(189l) Optimal Design of Feasible Clinical Tests for the Identification of Physiological Models of Type 1 Diabetes Mellitus | AIChE

(189l) Optimal Design of Feasible Clinical Tests for the Identification of Physiological Models of Type 1 Diabetes Mellitus

Authors 

Galvanin, F. - Presenter, University College London
Bezzo, F., University of Padova

Type
1 diabetes mellitus (T1DM) is a metabolic disorder characterised by inadequate
insulin secretion, causing damaging imbalance to the glucoregulatory system.
Cutting edge therapies involve the use of a wearable artificial pancreas (WAP),
that is a device capable of maintaining physiological glucose concentration
through accurate insulin infusions. A WAP consists of three elements: a glucose
sensor, an insulin pump and a control algorithm. Customisation of this device
to the individual needs may be accomplished provided that a precise identification
of the diabetes physiological model [1] used in the control algorithm is
performed [2]. The identification procedure is typically carried out by means
of clinical tests, such as the oral glucose tolerance test (OGTT) or the
intravenous glucose tolerance test (IVGTT).

Model-based
design of experiment (MBDoE) techniques have already been applied to the design
of clinical tests for the identification of individual parameters in subjects
with T1DM [3,4], however, the feasibility requirements are not always
satisfied. Considering the possibility of improving standard clinical tests,
this work applies MBDoE techniques to devise a new physiological test, whose
pivotal feature is its implementation feasibility. In order to satisfy this condition,
a novel approach based on heuristic indices is hereby introduced to assess
several aspects that could impact the most on the practical applicability of
the designed protocol. Therefore, the overall evaluation of the test is
performed considering 5 indices, taking into account the following features:
information, invasivity, safety, duration and number of samples.

A
constrained MBDoE strategy, applied to the design of a modified OGTT lasting 5h
[5], where sampling times are optimised while controlling insulin infusion and
imposing constraints on safety, generates the optimal test shown in Figure 1a.
In the MBDoE formulation, the lower bound on glucose concentration is treated
as a hard constraint (hypoglycaemic conditions are harmful even in the short period)
while the upper bound is treated as a soft constraint (hyperglycaemic
conditions can be tolerated for short periods of time). The designed protocol (MOGTT)
is easy to implement both in terms of insulin administration and glucose
measurement and also guarantees safety conditions throughout the execution. Evaluation
of the designed protocol through in silico studies attests its statistically
satisfactory parameter estimation capabilities and its high robustness. Beyond
its parameter identification performance, the MOGTT complies with the requirements
imposed by feasibility. In fact, the effectiveness of this MBDoE approach is
proved by a comparison between the OGTT and the MOGTT protocols in terms of the
indices introduced (Figure 1b): safety is deeply improved and information
obtainable is maximised.

Finally,
the significant enhancement of the information index reflects on the MOGTT
exhibiting excellent parameter estimation even upon utterly different
parametric sets.

                                                    (a)                        
                                                                        (b)

Figure 1: Glucose profiles of the MOGTT and OGTT, along
with sampling times and insulin infusion profile, horizontal dots represent
glucose bounds imposed in the design (a). Indices radar chart comparing MOGTT
and OGTT performance (b).   References

[1] Balakrishnan,
N. P.; Rangaiah, G. P.; Samavedham, L. Review and analysis of blood glucose
(BG) models for type 1 diabetic patients
. Ind. Eng. Chem. Res. 2011; 50(21):12041-12066.

[2] Cobelli, C.;
Renard, E.; Kovatchev, B. Artificial pancreas: Past, present, future.
Diabetes 2011; 60(11): 2672-2682.

[3]
Galvanin, F.; Barolo, M.; Macchietto, S.; Bezzo, F. Optimal design of
clinical tests for the identification of physiological models of type 1
diabetes in the presence of model mismatch
. Med. Biol. Eng. Comput. 2011; 49(3):
263-277.

[4]
Galvanin,
F.; Barolo, M.; Macchietto, S.; Bezzo, F. Optimal design of clinical tests
for the identification of physiological models of type 1 diabetes mellitus
.
Ind. Eng. Chem. Res. 2009; 48, 1989-2002.

[5]
Man,
C. D.; Campioni, M.; Polonsky, K. S.; Basu, R.; Rizza, R.A.; Toffolo, G. et al.
Two-hour seven-sample oral glucose tolerance test and meal protocol: Minimal
model assessment of β-cell responsivity and insulin sensitivity in
nondiabetic individuals
. Diabetes 2005; 54(11): 3265-3273.