A History Of Insulin & Pumps
Past, Present, and Future
John Walsh, P.A, C.D.E.
jwalsh@diabetesnet.com
Online slide presentation

Early history of diabetes
Discovery of insulin
When insulin was found to not be the full answer
High glucose as the culprit
Lack of change in the A1c since the DCCT
Why the dumb insulin pump has not helped
What smart pumps offer
The promise of intelligent devices
The Super Bolus
How simple and intelligent timers can help
Screen shots from an intelligent device
© 2004, John Walsh, P.A., C.D.E.

In 1500 BC
Diabetes First Described In Writing
Hindu healers wrote that flies and ants were attracted to urine of people with a mysterious disease that caused intense thirst, enormous urine output, and wasting away of the body
© 2004, John Walsh, P.A., C.D.E.

Apollonius of Memphis coined the name
"diabetes” meaning "to go through" or siphon. He understood that the disease drained more fluid than a person could consume.
Gradually the Latin word for honey,
"mellitus," was added to diabetes because it made the urine sweet.
© 2004, John Walsh, P.A., C.D.E.

150 BC
Aretaeus the Cappadocian
Diabetes is a wonderful affection, not very frequent among men, being a melting down of the flesh and limbs into urine…The flow is incessant, as if from the opening of aqueducts…it takes a long period to form, but the patient is shortlived…for the melting is rapid, the death speedy.
Moreover, life is disgusting and painful; thirst unquenchable; excessive drinking…and one cannot stop them either from drinking or making water... they are affected with nausea, restlessness, and a burning thirst; and at no distant term they expire.
© 2004, John Walsh, P.A., C.D.E.

In 1000, Greek physicians recommended horseback riding to reduce excess urination
In the 1800s, bleeding, blistering, and doping were common
In 1915, Sir William Osler recommended opium
Overfeeding was commonly used to compensate for loss of fluids and weight
In the early 1900s a leading American diabetologist, Dr. Frederick Allen, recommended a starvation diet
© 2004, John Walsh, P.A., C.D.E.

In 1798, John Rollo documented excess sugar in the blood and urine
In 1813, Claude Bernard linked diabetes to glycogen metabolism
In 1869, Paul Langerhans, a German medical student, discovered islet cells in the pancreas
In 1889, Joseph von Mehring and Oskar Minkowski created diabetes in dogs by removing the pancreas
In 1910, Sharpey-Shafer of Edinburgh suggested a single chemical was missing from the pancreas. He proposed calling this chemical "insulin."
© 2004, John Walsh, P.A., C.D.E.

In 1908, a young internist in Berlin, Georg Ludwig
Zuelzer created a pancreas extract named acomatrol.
After injecting acomatrol into a dying diabetic patient, the patient improved at first, but died when the acomatrol was gone
Zuelzer filed an American patent in 1911 for a
"Pancreas Preparation Suitable for the Treatment of Diabetes”
Disappointing results, however, caused his lab to be taken over by the German military during WWI
© 2004, John Walsh, P.A., C.D.E.

American scientist E. L. Scott was partially successful in extracting insulin with alcohol
A Romanian, R. C. Paulesco, made an extract from the pancreas that lowered the blood glucose of dogs.
Some claim Paulesco may have been the first to discover insulin about 10 years before Banting and Best.
© 2004, John Walsh, P.A., C.D.E.

JL on 12/15/22 and 2 mos later
Before insulin was discovered in 1921, everyone with type 1 diabetes died within weeks to years of its onset
© 2004, John Walsh, P.A., C.D.E.

In Jan, 1922, Banting and Best injected a
14-yearold "charity” patient who weighed
64 lb with 7.5 ml of a "thick brown muck" in each buttock
Abscesses developed and he became more acutely ill
However, his blood glucose had dropped enough to continue refining what was called "iletin” insulin
6 weeks later, a refined extract caused his blood glucose to fall from 520 to 120 mg/dL in 24 hours
Leonard lived a relatively healthy life for 13 years before dying of pneumonia (no Rx then) at 27
© 2004, John Walsh, P.A., C.D.E.

First produced as
“Connaught” by the Univ of Toronto
On May 30, 1922, Eli Lilly signed an agreement to pay royalties to the
University to increase production
First bottles contained U-10 insulin
3 to 5 cc were injected at a time
Pain and abscesses were common until purer U-40 insulin became available
© 2004, John Walsh, P.A., C.D.E.

Age at start of diabetes
Avg. age of death in 1897
Avg. age of death in 1945
Years Gained
50
58.0
65.9
8
30
34.1
60.5
© 2004, John Walsh, P.A., C.D.E.
26
10
11.3
45.0
34

Some early users died of hypoglycemia, but insulin seemed a remarkable cure.
By the 1940’s, however, diabetic complications began to appear
It became clear that injecting insulin was not the full answer
© 2004, John Walsh, P.A., C.D.E.

High Glucose Versus Genes
During the middle of the 20th century, it was unclear whether better glucose control could prevent diabetes complications
© 2004, John Walsh, P.A., C.D.E.

Research studies between 1970 and 2000 showed that complications could be prevented by lowering high glucose levels
Studies
DCCT 1984-1992
EDIC 1996
UKPDS 1978-1998
Kumamoto 1992-2000
Results
Better health
Fewer complications
Improved sense of well-being
More flexible lifestyle
© 2004, John Walsh, P.A., C.D.E.

Little Change In A1c Since DCCT
8.6% in 396 Canadian Type 1s in 1992 2
9.7% in 1,120 German children in 1996 3
9.7% in in U.S. in NHANES III, 1988 to 1994
8.6% in 2,873 European children and adolescents in 1997 1
9.2% in 62 Canadian Type 1s in 2004
GOAL: A1c < 6.5%
1.
2.
3.
HB Mortensen et al: Diabetes Care. 1997 May;20(5):714-20
Diabetes Care. 1997 May;20(5):714-20
Horm Res 1998;50:107
–140
© 2004, John Walsh, P.A., C.D.E.

We Know What Controls The A1c
Frequency of testing
378 pump (pre-smart) users Paul Davidson et al: Diabetes
© 2004, John Walsh, P.A., C.D.E.

Controls The A1c
Frequency of daily boluses
377 1-18 yo pump users, r = 0.068 TJ Battelino et al: Diabetes 2004
For injections: MP Garancini et al: Diabetes Care, 1997, 20, #11: 1659-1663
© 2004, John Walsh, P.A., C.D.E.

Controls The A1c
Recording of BGs
0.5% drop in A1c in several studies
Diet Approach 1
CHO Counting
Regulated
WAG
7.2%
7.5%
8.0%
1. Bode et al: Diabetes, 1999, 48 Suppl 1: 264
© 2004, John Walsh, P.A., C.D.E.

1992 2003
On 4 inj. 27.8% (0.4%) 72.6% (6.4%) or a pump
Median A1c 8.3% 8.3%
18,403 German children
W Hecker et al: 2004 ADA, poster 22B
© 2004, John Walsh, P.A., C.D.E.

Inaccurate carb counting *
Insulin doses that are incorrect, misunderstood, or missed entirely *
Too hard to log all the data *
Not adapting to spontaneous events *
Complexity of the challenge *
Unclear accountability *
* handled by well-designed intelligent device
© 2004, John Walsh, P.A., C.D.E.

Noncompliance is not a patient problem.
It is a system failure.
Dr. Paul Farmer
First to successfully use complex drug regimens to treat AIDs and TB in Haiti
© 2004, John Walsh, P.A., C.D.E.

Current Treatment Interval (CTI)
Unlike many other chronic diseases where
CTI is not critical, the current treatment interval in diabetes with a doctor’s visit every 3 to 4 months does not work
© 2004, John Walsh, P.A., C.D.E.

Required Treatment Interval (RTI)
The required treatment interval in diabetes is every 2 to 5 hours rather than 3 to 4 months
This is the typical time interval between decisions that significantly affect glucose levels, such as BG monitoring, food intake, and activity
Only something that is both available and intelligent can assist the person with a chronic disease like diabetes
© 2004, John Walsh, P.A., C.D.E.

When a system is not working for patients, trying harder will not work.
Only changing the care system or our approach to care will work.
© 2004, John Walsh, P.A., C.D.E.

r i t o
M o n i n g s u
I n i l n r y v e i l
D e
Insulin & syringes
You are here
Pumps
Pens
Data Management
Connectivity
Open Loop
Advice/Feedback
Closed Loop
Home Monitors
Clinic Monitoring
HCP Self Management Automation
Convergence Toward Automation
© 2004, John Walsh, P.A., C.D.E.

Results over Features!
Do not judge a device by how cool it is, but by whether it lowers the A1c.
© 2004, John Walsh, P.A., C.D.E.

Carb boluses
Personalized carb factors for different times of day
Easy carb bolus calculations
Personalized carb database (soon)
Correction boluses
Personalized correction factors for different times
Easier and safer correction of high BGs
Reveal when correction bolus is high, ie > 8% of TDD
Combined carb/correction boluses
Automatic bolus reduction for Bolus On Board
(BOB)
© 2004, John Walsh, P.A., C.D.E.

Track Bolus On Board
Improved bolus accuracy
Avoids stacking of bolus insulin
Helps prevent hypoglycemia
Requires BG reading for accuracy
Guide whether carbs or insulin are needed
Does not yet warn when carbs are needed
© 2004, John Walsh, P.A., C.D.E.

Reminders to
Test blood glucose after a bolus
Warn when bolus delivery was not completed
Test blood glucose following a low or high BG
Give boluses at certain times of day
Change infusion site
Direct BG entry from meter
Eliminates errors in data transfer
Ensures that all blood glucose data will be entered into a database or logbook format
© 2004, John Walsh, P.A., C.D.E.

Today’s pumps collect the information needed (insulin doses, BGs, carb intake, and timing), but they do not:
Identify problem patterns
Automatically test basals and boluses or warn when they are out of balance
Suggest dose adjustments
Warn of pending lows or suggest carb intake needed for excess BOB
Warn when excess correction boluses are used
Account for GI differences between foods
Guarantee an improved outcome
© 2004, John Walsh, P.A., C.D.E.

Today’s “smart” pumps are migrating to better pumps, pens, and PDAs
Calculus rather than formulas to set bolus amounts
Auto analysis of BG patterns
Fuzzy and artificial intelligence
Provide automatic (retrospective) carb/insulin balance
Use of A1c to focus therapy
© 2004, John Walsh, P.A., C.D.E.

The Intelligent Device Hypothesis
Intelligent devices: provide meaningful advice, * improve lifestyles, * improve medical outcomes with diabetes.
*
* Yet to be proven
Made by
Unidentified company here
© 2004, John Walsh, P.A., C.D.E.

Feature
Carb list
Basal testing
Bolus testing
Exercise
Timer
Corr. bolus
Super Bolus
# of hypos
Smart
Alphabetic
By user
By user
NA
Manual
Ignored
None
By user
Communication Verbal
© 2004, John Walsh, P.A., C.D.E.
Intelligent
By recent use
Automatic
Automatic
Automatic
Automatic
Redistributed
Automatic
Automatic
Bidirectional

Pumps
Pens
PDAs
Smart Phones
Meters
A central reporting station where data is filtered for minor versus major problems and who is to be alerted (user, guardian, MD/RN)
© 2004, John Walsh, P.A., C.D.E.

Intuitive interface and language
Must be impartial and fair
Outcome driven – user feels better and is more confident about control
Compatible with clinic workflow
Well funded
Able to rapidly evolve as errors appear
Must close the data loop between user and MD
© 2004, John Walsh, P.A., C.D.E.

Automatic BG timer
Automatic basal decrease
Super Bolus
Automatic basal/bolus balancing
Automatic adjustment when correction boluses are overused
Carb list and carb counter
Exercise intensity and duration
Database intelligence
© 2004, John Walsh, P.A., C.D.E.

Provide immediate advice on situations
Identify common or infrequent patterns
Constant surveillance of data for changes
Provide real meaning to BG values
Integrate well with continuous monitoring and artificial intelligence
© 2004, John Walsh, P.A., C.D.E.

Fast internet & email communication
Convenient remote insulin delivery
Larger food and carb database
Better graphics for BG analysis, display of patterns, etc
Larger event database for long-term analysis
© 2004, John Walsh, P.A., C.D.E.

300 personal carb selections with accurate carb counts
Carb factor (1:1 TO 1:100)
Correction factor (1:4 to 1:
400)
© 2004, John Walsh, P.A., C.D.E.
5 sec microdraw BG meter
0.1 unit precision motor
Non-volatile memory
3,000 events
Bluetooth data transfer

© 2004, John Walsh, P.A., C.D.E.

Basal insulin
~ 50% of daily insulin need
Limits hyperglycemia after meals
Suppresses glucose production between meals and overnight
Bolus insulin (mealtime)
Limits hyperglycemia after meals
Immediate rise and sharp peak at 1 hour
10% to 20% of total daily insulin requirement at each meal
© 2004, John Walsh, P.A., C.D.E.

A rapid basal reduction offsets excess BOB and eliminates the need to eat at bedtime.
© 2004, John Walsh, P.A., C.D.E.

A Super Bolus can be activated at a user-selected quantity, such as 40 or 50 grams
A Super Bolus helps cover high GI foods and prevent postmeal hyperglycemia. A 3 or 4 hour block of basal insulin is turned into a bolus to speed its effect.
© 2004, John Walsh, P.A., C.D.E.

To ensure safety and success, the Super
Bolus will require some clinical testing:
How long can basal delivery be stopped or reduced without increasing the risk for clogging of the infusion line
How long (3, 4, 5 hours?) can the basal be lowered before a rebound high will occur once the Super Bolus is gone?
Is a reduction of the basal delivery rather than complete stoppage a better policy?
If a person sets their basal delivery too low or too high, will this affect a Super Bolus?
© 2004, John Walsh, P.A., C.D.E.

If a pumper misjudges the carb content of a meal, a super bolus enables a faster, safe correction.
© 2004, John Walsh, P.A., C.D.E.

A simple timer alerts the user 25 minutes after a bolus that it is safe to begin eating a high GI meal.
© 2004, John Walsh, P.A., C.D.E.

An intelligent pump alerts the user when their
BG is likely to cross a selected threshold value, such as 120 mg/dl. They can then eat without exposure to extremely high readings.
© 2004, John Walsh, P.A., C.D.E.

The lower the blood glucose is at the start of a meal, the less exposure to glucose there will be.
© 2004, John Walsh, P.A., C.D.E.

An intelligent pump alerts the user when their blood glucose is low enough to begin eating
© 2004, John Walsh, P.A., C.D.E.

Useful reminders
© 2004, John Walsh, P.A., C.D.E.

Finding problem patterns enables solutions
Set BG targets
Gather and record data
Analyze patterns in data
Assess factors that influence patterns
Recommend action
© 2004, John Walsh, P.A., C.D.E.

The relatively low number of BG patterns in diabetes makes them easy to identify:
High most of the time
Frequent lows
High mornings (lunches, dinners, bedtime)
Low mornings (lunches, dinners, bedtime)
Postmeal spiking
High to low
Low to high
Poor control with little or no pattern
© 2004, John Walsh, P.A., C.D.E.

.
320
.
38
10 pm
Overtreated low
© 2004, John Walsh, P.A., C.D.E.

Insulin dose suggestions and an alert about past overtreatment of lows.
© 2004, John Walsh, P.A., C.D.E.

An intelligent device can provide a person’s precise carb requirement when the blood glucose is tested.
© 2004, John Walsh, P.A., C.D.E.

Breakfast
232
194
217
243
178
263
222
Breakfast highs
© 2004, John Walsh, P.A., C.D.E.

300 basal too low just right
Dawn
Phenomenon
200
100 just right too high bedtime 2 am breakfast
Goal for overnight BG change = +/- 30 mg/dl
© 2004, John Walsh, P.A., C.D.E.

User Interface – Critical Component
Despite 30 years of pump and meter development, device communication to the user is still in it’s infancy.
© 2004, John Walsh, P.A., C.D.E.

Carb database for accurate carb counts.
© 2004, John Walsh, P.A., C.D.E.

Suggestion for carb intake or to limit intake based on weight/calorie/carb goals
© 2004, John Walsh, P.A., C.D.E.

A high glucose can be analyzed to determine the magnitude of the error
© 2004, John Walsh, P.A., C.D.E.

Recommended carb intake (or insulin reduction) to balance activity.
© 2004, John Walsh, P.A., C.D.E.

New dose recommendations based on
A1c, % of TDD given as correction boluses, and frequency of hypoglycemia
© 2004, John Walsh, P.A., C.D.E.

Pattern alerts and advice
© 2004, John Walsh, P.A., C.D.E.

Fast lab results without calling. Messaging allows physician to make recommendations.
© 2004, John Walsh, P.A., C.D.E.

Automatic basal and bolus testing
Trends allow exact short-term BG predictions for rapid recognition of pending highs or lows
Both user and device can relate problems to their source
Unfortunately, insulin delivery from an external pump is too slow to create an effective artificial pancreas with this combination
© 2004, John Walsh, P.A., C.D.E.

The Closed Loop Will Close Slowly
Patents impede device development
FDA is slow to allow medical care from a device or via telemedicine
Slow acceptance by medical personnel and people with diabetes
Liability issues
Large financial incentives in current meter and pump technology
Even so, truly intelligent and helpful devices could be created soon.
© 2004, John Walsh, P.A., C.D.E.

© 2004, John Walsh, P.A., C.D.E.