Optimal Experimental Design for Parameter Estimation of an IL-6 Signaling Model

IL-6 signaling plays an important role in inflammatory processes in the body. While a number of models for IL-6 signaling are available, the parameters associated with these models vary from case to case as they are non-trivial to determine. In this study, optimal experimental design is utilized to reduce the parameter uncertainty of an IL-6 signaling model consisting of ordinary differential equations, thereby increasing the accuracy of the estimated parameter values and, potentially, the model itself. The D-optimality criterion, operating on the Fisher information matrix and, separately, on a sensitivity matrix computed from the Morris method, was used as the objective function for the optimal experimental design problem. Optimal input functions for model parameter estimation were identified by solving the optimal experimental design problem, and the resulting input functions were shown to significantly decrease parameter uncertainty in simulated experiments. Interestingly, the determined optimal input functions took on the shape of PRBS signals even though there were no restrictions on their nature. Future work should corroborate these findings by applying the determined optimal experimental design on a real experiment

Optimal Experimental Design for Parameter Estimation of an IL-6 Signaling Model

IL-6 signaling plays an important role in inflammatory processes in the body. While a number of models for IL-6 signaling are available, the parameters associated with these models vary from case to case as they are non-trivial to determine. In this study, optimal experimental design is utilized to reduce the parameter uncertainty of an IL-6 signaling model consisting of ordinary differential equations, thereby increasing the accuracy of the estimated parameter values and, potentially, the model itself. The D-optimality criterion, operating on the Fisher information matrix and, separately, on a sensitivity matrix computed from the Morris method, was used as the objective function for the optimal experimental design problem. Optimal input functions for model parameter estimation were identified by solving the optimal experimental design problem, and the resulting input functions were shown to significantly decrease parameter uncertainty in simulated experiments. Interestingly, the determined optimal input functions took on the shape of PRBS signals even though there were no restrictions on their nature. Future work should corroborate these findings by applying the determined optimal experimental design on a real experiment

Enhanced neoepitope-specific immunity following neoadjuvant PD-L1 and TGF-b blockade in HPV-unrelated head and neck cancer

BACKGROUND: Head and neck squamous cell carcinoma not associated with human papillomavirus (HPV-unrelated HNSCC) is associated with high rates of recurrence and poor survival. METHODS: We conducted a clinical trial in 14 patients with newly diagnosed, HPV-unrelated HNSCC to evaluate the safety and efficacy of neoadjuvant bintrafusp alfa, a bifunctional fusion protein that blocks programmed death-ligand 1 (PD-L1) and neutralizes transforming growth factor-beta (TGF-). RESULTS: Bintrafusp alfa was well tolerated, and no treatment-associated surgical delays or complications occurred. Objective pathologic responses were observed and 12 of 14 patients (86%) were alive and disease free at one year. Alterations in regulatory T cell infiltration and spatial distribution relative to proliferating CD8 T cells indicated reversal of Treg immunosuppression in the primary tumor. Detection of neoepitope-specific tumor T cell responses, but not viral-specific responses, correlated with development of a pathologic response. Detection of neoepitope-specific responses and pathologic responses in tumors was not correlated with genomic features or tumor antigenicity but was associated with reduced pre-treatment myeloid cell tumor infiltration. These results indicate that dual PD-L1 and TGF- blockade can safely enhance tumor antigen-specific immunity and highlight the feasibility of multi-mechanism neoadjuvant immunotherapy in patients with HPV-unrelated HNSCC. CONCLUSION: Our studies provide new insight into the ability of neoadjuvant immunotherapy to induce polyclonal neoadjuvant-specific T cell responses in tumors and suggest that features of the tumor microenvironment, such as myeloid cell infiltration, may be a major determinant of enhanced anti-tumor immunity following such treatment