Beyond Disease Labels

Authors: Brostoff N
Conference: AAPS
Keywords: AAPS Pharmasci 360, autoimmune modeling, machine learning, mechanistic modeling, Precision medicine, quantitative systems pharmacology (QSP)
Session Description and Objectives
  • Autoimmune treatment remains inefficient: in search of sustained response, patients may spend years if not decades cycling through the treatment options available for their disease-label
  • While disease-label-based assessments are conventional, the underlying immune processes can be viewed as a shared mechanistic system, under which different perturbations can result in autoimmune-driven symptoms, with substantial symptom overlap across those disease-labels
  • This presentation describes a disease-label-agnostic framework combining mechanistic quantitative systems pharmacology (QSP) modeling with interpretable machine learning to derive biomarker-based precision medicine treatment-assignment rules
  • Describe how a disease-label-agnostic autoimmune QSP framework can be combined with interpretable machine learning to guide precision medicine therapy-assignment
  • Describe applications of the framework
  • Describe benefits of the paradigm shift in thinking that the application suggests

By Noah Brostoff

AAPS PharmSci 360 2026, October 25-28, 2026, New Orleans, Louisiana