Evolving Therapies Accurately Estimating Patient

Populations in a Changing Healthcare

Market

Forecasting Excellence, Berlin

June 15th 2011

Changing Paradigm of Healthcare…

• Reduction in spending

– Cost-containment

– Avoidance of unnecessary resource consumption

– Patient-lead disease management

• Prevention rather than cure

• Better compliance & monitoring

• New players in the game

• New targets

..from “Late Disease” to “Early Health”

Patient Utility (state of health) 100% 0%

Healt

hcare

Indust

ry K

now

ledge

Rudimentary

High /

Complete

Fully Preventative

?

2nd sequelae /

events

Onset signs &

symptoms

primary

chronic disease

Accumulation

of „damage‟ /

increased risk

state

Basic intervention

at point of fatal

event

Long term

management chronic

disease symptoms

Delay / halt

chronic disease

Intervention at

pre-disease state

Prophylactic

“treatment”

Delay

death

Consequences for Forecasting

• The majority of strategic level forecasts should

(and most do) include a patient population

• This base-line patient population is one of the

most significant drivers of the forecast

• It is CRUCIAL to clearly understand & define a

robust patient base upon which to build your

forecasts

Epidemiology

• Historically, it was enough to be able to

quantify a population fairly broadly, we took

prevalence (or incidence) and that formed the

basis for our forecast

• However…

Epidemiology

• Now the challenge is different

– New diagnostic procedures enable physicians to

make better decisions around patient management

– Regulatory & reimbursement environment leading to

more tightly defined product labels

– Patient adherence more closely monitored as

physicians manage to targets

– Novel drug targets linked to general biology

“It’s a question of identifying the right patient populations and technologies

once a target has been validated and if you don’t, you’re foolish” Dr. Zerhouni, Head of R&D Sanofi-Aventis

Diagnostics

Diagnostics:

• Impact on Patient Pool

– Earlier detection of primary condition

– (Possibly) earlier detection of „pre‟- condition

– Better profiling & identification of target patient

groups

• Forecast Considerations

– Diagnostic patient algorithm – current & future state

– How does the current algorithm deliver patients to

your therapeutic?

– How will the new algorithm re-direct patients?

Niche Product Labels

Niche Labels (1):

• Impact on patient pool

– Product use confined to specific subset of patients

that could be defined according to:

◦ Clinical profile

◦ Biomarkers

◦ Medical / event history

◦ Risk & genetics

◦ Line of therapy / previous therapy / combination with other

therapeutics

• Forecasting Considerations

– Identify the appropriate subset of the population

matching label criteria

◦ Co-morbid conditions

◦ Patient history

◦ Clinical markers

◦ Diagnostic work-up

– Adding clearer detail around how the physician

manages the patient, what decision points they take

& make & how your product fits into the flow

Niche Labels (2):

Pan-Disease Targets

Pan-disease targets:

• Impact on Patients

– Well… definitions are slightly trickier

– Seek help from qualified medical professionals!

• Forecasting considerations

– Question & role here are likely to require different

skills

◦ Helping to focus & direct development

– “Portfolio” approach

◦ Prioritising likely patient target populations

And so…

Equipped for the Future

Research

Team work

Broad vision

External awareness

Challenge