1 / 19

How to Influence a GBDD (Gut Based Drug Developer)

How to Influence a GBDD (Gut Based Drug Developer). Communicating with Inter-Disciplinary Teams Joga Gobburu Brian Corrigan. Typical GBDD vs. MBDD Discussion. “Joga, did you finish your analysis. We need doses for the protocol tomorrow!”.

ilario
Télécharger la présentation

How to Influence a GBDD (Gut Based Drug Developer)

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. How to Influence a GBDD (Gut Based Drug Developer) Communicating with Inter-Disciplinary Teams Joga Gobburu Brian Corrigan

  2. Typical GBDD vs. MBDD Discussion “Joga, did you finish your analysis. We need doses for the protocol tomorrow!” “Yes, almost…. I just need to finish the VPCs and run a few more bootstrap analyses to estimate parameter uncertainties, but I should be ready to present the model later today if the grid stays up

  3. Pharmacometrics Project Update • The objective is to develop a markov mixed effects model to relate exposure and clinical response using data from Ph2 trials. J

  4. Markov Model Non-Responders Responders P10 Fraction of Transitions P01 Time J

  5. Likely Outcome “Brian, so what do you think?.” “Joga, the modeling is good but does the drug work? Which dose to take forward to Ph3?” “Brian, what part of my presentation did you not follow? Apologies to Lady Astor and Sir Winston

  6. Who is Right, the MBDD or the GBDD ? vs. Mindset Dataset • Has a deep understanding of the business • Can not articulate assumptions, but has a track record • “Will know it when he sees it”….intuition has lead to good decisions in the past • Perceives MBDD as inexperienced, narrow minded, and focused on only part(s) of the entire question • Has robust data and a toolkit of advanced models • Clear hypothesis and explicit assumptions • Clearly Defined Decision Criteria • Perceives GBDD as lacking objectivity, unscientific and non-quantitative B

  7. Point: It’s a False Choice! “Distinguishing the signal from the noise requires both scientific knowledge and self-knowledge”….(aka intuition) B

  8. Point: Quantitative Objective • Numbers do not speak for themselves • Predictions are based on models that in part reflect your views. Different models can (and often do) yield different results with the same data) • Stats vs. PMX • Health Authority PMX vs. Company PMX • PMX (internal) vs. PMX (consultant) • PMX (alliance partner 1) vs. PMX (alliance partner 2) • Do modelers have/need best practices? B

  9. The key to making a good forecast is not in limiting yourself to quantitative information.…. Nate Silver B

  10. Informing Decision Makers • Important Decisions in DD involve operating in a gray area • MBDDs role is to minimize the gray • You can not eliminate it from decisions • Intuition and experience (or ones gut) still needs to fill the gray areas left. • Inside the model • Outside the model B

  11. Point : Potential Uncertainties for extrapolation from Phase 2 to Phase 3 (Beyond the uncertainty in the model) • Phase 2 Selection Bias • Different patients (e.g. inclusion and/or exclusion criteria) • Different endpoints • Different countries • Different standards of care • Different doses or formulations • Different duration of treatment “What may be a Black Swan surprise for a turkey is not a Black Swan surprise for its butcher” Counterpoint: All of these items can be informed “quantitatively” by a model, as well or better than by expert opinion or “last paper carried forward”. If no data is available, an expert opinion is likely not useful either

  12. Point: Modelers Suffer from Bias in their Views/Communications about Models? • How often are Models wrong? • How many papers at ACOP 2103 report that the model results were wrong or lead to the wrong conclusions? B

  13. The Seven Five Steps to Influencing a GBDD (aka Decision Maker) B

  14. Communicate “Great Presentation Brian…..do it next time without any equations” Clinician Diane Jorkasky circa 2006 B

  15. Develop Rapport • How many individuals have or will take a NONMEM,R, ggplot, WINBUGS, PERL, MATLAB, or Phoenix training in the course of the year? • How many individuals in the room have had dinner with the clinical or stats lead on their Current team? • How many individuals have taken a Toastmasters, Stephen Covey, negotiations, or an effective writing course in the last year? • Consider spending one half hour on negotiation, writing or presentation skills and one half hour meeting with your clinician and Stats lead for every hour you spend in technical training. B

  16. Be Authoritative  “The thing that people associate with expertise, authoritativeness, kind of with a capital 'A,' doesn't correlate very well with who's actually good at making predictions.  Nate Silver B

  17. Accept Conflict “If you are not in trouble, you are not doing your job”. Robert Powell B

  18. Likely Outcome GBDD vs. MBDD MBDD (Joga): “Brian, I sent my recommendations to you a few days ago to get your feedback before the meeting. Have you had a chance to look at them? BTW, I also talked to stats over lunch to make sure they are on board. GBDD(Brian): “Joga, I agree with your recommendations.”

  19. Take Home Message For Success To Influence a GBDD • Communicate clearly (both listening and speaking) with team members early and often • Our deliverable is the ‘decision’, not the ‘model’ • “Socialize” your approach ideas early and often • Be authoritative and accept conflict • Be influenced by a GBDD • Value is added by experience and expertise 60% Soft Skills 40% Hard Skills J

More Related