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Pharmacology and Therapeutics

Connecting Rodent and Human Pharmacokinetic Models for the Design and Translation of Glucose-Responsive Insulin

  1. Jing Fan Yang1,
  2. Xun Gong1,
  3. Naveed A. Bakh1,
  4. Kelley Carr2,
  5. Nelson F.B. Phillips2,
  6. Faramarz Ismail-Beigi2,
  7. Michael A. Weiss3 and
  8. Michael S. Strano1⇑
  1. 1Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA
  2. 2Department of Biochemistry, Case Western Reserve University, Cleveland, OH
  3. 3Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN
  1. Corresponding author: Michael S. Strano, strano{at}mit.edu
Diabetes 2020 Aug; 69(8): 1815-1826. https://doi.org/10.2337/db19-0879
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    Figure 1

    Schematic of the model structure. Glucose (blue) circulates around the body along with blood, which is pumped by the heart and flows through vascular compartments of gut, liver, kidneys, brain, muscle, and adipose tissues. For the latter three, transcapillary diffusion of glucose into interstitial spaces is captured by the interstitial compartments. Insulin or GRI (orange), introduced into the circulation via the subcutaneous injection depot, flows through all but the brain interstitial compartment, into which insulin is unable to penetrate. Each compartment is equivalent to a CSTR (as shown on the right), where perfect mixing is assumed. INT., interstitial; VAS., vascular.

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    Figure 2

    Blood glucose responses in rodents to a single insulin injection. A–D: The agreement between murine in vivo data (squares) and the predicted glycemic responses (curves) to various doses of nonresponsive insulin administered at t = 0. PAMERAH predictions match well with experimental measurements from healthy (A) and T1DM rats (B) as well as healthy (C) and T1DM mice (D). Curves for rats are presented individually to avoid overlapping of data points and confidence limits, which indicate ±1 SD. Data were collected from male Lewis rats, the diabetes of which was induced by STZ (Supplementary Material Text 1). Measurements on mice (male C57BL/6J, STZ) are extracted from Chou et al. (11). The corresponding error bars are absent because they were undefined in Chou et al., and the clustered error bars cannot be precisely digitized from the original figures. E and F: The 24-h action profiles of a GRI example (kf = 0.1 L/mol-min, Keq = 0.02 L/mol, dosage = 300 μg/kg) in average diabetic rats (E) and mice (F). The blood glucose concentration drops to the normoglycemic range within 120 min after the initial injection at t = 0 and each of the three meal ingestions (1 g/kg glucose at t = 420, 720, and 1,080 min), periods represented by the unshaded areas. The peak postprandial concentrations are respectively 423.8, 434.9, and 450.2 mg/dL for diabetic rats and 415.2, 430.5, and 450.4 mg/dL for diabetic mice. The dashed lines indicate the upper bounds of normoglycemic ranges. Conc., concentration.

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    Figure 3

    Glucose clamp results simulated by PAMERAH compared with experiments. A: Glucose is clamped at 110 mg/dL (period 1) and 240 mg/dL (period 2) for 150 min each with constant infusion of either nonresponsive insulin or GRI, as described in research design and methods. B–D: Consistent with the published experimental data (37), the HGLs (B) for insulin and GRI do not differ at either clamp level. While the NHGBs (C) are positive in period 1, they switch signs at the higher clamp level, indicating a change from net glucose production to consumption in the liver. As with experiments (right), GRI induces a larger change than the nonresponsive control in period 2. Similarly, while both the GRI and the insulin groups trigger a surge in unidirectional HGU (D) at t = 150 min, GRI is more effective, a feature captured by the simulation. Data in B–D are normalized by the respective period 2 steady-state values for the insulin group due to the differences in GRI mechanisms and test animals. *P < 0.05 for GRI vs. control. E and F: Responsiveness of GRI and insulin to various glucose levels is shown alongside data from clamps (43). While the amount of active GRI released is increasing with the clamp level (E), the concentration of nonresponsive insulin (F) shows no dependence. Note that in the clamps described, GRI is solely responsible for the observed responsiveness because the pancreatic insulin production is inhibited by somatostatin. The concentrations in E and F are normalized by the corresponding values at 120 mg/dL. The prenormalization GRI concentrations ranged from 165.8 mU/L (at 120 mg/dL) to 290.4 mU/L (at 280 mg/dL) for simulations in rats and from 761.5 to 933.3 mU/L for MK-2640 in dogs. All experimental data are digitized from published figures. Conc., concentration.

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    Figure 4

    Exploring the optimal combinations of GRI design parameters for efficacy in rodents. PAMERAH explores the GRIDS and evaluates the hypo- and hyperglycemic risks associated with each GRI candidate for both healthy (A) and diabetic (B) rats. The shaded areas in GRIDS are the ODRs, which represent those combinations of kf, Keq, and dosage free of hypoglycemic (top), hyperglycemic (middle), or both (bottom, intersection of the other two single-risk ODRs) risks. The gray planes in B mark the global minimum effective dosage in diabetic rats. The GRI designs, which incur neither risk in normal and diabetic rats alike, are shaded blue (C). The characteristic L shape is consistent with prior reports (5), better visualized by contour plots (D) sliced at fixed GRI dosages (30, 150, and 300 μg/kg) (marked gray in the GRIDS). The colors in D correspond to the sum of all hypo- and hyperglycemic risks combined, with dark blue representing desirable GRI constructs that maintain normoglycemia over 24 h. ODRs and GRIDS for mice and humans are found in Supplementary Fig. 7. The inverted U symbol indicates intersection.

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    Figure 5

    Evaluating the GRI translatability from rodents to humans. A: The commonalities (solid) between ODRs (colored and outlined) of humans and rats (left), humans and mice (middle), and rats and mice (right). B: The ODR intersection (solid) is marked among all three species. The limited overlap between human and rodent ODRs forecasts the difficulties in interspecies translation of the therapeutic. C: By relaxing the dosage variable (0–330 μg/kg) and allowing it to assume flexible values for different species, we project the three-dimensional GRIDS onto a two-dimensional kf-Keq plot. We call the plot a translatability grid on which GRI designs are zoned according to their translatability. GRI constructs in zone 1 are predicted to be effective in both rodents and humans. They therefore translate well among species with appropriate dosages. Zones 2 and 3 represent the false-negative designs eliminated in rodent studies yet potentially clinically viable. Zones 4 and 5 are examples of false positives that appear effective in rat/mouse trials but do not translate well into humans. They will likely meet attrition at the clinical stage.

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Connecting Rodent and Human Pharmacokinetic Models for the Design and Translation of Glucose-Responsive Insulin
Jing Fan Yang, Xun Gong, Naveed A. Bakh, Kelley Carr, Nelson F.B. Phillips, Faramarz Ismail-Beigi, Michael A. Weiss, Michael S. Strano
Diabetes Aug 2020, 69 (8) 1815-1826; DOI: 10.2337/db19-0879

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Connecting Rodent and Human Pharmacokinetic Models for the Design and Translation of Glucose-Responsive Insulin
Jing Fan Yang, Xun Gong, Naveed A. Bakh, Kelley Carr, Nelson F.B. Phillips, Faramarz Ismail-Beigi, Michael A. Weiss, Michael S. Strano
Diabetes Aug 2020, 69 (8) 1815-1826; DOI: 10.2337/db19-0879
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