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Digital Medicine:
Returning Patients to the Center of Healthcare
George Savage, Co-Founder & Chief Medical Officer
Proteus Digital Health
Predictive Analytics World
October 30, 2017
@ProteusDH
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3
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Prescribe
Treat
Record
Response
Assess
Diagnose
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Prescribe
Treat
Record
Response
Assess
Diagnose
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JAMA. 1999;281(1):61-66. doi:10.1001/jama.281.1.61
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https://www.cdc.gov/mmwr/preview/mmwrhtml/mm4838a2.htm
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Prescribe
Treat
Record
Response
Assess
Diagnose
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Poor Treatment Adherence Problem
WHO 20033
Poor adherence to treatment of chronic diseases
is a worldwide problem of striking magnitude
Adherence to long-term therapy for chronic
illnesses in developed countries averages 50%
The impact of poor adherence grows as the
burden of chronic disease grows worldwide
The consequences of poor adherence to long-term
therapies are poor health outcomes and increased
health care costs
Improving adherence also enhances patients’
safety
Adherence is an important modifier of health
system effectiveness
Medication adherence
in heart failure1
Sources:
(1) Hauptman J, Heart Fail rev 2008;13:99
(2) Wong J, Can J Neurol Sci 2011; 38: 429
(3) Sabate E, WHO 2003, pp xiii-xiv.
Medication adherence
in multiple sclerosis2
17
Treatment Adherence Affects Outcomes
Kidney Transplantation1
Poor adherence to immunosuppression is
associated to graft loss
Tuberculosis2
Enhancing treatment adherence by directly
observed therapy (DOT) reduces relapses
and multi-drug resistance
Source:
(1) Pinsky BW, et al. Am J Transplant 2009; 9 :2597
(2) Weiss SE et al, N Engl J Med 1994;330:1179
Hazard ratio (p<0.001)
Fair adherence 1,63
Poor adherence 1,80
Rate(per100’000population)
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A new paradigm: ingestible computing
Tiny sensors are
embedded inside
small pills
A specified pharmacy puts these
pills inside a capsule along with
the patient's prescribed
medication on order of a physician
The sensor contains tiny amounts of silicon,
copper and magnesium that pass through
the body naturally, just like food
24
How it works
The sensor sends a
signal to the patch as it
passes through the
stomach
The patch sends this
information to the app
along with records of
activity and rest
The app allows patients
to see how they are
doing and share this with
their health care team via
the portal
Medications
with sensors
Used by patients Used by healthcare teams
Patch Discover app Discover portal
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Medications
with sensors
Prescribe
Treat
Record
Response
Assess
Diagnose
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Digital Medicines successful in “drug-refractory” hypertension and diabetes
Change in SBP
(mm Hg)
Change in LDL
(mg/dL)
Change in A1c
(%, Baseline ≥8)
Enter Trial: Week 24 after 24 weeks Analog Medicines: 0% at BP Goal
Complete Trial: Week 12 after 12 weeks Digital Medicines: 98% at BP Goal
Proteus Digital Medicines in Clinical Trial
Usual Care Analog Medicines in Clinical Trial
-24.6
-15.2
-30.1
-10.9 -0.31
0.26
Study Population, n=109
• SBP ≥140 mm Hg
• A1c ≥7%
• Diabetes duration ~10y
• Mean age = 59
• 57% earn < $20k/y
• 31% < high school
• 46% Hispanic
• 16% African American
• 22% psych comorbidity
• Ingestion adherence:
84% (12 weeks)
• Patch wear:
85%
• Patient satisfaction:
>90% stated digital
medicines easy to use
and helped take meds
regularly
• Net promoter score:
55 (patients)
57 (providers)
29
Real-world commercial experience shows a similar effect
Population
(N = 53; 40 have ≥6
months of data)
• Diagnosed CV or T2DM
• Mean age = 62
• 51% female
• 30% psychiatric
comorbidities
• 64% alcohol use
• 79% Caucasian
• Adherence:
87% (4 week use case)
• Patch wear:
94%
• Ease of use /
satisfaction:
95% stated Discover
easy learn to use
90% felt more
connected to their
healthcare team
84% said Discover
helped them understand
the importance of taking
meds regularly
154.4
90.8
139.4
82.0
140.5
83.3
60
100
140
Systolic Diastolic
90-day Pre-Proteus Proteus (avg 34 days) Follow-up (after off-boarding; average 165 days)
Reduction in SBP at follow-
up: -12.4 mm Hg; p<0.001
Reduction in
DBP at folllow-
up: -6.2 mm
Hg; p<0.001
BloodPressure(mmHg)
0.000
0.020
0.040
0.060
0.080
0.100
0.120
0.140
0.160
-12 -8 -4 0 4 8
37% reduction in ED visits
EmergencyDepartmentVisits/
Patient-Month
N=53; Mean ED visits on a per patient month difference [Pre:
0.094; Post: 0.059; Difference: -0.035; p-value: 0.280]
Months (Pre or Post-Discover start)
N=35 N=32 N=30 N=35 N=32 N=30
30
It is possible to achieve near-perfect adherence in high-risk hepatitis C patients
RESTRICTED
Medication pattern (Ledipasvir and Sofosbuvir)
Virologic outcomes:
• 20 patients with SVR12+
• 2 patients relapsed (one with documented suboptimal adherence
of <90% and the other with adherence ≥95%)2
Analytics-driven interventions
resulted in high medication
adherence in patients with
psychiatric comorbidities and
transient living situations
A targeted intervention
protocol for high risk Hepatitis
C patients with Proteus
Discover led to 97% of
adherence rate1
Study Population
• Number of patients: 283
• 1,838 days on Proteus
Discover
• Risk factors for poor
adherence include low
income (82% had <$25,000
annual income), current or
prior history of drug abuse
(for 39% of the population)
and psychiatric
comorbidities (for 46% of
the population)
• 39% patients required
targeted interventions
Footnotes:
1. Includes Proteus Discover analytics-
driven interventions
2. Other results pending
3. One patient discontinued although
interventions led to better adherence
92.0% 92.0% 88.0%
0%
20%
40%
60%
80%
100%
"DMO was easy to use in the
daily routine"
"Seeing data helped feel more
involved in the healthcare
treatment"
"DMO helped understand the
pattern of medication taking and
feel more connected to the
healthcare team"
Agree No comment / Disagree
Results Include Cure And High Patient Satisfaction
High Risk Patient Receives Intervention 44% of Time
31
50%
86%
84%
87%
94%
96%
97%
Average Adherence without Proteus
CMB Study (after 4 weeks on Proteus
Discover)
CMB Study (after 12 weeks on Proteus
Discover)
Real-World CMB Use Case (4 weeks on
Proteus Discover)
Pulmonary Arterial Hypertension (12 weeks
on Proteus Discover)
Tuberculosis Study (up to 14 weeks on
Proteus Discover)
Hepatitis C (8 - 12 weeks on Proteus
Discover)
Best Adherence Without Proteus
(based on medication possession data)
Adherence With Proteus
(based on medication ingestion data)
Digital Medicines yield similar effect across multiple conditions
“Wirelessly Observed Therapy”
captured 48% more doses than the
gold standard of directly observed
therapy
81% BP at goal after 4 weeks of
Discover Use
98% BP at goal after 12 weeks of
Discover Use
Demonstrated durability of BP effect
and downward trend in ED visits
Root cause for unresponsiveness to
treatment identified; Discover enabled
targeted treatment recommendations
High Adherence noted in patients with
risk factors for poor compliance
Widespread lack of medication
effectiveness
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Moore’s Law for technology, Eroom’s Law for pharma
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850 keynote savage_using his laptop

  • 1. 1 Digital Medicine: Returning Patients to the Center of Healthcare George Savage, Co-Founder & Chief Medical Officer Proteus Digital Health Predictive Analytics World October 30, 2017 @ProteusDH
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  • 16. 16 Poor Treatment Adherence Problem WHO 20033 Poor adherence to treatment of chronic diseases is a worldwide problem of striking magnitude Adherence to long-term therapy for chronic illnesses in developed countries averages 50% The impact of poor adherence grows as the burden of chronic disease grows worldwide The consequences of poor adherence to long-term therapies are poor health outcomes and increased health care costs Improving adherence also enhances patients’ safety Adherence is an important modifier of health system effectiveness Medication adherence in heart failure1 Sources: (1) Hauptman J, Heart Fail rev 2008;13:99 (2) Wong J, Can J Neurol Sci 2011; 38: 429 (3) Sabate E, WHO 2003, pp xiii-xiv. Medication adherence in multiple sclerosis2
  • 17. 17 Treatment Adherence Affects Outcomes Kidney Transplantation1 Poor adherence to immunosuppression is associated to graft loss Tuberculosis2 Enhancing treatment adherence by directly observed therapy (DOT) reduces relapses and multi-drug resistance Source: (1) Pinsky BW, et al. Am J Transplant 2009; 9 :2597 (2) Weiss SE et al, N Engl J Med 1994;330:1179 Hazard ratio (p<0.001) Fair adherence 1,63 Poor adherence 1,80 Rate(per100’000population)
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  • 23. 23 A new paradigm: ingestible computing Tiny sensors are embedded inside small pills A specified pharmacy puts these pills inside a capsule along with the patient's prescribed medication on order of a physician The sensor contains tiny amounts of silicon, copper and magnesium that pass through the body naturally, just like food
  • 24. 24 How it works The sensor sends a signal to the patch as it passes through the stomach The patch sends this information to the app along with records of activity and rest The app allows patients to see how they are doing and share this with their health care team via the portal Medications with sensors Used by patients Used by healthcare teams Patch Discover app Discover portal
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  • 28. 28 Digital Medicines successful in “drug-refractory” hypertension and diabetes Change in SBP (mm Hg) Change in LDL (mg/dL) Change in A1c (%, Baseline ≥8) Enter Trial: Week 24 after 24 weeks Analog Medicines: 0% at BP Goal Complete Trial: Week 12 after 12 weeks Digital Medicines: 98% at BP Goal Proteus Digital Medicines in Clinical Trial Usual Care Analog Medicines in Clinical Trial -24.6 -15.2 -30.1 -10.9 -0.31 0.26 Study Population, n=109 • SBP ≥140 mm Hg • A1c ≥7% • Diabetes duration ~10y • Mean age = 59 • 57% earn < $20k/y • 31% < high school • 46% Hispanic • 16% African American • 22% psych comorbidity • Ingestion adherence: 84% (12 weeks) • Patch wear: 85% • Patient satisfaction: >90% stated digital medicines easy to use and helped take meds regularly • Net promoter score: 55 (patients) 57 (providers)
  • 29. 29 Real-world commercial experience shows a similar effect Population (N = 53; 40 have ≥6 months of data) • Diagnosed CV or T2DM • Mean age = 62 • 51% female • 30% psychiatric comorbidities • 64% alcohol use • 79% Caucasian • Adherence: 87% (4 week use case) • Patch wear: 94% • Ease of use / satisfaction: 95% stated Discover easy learn to use 90% felt more connected to their healthcare team 84% said Discover helped them understand the importance of taking meds regularly 154.4 90.8 139.4 82.0 140.5 83.3 60 100 140 Systolic Diastolic 90-day Pre-Proteus Proteus (avg 34 days) Follow-up (after off-boarding; average 165 days) Reduction in SBP at follow- up: -12.4 mm Hg; p<0.001 Reduction in DBP at folllow- up: -6.2 mm Hg; p<0.001 BloodPressure(mmHg) 0.000 0.020 0.040 0.060 0.080 0.100 0.120 0.140 0.160 -12 -8 -4 0 4 8 37% reduction in ED visits EmergencyDepartmentVisits/ Patient-Month N=53; Mean ED visits on a per patient month difference [Pre: 0.094; Post: 0.059; Difference: -0.035; p-value: 0.280] Months (Pre or Post-Discover start) N=35 N=32 N=30 N=35 N=32 N=30
  • 30. 30 It is possible to achieve near-perfect adherence in high-risk hepatitis C patients RESTRICTED Medication pattern (Ledipasvir and Sofosbuvir) Virologic outcomes: • 20 patients with SVR12+ • 2 patients relapsed (one with documented suboptimal adherence of <90% and the other with adherence ≥95%)2 Analytics-driven interventions resulted in high medication adherence in patients with psychiatric comorbidities and transient living situations A targeted intervention protocol for high risk Hepatitis C patients with Proteus Discover led to 97% of adherence rate1 Study Population • Number of patients: 283 • 1,838 days on Proteus Discover • Risk factors for poor adherence include low income (82% had <$25,000 annual income), current or prior history of drug abuse (for 39% of the population) and psychiatric comorbidities (for 46% of the population) • 39% patients required targeted interventions Footnotes: 1. Includes Proteus Discover analytics- driven interventions 2. Other results pending 3. One patient discontinued although interventions led to better adherence 92.0% 92.0% 88.0% 0% 20% 40% 60% 80% 100% "DMO was easy to use in the daily routine" "Seeing data helped feel more involved in the healthcare treatment" "DMO helped understand the pattern of medication taking and feel more connected to the healthcare team" Agree No comment / Disagree Results Include Cure And High Patient Satisfaction High Risk Patient Receives Intervention 44% of Time
  • 31. 31 50% 86% 84% 87% 94% 96% 97% Average Adherence without Proteus CMB Study (after 4 weeks on Proteus Discover) CMB Study (after 12 weeks on Proteus Discover) Real-World CMB Use Case (4 weeks on Proteus Discover) Pulmonary Arterial Hypertension (12 weeks on Proteus Discover) Tuberculosis Study (up to 14 weeks on Proteus Discover) Hepatitis C (8 - 12 weeks on Proteus Discover) Best Adherence Without Proteus (based on medication possession data) Adherence With Proteus (based on medication ingestion data) Digital Medicines yield similar effect across multiple conditions “Wirelessly Observed Therapy” captured 48% more doses than the gold standard of directly observed therapy 81% BP at goal after 4 weeks of Discover Use 98% BP at goal after 12 weeks of Discover Use Demonstrated durability of BP effect and downward trend in ED visits Root cause for unresponsiveness to treatment identified; Discover enabled targeted treatment recommendations High Adherence noted in patients with risk factors for poor compliance Widespread lack of medication effectiveness
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  • 35. 35 Moore’s Law for technology, Eroom’s Law for pharma
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