Defining patient populations is a key trend shaping the pharma industry

Christopher Ehinger

Black Swan Analysis

In this article, Christopher Ehinger of Black Swan Analysis explores one of the key trends in the pharma industry at the moment: defining patient populations. He believes that in order to be successful in the future, the industry needs to have a better understanding of the patient populations for each individual disease.

(Continued from “Enablers of drug innovation could lie in the numbers”)

Challenge

The pharmaceutical industry is in a state of evolution. Many blockbuster drugs that have financially supported the industry well over the last few decades, no longer have patent protection, allowing generic products to enter and de-value the market.

The use of generic substitutes for branded products is being actively encouraged by the NHS, to help reduce the current spend on drug treatments, whilst enabling an ever growing number of patients to receive care. Currently, more than 67% of all the medicine dispensed by the NHS is generic, making up only a third of the entire NHS drug bill.1 This will deliver some of the savings needed to fill the £15-20 billion NHS funding gap by 2015.2

In markets like the US, nearly 80% of the four billion prescriptions written in 2011 were dispensed using a generics version of the branded product.3 Over the next three years in the US, the generic utility is expected to increase to almost 90%. Pharmaceuticals and branded biologics generating annual sales of over $90 billion will lose their patent protection.

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“Over the next three years in the US, the generic utility is expected to increase to almost 90%.”

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With increasing use of these generics, regulatory authorities such as the Medicines and Healthcare products Regulatory Agency (MHRA) are now viewing these as the ‘standard of care’, creating a challenge for any pharmaceutical company attempting to develop improved follow-on treatments that can be proven to be cost-effective to the healthcare system.

Outlook

These changing dynamics in the market have driven R&amp,D functions of many pharmaceutical companies to narrow their focus. They are beginning to look at niche opportunities in disease areas previously overlooked as too challenging or not having enough patients, to deliver a reasonable return. These opportunities will be looking at very specific patient criteria which correlate with the planned treatment, and be reflected in their eventual marketing authorisation, and indicated use, if they are successful.

Since 2005, the rate of introduction of new molecular entities (NME) in the global pharmaceutical industry has remained relatively flat. Over the past 5 years, there have been fewer than 30 NME launches with the orphan products, with the orphan-designated indications, as the segment growing the largest during this time period.4 This trend of developing healthcare innovation in these niche populations will continue as companies look for novel mechanisms of action for untapped patient populations.

Figure 1: The rate of introduction of NMEs has remained relatively flat since 2005

Along with this diminishing level of innovation entering the market, healthcare systems across the globe are now being tasked with how to treat a continuously growing, aging population, with a growing prevalence of chronic diseases with a heterogeneous profile. The “one treatment fits all” philosophy will not work as the cost of stacking the treatments will provide a significant burden and waste to the system which it cannot afford.

To guarantee any level of success in the future, it is imperative for the industry to have a better understanding of the patient population for a particular disease. This needs to go deeper than the basic incidence or prevalence data currently used today, to more detailed sub-populations that highlight specific attributes, co-morbid conditions or risk factors.

With this knowledge, treatments can be targeted toward patient profiles most likely to benefit from the new treatment, thus improving chances of a successful outcome. This sets the scene for more refined clinical trial plans with potentially a reduction in the numbers of patients in the trial, delivering a potential reduction in overall costs and development timelines for new treatments.

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“With this knowledge, treatments can be targeted toward patient profiles most likely to benefit…”

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A good example would be in chronic heart failure (CHF) where there is a very large eligible patient population in the UK of 973,000 patients.5 It is significantly less when we start looking closely at the population that would be affected by a specific new therapeutic treatment.

If you are trying to identify a sub-population of patients with medically defined heart failure NYHA class I, the answer can be either 169,000 or 438,000 depending on whether the sub-population has a preserved or reduced ejection fraction. The difference between these two populations across the top five markets of Europe can be the difference between a product being a commercial success or a failure.

From an NHS perspective, this detailed patient population information is ideal when reviewing new healthcare technologies to identify the patient group which will benefit the most, and set a suitable reimbursement price.

Solution

Basic information already exists from various patient groups, such as the Alzheimer’s Association, for prominent and well understood disease areas.6 However, this is inadequate for a large number of diseases and disorders where information can be limited.

To gain more relevant patient detail, information needs to be gathered from the many patient registries and epidemiology studies that look specifically at clinical attributes, risk factors and outcomes.

New resources have emerged to provide this missing insight and form the building blocks of patient segmentation. They will deliver for healthcare professionals and public health administrators a more intimate understanding of populations affected by particular conditions. They will better manage expectations for some of the novel technologies in development which will be appropriate for a smaller defined group of patients.

References

1. British Generic Manufacturing Association

2. NHS Chief Executive Annual Report 2008-09, Page 47

3. 2012 Generic pharmaceutical Association

4. IMS Institute for Healthcare Informatics, May 2012

5. Epiomic Patient Segmentation Database, Preserved Ejection Fraction sub-population, Chronic Heart Failure Disease Area , Heart &amp, Cardiovascular Category, epiomic.com

6. Alzheimer’s Society, ‘Statistics’. alzheimers.org.uk/site/scripts/documents_info.php?documentID=341

About the author:

Christopher Ehinger has over 14 years of pharmaceutical experience in various commercial roles in therapeutic, diagnostic and medical device businesses. This includes experience in blue-chip organizations such as SmithKline Beecham, GlaxoSmithKline, Amersham Health &amp, GE Healthcare where he was the Global Marketing Director for the Oncology and Neurology disease franchises.

He is currently the Managing Director for Black Swan Analysis, a unique fully integrated analysis practice founded in 2007. The company develops novel patient-related healthcare databases which are made available via the web to the pharmaceutical and healthcare professionals on a subscription basis.

Their current offering includes the Epiomic™ Patient Segmentation database that provides a robust, evidence-based source of patient populations that go beyond basic prevalence or incidence rates, to include essential conditions and patient attributes for each disease. It covers a comprehensive range of over 125 of the most prominent diseases, including over 2,500 unique patient sub-populations, displaying many of the clinically critical attributes and co-morbid conditions seen in these patients.

Black Swan Analysis Ltd., Moorbridge Court, 29-41 Moorbridge Road, Maidenhead, Berkshire SL6 8LT

+44 (0)1628 621790

christopher.ehinger@blackswan-analysis.co.uk

www.epiomic.com

www.blackswan-analysis.co.uk

How can pharma define patient populations?