Subject-Specific Dosage Estimation for Primary Hypothyroidism Using Sparse Data

Abstract

Subject-specific dosage estimation for primary hypothyroidism using subject-specific parameters of the thyrotropic regulation system is presented in this work. The data needed for such personalized modeling are usually sparse. This is addressed by utilizing available data along with domain knowledge for estimation of model parameters but with some uncertainty. Optimization-based dosage estimation approaches may not be applicable in the presence of such uncertainty. In this work, the optimal drug dosage range based on estimated parameter ranges for primary hypothyroid condition is estimated using the mathematical model through satisfiability modulo theory (SMT)-based analysis. The salient features of this work are as follows: (1) estimation of subject-specific model parameters with uncertainty using subject-specific pre-treatment and post-treatment observations, (2) modeling periodic drug administration as part of the ordinary differential equation model of thyrotropic regulation pathway through Fourier series approximation, (3) application of SMT-based analysis for determining optimal dosage range using this model and estimated parameter ranges, and (4) an initial dosage estimation method using the regression model. Results have been obtained to support the working of the developed computational procedures.