your personal guide in managing multiple sclerosis

MS SHERPA

...Using modern digital technology to monitor MS activity,

resulting in real world data on patient mobility, cognition and

fatigue.

...Getting clinically valid and relevant disease activity biomarkers in

between MS patients regularly clinical check ups.

...Getting noti�ed when a patient is showing disease activity and

thus getting the opportunity to adapt treatment directly when

needed

...How monitoring day to day disease activity will help your

patients get control over their disease. Improving adherence to

prescribed therapy and quality of life.

Imagine...

The biggest challenge in healthcare is and will be to deliver �tting and

a�ordable healthcare. Your health is not mine and my experience of �tting

care is di�erent from yours. With modern data science we are now able to

deliver high quality personalized healthcare at scale.

Orikami, a data science boutique specialised in health solutions, uses

advanced analytics to help deliver individualized diagnosis, prognosis and

treatment. Our health products are inherently personal: They combine and

�nd individual patterns in one’s biomarker data, lifestyle data and personal

preferences.

INTRODUCTION

When it comes to Multiple Sclerosis, people with this chronic condition all

follow their own highly individualized and so far unpredictable disease course.

We believe we can improve Quality of Life for persons with Multiple Sclerosis

by delivering personalized diagnosis, personal insights and eventually

personalized treatment. Our �rst step on this journey is day to day monitoring

of disease activity.

“We dream about a world where we treat your health

instead of a one-size-�ts-all treatment for the entire

population”

- Bram den Teuling, CEO Orikami B.V.

MS INDIVIDUAL TREATMENT IS MISSING DATAMultiple sclerosis (MS) is a highly heterogeneous neurodegenerative disease with a heavy

personal, economic and societal burden. No two people have the same combination of symptoms

and disease course is highly variable and unpredictable. Currently, clinical features and magnetic

resonance imaging (MRI) are used for diagnosis, prognosis and classi�cation of treatment

responders versus nonresponders. This strategy works for large patient cohorts, but because of

the variability of the disease, not for any individual patient.

Currently we see a lack of regular monitoring in Multiple Sclerosis1. Furthermore there is a lack of

monitoring disease activity in real world situations (outside of the clinic). In practice we often see

unsupervised gaps of more than 6 months, visits to a clinic only take place if patients take initiative

to contact their doctor and report their relapses. It is therefore mostly unknown if disease activity

is under control by current treatment. Because of the lack of monitoring patients feel

misunderstood and feel a lack of control over their disease, resulting in insecurity, dealing with

unpredictable setbacks over time and reduced quality of life. According to current consensus

regular monitoring of clinical and subclinical disease activity needs to become central to the

management of MS.

DAY TO DAY MS MONITORING

Our solution is a standalone software application intended to improve

the quality of life of persons with MS. The smartphone application and

wearable device (optionally) gives persons with MS more control over

their disease by helping them to self-monitor their disease activity and

giving them personal insights based on the prevalence of symptoms

related to MS. The app measures day-to-day disease activity with respect

to the following parameters:

• Walking ability

• Signal processing speed

• Patient reported outcomes (PRO) by means of visual analogue scales

(VAS) for in�uence of MS on his or her daily functioning, energy,

mood, stress, memory, concentration and pain

• Total active minutes per day (in case the user also uses the Fitbit

activity tracker)

MORE DIGITAL BIOMARKERS COMMING SOON

The app shows changes in disease activity over time per parameter, and

combines the parameters into a personal pro�le of the user, on which

the personal insights are based.

Any given time there seems to be signi�cant disease activity or the disease

doesn’t seem to be under control, you as the attending physician will be

able to get a signal. So you will be able to take a look at the test results,

invite the patient for an early consultation, and probably prevent things

from deteriorating, for instance by adjusting therapy.

PERSONS WITH MS: USER EXPERIENCE & BENEFITSWe believe patient engagement is crucial in delivering e�ective

monitoring to personalize diagnosis and treatment. Our e�orts are

therefore focussed on optimizing usability. Our solution is co-created

with a small group of patients and the local MS Patient Federation2. Here

you will �nd outcomes of several patient surveys on this speci�c topic.

1. A questionnaire conducted under 150 persons with MS without prior

knowledge about our product. 70% of MS patients are interested in

monitoring their disease. With the main reasons:

• Insights in disease progression and causes of symptoms.

• Provide data for their physicians.

• Insight in disease to take action

• Objective information on how it is going and was going over a period

of time.

2. We closely monitor our own co-creation/pilot group. In a small cohort

(5 people) we were able to maintain high levels of self-monitoring. All �ve

participants engaged at least once a week at one year and three out of the

�ve held this fairly constant in the subsequent 3 months. One participant

stopped using the app because the disease severity became too high

(EDSS >7.5).

3. During the MS Zelf study (see research section) the tests in the app are

being validated for clinical use. MS patients use the app for 4 weeks. The

evaluation of the in�uence of MS on their functioning is done on a daily

basis as requested by the researchers, whereas the walking test and

cognition test are requested every three days. The �rst twelve

participants used di�erent functionality of the app on between 60% and

100% of the requested days (see �gure).

Yes, I would like to monitor my MS with an app (61,6%)

Yes, I monitor my MS but I use something else for this (8,4%)

No, I don’t have the need to monitor my MS (18,9%)

Other (11,2%)

We believe patient engagement is crucial in delivering e�ective

monitoring to personalize diagnosis and treatment. Our e�orts are

therefore focussed on optimizing usability. Our solution is co-created

with a small group of patients and the local MS Patient Federation2. Here

you will �nd outcomes of several patient surveys on this speci�c topic.

1. A questionnaire conducted under 150 persons with MS without prior

knowledge about our product. 70% of MS patients are interested in

monitoring their disease. With the main reasons:

• Insights in disease progression and causes of symptoms.

• Provide data for their physicians.

• Insight in disease to take action

• Objective information on how it is going and was going over a period

of time.

2. We closely monitor our own co-creation/pilot group. In a small cohort

(5 people) we were able to maintain high levels of self-monitoring. All �ve

participants engaged at least once a week at one year and three out of the

�ve held this fairly constant in the subsequent 3 months. One participant

stopped using the app because the disease severity became too high

(EDSS >7.5).

3. During the MS Zelf study (see research section) the tests in the app are

being validated for clinical use. MS patients use the app for 4 weeks. The

evaluation of the in�uence of MS on their functioning is done on a daily

basis as requested by the researchers, whereas the walking test and

cognition test are requested every three days. The �rst twelve

participants used di�erent functionality of the app on between 60% and

100% of the requested days (see �gure).

0

20

40

60

80

100Day evaluation

Cognition test

Walking test

2520151051

“Using the app in combination with the wearable contributes to

my health. I’m more active because it gets more fun.”

- Janine, MS patient co-creation group, 43 years

Perc

enta

ge o

f par

ticip

ants

Days of the study

NotificationAccording to the data we have from your patient Jan van Kagel we advice you to check the data to see if it neccessary to plan a consult with him

GO TO DATAdismiss

RELEVANCE FOR PHYSICIANS

Modern technology can be used to address some of the inequalities in

access to diagnostic services and ongoing specialist care for people with

MS. There is also evidence that monitoring can improve adherence to

prescribed DMTs (which is associated with fewer serious relapses and

lower medical costs than non-adherence) and that data from monitoring

can be used to encourage conversations and collaboration between

people with MS and their healthcare professionals. Increased

engagement of people with MS in shared treatment decisions, is more

likely to take place if the routine monitoring of disease activity and

safety parameters becomes commonplace1.

• Many relapses go unreported. In turn, whether or not a relapse is

reported can depend on how frequently a person with MS sees a

neurologist.

• Systematically monitoring clinical and subclinical indicators of

disease activity can help to identify treatment failure (suboptimal

response to the current DMT). This, in turn, enables prompt

switching to an alternative DMT to be considered.

• The recommended treatment strategy of early intervention, regular

monitoring and timely switching of therapy to maximize lifelong

brain health, has the potential to reduce disability progression and

therefore to avoid some of these long-term costs.

Our solution enables people with MS to measure their own day to day

disease activity and is able to give an alert to physicians when there are

signs for disease activity.

The project won the second price on the �rst European MS Hackathon

21-22 may 20163 and has been selected by the european commission as

‘good practice’.4

RESEARCHWe have and will be conducting extensive research to understanding

day-to-day real world outcomes of our product, to deliver a reliable and

valid product. We reviewed the literature and present here documents

to understand relevance, reliability and validity. Furthermore, we have

conducted a clinical study in collaboration with the Nationaal MS Fonds

in Rotterdam, NL.5 We have been looking for proof that the walking and

cognition tests of our solution are comparable to standard clinical tests.

The one month study includes 30 MS patients and 100 Healthy controls.

A �rst pilot is being conductedwith VUmc (Amsterdam, NL) and MS

Research (Voorschoten, NL) in which 100 patients and 100 controls will

be followed with the product for 1 year, while comparing it to disease

activity as found on MRIs and in clinical tests.

KEY INSIGHTS

1. Walking ability is measured using the 2-Minute Walking Test (2MWT).

This variant of the frequently used 6-Minute Walking Test takes less time

to perform and is a smaller burden to persons with MS, especially to

those with decreased mobility.6 In our research we compared our

implementation of a self-administered 2MWT with the literature (see

�gure for some preliminary results N=10). Currently, a two-sample

75

100

125

150

175

200

225

250

75

100

125

150

175

200

225

250 HC

MS

MS Zelf study2MWT literature

Pilutti et al. 2013(n=256+49)

Orikami MS apppreliminary (n=9+9)

Wal

king

test

Dis

tanc

e w

alke

d (m

)

KS-test on the data collected with the orikami MS app yields a p-value

below 0.05.

2. Signal processing speed is measured during a cognition test, which is

a digital variant of the well-known symbol-digit-modalities-test (SDMT).

In the past 5 years, the SDMT has become the most commonly used test

to evaluate information processing speed in persons with MS.7 Alternate

versions of the test, including digital ones8, yield data nearly identical

with the standard test from Western Psychological Services.9 In our

research we compare our cognition test with paper based SDMT results.

A two-sample KS-test on the data we collected yields a p-value below

0.05.

3. Day-to-day disease activity measurement is partially possible through

the usage of VAS to obtain PRO on levels of energy, mood, stress,

memory, concentration, pain and and the in�uence of MS on daily

functioning. For some participants of the MS Zelf study, we found a

modest anticorrelation between the number of active minutes per day

measured with the Fitbit (see below) and the PRO of the in�uence of MS

on his/her daily functioning (Pearson's r = -0.5). Furthermore, we found

that a person scores signi�cantly lower on the cognition test on the days

where the PRO of the in�uence of MS on the daily functioning is the

highest. This can be seen in the following �gure, where the shaded areas

(between dotted lines) indicate the 1-sigma deviation from the mean

values.

4. To get insight into real-world daily physical behavior, a person’s total

active minutes per day, as well as his/her heart rate and sleep duration,

can continuously be monitored with an activity tracker such as the Fitbit.

A preliminary result of the MS Zelf study is that the Fitbit measures a

signi�cantly lower number of total active minutes per day for persons

with MS than for HC (two-sample KS-test p=0.02).

30

35

40

45

50

55

60

65

7075

2

3

4

5

6

7

8In�uence of M

S on daily functioning

cogn

ition

test

(SD

MT)

sco

re

15129630

Days of the study

We have and will be conducting extensive research to understanding

day-to-day real world outcomes of our product, to deliver a reliable and

valid product. We reviewed the literature and present here documents

to understand relevance, reliability and validity. Furthermore, we have

conducted a clinical study in collaboration with the Nationaal MS Fonds

in Rotterdam, NL.5 We have been looking for proof that the walking and

cognition tests of our solution are comparable to standard clinical tests.

The one month study includes 30 MS patients and 100 Healthy controls.

A �rst pilot is being conductedwith VUmc (Amsterdam, NL) and MS

Research (Voorschoten, NL) in which 100 patients and 100 controls will

be followed with the product for 1 year, while comparing it to disease

activity as found on MRIs and in clinical tests.

KEY INSIGHTS

1. Walking ability is measured using the 2-Minute Walking Test (2MWT).

This variant of the frequently used 6-Minute Walking Test takes less time

to perform and is a smaller burden to persons with MS, especially to

those with decreased mobility.6 In our research we compared our

implementation of a self-administered 2MWT with the literature (see

�gure for some preliminary results N=10). Currently, a two-sample

30

35

40

45

50

55

60

65

70

75

30

35

40

45

50

55

60

65

70

75 HC

MS

MS Zelf studySDMT Literature

Lopez-Gongora et al. 2015(n=237+57))

Orikami MS apppreliminary (n=7+7)

SDM

T te

stCo

rrec

t ans

wer

s

KS-test on the data collected with the orikami MS app yields a p-value

below 0.05.

2. Signal processing speed is measured during a cognition test, which is

a digital variant of the well-known symbol-digit-modalities-test (SDMT).

In the past 5 years, the SDMT has become the most commonly used test

to evaluate information processing speed in persons with MS.7 Alternate

versions of the test, including digital ones8, yield data nearly identical

with the standard test from Western Psychological Services.9 In our

research we compare our cognition test with paper based SDMT results.

A two-sample KS-test on the data we collected yields a p-value below

0.05.

3. Day-to-day disease activity measurement is partially possible through

the usage of VAS to obtain PRO on levels of energy, mood, stress,

memory, concentration, pain and and the in�uence of MS on daily

functioning. For some participants of the MS Zelf study, we found a

modest anticorrelation between the number of active minutes per day

measured with the Fitbit (see below) and the PRO of the in�uence of MS

on his/her daily functioning (Pearson's r = -0.5). Furthermore, we found

that a person scores signi�cantly lower on the cognition test on the days

where the PRO of the in�uence of MS on the daily functioning is the

highest. This can be seen in the following �gure, where the shaded areas

(between dotted lines) indicate the 1-sigma deviation from the mean

values.

4. To get insight into real-world daily physical behavior, a person’s total

active minutes per day, as well as his/her heart rate and sleep duration,

can continuously be monitored with an activity tracker such as the Fitbit.

A preliminary result of the MS Zelf study is that the Fitbit measures a

signi�cantly lower number of total active minutes per day for persons

with MS than for HC (two-sample KS-test p=0.02).

MS sherpa is an orikami service to help you personalize MS treatment:

• Using modern technology to monitor MS activity, resulting in real world data on patient

mobility and fatigue.

• Getting you quick overviews of objective clinically validated test results over the entire

period of time since your patient's last visit whenever you need it.

• Getting you automated alerts when patient data points towards relapses.

• Giving you the opportunity to adapt treatment as soon as needed.

• Giving your MS patients the opportunity to gain control again over their life by

monitoring day to day MS activity.

• Helping your patients to improve adherence to prescribed therapy.

• Helping your patients increase their quality of life.

CONCLUSION

REFERENCES

1 Giovannoni, Gavin, et al. "Brain health: time matters in multiple sclerosis." Multiple sclerosis and related disorders 9 (2016): S5-S48.

2 www.msvereniging.nl

3 www.mshackathon.nl

4 www.esifundsforhealth.eu

5 NL61291.028.17 conducted by Orikami, DrugtargetID, Ms4Research, Dutch MS Fund

6 D. Gijbels, B.O. Eijnde, P. Feys, Multiple Sclerosis Journal 17-10, 2011

7 S.L. Costa, H.M. Genova, J. DeLuca et al., Multiple Sclerosis Journal 23-6, 2017

8 N. Akbar, K. Honarmand, N. Kou et al., Journal of Neurology 258-3, 2011

9 R.H.B. Benedict, A. Smerbeck, R. Parikh et al., Multiple Sclerosis Journal 18-9, 2012

10 C. Finke, L.M. Pech, C. Sömmer, Journal of Neurology 259-12, 2012