titan medical market potential
TRANSCRIPT
J u n e 2 0 1 6
Market Analysis
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This presentation contains “forward-looking statements” which reflect the current expectations of management of the Company’s future growth, results of operations, performance and business prospects and opportunities. Wherever possible, words such as “may”, “would”, “could”, “will”, “anticipate”, “believe”, “plan”, “expect”, “intend”, “estimate”, “potential for” and similar expressions have been used to identify these forward-looking statements. These statements reflect management’s current beliefs with respect to future market potential and are based on information currently available to management. Forward-looking statements involve significant risks, uncertainties and assumptions. Many factors or related assumptions could cause the Company’s actual results, performance or achievements to be materially different from any future results, performance or achievements that may be expressed or implied by such forward-looking statements, including, without limitation, those risks and assumptions listed in the “Risk Factors” section of the Company’s Annual Information Form dated March 30, 2016 (which may be viewed at www.sedar.com). Should one or more of these risks or uncertainties materialize, or should assumptions underlying the forward looking statements prove incorrect, actual results, performance or achievements may vary materially from those expressed or implied by the forward-looking statements contained in this presentation. These factors should be considered carefully, and prospective investors should not place undue reliance on the forward-looking statements. Although the forward-looking statements contained in the presentation are based upon what management currently believes to be reasonable assumptions, the Company cannot assure prospective investors that actual results, performance or achievements will be consistent with these forward-looking statements. This presentation does not constitute an offer to sell any class of securities of the Company in any jurisdiction.
Forward Looking Statements, Risks, and Assumptions
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• American Hospital Directory (AHD)
• Centers for Medicare & Medicaid Services (CMS)
• Intuitive Surgical Annual Reports
• da Vinci Surgeon Locator
• Expert opinion provided by Reiza Rayman, President, Founder, Titan Medical
Data Sources
The following sources were commonly used to inform the assumptions and analyses in this document:
Limitations
Market Sizing
Executive Summary
Translating to Unit Sales
Conclusion
Limitations
Market Sizing
Executive Summary
Translating to Unit Sales
Conclusion
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• Titan has a market opportunity of approximately 1,120 healthcare facilities across US and Europe• 83% of facilities are in US, 17% in Europe• 87% of US opportunity is in hospitals, 13% in Ambulatory Surgery Centers (ASCs)
• Expected 1,965 unit sales opportunity in 15-year forecast• 73% of units are in US hospitals, 10% in US ASCs, and 17% in Europe• 77% are new units, while 23% are replacement units
• Titan could pursue a highly targeted marketing strategy• Targeting only 19% of US hospitals leads to a capture rate of 63% of target US hospital
market• Targeting only 6% of ASCs leads to a capture rate of 40% of target ASC market• 1st year sales have material impact on 15-year forecast, underscoring importance of starting
year sales• Replacements and 2nd unit sales comprise 30% of cumulative sales, underscoring
importance of ongoing relationships with healthcare facilities
Executive SummaryExecutive Summary
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A number of sales channels were considered in this analysis Market Sizing
Markets segments considered Types of sales considered
US Hospitals• Approximately 5,600 hospitals considered across the US• Data source: AHD1, CMS2, Intuitive Surgical
US ASCs
Europe
• Approximately 4,300 ASCs considered across the US• Data source: CMS2
• Opportunity modeled after Intuitive sales in Europe• Data source: Intuitive Surgical
1st Unit Sales• First-time SPORT sale to a healthcare facility
2nd Unit Sales
Replacements
• Sales to healthcare facilities that want a second operational SPORT unit
• Replacement sales for 1st and 2nd unit sales
Cross-section of all sales channels considered
1. American Hospital Directory2. Center for Medicare & Medicaid Services
1st Unit Sales 2nd Unit Sales ReplacementsUS Hospitals x x x
US ASCs x – xEurope x – x
Assumed no 2nd unit sales in ASCs and Europe
Limitations
Market Sizing
Executive Summary
Translating to Unit Sales
US Hospitals
US ASCs
Europe
Conclusion
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Titan can target 1,118 hospitals globally
Overview Opportunity(# hospitals)
US Hospitals
US ASCs
Europe
Insights
• Developed 2 models to estimate target market size
• Considered approximately 5,600 US hospitals
744
181
193• Modeled after da Vinci’s Europe sales
• Only international segment considered
• Approximately 2/3rd of total target market
• 3 factors are strong predictors of target hospitals: teaching status, revenue to price ratio, procedure volumes
• Half of target hospitals are concentrated in 10 states
• Considered approximately 4,300 US ASCs
• Approximately 1/6th of total target market
• 57% of targeted hospitals are concentrated in 10 states
• Approximately 1/6th of total target market
Breakdown by Segment
Market Sizing
Total: 1,118
US Hospitals
67%
US ASCs16%
Europe17%
Market Sizing
Executive Summary
US Hospitals
US ASCs
Europe
Limitations
Translating to Unit Sales
Conclusion
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Adjusted for SPORT’sprice and capabilities
RegressionModel
Projected Outcomes
744 potential target hospitals
All predictors were statistically significant (P Value < 0.001)
Highly accurate(Area under the curve = 0.93)
Trained on da Vinci machine market data
Robust analysis, 7 predictors used
UtilizationModel
Projected Outcomes
Based on procedure data for 5,661 US Hospitals
4 factors analyzed to determine machine utilization
Identified hospitals with sufficient procedure volumes
1025 potential target hospitals
40% of potential hospitals do not own a da Vinci
Sensitivity ranges from 909 to 1166
US HospitalsUS hospital market was estimated using two models
Model 1: Estimation Model 2: Validation
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LinkageData Aggregation TrainingRan a logistic regression using 7 factors; adjusted for SPORT’s factors to calculate a purchase probability for each hospital
Records werecomprehensive90%
Databases were joined through probabilistic record linkage; missing
values were imputed or found through research
Missing 10% of data were imputed
Imputing methods
Regional Income DataMean State income was used for missing records
For-Profit StatusMissing records were assumed to be non-profit (more conservative)
Aggregated 23 factors from four databases
Staffed BedsTotal DischargePatient DaysGross Patient RevenueAPC1 NumberAPC Number of ClaimsAPC Units of ServiceAPC Total Charges
APC Total CostAPC Total PaymentDRG2 CodeDRG Total CasesDRG Total ChargesDRG Total CostDRG Total PaymentRegional Population
HospitalIntuitive Surgeon Name
Surgeon’s SpecialisationsSurgeon’s Employers
Educational Facility For Profit StatusRegional Median Income
SPORT surgeries considered
US Hospitals –Model IModel I Methodology
Endometriosis resection Ventral hernia repairBenign hysterectomyCholecystectomy
Inguinal hernia repairColorectal procedures
Adjusted for SPORT capabilities and price at each hospital
1. APC = Ambulatory Payment Classification (Classification for out-patient hospital procedures)2. DRG = Diagnostic Related Group (Classification for in-patient hospital procedures)
Developed relevant factors using original factors as well as ratios of original factors
Ran regression on dependant variable: does the hospital have a da Vinci machine?
Market Potential Calculation
Determined probability of purchasing a SPORT machine per hospital
Calculated market potential as sum of purchasing probabilities across all hospitals
1
2
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Assumptions Results
Upper case• Will capture some da Vinci Hospitals • Penalty applied to be conservative and
account for da Vinci’s existing capacity and brand loyalty
Lower case• Will not capture any da Vinci Hospitals• Brand loyalty significantly influences hospital
decision making
Base case• Simple average between lower and upper
cases
0100200300400500600700800900
1000
Lower Base Upper
Num
ber o
f hos
pita
ls
Non da Vinci Hospitals da Vinci Hospitals
591
744
896
US Hospitals –Model IModel I predicts a base case of 744 target hospitals
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Projected Hospitals Heat Map Distribution Analysis by State
Potential Hospitals – Top 10 States
8969
54 48 40 37 37 32 29 26
020406080
100
CA TX FL NY PA IL OH NJ VA IN
Top 5 33%
Top 10 51%
Top 20 75%
Top 30 89%
Top 40 96%
80
70
60
50
40
30
20
10
744 Potential Hospitals (Base Case)
US Hospitals –Model ITop 10 states comprise 50+% of target hospitals
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Market PotentialMethodology
Set usage thresholds
Projected SPORT procedure volumes• Used hospital usage data to project
SPORT’s surgical volumes annually
Determined candidate hospitals• Hospitals that surpassed the utilization
threshold were deemed candidate hospitals
1239
4422
407 618
• Based on hospital revenues, for-profit status, teaching status, and da Vinci ownership
Hospitals with da Vinci SPORT targeted hospitals with da Vinci
Hospitals without da Vinci
SPORT targeted hospitals without da Vinci
• Market potential of 1,025 target hospitals; supports conservative market estimate of Model I
• Model I was selected as primary model given greater number of factors considered, simpler assumptions, and high accuracy of that model
US Hospitals –Model IIModel II – Validation: predicts 1,025 target hospitals
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Market Sizing
Executive Summary
US Hospitals
US ASCs
Europe
Limitations
Translating to Unit Sales
Conclusion
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Methodology
Market Sizing -ASCsTitan can target 181 ASCs in the US
Assumptions
181 Potential ASCs
Collected ASC data• Used CMS database of approximately 4,300 ASCs containing
procedure volumes by surgical category
Calculated financial metrics for ASCs• Using operating margin figures, estimated the average ASC’s
revenue assuming it had the same cost structure as hospitals• Allocated revenue estimate using procedure volumes as a proxy
Matched to the nearest US hospital on revenue basis • Calculated probability of purchase by matching ASC revenue to
hospital revenue• Used k-NN algorithm to find 3 nearest hospital neighbors
• ASCs are assumed to require a minimum of approximately 230 surgeries annually to qualify as a target
• ASC’s are a potential target because of SPORT’s low price tag
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Projected Hospitals Heat Map Distribution Analysis by State
Potential ASCs – Top 10 States
Top 5 39%
Top 10 57%
Top 20 79%
Top 30 92%
Top 40 98%
181 Potential ASCs
Market Sizing -ASCsTop 10 states comprise 57% of target ASCs
2217
149 9 8 7 6 6 6
0
10
20
30
FL CA TX NJ PA NY NC MD OH GA
20
15
10
5
0
Market Sizing
Executive Summary
US Hospitals
US ASCs
Europe
Limitations
Translating to Unit Sales
Conclusion
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Market PotentialMethodology
Market Sizing -EuropeTitan can target 193 hospitals in Europe
Assumptions
744
193
0
100
200
300
400
500
600
700
800
US hospitals (base case)
Europe
Num
ber o
f hos
pita
ls
Compared da Vinci’s Europe and US sales• On average, Europe sales comprised
26% of US sales
Applied multiplier to SPORT• 26% was applied to SPORT single unit
hospital sales, including replacements
• Europe is assumed to be the only international market for Titan sales
Limitations
Market Sizing
Executive Summary
Translating to Unit Sales
1st Unit Sales
2nd Unit Sales
Replacements
Summary
Conclusion
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Titan has a 1,965 unit sales opportunity over 15 years
Overview
1st Unit Sale
2nd Unit Sale
Replacements
Opportunity (# Units)
• All hospitals and ASCs across all segments are assumed to have a 1st unit sale
1,385
136
444
• Only US hospitals are considered to have 2nd unit sales
• 2nd unit sales are assumed to take place 2 years after 1st unit purchase
• Replacement units are considered for all 1st and 2nd unit sales across all channels
• Assumes 5 year life span for a SPORT machine
Breakdown by Segment
Total: 1,965
Translating to Units
1st Unit70%
2nd Unit7%
Replacements23%
Market Sizing
Executive Summary
Translating to Unit Sales
1st Unit Sales
2nd Unit Sales
Replacements
Summary
Limitations
Conclusion
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Representative Bass Curve
SPORT Forecasting Application
Bass Model Overview
• Used to model adoption of new products• Incorporates market size and saturation• Considers 2 sales channels: adopters and imitators• Used widely in sales forecasting
Core assumption: SPORT’s new sales follow same pattern as da Vinci’s historical sales
Unit sale forecasts were modeled using a Bass model
Starting sales values change in different channels
Bass Model
• Coefficients of innovation and imitation fitted to da Vinci sales
Ongoing sales Cumulative sales
S-shaped adoption curve: Market reaches saturation over time, causing sales to decline
Assumed 2% growth in number of target hospitals annually, in line with US and Europe average GDP growth
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Titan has 1,385 first unit sales opportunity
Bass Model Assumptions
US Hospitals
ASCs
Europe
15-year forecast (# Units)
• Assumes accelerated adoption, given exiting hospital relationships
• Base case assumes starting sales of 15 units in Year 1
964
170
251
• Assumes same innovation and imitation rates as US hospitals, but slower starting sales
• Modeled as a multiplier applied to the US hospital 1st
unit sales
Annual Sales
Total: 1,385
1st Unit Sales
-40 80
120 160
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Units
Sol
d
Year
010203040
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Units
Sol
d
Year
010203040
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Units
Sol
d
Year
Market Sizing
Executive Summary
Translating to Unit Sales
1st Unit Sales
2nd Unit Sales
Replacements
Summary
Limitations
Conclusion
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Hospital 2nd Unit Annual SalesMethodology
2nd Unit SalesTitan can sell 136 second units to US Hospitals over 15 years
Adjusted procedure volumes• Accounted for procedures conducted by
1st purchased SPORT unit
Determined probability of purchase• Ran logistic regression to determine
probability of a hospital purchasing a 2nd
SPORT unit given adjusted volumes
Applied Bass Model• Model was applied to base case estimate,
fitted to da Vinci sales; sales assumed to begin 2 years after initial sale
136 Second Unit Sales
0
5
10
15
20
25
30
35
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Units
Sol
d
Year
Market Sizing
Executive Summary
Translating to Unit Sales
1st Unit Sales
2nd Unit Sales
Replacements
Summary
Limitations
Conclusion
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Segmentation of Replacement Sales
Titan can sell 444 replacements in 15-year forecast
444 Replacement Units
Approach
Considered for all segments• Replacement units were considered
for US hospitals (1st and 2nd unit purchases), ASCs, and Europe
Assumed 5 year lifespan for SPORT• Operationalized as 20%
replacement of installed base every year, starting 5 years after first sale
Annual Replacement Sales
Replacements
335
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83US HospitalsUS ASCsEurope
0
50
100
150
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Uni
ts S
old
Year
Summary
Market Sizing
Executive Summary
Translating to Unit Sales
1st Unit Sales
2nd Unit Sales
Replacements
Limitations
Conclusion
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Annual Sales by Stream
SummaryDetailed summary of SPORT’s 15-year sales forecast
-
50
100
150
200
250
300
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Units
sol
d
YearHospital 1st Unit Hospital 2nd Unit Hospital 1st Unit ReplacementHospital 2nd Unit Replacement ASC 1st Unit ASC ReplacementEurope 1st Unit Europe Replacement
Sales Drivers
Hospital 1st unit sales are the primary sales driver in the earlier years, but begin to drop off after Year 11
Hospital unit replacements are the primary sales driver in the later years, overtaking new unit sales in Year 15
Limitations
Market Sizing
Executive Summary
Translating to Unit Sales
Conclusion
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Titan’s opportunity ranges 1202 to 2237 units in different scenarios Insights
15 Year Cumulative Sales
US Hospital sales
With 2nd unit sales
With 2nd unit and ASC sales
With 2nd unit, ASC, and European sales
Lower case 1202 1398 1697
Base case 1435 1631 1965
Upper case 1658 1854 2237
Base case
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LimitationsLimitations of modeling analysis
All Models (Except European)
Titan is a pre-revenue company; no historical sales to inform adoption
Difficult to estimate market diffusion
Used Bass Diffusion Model to forecast adoption, fitted based on comparable product (da Vinci)
US Hospitals Some demographic data missing for certain hospitals
Small potential error Imputed missing values using state averages
US Hospitals Brand loyalty to da Vinci is difficult to quantify
Overstates market size Low case scenario assumed da Vinci hospitals cannot be captured
US Hospitals Assumed future competitive landscape is equivalent to da Vinci's past competitive landscape
Overstates market size Conducted sensitivity analysis to consider low-case scenarios. SPORT also has its own competitive value proposition
Europe Difficult to estimate Titan’s market size in Europe given lack of hospital-level data
Potential error Assumed SPORT's European sales as % of US sales is the same as da Vinci’s historical average
ASC Limited ASC financial and procedure volume data
Potential error Matched ASCs to hospitals metrics using k-NN algorithm
All Models (Except European)
Uses only Medicare data Small Potential Error Assumed Medicare data is a consistent representation across all hospitals
Limitation Overall Impact MitigationModel
Conclusion
Limitations
Insights
Market Sizing
Executive Summary
Translating to Unit Sales
35
Summary of Findings
ConclusionSummary of findings
73% of units are in US hospitals, 10% in US ASCs, and 17% in Europe
1,965 units opportunity in 15 years (base case)
Titan can pursue a targeted marketing strategy to capture high-likelihood healthcare facilities or groups (i.e. Group Purchasing Organizations or Integrated Delivery Networks)
Estimated unit opportunity ranges from 1,202 to 2,237 in different scenarios
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Appendix
Appendix
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AppendixGlossary
Term DefinitionAHD American Hospital DirectoryCMS Center for Medicare & Medicaid ServicesASC Ambulatory Surgery Center – Stand-alone facilities that only perform outpatient
proceduresk-NN K-Nearest Neighbor Machine Learning AlgorithmBass Model Model to estimate market penetration based on market size, adoption rate, and
word of mouth effect. Trained on historical dataLogistic Regression
Machine learning model which predicts probability of a certain outcome based on factors
DRG Diagnostic Related Group (Classification for in-patient hospital procedures)APC Ambulatory Payment Classification (Classification for out-patient hospital
procedures)
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AppendixSPORT 5-year forecast by stream
Year
Category 1 2 3 4 5
Hospital 1st Unit 15 15 15 22 31 Hospital 2nd Unit 1 1 1 Hospital 1st Unit Replacement - - - - -Hospital 2nd Unit Replacement - - -Hospital - Total 15 15 16 23 32
ASC 1st Unit 1 1 1 2 2 ASC Replacement - - - - -ASC - Total 1 1 1 2 2
US - Total 16 16 17 25 34 Europe 1st Unit 4 4 4 6 8 Europe Replacement - - - - -Europe Total 4 4 4 6 8 Total - Global 19 20 21 30 42 Cumulative 19 39 60 91 133