1. Projecting Expenditure on
Medicines in the NHS
XXXIII Spanish Health Economics Association
Meeting Santander, Spain • 18-21 June 2013
1
Office of Health Economics
Jorge Mestre-Ferrandiz

2. Editor’s note: A revised version of this paper has since been published as: O’Neill, P., Mestre‐Ferrandiz, J., Puig‐
Peiro, R. and Sussex, J. (2013) Projecting expenditures on medicines in the UK NHS. PharmacoEconomics. Online
First article. doi 10.1007/s40273‐013‐0082‐1.
2
This presentation is based
on a recent OHE study.
Available to download
at www.ohe.org

3. • The model
• Results
• Conclusion
Agenda
3

4. • Bottom-up projection: built up from pack level to total market
• Detailed company input on more dynamic therapy areas (covering
approx. 80%+ of the market)
• Public data and industry intelligence used to:
• Generate current position
• Define erosion curves post LoE
• Identify possible future new products and their uptake
• Keep model at list prices (based on IMS data)
• Account for degree of ‘cannibalisation’ of sales from new launches,
i.e. substitution effect
• Scenarios – important to focus on ranges, rather than point
estimates
The Model
4

5. Overview of Projection Method
Whole
Medicines
Market
Core
Therapy
Areas (~80%
of market)
Non-core
Therapy
Areas
Key
Subclasses/
Products
Other
Subclasses
New Products
Products Losing
Exclusivity (LoE*)
Retail
• Alimentary
• Cardiovascular
• Central Nervous System
• Respiratory
Hospital
• Cancer
• Rheumatoid Arthritis
• HIV
• Other anti-infectives (non HIV)
Homecare
• EPO
Biosimilars
In-depth analysis
• ATC4 level volumes
• Epidemiology
• Government policy
• Clinical guidelines
Product level pipeline analysis
• Expected pipeline
• Uptake curves based on historical analysis
• Industry intelligence
Product level LoE analysis
• Specific price & volume erosion curves
for key products
• Set of erosion curves for
- PC and Hospital
- For easy vs. complex formulations
- Biosimilars
High level analysis
• Trending based on historical
performance
Expected LoE
• Set of erosion curves
*Loss of Exclusivity (LoE) is defined as the time when a product has lost all legal
protection and is expected to face generic competition
High level analysis
• Trending based on historical
Performance
Products Losing
Exclusivity (LoE*)
New Products
5
Product level pipeline analysis
• Expected pipeline
• Uptake curves based on historical analysis
• Industry intelligence

6. Four ‘types’ of products
1. LoE products between 2012 – 2015
• Distinguishing between generics and biosimilars
2. Future launches (launched between 2012
and 2015)
3. Recent launches (launched 2007-11)
4. Non-recent (launched before 2007), non-LoE
products
Building Blocks of the Model: Structure
6

7. • Key issue for the forecast: how will generic competition
evolve for those medicines losing patent protection
between 2012 and 2015?
• Four (price and volume) erosion curves, depending on
manufacturing complexity (‘easy’ or ‘difficult’) and primary
or secondary care
• Primary care: Based on historical analysis for LoE products in
primary care (2003-11) [IMS data sufficient]
• Secondary care: case study approach
• Use erosion curves to predict impact of generic
competition
LoE: Methodology
7

8. LoE: Methodology Primary Care
8
Bases on historical analysis for LoE products between 2003 and 2011 (weighted by sales)
RETAINED VOLUME by the originator
RETAINED PRICE: Generic prices as a % of
originator
Formulation Year 1 Year 2 Year 3 Year 4 Year 5 Formulation Year 1 Year 2 Year 3 Year 4 Year 5
Easy 51% 25% 15% 13% 10% Easy 90% 54% 35% 26% 14%
Difficult 59% 45% 35% 33% 30% Difficult 98% 96% 89% 81% 74%
Number of observations
Easy 71 53 44 35 26
Difficult 19 17 13 6 4
Note on sample size: There were only 6 and 4 observations for year 4 and year 5 respectively for ‘difficult’ formulations, and results
derived for the volume erosion curve presented some anomalies. For this reason we decided to trend for years 4 and 5, assuming a
33% and 30% erosion rate respectively. For the price erosion curve, we used the result obtained from the historical analysis for year 4
and year 5 (81% and 74% respectively).

9. • In secondary care, IMS data do not capture real prices as we know
discounting takes place in hospitals. For this reason, we used a
different approach to estimate erosion curves in secondary care.
• Based on real examples of products that faced generic competition
during the last few years in the hospital market, we constructed
three case studies, representing the following market
characteristics:
• Existing biosimilars
• ‘Easy to manufacture’ product
• ‘Difficult to manufacture’ product
• We used a panel of four hospital pharmacists to validate our 3 case
studies (‘Delphi-type’ analysis)
LoE: Methodology Secondary Care
9

10. Building Blocks of the Model – LoE:
Methodology Secondary Care
10
RETAINED VOLUME by the originator
RETAINED PRICE: Generic prices as a % of
originator
Formulation Year 1 Year 2 Year 3 Year 4 Year 5 Formulation Year 1 Year 2 Year 3 Year 4 Year 5
Easy 15% 13% 11% 11% 11% Easy 15% 13% 9% 9% 9%
Difficult 71% 48% 38% 35% 30% Difficult 80% 70% 60% 30% 30%

11. • Great uncertainty. No good analogues to predict impact
(similar feedback received by Delphi-type analysis)
• Two areas:
• Anti-TNFs (etanercept (Embrel), infliximab (Remicade):
• Cancer
• L01X3 (antineoplastic MABs; Herceptin, Mabthera, Erbitux):
• L01X4 (A-NEO PROTEIN KINASE INH; Glivec, Iressa, Afinitor) and others
• Use less aggressive curves for anti-TNFs and cancer relative
to ‘2ry difficult’
• Cancer less aggressive than anti-TNFs (earlier years only)
Future Biosimilars
11

12. Future Biosimilars
12
RETAINEDVOLUMEby originator
Therapeutic area Year 0 Year 1 Year 2 Year 3 Year 4 Year 5
Anti-TNFs 100% 90% 80% 70% 60% 40%
Cancer 100% 90% 85% 80% 60% 40%
Price of generics as a% of originator brand
Therapeutic area Year 0 Year 1 Year 2 Year 3 Year 4 Year 5
Anti-TNFs 100% 85% 80% 75% 70% 65%
Cancer 100% 95% 90% 85% 70% 65%

13. • The model
• Results
• Conclusion
Agenda
13

14. • Baseline – status quo; no major changes in policy
assumed
• History is a good predictor of the future (with few
adjustments)
• High
• Uptake of new medicines improves relative to past
experience
• Oncology biosimilars have little penetration
• Low
• Uptake of new medicines worsens
• More aggressive generic and biosimilar competition
Scenarios - Narrative
14

15. Summary – Top Line Projections
15
CAGR 2011 - 15
Baseline 3.5%
High 4.1%
Low 3.1%
Total UK NHS medicines bill: actual and forecast (£m) [at list prices]
Total UK NHS Medicines Bill: CAGRs [At list prices]Total UK NHS Medicines Bill: CAGR 2007-11
CAGR 2007 - 11
IMS 3.9%

16. Summary – Brands vs. Biosimilars vs. Generics
[at list prices]
16
CAGR 2011 – 15
[At list prices]
Brands 1.1 %
Generics 10.2%
Biosimilars 37.2%

17. Elements Driving Total Expenditure: Baseline
17

18. How Good Are Our Projections for 2012?
18
• For the total market: actual sales are within our projected range
• For total brands: our baseline negative growth rate is higher in magnitude
than the actual (-2.3% vs. -1.5%); but, again, actual sales are within our
range
• Generics: overall, we have slightly overestimated growth (14.0% in the
baseline scenario vs. 12.6% actual)
Growth Rates: 2012 vs. 2011 Actual Baseline High Low
Total Market 1.3% 1.0% 4.4% 0.8%
Total Brands -1.5% -2.3% 0.3% -2.6%
Total Generics 12.6% 14.0% 27.4% 14.0%
Total Primary Care -3.7% -1.9% 3.2% -2.2%
Total Secondary Care 10.3% 6.5% 6.6% 6.3%
Source: Actual: IMS BPI and HPAI (2012); Baseline, High and Low: author’s analysis

19. Why Bother?
19
• The CAGR for the period 2003–2011 (3.8%) for the total
medicines bill would lie within our projected growth range for
2011–2015 (3.1–4.1%)
• Our projections for brands and generics are considerably
lower and higher respectively than they were historically for
the 2003–2011 period
CAGR
2003−2011
CAGR
2011−2015e
Total medicines bill 3.8% 3.1%‒4.1%
Total brands 3.4% 0.5%‒1.8%
Total generics 5.8% 10.0%‒11.0%
Source: 2003–2011 authors’ calculations from IMS BPI and HPAI (2003–2011); 2011–2015
authors’ analysis

20. • The model
• Results
• Conclusion
Agenda
20

21. • Method for projecting UK NHS expenditure on medicines over the
medium term
• The basis for our projections includes historical trends, knowledge of the
unfolding lifecycles of existing medicines, published information about
R&D pipelines that will produce future new medicines, and expert input
• Key challenges: future impact of new launches and generic competition
• Two broad approaches may be used to project future medicines
expenditure in any health care system: bottom-up or top-down
• The choice of approach depends on the reason for projecting medicines
expenditure.
• We have used a bottom-up model because we were particularly interested
in exploring the impact of generic competition and new products over the
medium term
Summary and Conclusions
21

22. To enquire about additional information and analyses, please contact
Dr Jorge Mestre-Ferrandiz at jmestre-ferrandiz@ohe.org
To keep up with the latest news and research, subscribe to our blog, OHE News.
Follow us on Twitter @OHENews, LinkedIn and SlideShare.
Office of Health Economics (OHE)
Southside, 7th Floor
105 Victoria Street
London SW1E 6QT
United Kingdom
+44 20 7747 8850
www.ohe.org
OHE’s publications may be downloaded free of charge for registered users of its website.
©2013 OHE