Flix Jaminion PhUSE Edinburgh 08/10/2017 Plan Background Data - - PowerPoint PPT Presentation

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Flix Jaminion PhUSE Edinburgh 08/10/2017 Plan Background Data - - PowerPoint PPT Presentation

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Interactive Oncology Tumour Dashboard Flix Jaminion PhUSE Edinburgh 08/10/2017 Plan Background Data Demo Conclusion 2 Flix Jaminion, PhUSE Edinburgh 08/10/2017 Background Clinical Pharmacology Help Clinical

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SLIDE 1

Interactive Oncology Tumour Dashboard

Félix Jaminion

PhUSE Edinburgh – 08/10/2017

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SLIDE 2

Plan

  • Background
  • Data
  • Demo
  • Conclusion

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Félix Jaminion, PhUSE Edinburgh – 08/10/2017

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SLIDE 3

Background

Clinical Pharmacology

  • Help Clinical Teams to understand the Pharmacokinetic behaviour of drugs
  • Try to answer some questions such as:

– What is the best dose? – What is the best formulation? – What is the best dosing interval?

  • Perform Pharmacokinetic (PK) and Pharmacodynamic (PD) modeling activities
  • Also known as the « PK guys »

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Félix Jaminion, PhUSE Edinburgh – 08/10/2017

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SLIDE 4

Background

Clinical Pharmacology

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Félix Jaminion, PhUSE Edinburgh – 08/10/2017

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SLIDE 5

Background

Clinical Pharmacology

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Félix Jaminion, PhUSE Edinburgh – 08/10/2017

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SLIDE 6

Background

Clinical Pharmacology

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Félix Jaminion, PhUSE Edinburgh – 08/10/2017

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SLIDE 7

Background

Clinical Pharmacology

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Félix Jaminion, PhUSE Edinburgh – 08/10/2017

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SLIDE 8

Background

Clinical Pharmacology

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Félix Jaminion, PhUSE Edinburgh – 08/10/2017

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SLIDE 9

Data

SDTM / ADAM

  • Use clinical data from different domains

– DM – VS – EX – PC – LB – TR

  • Deliver ready to use analysis dataset

– Describing all the events that occurred for all the patients during a study

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Félix Jaminion, PhUSE Edinburgh – 08/10/2017

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SLIDE 10

Data

Example of modeling file

PT TIMED TAFDD CMT LABEL VALU E AMT 601 ... ... ... ... ... 601 363.83 362.94 1 Dose 300 601 364.33 363.44 1 Dose 300 601 364.78 363.89 2 PK 562 601 364.83 363.94 1 Dose 300 601 365 364.1 3 SLD 27.42 601 365 364.1 4 CFBL

  • 75.2

601 365 364.1 5 Target Les. 7.55 601 365 364.1 5 Target Les. 7.81 601 365 364.1 5 Target Les. 601 365 364.1 5 Target Les. 12.06 601 365 364.1 6 Overall Resp. 4 601 365 364.1 7 New Les. 1 601 365.33 364.44 1 Dose 300 601 365.83 364.94 1 Dose 300 601 366.33 365.44 1 Dose 300 601 ... ... ... ... ... 10

Félix Jaminion, PhUSE Edinburgh – 08/10/2017

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Demo

Interactive Oncology Tumour Dashboard

  • Create an interactive and dynamic visualization for tumour modeling files
  • Summarizing many different information:

– Baseline Covariates – PK Exposure – RECIST Criteria

  • Overall Response (OR)
  • Best Overall Response (BOR)
  • Appearance of non target New Lesions (NL)

– Target Lesions (TL) – Sum of Longest Diameter (SLD) – SLD %-Change From Baseline (CFBL)

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Félix Jaminion, PhUSE Edinburgh – 08/10/2017

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Conclusion

Interactive Oncology Tumour Dashboard

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Félix Jaminion, PhUSE Edinburgh – 08/10/2017

  • User friendly tool to display and visualize interactively individual and population tumour data
  • Helping data exploration and data quality check
  • Next steps:

– Add new elements (tumor location, method of identification or key endpoints) – Link the modeling results with the dashboard – Allow a complete customization – R-Shiny App

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SLIDE 13

Doing now what patients need next

Félix Jaminion, PhUSE Edinburgh – 08/10/2017