Data-Powered Decision-Making in Personalized Medicine: Cost-Effective Integration of Expert PM IT System into Lifecycle Therapy Planning Process - Diaceutics

Data-Powered Decision-Making in Personalized Medicine: Cost-Effective Integration of Expert PM IT System into Lifecycle Therapy Planning Process

July 29th, 2013

Ryan Keeling

Personalized medicine business planning is complex, with over 400 decisions to be made in order to integrate diagnostics into the patient pathway.  Knowledge of how to do this can vary across the therapy team and result in a lag in therapy launch and reduced revenue opportunity. Ryan Keeling of Diaceutics shows how, through use of a software platform, project teams can be enabled to plan the commercial strategy themselves, reach consensus faster, reduce the risk of time lag and thus increase the overall therapy revenue opportunity.

It’s no secret that Diaceutics started life as a consulting company before adding personalized medicine-focused software and implementation services as part of its mission to provide an end-to-end service for pharma and diagnostic companies. In particular, our investment in software has enabled some of the most compelling client benefits. Personalized medicine planning is not intuitive:  there are some 400 decisions which need to be made in order to incorporate a companion diagnostic into the targeted therapy project. Many of these decisions require expert insight across not only the drug development and commercialization model but the diagnostic one, too. To explain this let me focus on one example.

In 2007, a top ten pharma company approached our consulting team to help them define a personalized medicine-focused strategy for a new PARP inhibitor they had in Phase II development. After interviewing many of the project team leaders, it was revealed that the team had spent some 3,600 full time equivalent (FTE) hours in discussion over the previous 12 months on this same topic but had failed to reach a consensus on strategy. At current FTE rates, this equates to a cost of $818,000 of direct executive time, excluding the indirect costs of indecision to the overall project. To calculate the indirect costs to the project, we have assumed that a 12 month lag in decision-making likely translates into a three month lag in therapy launch, or three months of reduced revenue opportunity. The average first three months’ revenue for a targeted oncology therapy is estimated at $150 million with a NPV (Net Present Value) of $15 million.

This is not unusual to many of us who have worked in pharma, as often the road to decision-making goes through many consensus building and market research steps. Additionally, with executives unfamiliar with the rapidly evolving companion diagnostic space this type of time investment is understood, if potentially wasteful.

Armed with a specific IT-enabled platform which combines fit-for-purpose decision tools with in-depth benchmarking insights, Diaceutics was able to help the same team reach consensus and commercialization strategy in under 400 FTE hours – about a quarter of the direct cost and in under two months’ (versus the original 12 months) planning duration. Using the same NPV method as above, the launch lag costs would be approximately $2.5 million.

The story does not end there. We have continued to develop our software platform to enable project teams to do the planning themselves (in-line beside other timely decisions) without the need for a consultant standing over their shoulder. This presented some challenges to us, as despite the complexity of personalized medicine planning, the user interface needed to be very easy to use. Several project teams within our leading clients are interfacing with our platform daily to achieve the same planning excellence as the team discussed above. Whilst the amount of time spent using the software directly is about the same, there is no lag to the planning period, as decisions are taken in the right place at the right time.

So there you have it, the comparative value of using an expert system to help with the complex world of personalized medicine planning.

–       Method 1:

  •    Team Consensus
  •    Direct Cost: $818,000
  •    Indirect Cost: $15,000,000
  •    Launch Lag : 3 months

–        Method 2:

  •    IT-Enabled / Facilitated
  •    Cost: $265,000*
  •    Indirect Cost: $2,500,000
  •    Launch Lag: 2 weeks

–       Method 3:

  •    IT-Enabled / Inline
  •    Cost: $265,000*
  •    Indirect Cost: None
  •    Launch lag: 2 weeks

*includes the cost of software licensing.


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