The dramatic improvements in computing capacity, both in terms of raw computational power as well as architectural advancements including Industry 4.0, have profoundly altered the data analytics landscape.

Although it may not be directly evident, the effects of this shift manifest themselves in various aspects of our day-to-day lives. To achieve the fundamental goal of improving the quality of healthcare and patient lives, the field of advanced analytics is becoming a critical enabler.

The advancement of data computing power along with cloud architecture, has made it both technically and economically feasible to manage the exponential growth of data across the life sciences and healthcare industry ecosystem.

The advancement in the precision medicine, including new and innovative therapies like biologics, RNA, gene therapy and CAR-T combined with digital health initiatives are providing new opportunities to improve patient lives, which could not have been imagined 10 years back.

With patient being the real customer, these treatments also have a very complex patient journey life cycle. This requires generating insights from billions of data points collected across the treatment pathway both during the treatment and several years post treatment to assess the effectivity of the treatment, cure and adverse events.



Clinical and Quantitative Systems Pharmacology (QSP)


Supply Chain & Operations


Manufacturing, Quality and Regulatory



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At RxDataScience we believe that the challenges faced by the Life Sciences and Healthcare industry is very unique based on the specific sub sector. We bring relevant industry and domain expertise combined with our deep analytics, data science and technology expertise to support our clients on their analytics journey. 

We deliver based on a highly customer focused and tailored approach in a flexible and agile model. Our unique methodology is based on Asset based consulting and services, that leverages RxDS platform and products, and drive long term value to our clients.

We have prioritized on the following sub sector within Life Sciences & Healthcare as the primary focus:

  • Bio-pharma
  • Biotech
  • Med Tech / Devices
  • Providers & Payers



RxDS Key differentiators include the high customer focus and the agile / dynamic approach of the solution which has been a critical requirement to rapidly generate real-time insights.


Analytics Enabled Business
Transformation Vision
Table Stakes
(Strategic Advantage)
Business Process Optimization Industry 4.0
How will we measure the
success & business value?
Blockchain for contracts, patient
consent, data query
How will this help us differentiate? EMR Data Integrated Insights
Outcome & KPI IoT, Devices, Sensors, Wearable
Automate & Workflow Advanced Analytics - Predictive,
Prescriptive Scientific
Org. Culture, Change
Management & Talent
Digital Marketing, Patient
Finder & Access
Technology Patient Journey
Data Late - Data Sources, Data
Capture, Integrate, Data Quality
De-centralized & Virtual
Clinical Trials
When will we get there? Maturity
model, Roadmap (gaps, priority
speed, & sequence)
Real-world Evidence (RWE)
Governance Governance
  Supply Chain Control Tower
& Visibility
  Quantititaive Systems
Pharmacology (QSP)
  Remote Patient Monitorying
  Supply Chain Traceability &


A number of data sources and categories to support the data and information requirements for the Analytics journey


Clinical and QSP (Quantitative Systems Pharmacology)


Translational Medicine and Clinical - Leveraging data, analytics and technology to accelerate the drug discovery and research, including enhancing the outcome of the clinical trial.

Quantitative and Systems Pharmacology (QSP) is an emerging discipline within translational medicine, focused on identifying and validating drug targets, understanding existing therapeutics and discovering new ones. 

  1. QSP extends the classical discipline of pharmacology and to develop new concepts that can be applied to specific problems in drug development including:
         - Identifying novel drug targets and pharmacodynamic bio markers
         - Predicting which drugs will work together (as combination therapies) to achieve defined pharmacological endpoints
         - Determining action of existing drugs and whether they might be effective in diseases for which they were not originally tested
  2. Predict which patients will respond to and benefit from a given therapy and assess the reasons for variability in efficacy
  3. Improve ability to perform key steps in drug discovery and mitigate the current challenges faced in the drug development.
  4. Develop systematic approaches to understanding adverse drug reactions and identify subsets of patients who are at increased risk for acute and delayed toxicity

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Clinical Data Lakes & Analytics

Industry Drivers

  • Explosive growth in data resulting from clinical trials resulting in the need to process larger variety of data within a shorter time span and generate timely insights
  • Companies as well regulatory agencies are moving towards highly standardized study reporting and data exchange such as SDTM (Study Data Tabulation Model)
  • Lack of ability to track the various aspects of the clinical trials lifecycle in an integrated manner in real-time, by various stake holders

Business Benefits

Clinical DataLake (CDL) allows to integrate disparate data across multiple sources enabling new capabilities

  • Source of statistical analysis for clinicians and scientists
  • Foundation upon which to automate the analysis and reporting.
  • End-2-end visibility across the clinical trial operations
  • Capabilities to perform ad hoc analysis across trials,
  • Meet compliance and regulatory agency reporting


Clinical Data Lake and Analytics Capabilities

Level 1 & 2 KPI, Thresholds, Alerts and Exception Tracking

  • Clinical Operations
  • Clinical Supply Chain
  • Clinical Data Management and Scientific Analysis
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Supply Chain & Operations Manufacturing and Quality

  • Supply Chain across both Biopharma & Life Sciences and cross industry manufacturing sector, present a huge opportunity where analytics can drive real and hard ROI
    Based on several analyst research reports the top 3 areas across the industry where Advanced Analytics and AI has the maximum return on investment includes Drug Discovery, Supply Chain Operations and Sales & Marketing
  • The industry is moving away from traditional linear supply chain to network model with high levels of collaboration.
  • Industry 4.0 (e.g. IoT and sensors) is providing a unique opportunity to connect and get real time insights from the execution level including manufacturing, quality and logistics
  • RxDS brings unique capabilities and service offerings on the Supply Chain Analytics based on a consultative model. Our approach combines deep Supply Chain domain experience with our assets (platform and products), that allows our clients to rapidly pilot specific use cases to assess the value, before expanding across the enterprise.
  • A Rapid Development Advanced Analytics Lab i(RDAL) has been established at the RTP. This will be leveraged to accelerate and test the feasibility of new ideas and innovation, before they are prioritized and included in the formal project pipeline


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Framework – Analytics Enabled Supply Chain Transformation


What Others Are Saying

“RxDataScience’s customer service focus in just fantastic.  They are incredibly responsive to requests, and, in the rare instance an issue arises, the team is very proactive about communicating resolution timelines.  I have worked in the industry for 20+ years and my experience with RxDataScience has ranked among my top data & analytics vendor experiences.”


Senior Director, Market Insights

Global Pharma Company

“The RxDataScience team brings agility, advanced capabilities and technology we simply cannot get from the other top consulting firms.”

Chief Data Officer

Top 10 Pharma

“Vendors like to talk agile and use the latest buzzwords, but the RxDataScience team has Agile as part of your DNA. We benefit from it everyday working with your team”

Director, Commercial Systems

Orphan Drug Company

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