CytoSolve® Accelerates USFDA-Oriented Discovery of Combination Therapeutics for Pancreatic Adenocarcinoma

Partner Description

U.S. Food and Drug Administration (FDA) is the U.S. regulatory body responsible for evaluating the safety and efficacy of therapeutics entering clinical development. In this case study, the FDA's involvement reflects the downstream regulatory approval and advancement of drug combinations identified through CytoSolve®'s innovative systems biology platform for pancreatic cancer.

Challenge

Pancreatic adenocarcinoma is one of the most aggressive cancers, often progressing without symptoms until advanced stages, which limits the opportunities for early intervention. Although gemcitabine is an FDA-approved treatment for this malignancy, it has limited efficacy when administered at tolerable doses and is associated with significant toxicity at higher doses.

Traditional drug combination discovery is a slow, resource-intensive process that can take 10 to 15 years, often driven by trial-and-error and incomplete mechanistic understanding. The challenge was to accelerate the discovery of effective drug combinations that could maximize therapeutic benefit while minimizing toxicity, using a scalable systems architecture for mechanistic evaluation.

How CytoSolve Helped

CytoSolve® developed and implemented a mechanistic systems architecture that allowed for the rapid, in silico identification and evaluation of potential drug combinations. This architecture was designed to simulate complex biological processes driving pancreatic cancer progression and to assess therapeutic combinations in a way that traditional methods could not.

  • Modular Systems Architecture: CytoSolve® developed a modular in silico platform integrating independent mathematical models of key pancreatic cancer pathways, including:
    • Epidermal growth factor receptor (EGFR) signaling
    • Cell cycle regulation
    • Apoptotic signaling
    This architecture enabled parallel simulation of pathway interactions to explore drug combination effects while preserving biological fidelity.
  • Construction of Cyto-001: Using this systems framework, CytoSolve® designed Cyto-001, a combination of two FDA-approved chemotherapeutics, simulating effects on:
    • Reducing cancer cell proliferation
    • Maximizing apoptosis (programmed cell death)
    • Minimizing toxicity at low, effective doses
    Synergistic effects between the two drugs were identified to enhance therapeutic outcomes while reducing toxicity.
  • Simulating Combinatorial Drug Interactions: The platform enabled rapid simulation of multiple drug combinations, identifying promising candidates for further testing and accelerating discovery timelines compared with traditional methods.
  • Regulatory Alignment: In silico results provided a mechanistic rationale for the combination therapy aligned with FDA expectations, supporting regulatory submissions and facilitating faster advancement through the approval process.

Key Benefits Realized

  • Modular Systems Architecture: Integrated EGFR signaling, cell cycle control, and apoptosis pathways to provide a nuanced understanding of drug interactions and their impact on cancer cell behavior.
  • Evaluation Beyond Single-Agent Limitations: CytoSolve® enabled simulation of drug combinations in a systems context, identifying synergistic interactions that traditional single-agent studies might miss.
  • Significant Reduction in Discovery Timelines: Computational modeling compressed typical drug discovery timelines from 10–15 years to a shorter timeframe, accelerating identification of promising combinations.
  • Low-Dose, High-Efficacy Combination: The platform identified a low-dose, high-efficacy drug combination that maximized therapeutic benefit while minimizing toxicity.
  • Regulatory Alignment: Mechanistic evidence from the modeling was robust and aligned with FDA expectations, facilitating faster progression of Cyto-001 into clinical trials.

Outcome

CytoSolve®'s systems architecture enabled the discovery of Cyto-001, a novel combination therapy for pancreatic adenocarcinoma. The mechanistic evidence produced through CytoSolve®-supported modeling led to FDA approval for the advancement of this drug combination into further clinical trials.

This case study demonstrates how CytoSolve®'s scalable systems architecture can revolutionize cancer drug development by:

  • Compressing Discovery Timelines
  • Minimizing Toxicity Risk
  • Providing a transparent, mechanistically grounded pathway from computational predictions to regulatory approval.
CytoSolve®'s approach enables the rapid, efficient identification of combination therapeutics, significantly accelerating the development of life-saving therapies for complex diseases like pancreatic cancer