Life Sciences Examples

Life Sciences Example #1

Pharmaceutical R&D Prioritization

Techniques:
  • Excel linking
  • Downstream decisions
  • Promoting get/pay expressions
  • Asymmetry
  • Perform subtree
  • Initialization links
  • Calculation links
Files:

Overview: Pharmaceutical R&D Prioritization.pdf
Model: Drug Development.da
Spreadsheet: Drug Development.xslx

DPL Decision Tree Model for Pharma R&D Decision

More than any other factor, the choice of R&D projects defines the future of a life sciences company. Unfortunately all the easy blockbusters are done, and creating value within a project portfolio requires a keen understanding of clinical, market and regulatory risk. High costs and high failure rates keep the stakes high, but DPL can help you discover value with rigor and confidence.

Life Sciences Example #2

Pharmaceutical Business Development & Licensing

Techniques:
  • Arrays
  • Multiple Attributes
  • Time Series Percentiles
  • Downstream Decisions
  • Perform subtrees
  • Initialization links
  • Calculation links
Files:

Overview: DPL Commercial Strategy Case.pdf
Model: Neuropriza.da
Spreadsheet: Neuropriza.xlsx

DPL Decision Tree for Pharmaceutical Commercial Strategy and Licensing Decision

Bringing in the right product at the right price sounds simple enough, but the challenges of high uncertainty, limited information and tight timescales make it a hard problem. Getting the value wrong, or just being too slow, can mean ceding a gem to a competitor. Honed in a specialized valuation group at a leading professional services firm, DPL is designed to take on these problems and produce clear, timely results.

Life Sciences Example #3

A Medical Device Regulatory Vigilance Example

Techniques:
  • Deterministic Modeling
  • Value-wise Conditioning
  • Deterministic Sensitivity Analyses
  • Local Modeling
  • Introducing Uncertainty
  • Asymmetry
  • Minimization
Files:

Overview: Pharma Medical Device Vigilance Case
Model: Defib.da
Further Reading: Medical Devices and Their Regulatory Pathways

DPL Influence Diagram for Medical Device Regulatory Vigilance

Regulatory bodies have the responsibility of managing the long and winding pathway to the approval (or disapproval) of a medical device. Devices that prove most invasive must pass through a rigourous process to ensure the benefits to health of a particular population outweigh the risks -- an analytic process that must be consistent as it is transparent. DPL's flexible modeling interface allows a regulatory analyst the ability to make informed decisions based on minimizing negative medical outcomes -- just easily as the financial analyst seeking to make decisions that maximize profits.

Life Sciences Example #4

Regional Sales Forecasting for a Pharmaceutical Drug

Techniques:
  • Sales forecasting
  • Additive modeling
  • Promoting get/pay expressions
  • Symmetric modeling
  • Perform subtrees
Files:

Model: Pharma Sales Forecast.da

DPL Model for Pharma Sales Forecast

You may have noted from the screenshot above that this atypical DPL "decision model" is in fact, decision-less! The model represents a sales forecast for Miebedar, a new pharmaceutical drug in development, and incorporates uncertainties surrounding dosing and usage within various therapeutic areas in order to come up with a projection of units sold per region. Units are then multiplied by a pricing uncertainty for each region to result in a forecast of Total Miebedar Sales.

In this example model only a single output metric, Total Miebedar Sales, is of interest. But instead of placing this value as the get/pay at the end of this rather large, symmetric decision tree -- totals sales are broken into component values and moved up in the tree (a process we call "promoting get/pays", shown below). Doing so allows DPL's proprietary optimizations pick apart and calculate the decision tree, one that boasts over 500+ million paths, in a matter of seconds!

DPL Model for Pharma Sales Forecast