new pr ofesy conference presentation
TRANSCRIPT
Generic Prices Forecasting and Mega Trends
How do companies How do companies forecast generic prices?forecast generic prices?
Some just react to Some just react to market changesmarket changes
Fitting trends to pricesFitting trends to prices
But reality was differentBut reality was different
Same Therapeutic CatSame Therapeutic CatSelective Serotonin Re-Uptake Inhibitors
Month after launch
Citalopram Tabs 20mg28Paroxetine Tabs 20mg30
Same TherapeuticCategory,
But DifferentDecay Rates
Selective Serotonin Re-Uptake Inhibitors
Month after launch
Citalopram Tabs 20mg 28
Paroxetine Tabs 20mg 30
Selective Serotonin Re-Uptake Inhibitors
Same Market ValueSame Market Value£450 - £550 000
Months after launch
Quinapril Tabs 10mg 28
Nicardipine Caps 20mg 56
Same Value,But DifferentDecay Rates
£450,000 - £550,000
£450 - £550 000
Months after launch
Quinapril Tabs 10mg 28
Nicardipine Caps 20mg 56
Same moleculeSame moleculeOne Molecule But NO Uniformity!
Fluconazole Caps 150mg 1
Fluconazole Caps 200mg 7
Fluconazole Caps 50mg 7
Same MoleculeBut
No Uniformity
One Molecule But NO Uniformity!
Fluconazole Caps 150mg 1
Fluconazole Caps 200mg 7
Fluconazole Caps 50mg 7
Fluconazole Caps
But actual patterns are But actual patterns are very complex very complex
• Sophisticated Wild Ass Guesses
SWAGsSWAGs
Data CollectionData Collection
• Wavedata founded in 2000
• 60,000 hours of data entry
• 160 wholesalers and suppliers
• Thousands of generic products
• 2 years of analysis
Trend in average generic Trend in average generic priceprice
Each product follows a Each product follows a patternpattern
PatternsPatterns & Relationships& Relationships
£ ?Generic Price
Volume
Market Share
Value
Brand Generic Spilt
No of Manufacturers
Reimbursement
Statisticians found each Statisticians found each product can be modelledproduct can be modelled
0.000
2.000
4.000
6.000
8.000
10.000
12.000
14.000
16.000
18.000
Sep-0
0
Mar
-01
Sep-0
1
Mar
-02
Sep-0
2
Mar
-03
Sep-0
3
Mar
-04
Sep-0
4
Mar
-05
Sep-0
5
Mar
-06
Simvastatin Tabs10mg 28
Predicted
0.000
2.000
4.000
6.000
8.000
10.000
12.000
14.000
May-0
2Sep
-02
Jan-
03May
-03
Sep-0
3Ja
n-04
May-0
4Sep
-04
Jan-
05May
-05
Sep-0
5Ja
n-06
Omeprazole Caps 40mg 7
Predicted
Multiple models were produced,Multiple models were produced,one for each productone for each product
0.000
5.000
10.000
15.000
20.000
25.000
Jun-
04
Aug-0
4
Oct-0
4
Dec
-04
Feb-05
Apr-0
5
Jun-
05
Aug-0
5
Oct-0
5
Dec
-05
Feb-06
Apr-0
6
A1002
Predicted
0.000
5.000
10.000
15.000
20.000
25.000
30.000
Mar
-02
Jul-0
2
Nov
-02
Mar
-03
Jul-0
3
Nov
-03
Mar-04
Jul-04
Nov
-04
Mar-05
Jul-05
Nov
-05
Mar
-06
A1021
Predicted
0
1
2
3
4
5
6
May
-04
Jul-0
4
Sep-0
4
Nov
-04
Jan-
05
Mar
-05
May
-05
Jul-0
5
Sep-0
5
Nov
-05
Jan-
06
Mar
-06
A1010
Predicted
0.000
1.000
2.000
3.000
4.000
5.000
6.000
7.000
Jan-
04
Mar
-04
May
-04
Jul-0
4
Sep
-04
Nov
-04
Jan-
05
Mar
-05
May
-05
Jul-0
5
Sep
-05
Nov
-05
Jan-
06
Mar
-06
A1011
Predicted
0
1
2
3
4
5
6
7
8
9A
ug-0
0
Dec-0
0
Apr-
01
Aug-0
1
Dec-0
1
Apr-
02
Aug-0
2
Dec-0
2
Apr-
03
Aug-0
3
Dec-0
3
Apr-
04
Aug-0
4
Dec-0
4
Apr-
05
Aug-0
5
Dec-0
5
Apr-
06
A1012
Predicted
0
0.5
1
1.5
2
2.5
3
Mar-02
Jul-02
Nov
-02
Mar-03
Jul-03
Nov
-03
Mar-04
Jul-04
Nov
-04
Mar-05
Jul-05
Nov
-05
Mar-06
A1013
Predicted
0
1
2
3
4
5
6
7
Ma
r-0
2
Ju
n-0
2
Se
p-0
2
De
c-0
2
Ma
r-0
3
Ju
n-0
3
Se
p-0
3
De
c-0
3
Ma
r-0
4
Ju
n-0
4
Se
p-0
4
De
c-0
4
Ma
r-0
5
Ju
n-0
5
Se
p-0
5
De
c-0
5
Ma
r-0
6
A1014
Predicted
0.000
2.000
4.000
6.000
8.000
10.000
12.000
14.000
Dec-0
0
Apr-
01
Aug-0
1
Dec-0
1
Apr-
02
Aug-0
2
Dec-0
2
Apr-
03
Aug-0
3
Dec-0
3
Apr-
04
Aug-0
4
Dec-0
4
Apr-
05
Aug-0
5
Dec-0
5
Apr-
06
A1015
Predicted
0.000
2.000
4.000
6.000
8.000
10.000
12.000
14.000
May-0
2Sep
-02
Jan-
03May
-03
Sep-0
3Ja
n-04
May-0
4Sep
-04
Jan-
05May
-05
Sep-0
5Ja
n-06
Omeprazole Caps 40mg 7
Predicted
Each with its own formulaEach with its own formula
0.000
5.000
10.000
15.000
20.000
25.000
Jun-
04
Aug-0
4
Oct-0
4
Dec
-04
Feb-05
Apr-0
5
Jun-
05
Aug-0
5
Oct-0
5
Dec
-05
Feb-06
Apr-0
6
A1002
Predicted
0.000
5.000
10.000
15.000
20.000
25.000
30.000
Mar
-02
Jul-0
2
Nov
-02
Mar
-03
Jul-0
3
Nov
-03
Mar-04
Jul-04
Nov
-04
Mar-05
Jul-05
Nov
-05
Mar
-06
A1021
Predicted
0
1
2
3
4
5
6
May
-04
Jul-0
4
Sep-0
4
Nov
-04
Jan-
05
Mar
-05
May
-05
Jul-0
5
Sep-0
5
Nov
-05
Jan-
06
Mar
-06
A1010
Predicted
0.000
1.000
2.000
3.000
4.000
5.000
6.000
7.000
Jan-
04
Mar
-04
May
-04
Jul-0
4
Sep
-04
Nov
-04
Jan-
05
Mar
-05
May
-05
Jul-0
5
Sep
-05
Nov
-05
Jan-
06
Mar
-06
A1011
Predicted
0
1
2
3
4
5
6
7
8
9A
ug-0
0
Dec-0
0
Apr-
01
Aug-0
1
Dec-0
1
Apr-
02
Aug-0
2
Dec-0
2
Apr-
03
Aug-0
3
Dec-0
3
Apr-
04
Aug-0
4
Dec-0
4
Apr-
05
Aug-0
5
Dec-0
5
Apr-
06
A1012
Predicted
0
0.5
1
1.5
2
2.5
3
Mar-02
Jul-02
Nov
-02
Mar-03
Jul-03
Nov
-03
Mar-04
Jul-04
Nov
-04
Mar-05
Jul-05
Nov
-05
Mar-06
A1013
Predicted
0
1
2
3
4
5
6
7
Ma
r-0
2
Ju
n-0
2
Se
p-0
2
De
c-0
2
Ma
r-0
3
Ju
n-0
3
Se
p-0
3
De
c-0
3
Ma
r-0
4
Ju
n-0
4
Se
p-0
4
De
c-0
4
Ma
r-0
5
Ju
n-0
5
Se
p-0
5
De
c-0
5
Ma
r-0
6
A1014
Predicted
0.000
2.000
4.000
6.000
8.000
10.000
12.000
14.000
Dec-0
0
Apr-
01
Aug-0
1
Dec-0
1
Apr-
02
Aug-0
2
Dec-0
2
Apr-
03
Aug-0
3
Dec-0
3
Apr-
04
Aug-0
4
Dec-0
4
Apr-
05
Aug-0
5
Dec-0
5
Apr-
06
A1015
Predicted
First Model (2005)First Model (2005)
• 80 products analysed
• Linear dynamic model • 3 forecast models
• A, B and C
• Based on statistical coefficients
Further development (2006)Further development (2006)
• Another year of modelling
• 120 products analysed
• Non-linear polynomial model
• Adding Reimbursement arguments
• Including Tariff M
• Works for 99% of products
• No therapeutic adjustment needed
• No strength adjustment needed
• Integrated into a web site
Current model completed (2007)Current model completed (2007)
• Can generic prices really be forecast? • Before
• During
• Actuality
Does it work?Does it work?
• Model can be adapted for new markets
• Different coefficients for each market
• USA
• EU States
Other MarketsOther Markets
USAUSA
USA vs UKUSA vs UK
Other ProductsOther Products
The ‘Dead Cat Bounce’The ‘Dead Cat Bounce’
• Cost of goods
• Manufacturer withdrawal
• Short or long residual life
• Holiday link?
• Bounces are visible side of seasonality?
• Disease timings – ie hay fever
Key Bounce factorsKey Bounce factors
• 282 products analysed
• 42 products bounced once
• 6 products bounced twice
• 4 products bounced three times
• ∴ 18% of products bounced
How often bounces happenHow often bounces happen
Bounces after generic launchBounces after generic launch
Bounces
0%10%20%30%40%50%60%70%80%90%
100%
0 10 20 30 40 50 60 70 80
Months after launch
% o
f sta
rt p
rice
Bounces – the real pictureBounces – the real picture
Bounces
0%10%20%30%40%50%60%70%80%90%
100%
0 10 20 30 40 50 60 70 80
Months after launch
% o
f sta
rt p
rice
Bounce frequencyBounce frequency
Monthly Average PercentAmoxicillin Caps 250mg 21
0%
20%
40%
60%
80%
100%
120%
140%
160%
Aug
-00
Dec
-00
Apr
-01
Aug
-01
Dec
-01
Apr
-02
Aug
-02
Dec
-02
Apr
-03
Aug
-03
Dec
-03
Apr
-04
Aug
-04
Dec
-04
Apr
-05
Aug
-05
Dec
-05
Apr
-06
Aug
-06
Dec
-06
Month
%
Seasonality – OmeprazoleSeasonality – Omeprazole
Omeprazole Caps 40mg 7
0.80000.82000.84000.86000.88000.90000.92000.94000.96000.98001.00001.02001.04001.06001.08001.10001.12001.14001.1600
Janua
ry
Feb
ruary
Marc
h
April
May
Jun
e
July
August
Sep
tem
ber
Octo
ber
Nove
mber
De
cem
ber
Apr 02- Mar 06
Seasonality - OmeprazoleSeasonality - Omeprazole
Oct 02- Sep 06
Seasonality - CiprofloxacinSeasonality - Ciprofloxacin
Jan 03 – Dec 05
Seasonality - LevothyroxineSeasonality - Levothyroxine
Levothyroxine Tabs 100mcg 28
0.9000
0.9200
0.9400
0.9600
0.9800
1.0000
1.0200
January
Febru
ary
Marc
h
April
May
June
July
August
Septe
mber
Octo
ber
Novem
ber
Decem
ber
Oct 00-Sep 06
Seasonality - AtenololSeasonality - Atenolol
Atenolol Tabs 50mg 28
0.90000.92000.94000.96000.98001.00001.02001.04001.06001.08001.1000
January
Febru
ary
Marc
h
April
May
June
July
August
Septe
mber
Octo
ber
Novem
ber
Decem
ber
Oct 00-Sep 06
Jan 01- Dec 05
Seasonality - SimvastatinSeasonality - Simvastatin
Simvastatin Tabs 80mg 28
0.9600
0.9800
1.0000
1.0200
1.0400
January
Febru
ary
Marc
h
April
May
June
July
August
Septe
mber
Octo
ber
Novem
ber
Decem
ber
Oct 03-Sep 06
Seasonality - LisinoprilSeasonality - Lisinopril
Lisinopril Tabs 5mg 28
0.9000
0.9200
0.9400
0.9600
0.9800
1.0000
1.0200
1.0400
1.0600
January
Febru
ary
Marc
h
April
May
June
July
August
Septe
mber
Octo
ber
Novem
ber
Decem
ber
Jan 01 – Dec 05
ClustersClusters
• 8 Clusters seen so far
• Some product specific
• Some not
Clusters 1 - 4Clusters 1 - 4Cluster 1
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec
Cluster 2
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
1
Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec
Cluster 3
0.6
0.650.7
0.75
0.80.85
0.9
0.95
11.051.1
Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec
Cluster 4
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec
Clusters 5 - 8Clusters 5 - 8Cluster 5
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec
Cluster 6
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
1
1.05
Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec
Cluster 7
0.6
0.7
0.8
0.9
1
1.1
1.2
Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec
Cluster 8
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
1
1.05
Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec
• Low price point▪ February▪ June▪ November
• High price points▪ April▪ August▪ December
Highs and LowsHighs and Lows
• Highs▪ When commercial people are on holiday
• Lows▪ When commercial people are all working
• But what about the others?
Possible reasonsPossible reasons
• Natural decline √
• Reimbursement √
• Seasonality √
• UK √
• Other Markets ?
SummarySummary
Many ThanksMany Thankswww.wavedata.biz