Designing and leveraging ‘high throughput’ aspects of efficient engineering models can
increase their relevance in understanding biological systems. This thesis explores the use of
design of experiments, optimization, and perturbation analysis to fit models to two complex
cardiovascular problems: one computational (Case A: Living Heart Project®) and one
experimental (Case B: FlowMAP™).
A) The Living Heart Project® considers the physiological optimization and calibration of an
electro-mechanical computational heart model designed for virtual patient testing. Given
several interdependent parameters that interact nonlinearly, understanding how to best fit the
model to specific individuals and disease states is challenging. This thesis discusses
strategies of calibration and considers methods of increasing software and hardware
efficiency to enable efficient, multivariate optimization for complex models of living systems.
B) FlowMAP™ is a platform technology developed in a research setting that allows detailed
measurement of an individual´s clotting and bleeding risk by constructing an experimentally
derived ´model´ of an individual´s blood state. It is a microfluidic-based technology that,
having completed preliminary laboratory testing, now requires translation for clinical
diagnostic applications such as improved, personalized management of conditions such as
heart attack and stroke. This study describes the manufacturing and scale up of the
technology, to permit precisely controlled measurement of blood clotting and enable
assessment and prediction of a patient’s clotting and bleeding risk.
While each scenario is distinct, together they demonstrate a relevant cross-functional work
path that combines computational and experimental models to reduce the translational gap
that exists between research environments, market application, and clinical viability. |