NewtherapiesinType1Diabetes · ArtiicialPancreas Objecve Insulindeliverymodulaon Reduce%severity%and/or%duraon%of% hypoglycemia Suspension%of%insulin%delivery%at hypoglycemia(low%glucose%suspend)%

New therapies in Type 1 Diabetes

Carol Huang, MD, PhD Alberta Children’s Hospital University of Calgary

Outline

• History of insulin • Ar=ficial Pancreas •  Inhaled insulin •  “Smart” insulin

History of Insulin

•  1869 -‐ Paul Langerhans iden4fy “Islets” in the pancreas •  1889 – Oscar Minkowski removed pancreas from dogs to study diges4on, and found the dogs have sugar in their urine – first link of pancreas and diabetes

•  1906/1916 – George Ludwig Zuelzer/Nicolae Paulescu were par4ally successful trea4ng dogs with pancrea4c extract

•  1921 –Ban4ng, Best, kept a diabe4c dog Marjorie alive for the en4re summer by injec4ng her with the pancrea4c extract. Macleod and Collip assisted them to purify fetal calf pancreas

•  Jan 11, 1922 – Leonard Thompson received the first insulin injec4on, but impurity caused severe allergic reac4on. Jan 23, second injec4on successfully eliminated glycosuria. First American pa4ent, Elizabeth Hughes Gosse[, daughter of the governor of New York.

•  November, 1922 – Eli Lilly and Company was able to make large quan4ty of insulin for sale.

History of Insulin •  1930s-‐1950s – long-‐ac4ng insulin, protamine zinc insulin was used to reduce the number of injec4ons needed

•  1950s – neutral protamine Hagedorn (NPH) became available •  1977 – Arthur Riggs and Keiichi Itakura at City of Hope and Herbert Boyer at Genetech made the first gene4cally engineered human insulin using E. Coli

•  1982 – Genetech and Eli Lilly sold the first commercially available biosynthe=c human insulin (Humulin)

•  1993 – DCCT showed importance of good glycemic control

History of Insulin

•  1996 – Lispro (Humalog) •  2000 – Aspart (Novo Rapid), Glargine (Lantus) •  2004 – Glulisine (Apidra) •  2005 – Detemir (Levemir) •  2006 – Exubera® launched (withdrawn in 2007) •  2008 – Ontario funds insulin pump •  2013 – Alberta funds insulin pump •  (2013 – degludec – rejected by FDA) •  (Oct 2013 – MannKind filed for inhaled insulin approval with FDA)

•  Oct 2013 – FDA approved “ar=ficial pancreas” – MiniMed 530G (Metronic)

Arti:icial Pancreas

BMC Medicine, 2011

Arti:icial Pancreas Objec=ve Insulin-‐delivery modula=on

Reduce severity and/or dura4on of hypoglycemia

Suspension of insulin delivery at hypoglycemia (low glucose suspend)

Hypoglycemia preven4on Pre-‐emp4ve suspension

Control to range Modula4on of insulin delivery outside target range to limit hypo/hyperglycemia

Closed-‐loop system with meal/exercise announcement

Modula4on of insulin delivery aher meals using boluses administered by pa4ent with announcement of these, and exercise to the algorithm

Fully closed-‐loop system Modula4on of insulin delivery when the control algorithm is unaware of meals, exercise, stress and other lifestyle disturbances that affect glucose control; glucagon may be co-‐administered to reduce risk of hypoglycemia

BMC Medicine, 2011

BMC Medicine, 2011

Nocturnal Glucose Control with an Arti:icial pancreas at camp

•  Mul4na4onal (Israel, Germany, Slovenia) •  Safety and efficacy of an ar4ficial pancreas system for control of night 4me glucose levels in pa4ents (10-‐18 year olds) at diabetes camp

•  Compare “closed-‐loop” (i.e. ar4ficial pancreas) vs. “open-‐loop” (i.e. sensor-‐augmented insulin pump)

•  Primary goal: •  Number of hypoglycemia (sensor glucose value of <3.5mmol/L for at least 10 consecu4ve minutes)

•  Time spend with glucose levels <3.3 mmol/L •  Average overnight glucose levels

NEJM, 2013


•  Insulin pump (Paradigm Veo, Metronic) •  Sensor (Enlite sensor, Medtronic) •  Alarms for BG>19.4mmol/L or BG<4.2 mmol/L)

•  Glucose meter (Contour) •  Finger poke at meals, 2 hrs post meals, bed4me, 3-‐hour intervals throughout the night

•  Info on all meals, hypoglycemic episodes, exercise were used to derive personalized sepngs for the ar4ficial pancreas

NEJM, 2013


•  Ar4ficial pancreas and remote monitoring system •  MD-‐Logic

•  wireless, fully automated closed-‐loop system uses an algorithm based on •  fuzzy-‐logic theory (to imitate the line of reasoning of diabetes caregivers) •  a learning algorithm and •  an alerts module and personalized system sepngs

•  Insulin is administered according to the glucose readings in a fully automated manner without informa4on on the size or 4me of meals

•  Uses an individual pa4ent’s treatment management •  Insulin delivery regimen (i.e. basal insulin plan and insulin correc4on factor) •  Insulin pharmacodynamic parameters •  Pa4ents physical characteris4cs •  CGM readings •  Glucometer measurements •  Physical ac4vity

è Use all of the above to determine insulin treatment NEJM, 2013


•  Fuzzy-‐logic •  Science of reasoning, thinking, and inference that recognizes that not everything is true or false in the real world

•  The correctness of any statement becomes a ma[er of degree •  Main elements of the fuzzy logic controller:

•  Fuzzy sets of mul4ple inputs •  Single or mul4ple outputs •  Fuzzy rules structured according to the form of •  IF (input) – THEN (output) and methods of “fuzzifica4on” and

“defuzzifica4on” to evaluate the fuzzy rule output based on the input

NEJM, 2013


NEJM, 2013

(3.5)

(3.3)

(7.0) (7.8)


NEJM, 2013


NEJM, 2013


NEJM, 2013

Feasibility of Outpa=ent Fully Integrated Closed-‐Loop Control

First studies of wearable ar4ficial pancreas

Featured Ar=cle:

Boris P. Kovatchev, Ph.D., Eric Renard, M.D., Ph.D., Claudio Cobelli, Ph.D., Howard C. Zisser, M.D., Patrick Keith-‐Hynes, Ph.D., Stacey M. Anderson, M.D., Sue A. Brown, M.D.,

Daniel R. Chernavvsky, M.D., Marc D. Breton, Ph.D., Anne Farret, M.D., Ph.D., Marie-‐Josée Pelle4er, M.D., Jérôme Place, M.S.C., Daniela Bru[omesso, M.D., Ph.D., Simone del Favero, Ph.D., Roberto Visen4n, M.S.C., Alessio Filippi, M.D., Rachele Sco[on, M.D.,

Angelo Avogaro, M.D., Ph.D., Francis J. Doyle III, Ph.D.

Diabetes Care Volume 36: 1851-‐1858

July, 2013

Feasibility of outpatient Fully Integrated Closed-‐Loop Control

•  Inexpensive •  wearable hardware

•  computa=onally capable of running closed-‐loop control algorithms

• Wirelessly connectable to CGM devices and insulin pumps

•  Capable of broadband communica=on for remote monitoring and safety supervision

Objectives

•  To evaluate the feasibility of a wearable ar=ficial pancreas system, the Diabetes Assistant (DiAs)

•  System uses a smart phone as a closed-‐loop control

plaZorm

Kovatchev B. P. et al. Diabetes Care 2013;36:1851-‐1858

Study Designs and Methods

•  20 pa4ents with type 1 diabetes were enrolled at the Universi4es of Padova, Montpellier, and Virginia and at the Sansum Diabetes Research Ins4tute

•  U.S. studies were conducted en4rely in an outpa4ent sepng •  Studies in Italy and France were hybrid hospital–hotel admissions •  A con4nuous glucose monitoring/pump system was placed on the

subject and was connected to DiAs •  Pa4ent operated the system via the DiAs user interface in open-‐

loop mode (first 14 h of study), switching to closed-‐loop for the remaining 28 h

•  Study personnel monitored remotely via 3G or WiFi connec4on to DiAs and were available onsite for assistance



Results

• Total dura=on of proper system communica=on func=oning was 807.5 h (274 h in open-‐loop and 533.5 h in closed-‐loop) •  97.7% of the total possible =me from admission to discharge represented •  Predetermined primary end point of 80% system func=onality was exceeded


Conclusions

•  Contemporary smart phones are capable of running outpa=ent closed-‐loop control

•  Future steps should include equipping insulin pumps

and sensors with wireless capabili=es, as well as studies focusing on control efficacy and pa=ent-‐oriented clinical outcomes


Arti:icial pancreas

Factor Desirable improvements

Insulin delivery Faster absorp4on (or intraperitoneal delivery)

Glucose sensing Increased accuracy and reliability; reduced false-‐posi4ve hypoglycemia alarms

Insulin modula4on Adap4ve algorithm

Dual-‐hormone systems Dual-‐chamber pumps

Communica4on between glucose sensor and insulin pump

More reliable connec4vity

Human factors Reduced size of devices

BMC Medicine, 2011

Inhaled Insulin

•  Technosphere insulin (IT), or Afrezza •  Lung allows faster absorp4on of insulin, reach blood earlier

Journal of Diabetes Science and Technology, 2012

Journal of Diabetes Science and Technology, 2012

Inhaled Insulin

The Lancet, 2010

Inhaled Insulin

•  Inhaled insulin at meal 4mes + bed4me insulin glargine (n=216) vs. twice daily premixed biaspart insulin (n=246)

•  Inhaled insulin was 4trated to target fas4ng and pre-‐dinner BG of 4.4-‐6.1 mmol/L

•  Followed for 52 weeks •  Argen4na, Brazil, Canada, Chile, Mexico, Poland, Russia, Spain, UK and USA

•  Technosphere insulin (IT, AFREZZA®) reach maximum blood concentra4ons ~14 min and a 4me to maximum effect of 35-‐40 min

The Lancet, 2010

Inhaled Insulin

The Lancet, 2010

Inhaled insulin + Glargine

Biaspart Insulin Difference

Change in HbA1c -‐0.66% -‐0.72% 0.06%

The Lancet, 2010

Inhaled Insulin

Inhaled insulin: less weight gain (0.9kg vs 2.5kg)

The Lancet, 2010

“Smart” insulin

ACSNANO, 2013

ACSNANO, 2013

Ques4ons?

Documents

NewtherapiesinType1Diabetes · ArtiicialPancreas Objecve Insulindeliverymodulaon Reduce%severity%and/or%duraon%of% hypoglycemia Suspension%of%insulin%delivery%at hypoglycemia(low%glucose%suspend)%