Generic Prices Forecasting and Mega Trends

How do companies forecast generic prices?

Some just react to market changes

Fitting trends to prices

But reality was different

Same Therapeutic Cat Same Therapeutic Category, But Different Decay Rates Selective Serotonin Re-Uptake Inhibitors

Same Market Value Same Value, But Different Decay Rates £450,000 - £550,000

Same molecule Same Molecule But No Uniformity Fluconazole Caps

But actual patterns are very complex

Sophisticated Wild Ass Guesses SWAGs

Data Collection Wavedata founded in ,000 hours of data entry 160 wholesalers and suppliers Thousands of generic products 2 years of analysis

Trend in average generic price

Each product follows a pattern

Patterns & Relationships £ ?  Generic Price Volume Market Share Value Brand Generic Spilt No of Manufacturers Reimbursement 

Statisticians found each product can be modelled

Multiple models were produced, one for each product

Each with its own formula

First Model (2005) 80 products analysed Linear dynamic model 3 forecast models A, B and C Based on statistical coefficients

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)

Can generic prices really be forecast? Before During Actuality Does it work?

Model can be adapted for new markets Different coefficients for each market USA EU States Other Markets

USA

USA vs UK

Other Products

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 factors

282 products analysed 42 products bounced once 6 products bounced twice 4 products bounced three times  18% of products bounced How often bounces happen

Bounces after generic launch

Bounces – the real picture

Bounce frequency

Seasonality – Omeprazole Apr 02- Mar 06

Seasonality - Omeprazole Oct 02- Sep 06

Seasonality - Ciprofloxacin Jan 03 – Dec 05

Seasonality - Levothyroxine Oct 00-Sep 06

Seasonality - Atenolol Oct 00-Sep 06 Jan 01- Dec 05

Seasonality - Simvastatin Oct 03-Sep 06

Seasonality - Lisinopril Jan 01 – Dec 05

Clusters 8 Clusters seen so far Some product specific Some not

Clusters 1 - 4

Clusters 5 - 8

Low price point ▪ February ▪ June ▪ November High price points ▪ April ▪ August ▪ December Highs and Lows

Highs ▪ When commercial people are on holiday Lows ▪ When commercial people are all working But what about the others? Possible reasons

Natural decline √ Reimbursement √ Seasonality √ UK √ Other Markets ? Summary

Many Thanks