Adoption of Data Management, Analytics & AI Technologies Across the Pharmaceutical Business Value Chain

Pharmaceutical companies are under immense pressure to:

  • bring innovative & personalized products to market with drastically reduced R&D timelines
  • attain precision in production planning & protect high-value inventory requiring cold chain monitoring
  • effectively sell products globally in markets already saturated with competing sales reps
  • proactively identify unexpected adverse even reactions

However, with these challenges comes significant opportunities across the entire business value chain of a pharmaceutical organization, due to the innovative and disruptive Data Management, Analytics & AI technologies which are exponentially increasing in their maturity, computing capacity & availability and decreasing in cost. What follows are examples of the business value that can be created or is already being created by Data Management, Analytics & AI technologies for pharmaceutical companies in order to produce radical improvements in their business in spite of severe challenges introduced in recent years in the overall Healthcare eco-system.

Drug Discovery to Trials

  • Analyzing insurmountable volumes of research - A big challenge which scientists face is analyzing insurmountable volumes of research which can now be automated & processed with minimal manual efforts leveraging Data Management, Analytics & AI technologies. AI deep learning can be leveraged to investigate data from a variety of sources to improve the accuracy of determining which compounds would be effective in drug treatments for a variety of diseases.
  • Clinical trials patient recruitment and retention - Pharmaceutical companies spend up to $19 billion annually on patient recruitment representing the largest component of clinical trial costs. Leveraging Real World Data (RWD) and AI & Analytics to recruit and retain patients can provide dramatic cost savings. AI can mine patient records and find the right patients for clinical trials leveraging Big Data, data from wearables, connected Electronic Health Records to name a few.
  • Accelerate Personalized Medicine Products Speed-to-Market – AI can be leveraged to build a picture from a human genome and find different areas in the genetic code which are “drugable”, offering new targets for Pharmaceutical companies, which are constantly looking to improve drug development pipeline.

Manufacturing & Supply Chain

  • Inventory Optimization - inventories are a major driver of working capital for Pharmaceutical companies, and thus intensively monitored by shareholders & investors. Also, safety stocks are critical to attain the necessary levels of customer service. Data Management, Analytics & AI can be leveraged to develop predictive models with combinations of Portfolio, Stock outs and Lead time variance and Demand variance.
  • Improve Forecasting - many pharmaceutical companies experience challenges such as poor forecasting performance, resulting in out-of-stock and excess inventory, and fragmented & reactive demand planning. AI can be leveraged to conduct Statistical Analysis to identify Demand Patterns and help drive more precision in this area.
  • Cold Chain Analytics - a sum of $16 Billion is the approximate value of costs incurred by top 10 pharmaceutical companies for temperature excursions. Healthcare products such as vaccines, blood plasma products, frozen pharmaceuticals and insulin require specific temperatures to be maintained throughout storage & transportation. AI can be leveraged to build predictive models to select the best cold chain location, plant size and other requirements based on fluctuating external parameters.

Commercial

  • Increase Salesforce Productivity - with the aid of machine learning algorithms, pharmaceutical companies would be empowered to accurately identify the number of calls that sales reps should make to specific types of doctors for optimal results, and analyze historical data and past behaviors to predict which stimuli will propel the sales team to modify its behavior.
  • Improvements in Order to Cash – AI can be leveraged to identify bottlenecks and improve process efficiency, and in turn free up cash by optimizing working capital and recapturing profits. Further, productivity savings would be gained allowing more time for customer service and accounts receivable teams to focus on more critical issues.
  • Improvements in Brand Strategy – Data Management, Analytics & AI technologies enable the prediction of the next best channel, message, and timing for customer engagement, allowing marketers to leverage the learnings of AI to refine their brand strategy and develop personalized experience journeys for individual physicians.

Post-Market Monitoring

  • Identify Unexpected Drug Safety Problems – Data Management, Analytics & AI can be leveraged for identification of any indication of an unexpected drug safety problem which may be either new Adverse Drug Reactions (ADR) or a change of the frequency of ADRs that are already known to be associated with the drug involved.
  • Identify Missed Adverse Event Reactions – AI is leveraged to correlate social media data to Adverse Event Reporting System in order to assist in identifying additional Adverse Event listings that might have been missed before a drug was authorized for marketing.
  • Enable Pharmacovigilance – Data Management & AI can be leveraged to enable faster case intake and processing through automation and effectively handle case volume growth and diverse types of incoming data formats effectively.

In summary: while the pressure on Pharmaceutical manufactures is immense with the disruption of the Healthcare eco-system as we know it, there is significant opportunity for Pharmaceutical companies to not only survive, but thrive & continue elevating their relevance in the marketplace leveraging Data Management, Analytics & AI technologies across the entire business value chain. Tenthpin Analytics practitioners are deeply passionate about the Life Sciences Industry problem statements and enabling solutions to these problem statements from business value discovery, to strategy, to realization through enterprise Data Management and Analytics & AI transformation execution.

Contact our industry experts at Tenthpin Management Consultants if you would like to learn more.

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About the Author

Dmitry Soloveychik

Partner – US

Dmitry is a leader in our Analytics Practice