Pharma Strategy Blog

“The problem at the moment is that it takes $1bn [£600m] to get a drug to market and 15 years or more. That is the justification for the pharmaceutical industry charging high prices.

If on the other hand by the time you get to phase 2 you know exactly which patients it is going to work on, you only put those patients through and instead of 10% you get an 80% response rate.

You get a licence on the basis of the data and don’t have to go to phase 3 (a trial involving thousands of people). That saves vast sums of money and years of development. What that does to the business model is it means you can justify charging lower prices because it cost a lot less in the first place.

If we get this right, it changes the entire dynamics of the business model of the pharmaceutical industry.”

Source Harpal Kumar, the chief executive of Cancer Research UK (CRUK) via The Guardian

A UK friend kindly sent me this article today and provocatively asked me what I thought. Hmmm, a very interesting, meaty and relevant topic indeed.  Here goes…

Will this change the way we do business in cancer research?

The theory behind this statement by CRUK is that if we develop more targeted drugs to fewer patients and generate higher response rates e.g. 70-80% in a specific biologic subset, instead of say, 10% in a broader population, then the costs of development will come down and thus the treatment cost of the disease will ultimately lower.

Not so fast!

The reality might actually be different, and here’s why:

1. For this to happen you need more translational research, biomarkers and companion diagnostics.
2. The cost of researching and developing the targets is quite high.
3. While clinical development costs might be lower with fewer large scale trials, the costs of iterative phase II trials will go up and the available pool of patients for commercialization is now much lower e.g. 5% of patients with the ALK translocation in lung cancer not 100% of all available relapsed patients.
4. In order to maintain revenues, it is basic economics 101 that smaller patient niches will equal higher costs.

If you are not convinced of the last point, take a look at the costs of treating rare diseases or small subsets of patients.

Some good examples exist in the hematology space include:

1. Alexion’s Soliris (eculizumab),which is approved for the treatment of patients with paroxysmal nocturnal hemoglobinuria (PNH). This is a rare hematologic disorder that affects approx. 8,000 to 10,000 people in North America and Europe. The cost is something like $400K per annum.
2. Genzyme’s Fabrazyme (agalsidase beta) for the treatment of Fabry Disease, another rare hematologic condition, this time an inherited metabolic defect that affects 1 in every 40-50,000 people in the US. Fabrazyme lowers the amount of a substance called globotriaosylceramide (GL-3), which builds up in cells lining the blood vessels of the kidney and certain other cells. It’s very effective, but certainly not inexpensive at around $160K per annum.

What is the likely impact of the changing research paradigm?

Both of the above patient pool sizes are not out of the realm of reality for a comparison with oncology.

In the old model, clinical trials tended to involve more allcomer trials, i.e. patients with a particular tumor type (e.g. non-small cell lung cancer), stage of disease (metastatic) and line of therapy (frontline, relapsed or refractory).

In the new world order, things are changing in clinical trials already:

1. Roche’s Zelboraf (vemurafenib) was recently approved in metastatic melanoma in patients with the BRAF V600E mutation, reducing the available pool who might respond by 50%. It was launched last week with a price tag of around $56.4K for an average of 6 months treatment.
2. Crizotinib (Xalkori) is being evaluated in patients with NSCLC who have the ALK translocation and have failed prior therapy. That’s a tiny subset of patients. Patients with this aberration make up maybe 4-7% of the total NSCLC pool. Imagine how small the target population will be for other ALK inhibitors in crizotinib refractory disease?!
3. The cost of funding and finding biomarkers that predict response is a huge undertaking.  Genentech have no doubt spent many millions looking for a predictive biomarker for Avastin, so far to little avail.

Of course, there are plenty of other exciting targets with small subsets being evaluated in the clinic, but there are several factors to consider:

1. Small subsets = fewer patients = higher cost.
2. Will combination strategies be affected by the cumulative costs that will inevitably result? e.g. Yervoy + Zelboraf in metastatic melanoma potential treatment cost = $170-180K if the studies are successful in showing that survival is improved.
3. Since Dendreon’s Provenge ($93K) was recently given the green light by the CMS, the costs of new targeted entrants is creeping up over the $100K watershed marknot down, viz Yervoy ($120K) and Adcetris (~108K), for example.

In conclusion…

I admire the chutzpah of CRUK, but disagree with some of their conclusions, which I think are rather naive.

Today, I will go on record here and declare that I believe specialised treatment based on the underlying biology will ultimately cost more, not less, in the long run in terms of research and development, diagnostics/biomarkers and treatment costs of ever smaller subsets.

However, I have no doubt we will ultimately see better results clinically with this more scientific approach but this will come at a cost.  While that’s great news for patients and caregivers, it is not so great for the payers, Government or investors, because higher risks and R&D costs will inevitably equate to more failures and this drives higher costs in a spiral fashion.  Ultimately, those costs will trickle down to all of us in the form of higher co-pays and more expensive medical plans to cover the payers margins.  Success has to be paid for somewhere down the line.

And the constant refrain from everyone in Pharma of “let’s do more with less” will increase.

It’s a vicious cycle of unsustainability, with no end in sight.