Systems Architecture Case Study: CytoSolve® Accelerates USFDA-Oriented Discovery of Combination Therapeutics for Pancreatic Adenocarcinoma

U.S. Food and Drug Administration
The FDA is the U.S. regulatory authority responsible for evaluating the safety and efficacy of therapeutics entering clinical development. In this case study, FDA engagement reflects downstream regulatory advancement of CytoSolve®-enabled combination therapeutics for pancreatic cancer.

Challenge

Pancreatic adenocarcinoma is an aggressive malignancy that often progresses asymptomatically, limiting opportunities for early intervention. While gemcitabine is an FDA-approved therapy, it demonstrates limited efficacy at tolerable doses and is associated with significant toxicity at higher concentrations. Traditional approaches to identifying effective drug combinations require 10–15 years of experimental research, driven by trial-and-error testing and incomplete mechanistic understanding. A scalable systems architecture was needed to mechanistically evaluate drug combinations, minimize toxicity, and accelerate discovery timelines.

How CytoSolve Helped

CytoSolve® implemented a mechanistic systems architecture that integrated mathematical models of epidermal growth factor receptor (EGFR)–induced cell cycle regulation and apoptosis—two core biological processes driving pancreatic cancer progression. Rather than relying on monolithic models or empirical screening, CytoSolve®’s architecture enabled independent pathway models to be computationally bound and simulated in parallel, preserving biological fidelity while enabling large-scale combinatorial exploration.

Using this architecture, CytoSolve® constructed Cyto-001, an in silico–optimized combination of two FDA-approved chemotherapeutic agents. The platform evaluated how drug combinations influenced cancer cell proliferation and apoptotic signaling at minimal doses, identifying synergistic interactions that maximized tumor cell apoptosis while reducing overall toxicity burden. This systems-driven approach enabled rapid narrowing of viable therapeutic combinations grounded in mechanistic evidence.

Key Benefits Realized

  • Modular systems architecture integrating EGFR signaling, cell cycle control, and apoptosis pathways
  • Mechanistic evaluation of drug combinations beyond single-agent limitations
  • Significant reduction in discovery timelines compared to traditional experimental approaches
  • Identification of a low-dose, high-efficacy combination using FDA-approved agents
  • Architecture aligned with regulatory expectations for mechanistic rationale

Outcome

CytoSolve®’s systems architecture enabled the discovery of Cyto-001, a novel in silico–derived combination therapy for pancreatic adenocarcinoma. The mechanistic evidence generated through CytoSolve®-supported modeling led to FDA approval for advancement of this drug combination into further clinical trials. This case study demonstrates how CytoSolve®’s scalable systems architecture can transform cancer drug development—compressing timelines, reducing toxicity risk, and providing a mechanistically transparent pathway from computation to regulatory progression.