1. Portfolio Risk Analysis Kimber Hardy November 2012

2. 2 The Flaw of Averages Sam L. Savage John Wiley & Sons, Inc., 2009

3. 3 Pipeline values and risk… … single, average values can be misleading …. “plans based on average assumptions are wrong on average”

4. 4 Role of Portfolio Management Portfolio Management Align portfolio with Strategy Maintain portfolio balance Maximize portfolio value Company Strategy R&D investment allocation Resource Management TA1 TA2 TA3 NME Dev LCM Res Total R&D Investment Company Strategy Resource supply and demand, by project and Department Total R&D Investment Project Prioritization & Optimization Pipeline-derived sales Value and Risk Portfolio Value Change

5. 5 eNPV: often used for (late-stage) project valuation Success Failure 50% eNPV* 04710 –5090100 –50000 Probability of Success Cash Flows by Year NPV* 25 eNPV: to account for timing and technical risks, NPV and probabilities are combined *at 10% discount rate

6. 6 -250 -50 0 +200 +400 project value (€m) probability 0.01 0.02 0.03 0.04 0.05 Fails in Preclinical. Project stopped Successful Development & Registration. Generates sales -250 -50 0 +200 +400 Mean value €80m project value (€m) probability 0.01 0.02 0.03 0.04 0.05 Fails in Clinical. Project stopped Project values: range of possible outcomes Mean value by itself doesn’t capture enough about the value and risk of the project

7. 7 Many ways to present project values and risks e.g. Sensitivity analysis Decision trees and scenarios Monte Carlo simulation Value change over time

8. 8 How to analyse and present pipeline values, ranges and risks?

9. 9 Typical portfolio analyses Pipeline-derived sales Project prioritization Project value and risk Pipeline value change

10. 10 It can be very useful to show an analysis of potential sales with ranges … Pipeline-derived sales * *indicates that there is a 10% probability that sales will be greater than the value shown and 90% probability that it be less

11. 11 Pipeline value change: + €1’100m (+24%) Pipeline value (€ millions) -800 400 1’500 5’600 4’500 2011 2010 … or an analysis of portfolio values with an indication of confidence limits

12. 12 An analogy with Financial Portfolios Probability analyses increasingly used: e.g. assessing downside risk in pension portfolios *Illustrative only! Adapted from www.ProbabilityManagement.org

13. 13 Pipeline Value as the sum of project mean eNPVs Total pipeline value = €5’600m

14. 14 Pipeline Value as the sum of project eNPVs This is a mean value How to show more information about the portfolio: values and risks? For example, what’s the probability that the value is less than €2’000m? Total pipeline value = €5’600m

15. 15 Defined scenarios for projects Scenarios High (x%) Base (y%) Low (y%) Competition Pricing & Reimbursement Price Patent status Launch date Year of peak sales Marketing Strength Etc.

16. 16 Scenarios vs. Sensitivity analysis Both useful, but prefer scenarios as more clearly defined NPV given Technical Success, Rebif in Colorectal Cancer $5,800 Low 2017 $5MM $5,800 0% 7 20% $7,100 High 2015 $28MM $7,100 -3% 40 40% TPP 050100150200250300350400450500 Product Profile EU Market Share US Final Market Share EU Annual Launch Costs EU Price Growth Rate EU Initial Price US Annual Launch Costs EU Launch Year Material cost per mcg US Initial Price Base Value: $170 million MAP 30% 25 -2% $6,500/yr $20MM 2016 Base $6,500/yr Base Case Sensitivity analysis

17. 17 Global peak sales (€ millions) 20% 60% 20% = scenario probability Sales forecasts & costs defined for each scenario 1036 819 519 HighBase case Low e.g. for sales...

18. 18 Project probability of success  CMR & KMR benchmarks –Useful background information when assessing project probabilities –However, benchmarks for certain therapeutic areas have insufficient data –And certain types of project differ markedly from benchmark E.g. phase III projects from small vs. large Pharma companies Phase III Oncology trials: 2000 to 2009* Company sizePositive Phase III <$300m0/21 (0%) >$1’000m21/27 (78%) *A. Feuerstein & M.J. Ratain. J. National Cancer Institute.103(20):1-2. Nov 2 nd 2011

19. 19 Commercial and Technical Risks: project data needed for Monte Carlo simulation of portfolio value 54% 46% 750 400 200 -240 -220 NPV Phase IIIFilingScenario Outcome Probability 20% Succeed 60% Succeed Fail Scenario 1 Scenario 2 Scenario 3 Launch Fail 11% 32% 6% 40% 20% 60% 10% 90% 60% 40%

20. 20 Portfolio value: Monte Carlo simulation 0%10%20%30%40%50%60%70%80%90%100% Cumulative distribution € millions Proj A Proj B Proj C Proj A Proj B Proj C 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000

21. 21 Portfolio Value Ranges « Value at Risk » 22% of median value 0%10%20%30%40%50%60%70%80%90%100% Cumulative distribution € millions 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000

22. 22 Portfolio Value Ranges The shape of the curve describes the value – risk profile of the portfolio

23. 23 Portfolio values: “the flaws of averages” Portfolio A Mean value: €500m Low Risk/ Low Reward Portfolio B Mean value: €500m High Risk/ High Reward

24. 24 Impact of correlation on portfolio risk/reward profile Four phase II projects: 70% correlation vs. no correlation -2'000 0 2'000 4'000 6'000 8'000 10'000 12'000 14'000 0%5% 10%15%20%25%30%35%40%45%50%55%60%65%70%75%80%85%90%95% 100% Cumulative distribution Value (€m) 4 projects. 70% correlation 4 projects. No correlation 70% correlation no correlation

25. 25 But a final word on keeping presentations to the Board simple. At most this…

26. 26 Pipeline value change: + €1’100m (+24%) Pipeline value (€ millions) -800 400 1’500 5’600 4’500 2011 2010 … or this to show confidence limits

27. 27 The Flaw of Averages Sam L. Savage John Wiley & Sons, Inc., 2009