Forecasting for pharmerging markets
Peter Mansell explores why new forecasting models and methods are needed as pharmaceutical companies increasingly turn to emerging markets to offset faltering growth.
By on Jul 8, 2010Peter Mansell explores why new forecasting models and methods are needed as pharmaceutical companies increasingly turn to emerging markets to offset faltering growth.
Earlier this year, IMS Health redefined the pharmerging market opportunity to include another 10 countries, bringing the total to 17: China, Brazil, Russia, India, Venezuela, Poland, Argentina, Turkey, Mexico, Vietnam, South Africa, Thailand, Indonesia, Romania, Egypt, Pakistan, and Ukraine.
This compares to just seven countries in 2006.
In aggregate, IMS Health predicts, the 17 pharmerging markets will expand by $90 billion between 2009 and 2013, contributing 48% of annual pharmaceutical sales growth by the end of that period, versus 37% in 2009.
According to Murray Aitken, senior vice president, Healthcare Insight for IMS, a new world order is taking hold in the sector.
For experts charged with calculating how these new global parameters play out for individual products or therapeutic categories, that means shedding assumptions about what constitutes a global marketplace and determining which forecasting tools can usefully be applied in the pharmerging space.
In search of new sources of revenue
Kevin Norell, senior vice president of advanced methods for Kantar Health, cites a number of factors pushing the boundaries of global interest beyond the traditional focus on the US, Japan, and the five major European Union markets.
Depleted R&D pipelines, key patent expiries, and healthcare reform have all left pharmaceutical companies looking for new sources of revenue.
This, in turn, intensifies demand for truly global forecasts.
As a measure of how fast the landscape is changing, Arnaud Grunwald, director, global market analytics and forecasting for Novartis Pharma, points to IMS data projecting a compound annual growth rate (CAGR, in constant US dollars) of 23-26% for China between 2008 and 2013, 12-15% for Russia, 11-14% for India and 8-11% for Brazil.
Coupled with the 13 other pharmerging markets, the total basket could be worth $190-234 billion by 2013, compared with $107 billion in 2008 (CAGR = 13-16%).
This reflects both demographic and economic drivers, Grunwald notes.
The demographics include growing and ageing populations, together with the increasing prevalence in emerging markets of chronic conditions such as asthma, heart disease, or hypertension, underpinned by changes in quality of life such as urbanization, pollution, and more Westernized diets.
Among the economic drivers, Grunwald observes, are the impact of the global recession in developed countries and its more muted effects in emerging markets.
Then, more specifically, there are aggressive price reductions on medicines in countries like Greece and Germany, the prospect of massive genericization in the US and the EU over the next few years, and healthcare reforms in developing countries that are expanding investment, reimbursement, and access to care.
More rigorous forecasts
Five years ago, Norell says, companies never even asked about some of the smaller countries now appearing on the radar.
And while the number of markets that will make up a global overview is highly variable, he says, the level of detail required within individual markets is significantly more demanding.
In the past, and particularly for products still in development, it was usually a case of defining a factor that could be used to gross from a core estimate for the major markets.
So youd look across various markets and say, US, EU5, and Japan account for 60% of the global number, so just take our forecast for those markets and divide it by 0.6, then theres your global forecast, Norell comments.
And now more and more theres a desire for more rigor around that.
Grunwald paints a similar picture. It used be relatively easy just to add 25% to the top seven market calculation, whereas now the ratio of sales in these markets to the pharmerging universe is edging closer to 50:50, he points out.
That begs the question of which emerging markets to forecast individually and where to apply a bulk-up factor.
Since some of the former top seven countries can no longer reasonably be used as a basis for bulking up, a much broader forecast is required one that will re-instate the old 80:20 formula applied when, nine years ago, those top seven markets still accounted for 80% of global pharmaceutical sales.
The goal for us is to get back to that 80:20 rule, Grunwald explains.
Focused but flexible forecasts
The solution, he suggests, is to focus on priority countries such as China, Brazil, Russia and Turkey, while retaining a measure of flexibility for therapeutic areas in which other markets may be key drivers.
Brand management and senior management teams can help with the prioritization process.
Taking a wider view one where 11 instead of seven markets may account for 80% of the global forecast calls not only for better forecasting capacity but for more efficiency, Grunwald points out.
Basically this is about identifying analogue situations.
For example, Grunwald continues, I would look at a current product, or a similar product or similar therapeutic area, or even my own product, and see what is the split as of today between my top 11 and the rest of the world [RoW] say, 77% versus 23% and then I can write a formula to add this 23% to what I forecast for individual countries.
At the same time, though, the RoW portion will keep expanding, so a growth rate needs to be applied that takes into account metrics such as the pricing parity index, purchasing power index, and gross domestic product.
One drawback of addressing emerging markets is that forecasters are used to working with a lot more available data.
Without that kind of coverage, the projections turn into large reconciliation exercises, Norell comments.
This involves taking an array of considerations into account, such as patient- versus prescription-based forecasting, access to care, ability to pay, and defining a commercially available population.
Local and global knowledge
It is particularly important in the newer geographies to try and tie that all together and make sense of it all, Norell says.
In this context, he adds, local affiliates need to make sure they are working with people who have real epidemiological expertise, as it is likely to be one of seven other jobs.
A practical approach is for clients to use technical experts from their global headquarters or one of the larger geographies to interface with people working on the ground locally.
Grunwald agrees. Companies can buy in epidemiological data or syndicated reports but, beyond that, We truly believe in just talking to our country affiliate, he says.
Its critical for us to be on e-mail and, as often as possible, face to face, to be able to exchange [experiences], construct the forecasting assumptions, to rely on them when [the affiliates] know better than us, and when theres a gap, to discuss whether we can use different benchmarks.
And that helps both parts, Grunwald adds. It helps global, because this is information we lack and it helps us forecast our top 11 countries, but for [the local affiliates] also, we can approach them with forecasting methodology, provide forecasting training, new tools and new ways to approach the problem.
Opening communication channels
Capacity and capability are the watchwords. In Novartis case, the central function is offshored to a team of analysts based in India, who cover all of the companys products and are directly in touch with local affiliates.
Some of the countries also use India-based analysts located in the same office to make their forecasts, which helps ensure the same methodologies and tools are employed in the process.
On the capability side, Novartis has developed a forecasting model that is nimble enough but standardized enough for everyone in the pharmaceutical division to use, Grunwald says.
It is one single model with one single structure which is, of course, flexible. It helps us with quality, because all the calculations are done automatically, with consistency, efficiency all the inputs are done in the same way, all of the outputs are standardized, and all of our forecasts are linked to an online repository.
For staff at headquarters, that means theres less time spent re-inventing the wheel, while in-country staff can leverage the work done at headquarters.
Instead of debating methodology issues, Grunwald says, at the end of the day what were talking about is the assumptions.
This strategy also improves communication, Grunwald observes.
When I send a tool, when I advise a country on methodology, it opens the communication channel, so its been a great way to start talking to people.
Different stages of market development
With these parameters in place, translating disease incidence and prevalence in emerging markets into a pool of patients available for treatment is the real challenge, as the available data are often not solid enough to calibrate the numbers of patients likely to be diagnosed and likely to have access to treatment (usually lower than in the West).
Moreover, pricing paradigms are much more uncertain now, Norell notes.
Years ago, the hardest question was [market] share. If youd do a US forecast, it was, What percentage of patients are going to get my drug if it hits the market? You just assumed this premium price.
But the world is changing dramatically, with considerable pricing differentials and fluctuations not only in emerging markets but in more established regions such as Europe.
If you think of what youre trying to do with a Phase II product that may not launch until 2014, 2015, and sometimes its peak sales may not be achieved until 2020, Norell comments. Tell me what the pharmacoeconomic environment in Greece is going to look like then.
And despite trends towards globalization of disease profiles, there can still be tremendous variances in rates of conditions such as hepatitis C, even between geographies that are physically very close to each other, Norell points out.
As Grunwald notes, the pharmerging markets are at different stages of development and quality of life, while ethnic specificities further muddy the water.
Updating and evolving information
And it gets extremely complex, Norell observes, when factors such as disease migration (e.g., between the Middle East and Europe) to seek out better care are taken into account.
This may not happen with a relatively benign or common condition such as hypercholesterolaemia or hypertension, but when it comes to a life-threatening disease, people may be asking, Should I pack up and move here, because my chances of surviving are much greater if I do?
A forecaster then needs not only to identify and track the pattern of migration but, according to Norell, to plan for the possibility that at some point somebody may notice that if a given country is becoming a magnet for patients, will they shut that down?
All of this calls for forecasting approaches that can pull together the best available data at a point in time to make the decision you need to make now, and then just keep updating and evolving that information, Norell says.
It also requires a lot of work around scenarios, things like Monte Carlo simulations are all excellent and valid techniques, but when youve got some of these markets where theres so much uncertainty, it really comes down to much more digestible forecasting approaches to vary the number of scenarios.
In some countries, you may have 20% of the puzzle pieces, he comments.
Youll end up extrapolating some things from other geographies, speculating about changes and things like access to government care, and just trying to assemble a reasonable picture from that limited data with which a company can make a sound business decision.
For more on pharmerging markets, see Cracking the Chinese pharma market, Breaking into the Brazilian pharma market, Reassessing Russia's pharma market, and The Middle East: A pharma market in the making,