ubiqi pitch deck
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Get insights. Better health.
Jacqueline Thongco-founder / CEO

Healthcare is not serving the patient...
OK, I’ll give it a try but I’ve already tried so many different meds!
I’m not sure what to recommend for your increased pain... maybe you can try this new drug?

Big data... big dealPower of secondary data lost if not used to change healthcare delivery
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How can patient data be useful?
Personal Discovery Engine
DISEASE TRACKER
PASSIVE MOBILE/DEVICE DATA
3RD PARTY DATA
PERSONALIZED FEEDBACK
CLINICAL EFFECTIVENESS
ITERATE
Ubiqi provides a structured experiment framework

BASELINE SAMPLE HYPOTHESES
We power “citizen science” through n=1 experiments
A B B A
A A B B
RANDOMIZATION OUTCOME AGGREGATION
PATIENT:Identify triggersUnderstand symptomsCompare therapiesReport side-effects
HEALTHCARE ORGANIZATIONS:Understand patient behaviorAnalyze patient responseCompare therapiesReview safety data

Apply same framework across multiple conditions
pain respiratory gastrointestinal

We create value for many healthcare organizations
PATIENT
PAYER
PHARMACY BENEFITS
MGMT
PHARMACY CHAINS PROVIDERS DISEASE
MGMT
PHARMA HEALTHCARE IT (EMR)

$1-5PER USER PER MONTH
Software-as-a-Service revenue model
$50-100KBASE SETUP
1X
GROWS WITH USER BASEONE-TIME FEE

Addressable market is 63M people in US alone
250MAMERICANS COVERED BY HEALTH INSURANCE
125MHAVE CHRONIC CONDITION
63MBENEFIT FROM SELF-MANAGING
OUR ADDRESSABLE MARKET

Ubiqi has a unique approachACTIONABLE INSIGHTS
PATIENT-DRIVEN PROTOCOLS
CONDITION TRACKING
PROVIDER-DRIVEN PROTOCOLS
UBIQI
RINGFUL HEALTH
STUDY CURE
GENOMERA
THECARROT

30+ years of experience in healthcare, technology, and design
Jacqueline Thong, CEOAnshuman Sharma, CTOWilliam Tang, Design Lead
ADVISORS ESTHER DYSONJAYANT PARTHASARATHY, PHDCHRIS ADAMS, MBA, PHDEGILIUS SPIERINGS, MD, PHDMATTHEW MAMET

We have strong resultsFrom initial migraine minimum viable product: 18K+ patients 20% active for more than 6 months Positive health outcomes!
Paying customer
Partnerships
In discussion
Partnerships

Go-to-market approach
MIGRAINEMVP
REPLICATE MODEL FORBACK PAIN
MINIMUM VIABLE PRODUCT - Prove utility to patients- Gather data- Evaluate pharma interest- Validate pharma revenue model
REFINEPRODUCT FOR
MIGRAINE
REFINE PLATFORM - Prove clinical validity - Gather data- Scale pharma model- Evaluate payer interest
SCALE PLATFORM - Prove utility beyond migraine- Gather data- Validate payer revenue model

Payers are our key target; first build credibility
2013 $600K
2014 $4M
2015 $16M
PHARMA PILOTS
SCALE PHARMA MODEL
PAYER PILOTS
SCALE PAYER MODEL
2016 $45M
2017 $75M REVENUE

Seeking guidance in partnership development and $700KKEY USE OF FUNDS FOR Q12013 - Q42013
3%3%
9%
10%
20%
55%
R&DBusiness developmentCOGSAdminB2B MarketingUser acquisition

We envision acquisition by a payer or disease management company
Disease management companies
Healthcare payers

That’s great! Let’s work together to make that even better.
I saw that when I do yoga AND take the new meds, my daily pain scores are 20% lower!
Help us create this alternative future!

Get insights. Better health.
Jacqueline Thongco-founder / [email protected]+1 617 794 2089www.ubiqihealth.com

Financial projections

ROI to pharmaExample: Eli Lilly / Boehringer-Ingelheim’s Tradjenta
Revenues are $3.5B annually (2.3M pts)Adherence is 50% for oral anti-diabetic medicationsEstimated $1.75B revenue lost per year250K patients enroll in UbiqiAt $5 per patient per monthB-I PAYS UBIQI $1.25M (1 year)
10% of users get better results25K patients increase adherence to 75%B-I INCREASES REVENUES BY: +$47M (1 year)

ROI to payersExample: Aetna has 16 million subscribers
8% have asthma, costs them $2500/pt25% enroll in Ubiqi program: 320K subscribersAt $1 per member per month...AETNA PAYS UBIQI $3.8M (1 year)
25% of users get better results80K subscribers reduce ER visits, hospital visits, unnecessaryprescription meds, save $500 each/yrAETNA SAVES: $40M (1 year)

Intellectual PropertyItems we anticipate constitute defensible IP:i) process of taking structured / unstructured data and extractingfeature sets that are disease-specific and map to clinical evidence;
ii) learning engine which allows user to construct personalizedexperiments that they can run to create evidence;
iii) algorithm that makes suggestions on what pieces of anexperiment the user might want to choose to ensure success basedon base-line and crowd-sourced data;
iv) algorithm that aims to increase the information contained inunstructured patient-reported data to have stronger mappingbetween evidence and outcomes