Saturable adsorption as a central determinant of drug penetration in complex biological tissues

The National Institute of General Medical Sciences awarded $419,823 to Regents of the University of Michigan on August 3, 2026, under the Biomedical Research and Research Training program (CFDA 93.859) to establish a predictive science of adsorption-limited drug transport across complex biological tissues.

The research addresses saturable adsorption to tissue matrices—a hidden barrier that prevents potent therapeutics from reaching their targets in airway mucus, biofilms, granulomas, and tumors. The program combines equilibrium and kinetic binding constants with diffusion modeling to derive dimensionless descriptors including capacity ratio, binding Damkohler number, and therapeutic range, enabling construction of regime maps and the "adsorption window," a clinically actionable metric defining where and when free drug concentrations remain above therapeutic thresholds.

Work is organized into three thrusts: constructing the first adsorption atlas for pathological matrices by systematically mapping drug chemistry and matrix composition interactions; translating these parameters into predictive models and transport charts yielding adsorption windows that connect molecular energetics to therapeutic outcomes; and leveraging these models to design interventions around reducing, exploiting, or reprogramming adsorption, validated by blinded predictions and culminating in an intervention playbook. Initially focused on antibiotics in airway mucus and biofilms, the framework generalizes to biologics, nanoparticles, and oncology.

Performance occurs at Ann Arbor, Michigan. The period of performance runs through March 31, 2031.

Abstract

Potent therapeutics often fail not because of resistance, but because a hidden barrier, saturable adsorption to the tissue matrix, prevents them from reaching their target. Across airway mucus, biofilms, granulomas, and tumors, reversible binding collapses the free drug fraction, a challenge underrepresented in pharmacokinetic frameworks that treat tissues as passive volumes rather than dynamic, capacity-limited sorbents. This program will establish a predictive science of adsorption-limited transport, reframing drug access as a capacity problem defined by measurable parameters. By combining equilibrium (qmax, k) and kinetic (KON, koff) constants with diffusion, we derive dimensionless descriptors such as the capacity ratio (γ), binding damköhler number (DA), and the therapeutic range (l*). These parameters enable construction of regime maps and the "adsorption window," a clinically legible metric defining where and when free drug concentrations remain above therapeutic thresholds. The research is organized into three synergistic thrusts: thrust 1 will construct the first adsorption atlas for pathological matrices, systematically mapping how drug chemistry and matrix composition interact. Thrust 2 will translate these parameters into predictive models and transport charts, yielding adsorption windows that connect molecular energetics to therapeutic outcomes. Thrust 3 will leverage these models to design interventions around reducing, exploiting, or reprogramming adsorption that are validated by blinded predictions and culminate in an intervention playbook. Together, these efforts convert adsorption from an overlooked liability into a designable determinant of therapeutic fate. While initially focused on antibiotics in airway mucus and biofilms, the framework generalizes to biologics, nanoparticles, and oncology, where adsorption governs drug sequestration in protein coronas, depots, and tumor stroma. By establishing adsorption as a quantifiable and designable rate process, this program fulfills the mira mission: shifting drug delivery from trial-and-error toward predictive, systems-level design.