[NMusers] Webinar with Dr. Trujillo, Merck on QSP Model for Proinsulin to Insulin Conversion Therapy

From: Rebecca Baillie <rbaillie_at_rosaandco.com>
Date: Wed, 3 Jul 2019 00:37:14 +0000

Leveraging a Diabetes QSP Model to Drive Decisions in Target Identification=
 and Validation for Proinsulin to Insulin Conversion Therapy

Maria Trujillo PhD
Principal Scientist, Merck and Co Inc, Kenilworth, NJ

July 18, 2019 12:00-1:00 PM EDT
Registration (Free) at https://register.gotowebinar.com/register/4089794427=

Abstract: Proinsulin is a precursor to insulin that is co-secreted into the=
 blood by the beta cell as a result of incomplete processing. Circulating p=
roinsulin levels increase with increasing insulin resistance in type 2 diab=
etes mellitus (T2DM). Unlike insulin, proinsulin has limited activity on th=
e insulin receptor. To assess whether the development of peptides engineere=
d to convert proinsulin to insulin in the blood would provide therapeutic v=
alue in T2DM, we leveraged a diabetes quantitative systems pharmacology (QS=
P) model (a physiologically based computational model of glucose homeostasi=
s in humans); internal clinical datasets, and external data from the litera=

In silico hypothesis testing included 1) the addition and qualification of =
proinsulin biology into our diabetes QSP model, 2) the creation of virtual =
patients (VP) to determine whether proinsulin conversion therapy may provid=
e value to a subpopulation of patients with T2DM based on phenotypic traits=
, either as a monotherapy or in addition to standards of care (sulfonylurea=
s and metformin), and 3) the simulation of a phase 3 clinical trial with re=
levant endpoints (including HbA1c and glucose, insulin, and proinsulin) and=
 additional mechanistic readouts (changes in circulating hormones and metab=
olites during meals and glucose tolerance tests) to interrogate and interpr=
et results.

As monotherapy, proinsulin conversion to insulin led to a ~0.2% reduction i=
n HbA1C in diabetic VPs with lesser effects (~0.1%) when added to a standar=
d of care. Virtual patients with higher proinsulin: insulin ratios at basel=
ine showed the greatest reductions. However, to achieve a clinically meanin=
gful HbA1C reduction of 0.5%, most VPs needed ratios above the reported=
 physiological range. The minimal influence of proinsulin conversion could =
be explained by the proinsulin secretion and degradation rates relative to =
respective rates for insulin; these system dynamics were a key learning fro=
m the QSP modeling effort.

The lack of projected impact on HbA1C through conversion of proinsulin to i=
nsulin was not intuitive prior to the in silico hypothesis testing using QS=
P approaches. The simulation results were examined and challenged with rigo=
r both quantitatively and qualitatively and led to a recommendation not to =
pursue proinsulin conversion as a potential T2DM therapy. The QSP modeling =
approach was chosen to capture not only the dynamic interplay between proin=
sulin and insulin kinetics but their impact on a complex multi-organ system=
 that maintains glucose homeostasis in the body. By thoroughly evaluating t=
he putative therapeutic in diabetic VPs in a Phase 3 setting, we were able =
to generate sufficient scientific rationale for the termination decision. T=
his effort demonstrates how in silico hypothesis testing through QSP modeli=
ng may aid in target identification and validation efforts in the discovery=
 space, conserving R&D resources for targets with greater probability of cl=
inical success.

Received on Tue Jul 02 2019 - 20:37:14 EDT

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