Empowering Healthcare Start Ups

Background: A stealth-mode startup aims to revolutionize the non-insured prescription drug market, intending to lower consumer prices and increase pharmacy revenues affected by PBMs and discount cards

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Challenge: Uncertainty about the technological feasibility of aggregating up-to-date drug prices from multiple public sources.

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Objective: Validate the concept by building a proof of concept for collecting drug price data, enabling objective evaluation and fundraising efforts.

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Proposed AWS Solutions:Utilization of AWS Lambda, SQS, Step Functions, and Athena for a serverless architecture.Implementation:Initiated with a proof of concept for data collection.Built and scaled the comprehensive data collection system on AWS.‍‍

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Generally, when you think about data partitioning, you start by thinking about whether the data will be siloed or pooled. In a siloed model, you have a distinct storage construct for each tenant with no co-mingled data. For pooled partitioning, the data is co-mingled and partitioned based on a tenant identifier that determines which data is associated with each tenant.

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As an example, with Amazon DynamoDB, a siloed model uses a separate table for each tenant. Pooling data in Amazon DynamoDB is achieved by storing the tenant identifier in the partition key of each Amazon DynamoDB table that manages data for all tenants.

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You can imagine how this might vary across the range of AWS services, with each one introducing its own constructs that may require a different approach to realizing silo and pooled storage models with each service.

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While data partitioning and tenant isolation are separate topics, the data partitioning strategies you choose are likely to be influenced by the isolation model of your data. For example, you might silo some storage because that approach best aligns with the requirements of your domain or customers. Or, you might choose silo because the pool model may not allow you to enforce isolation with the level of granularity that your solution requires.

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Outcomes:Successful proof of concept led to substantial Series A funding.Built a scalable infrastructure that collects, normalizes, and aggregates data from diverse sources into a unified prescription drug price data feed.

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Summary:West Loop Strategy’s AWS expertise enabled the startup to validate and launch their innovative project, providing a unified solution to the healthcare and pharmacy industry's pressing challenges.

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We Invite other startups and enterprises to explore similar innovative solutions with West Loop Strategy.‍‍