Methods for determining key components in a mathematical model for tumor–immune dynamics in multiple myeloma. (7th December 2018)

• Record Type: Journal Article
• Authors: Gallaher, Jill; Larripa, Kamila; Renardy, Marissa; Shtylla, Blerta; Tania, Nessy; White, Diana; Wood, Karen; Zhu, Li; Passey, Chaitali; Robbins, Michael; Bezman, Natalie; Shelat, Suresh; Jay Cho, Hearn; Moore, Helen
• Is Part Of: Journal of theoretical biology. Volume 458(2018)
• Page Start: 31
• Page End: 46
• Publication Date: 2018-12-07
• Subjects: Disease modeling -- Sensitivity analysis -- Identifiability -- Latin hypercube sampling -- Partial rank correlation coefficient; Biology -- Periodicals; Biological Science Disciplines -- Periodicals; Biology -- Periodicals; Biologie -- Périodiques; Theoretische biologie; Biology; Periodicals; 571.05
• DOI: 10.1016/j.jtbi.2018.08.037
• Languages: English
• ISSNs: 0022-5193

Abstract

Highlights: We explore a mathematical model of multiple myeloma that was presented previously. We justify model parameter ranges and values using published data and calculations. We use global methods to determine parameters the model is most sensitive to. We determine which of those parameters could be estimated from data. We numerically explore the behavior of the model over time. Abstract: In this work, we analyze a mathematical model we introduced previously for the dynamics of multiple myeloma and the immune system. We focus on four main aspects: (1) obtaining and justifying ranges and values for all parameters in the model; (2) determining a subset of parameters to which the model is most sensitive; (3) determining which parameters in this subset can be uniquely estimated given certain types of data; and (4) exploring the model numerically. Using global sensitivity analysis techniques, we found that the model is most sensitive to certain growth, loss, and efficacy parameters. This analysis provides the foundation for a future application of the model: prediction of optimal combination regimens in patients with multiple myeloma.