There is no need to buy any extra software license.
- Integration with Alexa: Platform is modularized and provides easy to consume Insights API which can be integrated with Amazon Alexa skills. This results in improving digital experience and productivity of field teams.
- Industry-leading MDM integration: This approach drives better customer data quality and improves model accuracy.
- Key data templatization: This approach follows life sciences industry standards for sales, calls, and claims, which is now more of a configuration than a build for a new product and one of the platform’s key differentiators.
- Data and technology partner ecosystem: This includes IQVIA and Snowflake to deliver data at lightning speed.
- Commercial model: Infosys’ componentized and industry-leading assets can be provided as open-source code through a BOT model and can differentiate from other vendors who run the platform as a black box.
Customer Success Story
The Infosys Life Science Commercial Insights Platform enabled a top pharma company to drive optimal returns on their commercial investments by integrating real-world data through agility, innovation, and scalability.
The pharma leader was struggling to manage drug launches because data coming from multiple sources makes it a complicated process.
In a rapidly evolving market, an average time of 4-6 months for launching a new product was a key concern for the client. At the same time, they required clarity and understanding of different data assets linked to their recently launched drug to be administered to patients.
Infosys and AWS jointly built a comprehensive suite of modular capabilities that are persona-based, cloud and AI-enabled, and available in a flexible subscription-based pricing model. We combined all enterprise customer, commercial, and real-time sales data available in single a data-lake on Amazon S3. This helped us simplify data processing using AWS Glue and AWS container services.
This enabled a platform for advanced analytics, such as demand forecasting and improved visibility on patient outcomes for cure. As a result, the solution improved average response time of insights by six-fold. A key to success was the combination of AWS coupled with Infosys’ expertise and in-depth industry knowledge.
Figure 2 – Customer transformation journey.
Infosys advanced analytics provided actionable insights to enable smart actions in the market by the sales reps.
Figure 3 – Capability quadrant.
Pharma companies are demanding more from their data and need detailed insights on drug outcomes. When it comes to advanced analytics, companies are rethinking how they can launch new drugs faster, proactively manage risk conditions, and monitor their commercial operations to keep drug prices low and focus on patient’s health outcomes.
Infosys brings a combination of deep domain, advanced analytics, real-world data, and technology expertise to drive enterprise transformation and specifically help commercial teams do more with less.
Infosys and AWS are collaborating to help pharma companies rethink the new drug launch delivery and sales operations. The Infosys Life Science Commercial Insights Platform enables drug manufacturers to develop the integrated data analytics capabilities needed to improve outcomes. It lowers cost, strengthens population health interventions, and increases stakeholder satisfaction while building an enterprise-level advanced data science foundation.
Infosys – AWS Partner Spotlight
Infosys is an AWS Premier Tier Consulting Partner and MSP that enables clients to outperform competition and stay ahead of the innovation curve.
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