QSP SIG Working Grous

Working groups are one of the best ways to get involved in the QSP-SIG and contribute your energy and passion to the advancement of the field. Over the last several years the QSP leadership had the privilege to endorse the formation of several working groups that have delivered outstanding achievements. All started with an idea and a few enthusiastic champions that have managed to get wider engagement from our community. We anticipate several working groups may end soon, having completed their objectives, and others may seek new membership to drive a transition to new objectives. 

If you are interested, do not hesitate to contact us on our email: isop_qsp_sig@isop.org.

Description:

The goal of this working group is to advance the CDISC Data Standards Implementation for Pharmacometric datasets across the industry

Objectives: 

To assess the adoption and implementation of ADaM ADPPK Data standard across the industry. Understand any challenges in implementing these standards, and impact to existing workflows. Educate the benefits of adopting the CDISC standards and recommend potential solutions to address the challenges.

Outcome: 

Create more awareness of CDISC ADPPK Standards and benefits of adopting them across industry. Make implementation clear and easy to understand. Inform workstream readout to FDA for update to guidance.

Lead: Neelima Thanneer (Lead), David Radtke, Kiran Kumar Kode

Contact: PMxDataSIG@isop.org if you are interested in joining the working group

Chair(s): Prakash Packrisamy, Vincent Hurez

Goals: 

  1. Promote and share ongoing QSP modeling endeavors in the inflammation and immunological disorders therapeutic areas. 
  2. Identify challenges specific to QSP modeling of inflammation and immunological disorders and propose potential solutions to some of these challenges.

Chair(s): Suruchi Bakshi, Shaina Short

Goals: 

  1. Build a network of scientists in neuroscience QSP to advance the exchange of ideas, collaborations, model development, and career networking. 
  2. Promote interdisciplinary approaches to neuroscience QSP through tutorial manuscripts and/or review articles.

Chair(s): Carolyn Cho, Tongli Zhang

Goal:

Bring researchers together to critique, share and develop new approaches for integrating QSP models with multi layer omics data as well as applying machine learning methods to better characterize QSP models. 

Chair(s): Blerta Shtylla

Goals: 

  • Identify Key COUs: Summarize and assess key COUs for credibility assessment of QSP modeling using FDA reviews and existing guidance.
  • Develop Best Practices: Propose common terminology and best practices for validation, verification, and uncertainty quantification in QSP modeling.
  • Engage Stakeholders: Regularly seek feedback from the QSP community and regulatory agencies to align priorities and educate stakeholders.
  • Propose Reporting Guidance: Suggest good practices for reporting QSP models to ensure clear communication of model credibility assessment.

If you are interested in joining a working group, please email us at isop_qsp_sig@isop.org.