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Workshop

Clinical Pharmacology & Modeling Strategies for your Drug Development Program: Fundamentals, Best Practices and Real World Applications


Speakers: David Lau (Foresee Pharmaceuticals), Geoff Banks (Nuventra), Mark Sale (Nuventra), Lauren Lohmer (Nuventra)
Organizers: Kelly Gelinne (Nuventra), David Lau (Foresee Pharmaceuticals)
Date: 2017-12-11
Time: 8:45-17:00 Pacific Time
Registration fee (USD): Academic: $125; Regular: $195; For unemployed or students: $30; For major-sponsor rep (incl lunch): $0; For vendor-show rep: $35
Location: SF Bay Area: Foster City Crowne Plaza
Major Sponsor:
Vendor show vendors registered to date: (4)Altasciences; Applied BioMath; Spaulding Clinical Research; WORLDWIDE CLINICAL TRIALS
Registration: http://www.PBSS.org
Registration deadline:2017-12-08  (it will close sooner if the seating cap is reached)

About the Topic

Preliminary Agenda

8:45 – 9:00 Welcome and Intro

9:00 – 10:30 – David Lau (Senior Vice President, NCE Preclinical and Clinical Development, Foresee Pharmaceuticals)

Purpose of Clin Pharm Studies in Drug Development

Type of Clin Pharm studies (SAD, MAD, BA/BE, DDI, Disease population, QT, etc)

  • What are these studies
  • When to do the studies
  • Typical study design
  • Examples

10:30 – 11:00 – Break and Vendor Presentation

11:00 – 12:30 – Geoff Banks (CEO, Nuventra)

How to Form a Clin Pharm Strategy for your NDA / BLA

  • What studies you do & don’t need
  • “Gap analysis” in your program
  • Real world examples

12:30 – 1:30 – Lunch

1:30 – 3:00 – Mark Sale (Senior Vice President, Pharmacometrics, Nuventra)  

Modeling & Simulation / Population PK Fundamentals

  • What is it?
  • How do you do it?
  • Allometric scaling
  • How do you use it for safety and efficacy?

3:00 – 3:30 Break and vendor presentation

3:30 – 5:00  – Mark Sale and Lauren Lohmer (Manager, Clinical Pharmacology, Nuventra)

Using Modeling & Simulation to Avoid Clinical Trials

  • Overview and case studies:
    • CQT
    • Exposure response
    • Additional DDI studies
    • Special population studies
    • Renal impairment


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